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![UOIG 5
University of Oregon Investment Group January 29th
, 2016
Macro factors
External factors influencing the biotechnology industry tend to be based in
demographics and government policy. The largest demand driver for immuno-
oncology treatments, for example, is growth in over-65s (Figure 11), the age-
cohort most likely to develop cancer. Furthermore, the Affordable Care Act has
led to a marked decrease in the uninsured, increasing the addressable market for
cancer treatments.
Recently, scrutiny over dramatic price increases of previously affordable generics
has led to political pressure to mitigate the rise of medical costs. One response has
been to whether to restrict government drug formularies based on drug pricing
and value-based efficacy. (Formularies refer to drugs approved for reimbursement
by insurers, government payers and pharmacy benefits managers.) Drug firms
unable to secure formulary approval risk losing physician coverage and hence,
sales to similar drugs eligible for reimbursement.
Strategic Positioning
Proprietary Technology Platform
Macrogenics’ proprietary technology platforms employ methods in protein
engineering to treat diseases by multiple theoretical mechanisms which seek to
fortify the body’s immune system and response to foreign threats. The firm keeps
an extensive library of 2,000+ purified antibodies aimed at a large number
of cell targets, allowing for the ability to simultaneously address multiple
theorized mechanisms against cancerous and other pathogenic cells. This library
is used in the drug discovery process by offering potential candidates for further
analysis.
Dual Affinity Re-Targeting (DART)
The DART platform seeks to take advantage of the immune system’s natural
mechanisms towards targeting and destroying pathogens. The platform enables
antibody molecules to simultaneously bind to two targets at the cellular level with
the goal of creating “a more significant biological effect than binding [to] either
one of [them] separately.” This contrasts with most current antibody-based
treatments, which bind to a single target (“monoclonal”). Previous attempts by
researchers to create dual affinity antibodies were thwarted by manufacturing
inefficiencies.
Fc Optimization
Macrogenics’ Fc Optimization platform modifies the constant (“FC”) region of
the immune system’s existing antibodies. This modification enhances how
immune cells recognize therapeutic antibodies to better cooperate in destroying
cancerous cells.
Cancer Stem-Like Cells (CSLC)
The CSLC platform is employed in discovering potential cancer cell attributes
that can be targeted using one of the above technologies. It aims to ascertain novel
cell targets not amenable to current antibody-based cancer treatments. This is
accomplished through the theorized notion that cancer stem cells serve as the basis
for tumor regrowth.
Business Growth Strategies
Overview
Macrogenics’ long-term objective is to be involved in all aspects of the drug-
making process, from discovery and development to manufacturing,
commercialization, marketing and sales. Prior to gaining drug approval, this will
Figure 10: US Prescription Expenditure
Components, 2000-2014
Source: CMMS.gov
Figure 11: US Population Over-65, 2000A-2020E
Source: IBISWorld
Figure 12: Macrogenics Pipeline by Platform
Source: Macrogenics Investor Relations
Figure 13: Platform Patent Expirations
Source: Macrogenics Investor Relations
$0B
$50B
$100B
$150B
$200B
$250B
$300B
2000 2002 2004 2006 2008 2010 2012 2014
Out of Pocket Private Health Insurance Medicare Medicaid
0%
1%
2%
3%
4%
5%
0
10
20
30
40
50
60
70
2000 2005 2010 2015 2020
Population Over-65 % Change
Drug Name Platform
Enoblituzumab Fc Optimization
Margetuximab Fc Optimization
MGD006 DART
MGD007 DART
MGD009 DART
MGD010 DART
MGD011 DART
MGD012 Fc Optimization
MGD013 DART
MGD014 DART
Platform Patent Expiration
CSLC 2028
DART 2026 - 2031
Fc Optimization 2024](https://image.slidesharecdn.com/mgnx-171111032653/85/Macrogenics-Equity-Research-Report-5-320.jpg)
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- 1. University of OregonInvestment Group January 29th , 2016 Healthcare Covering Analyst: Jeremy Garbellano jgarbell@uoregon.edu Investment Thesis ▪ Macrogenics’ positioning as a developmental oncology firm in the most competitive area of the biotech industry with the lowest probability-to- market for early stage drug candidates bodes poorly in light of their having 9 of 10 pipeline drugs filling this role ▪ Pending approval, Macrogenics’ lead pipeline candidate, margetuximab, is unlikely to emerge as a favored breast cancer treatment following expected biosimilar releases in the near-term future ▪ Macrogenics will continue to tap equity markets to fund planned expansions in manufacturing capacity and late stage clinical development programs, leading to material shareholder dilution over the next 3-5 years ▪ A lack of FDA approvals yields Macrogenics’ three research platforms speculative at best in demonstrating clinical safety and efficacy ▪ Given inherent binary risks, uncertainty in forecasting clinical approvals, and overvaluations on both a relative and intrinsic basis, Macrogenics is fundamentally opposed to the Tall Firs portfolio’s value investing strategy Macrogenics, Inc. Ticker: MGNX Current Price: $20.54 Recommendation: Sell Price Target: $17.13 One-Year Stock Chart 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 $0.00 $5.00 $10.00 $15.00 $20.00 $25.00 $30.00 $35.00 $40.00 $45.00 Aug-14 Oct-14 Dec-14 Feb-15 Apr-15 Jun-15 Aug-15 Oct-15 Dec-15 Volume Adjusted Close 50-Day Avg 200-Day Avg Key Statistics 52 Week Price Range $19.67 - $39.90 % 52-Week High 57.14% 52-Week Return (31.23%) Estimated Beta 1.69 Market Capitalization $792.61M Price/Earnings Multiples (LTM) Macrogenics P/E (73.07x) Biotech Industry P/E 26.68x Healthcare Sector P/E 22.64x Russel 2000 P/E 107.00x MCSI World P/E 16.15x Trading Statistics Diluted Shares Outstanding 35,760.98M Average Volume (3-Month) 272.69K Institutional Ownership 64.60% Insider Ownership 21.45% Short Interest 9.54%
- 2. UOIG 2 University ofOregon Investment Group January 29th , 2016 Business Overview Overview Headquartered in Rockville, MD and employing a staff of 317, Macrogenics is a biopharmaceutical firm engaged in the discovery and development of novel antibody-based treatments for cancer, autoimmune and infectious diseases. Their core expertise lies in the burgeoning field of immuno-oncology, which seeks to target cancerous and other pathogenic cells by activating the immune system. Macrogenics focuses on both novel, first-in-class biologics, as well as “bio- betters” – treatments designed to improve upon currently marketed drugs – with both targeted primarily at the US market. As a developmental firm, Macrogenics has neither currently nor historically had any FDA-approved products on the market. Since their founding in 2000, the company has been devoted to raising capital, building drug discovery platforms, and advancing potential treatments through research and development (R&D). In 2008, Macrogenics acquired the privately-held Raven Biotechnologies in a stock-for-stock transaction to bolster their research platform through stem cell- based technologies. Macrogenics went public in October 2013, raising $92M. Revenue Streams At present, Macrogenics generates over 90% of their revenue from out-licensed R&D partnerships with larger, more mature firms, as well as the sale of options and licenses for the right to market their developmental drugs upon FDA approval in exchange for upfront and milestone payments (Figure 1). As of 2015, Macrogenics had 10 drugs undergoing preclinical and clinical testing; a majority target towards various forms of cancer (Figure 2). Macrogenics’ lead clinical candidate, margetuximab, entered phase III testing in Q3 2015. Pending approval, it is scheduled to launch by 2020 for the treatment of advanced breast and gastric cancers showing overexpression of human epidermal growth factor 2 (HER2), a protein associated with tumor activity in cells with genetically tested overexpression. Industry Overview Overview Biotechnology firms engage in the research, development, manufacturing and commercialization of therapeutic molecules engineered from living organisms. While traditional pharmaceuticals are chemical-based and relatively easy to synthesize, biotech drugs require far greater expertise to manufacture, as minute impurities can have disastrous health consequences. The biotech industry is generally divided by large, profitable companies with drugs on the market as well as clinical testing, and early-stage firms engaged in drug discovery and clinical testing. According to Ernst & Young, there were approximately 1,800 firms in the industry as of 2013, of which 400 were publicly- traded. Though a majority of these firms have fewer than 50 employees, just four account for more than 50% of total industry market share (Figure 3). Developmental-stage biotech firms raise funds through the issuance of equity and the negotiation of partnerships with larger, more mature firms in exchange for the outsourcing of R&D and sale of product rights and licensing agreements. (Given a lack of tangible assets and consistent cash flows, debt is not typically issued until after a firm is granted regulatory approval to market one or more drugs.) IPO Figure 1: Macrogenics Revenue by Source Source: Macrogenics 10-K Figure 2: Macrogenics Developmental Pipeline Source: Macrogenics Investor Relations Figure 3: Biotech Firms by Market Share (2014) Source: IBISWorld $0M $100M $200M $300M $400M $500M $600M $700M 2011 2012 2013 2014 Partnerships and Collaborations Government Grants Drug Name Indication Phase Margetuximab Breast Cancer II and III Margetuximab Gastric Cancer I/II Combined Enoblituzumab Solid Tumors I MGD006 Acute Myeloid Leukemia I MGD007 Colorectal Cancer I MGD009 Solid Tumors I MGD010 Autoimmune Disorders I MGD011 B-Cell Malignancies I MGD012 Solid Tumors/Heme Preclinical MGD013 Solid Tumors/Heme Preclinical MGD014 HIV Preclinical AbbVie Amgen Genentech Gilead All Others
- 3. UOIG 3 University ofOregon Investment Group January 29th , 2016 activity tends to rise in line with industrywide price-to-earnings. Follow-on equity issuance is generally also required, diluting existing shareholders. While equity markets are a viable funding source during periods of rising valuations and declining interest rates, funding windows are highly cyclical and subject to volatile investor risk preferences. Because almost all of a firm’s expected future cash flows hinge on the approval of one or more pipeline candidates, early-stage biotech firms can have option-like payouts, and clinical failures lead to sudden, dramatic share price declines. Given this, partnership arrangements represent not only a source of non-dilutive financing, but can oftentimes also signal a vote of confidence in the management and scientific potential of an early stage firm. As such, a demonstrated ability to raise capital on preferential terms is one criterion for prospective investors to evaluate biotech firms’ executives. Clinical Testing The Federal Drug Administration (FDA) is the primary arbitrator on prescription drug evaluation and approval in the US, and requires all marketed drugs pass the following clinical phases prior to commercialization: ▪ Pre-clinical, characterized by in vitro and animal testing to assess a drug’s potential safety in humans ▪ Phase I, where between 20-100 healthy volunteers receive the drug for 6-12 months to assess safety, metabolism and dosage ranges ▪ Phase II, where dosage and efficacy are evaluated in 100-300 patients ▪ Phase III, where safety and efficacy are evaluated on 300-3000 patients for up to 4 years to assess clinical value and longer-term effects ▪ Phase IV, where longer term studies are performed following a drug’s commercialization R&D expenses increase in a stepwise fashion after each clinical testing phase. Business Models Pre-drug launch biotech firms generally take one of three approaches – drug development, platform development or a hybrid of the two. The developmental model seeks to research and develop drugs for clinical approval and reap the potential cash flow from commercialization and market exclusivity. In contrast, the platform model is based on developing scientific and technological expertise in the drug discovery process (traditionally the riskiest portion of R&D) to out- license preclinical candidates to other firms. For Big Pharma, a better return on investment can often be made by purchasing candidates from these specialist platform firms rather than developing internally. Superior scientific and technological platforms are marked by greater efficiency and decreased durations in transitioning newly-discovered drugs into testing. Macrogenics employs the hybrid model, with multiple technology platforms forming the foundation for its developmental drug portfolio. Competition Competition by firm is based on chosen therapeutic focus. Generalist strategies are not typically possible at the developmental stage due to limited funding and headcount. As a result, most early-stage firms tend to specialize in a targeting a small number of related diseases. Immuno-Oncology Historically, cancer treatments took one of three forms – surgery, chemotherapy and radiation therapy. While each carry moderate-to-severe side effects, chemo- Figure 4: Biotech Public Offerings (Left Axis) vs. Industry ETF Returns (Right Axis) Source: S&P Capital IQ Figure 5: 50-Day Rolling Correlation Between Macrogenics and Industry ETF Daily Returns Source: Analyst’s Calculations Figure 6: Industry R&D by Cost Component Source: Biotechnology Valuation (60%) (40%) (20%) 0% 20% 40% 60% 80% 0 5 10 15 20 25 30 35 Public Offerings Industry Return 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Clinical Discovery Manufacturing Miscellaneous Regulatory Safety
- 4. UOIG 4 University ofOregon Investment Group January 29th , 2016 and radiotherapy are especially debilitating given their potential to non- discriminately kill healthy cells alongside cancerous ones. In recent years, a fourth option emerged – immune-oncology. This treatment category takes a more targeted approach based on monoclonal antibodies – proteins produced by the immune system to render external threats harmless – to dampen tumor growth and prolong survival rates while reducing negative side effects. Immuno-oncology treatments can be individualized based on tumor type, representing a clinically superior option for medically-eligible patients. Despite their promise, clinical phase approval rates for immune-oncology drugs have steadily declined over the past decade, even as aggregate industry R&D expenditures nearly doubled1 . Moreover, upon entering phase I, oncology drugs represent the lowest launch success rates in the industry2 . Market Potential A recent report by Leerink placed current total market potential for immuno- oncology products at $40B. Consequently, the industry’s largest players (e.g., Amgen, AstraZeneca, Bristol Myers Squibb, Merck, Novartis, Pfizer and Roche) have made significant investments in their immune-oncology portfolios. The Pharmaceutical Research and Manufacturers of America (PhRMA), an industry group, estimates nearly 800 novel biologics currently undergoing clinical testing for cancer treatment. According to Fierce Biotech, 4 of the 10 best-selling newly launched drugs in 2015 were cancer treatments. The explosion in antibody-based therapies over the past decade has contributed to declining cancer mortality rates in the US, which decreased nearly 22% since their peak in the 1990s. Drug Pricing Given enhanced specificity and safety profiles, immune-oncology drugs are among the most expensive drugs on the market, and with prices rising dramatically in the past decade. For example, the retail price for Novartis’ leukemia drug Gleevac stood at $30,000/year after gaining approval in 2001; by 2012, it retailed for $92,000. Such price appreciation has led many firms to produce “me-too” drugs that improve marginally on existing treatments and priced at sizable premiums. However, oncologists have begun pushing back, opting to weigh price more heavily in their recommendations after increasing numbers of patients have had to discontinue treatment altogether in lieu of financial constraints. Biosimilars Given greater manufacturing complexity and a difficulty in demonstrating clinical equivalence across different manufacturers, biologic drugs have historically been immune to generic drug competition and market share erosion following patent expiration, a common theme among traditional pharmaceuticals. However, interest among drug makers to produce generic biologics (“biosimilars”) has heightened markedly following the expiration of a number of best-selling drug patents. For their part, lawmakers put in place the regulatory framework to define how the FDA would evaluate and approve such products in the Affordable Care Act. While biosimilars have been sold in the European Union since 2006, the first FDA approved biosimilar drug did not enter US markets until March 2015. Among developmental biotech firms, the threat of biosimilars is expected to grow in the near-to-midterm. “Biobetters” (i.e., those that improve marginally on existing treatments) will have to demonstrate either a compelling case for superior safety and efficacy, or lower price points. Significantly, this includes Macrogenics’ phase III candidate, margetuximab, which was designed to improve upon Roche’s top-selling HER2+ breast cancer treatment Herceptin (Figure 10). Figure 7: Biotech Revenue, Headcount and R&D Growth, 2010A-2020E Source: IBISWorld Figure 8: Disease Category by Sales (2012) Source: Deutsche Bank Figure 9: Biosimilar Competition to Macrogenics’ Breast Cancer Drug Margetuximab Source: Generics and Biosimilars Initiative 0% 5% 10% 15% 20% 25% 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Revenue Headcount R&D Oncology Lipid Regulators Respiratory Anti-Diabetics Autoimmune All Others Company Country Clinical Stage Allergan, Amgen USA Phase III Biocad Russia Phase III Biocon, Mylan India Launched 10/13 Celltrion South Korea Launched 1/14 Hanwha Chemical South Korea Phase I Hospira USA Phase III Mylan India Phase III Pfizer USA Phase III PlantForm Canada Launching 2016 Samsung Bioepis South Korea Phase III
- 5. UOIG 5 University ofOregon Investment Group January 29th , 2016 Macro factors External factors influencing the biotechnology industry tend to be based in demographics and government policy. The largest demand driver for immuno- oncology treatments, for example, is growth in over-65s (Figure 11), the age- cohort most likely to develop cancer. Furthermore, the Affordable Care Act has led to a marked decrease in the uninsured, increasing the addressable market for cancer treatments. Recently, scrutiny over dramatic price increases of previously affordable generics has led to political pressure to mitigate the rise of medical costs. One response has been to whether to restrict government drug formularies based on drug pricing and value-based efficacy. (Formularies refer to drugs approved for reimbursement by insurers, government payers and pharmacy benefits managers.) Drug firms unable to secure formulary approval risk losing physician coverage and hence, sales to similar drugs eligible for reimbursement. Strategic Positioning Proprietary Technology Platform Macrogenics’ proprietary technology platforms employ methods in protein engineering to treat diseases by multiple theoretical mechanisms which seek to fortify the body’s immune system and response to foreign threats. The firm keeps an extensive library of 2,000+ purified antibodies aimed at a large number of cell targets, allowing for the ability to simultaneously address multiple theorized mechanisms against cancerous and other pathogenic cells. This library is used in the drug discovery process by offering potential candidates for further analysis. Dual Affinity Re-Targeting (DART) The DART platform seeks to take advantage of the immune system’s natural mechanisms towards targeting and destroying pathogens. The platform enables antibody molecules to simultaneously bind to two targets at the cellular level with the goal of creating “a more significant biological effect than binding [to] either one of [them] separately.” This contrasts with most current antibody-based treatments, which bind to a single target (“monoclonal”). Previous attempts by researchers to create dual affinity antibodies were thwarted by manufacturing inefficiencies. Fc Optimization Macrogenics’ Fc Optimization platform modifies the constant (“FC”) region of the immune system’s existing antibodies. This modification enhances how immune cells recognize therapeutic antibodies to better cooperate in destroying cancerous cells. Cancer Stem-Like Cells (CSLC) The CSLC platform is employed in discovering potential cancer cell attributes that can be targeted using one of the above technologies. It aims to ascertain novel cell targets not amenable to current antibody-based cancer treatments. This is accomplished through the theorized notion that cancer stem cells serve as the basis for tumor regrowth. Business Growth Strategies Overview Macrogenics’ long-term objective is to be involved in all aspects of the drug- making process, from discovery and development to manufacturing, commercialization, marketing and sales. Prior to gaining drug approval, this will Figure 10: US Prescription Expenditure Components, 2000-2014 Source: CMMS.gov Figure 11: US Population Over-65, 2000A-2020E Source: IBISWorld Figure 12: Macrogenics Pipeline by Platform Source: Macrogenics Investor Relations Figure 13: Platform Patent Expirations Source: Macrogenics Investor Relations $0B $50B $100B $150B $200B $250B $300B 2000 2002 2004 2006 2008 2010 2012 2014 Out of Pocket Private Health Insurance Medicare Medicaid 0% 1% 2% 3% 4% 5% 0 10 20 30 40 50 60 70 2000 2005 2010 2015 2020 Population Over-65 % Change Drug Name Platform Enoblituzumab Fc Optimization Margetuximab Fc Optimization MGD006 DART MGD007 DART MGD009 DART MGD010 DART MGD011 DART MGD012 Fc Optimization MGD013 DART MGD014 DART Platform Patent Expiration CSLC 2028 DART 2026 - 2031 Fc Optimization 2024
- 6. UOIG 6 University ofOregon Investment Group January 29th , 2016 require significant financing through the issuance of equity and the negotiation of additional partnerships, as the firm’s manufacturing capacity is at present insufficient to handle the demands that commercial manufacturing at scale requires. Moreover, the firm is preliminary steps of building a sales team in anticipation of future drug approvals. Lead Developmental Pipeline Candidates Margetuximab – Phase III Margetixmab is a phase III candidate being evaluated for the treatment of advanced (metastatic) gastric and breast tumors with genetic overexpression of human epidermal growth factor 2 (HER2+), a known protein involved in cancer growth. (Metastatic cancer is defined as the stage where cancerous cells have progressed to distant regions of the body from their original tumor site. Once this progression occurs, survival rates drop markedly and patients are considered terminally ill.) The drug aims to compete with Roche’s currently marketed Herceptin, both of which are projected to encounter significant biosimilar competition in the years ahead for HER2+ breast cancer. Margetuximab is being studied in conjunction with drug-resistant patients who have failed previous round of treatment (including to Herceptin). Enoblituzumab – Phase I Also known as MGA-271, this first-in-class treatment targets the BH-73 receptor, which is expressed across many different types of solid tumors (but not in normal tissue). The drug’s exact biological mechanism is currently unknown, and the research on BH-73 is at times contradictory (i.e., in some cancers, its expression at the tumor site is associated with better patient outcome rather than worse) and recent – most published articles covering it began appearing in the last decade. No other firm is currently targeting solid tumor inhibition from this cell receptor. Enoblituzumab is currently being evaluated in phase I safety and dose escalation studies for patients with a broad array of solid tumors, including bladder, lung, skin and triple-negative breast cancers. The drug is being targeted at a much wider sample of cancer types than current practices; given its early stage in clinical development, little evidence exists in demonstrating tumor growth inhibition. MGD006 – Phase I This drug is currently being evaluated for phase I safety and dose escalation testing for patients with acute myeloid leukemia (AML), a blood cancer. MGD006 is indicated for treatment in refractory patients – those who have developed drug resistance to previous therapies. In preclinical testing, it was found to activate portions of the immune system for targeted killing of immune cells. MGD006 is licensed to Servier for rights outside North America, Japan, South Korea and India. At present, no equivalent treatment exists on the market. MGD007 – Phase I MGD007 is being evaluated for advanced colorectal cancer, which represents approximately 35% of new diagnoses. In vitro evidence demonstrated its ability to mediate immune system-led killing of cancerous cells. MGD007 is being evaluated for more convenient dosing regimens than current colorectal cancer biologics, e.g., Genentech’s top-selling drug Avastin. MGD009 – Phase I Like enoblituzumab, MGD009 is thought to possess anti-tumor activity across a wide range of cancer types, a claim derived from pre-clinical experiments in animal and test tube studies. As the drug began phase I safety and dose escalation studies in October 2015, little is known about its purported efficacy in humans. Figure 14: Margetuximab Revenue Forecast Source: Analyst’s Calculations Figure 15: Enoblituzumab Revenue Forecast Source: Analyst’s Calculations Figure 16: MGD006 Revenue Forecast Source: Analyst’s Calculations Figure 17: MGD007 Revenue Forecast Source: Analyst’s Calculations (100%) 0% 100% 200% 300% 400% $0 $500M $1000M $1500M $2000M 2020E 2022E 2024E 2026E 2028E 2030E Unadjusted Probability-Adjusted % Annual Growth (500%) 0% 500% 1000% 1500% $0 $1000M $2000M $3000M $4000M 2022E 2024E 2026E 2028E 2030E Unadjusted Probability-Adjusted % Annual Growth (500%) 0% 500% 1000% 1500% 2000% 2500% $0 $20M $40M $60M $80M $100M $120M 2024E 2026E 2028E 2030E Unadjusted Probability-Adjusted % Annual Growth (50%) 0% 50% 100% 150% $0 $500M $1000M $1500M $2000M $2500M 2025E 2027E 2029E Unadjusted Probability-Adjusted % Annual Growth
- 7. UOIG 7 University ofOregon Investment Group January 29th , 2016 Management and Corporate Governance Dr. Scott Koenig, PhD – Co-Founder, President and CEO Dr. Koenig has served as Macrogenics’ President and CEO for the past 15 years. Following the completion of a Ph.D. at Cornell and an M.D. at University of Texas, Dr. Koenig has spent his entire career in the biotechnology industry, including a lab research role at the National Institute of Health (NIH) from 1984 to 1990 and a stint as MedImmune’s Senior Vice President of Research from 1990 to 2001, where he oversaw the launch three biologics. Dr. Koenig is also Chairman of the early stage biotech firm Applied Genetic Technologies Corporation, a position he has filled since 2004. In 2014, Dr. Koenig was given a total compensation of $3.34M, representing 7% of 2014 annual revenue. His salary is evaluated according to the passage of drug candidates through various clinical phases, new partnership arrangements, and cash balance maintained above a defined minimum. Corporate Governance On their 10-K, Macrogenics details corporate bylaw provisions intended to deter potential activist investors, including a required 75% shareholder approval needed to amend corporate bylaws, the nomination of company executives by current Board members, and authorization, without shareholder approval, of a blank check of preferred stock that would function as a “poison pill" to dilute the stock ownership of any would-be acquirer. Management Guidance and Analysis Given the lack of marketed products and the difficulty in predicting clinical approval rates, management guidance from developmental biotech firms is generally minimal at best. Macrogenics is no exception, with guidance offered only on expected cash burn rates and updates from various clinical trials. As of Q3 2015, Macrogenics stated having sufficient funds to conduct operations through 2018. (Two years of cash is considered the industry minimum to remain operational in light of any single pipeline drug failing to gain approval.) On their most recent 10-K, the firm also stated that net losses are expected to increase through the “foreseeable future,” driven by increased capital needed to build their manufacturing capacity to commercial proportions, a planned buildout of their salesforce before their first anticipated drug launch in 2019-2020, and the greater R&D expenses generated in phase III testing versus earlier clinical stage testing. Differential Disclosure Differential disclosure is the practice of companies making claims on financial reports that appear contradictory and/or misleading when viewed across time. Macrogenics’ management has, at times, demonstrated an aptitude for making over-exuberant statements on the estimated market potential of their drug candidates in SEC filings. In their prospectus from October 2013, Macrogenics stated the market potential for their lead breast cancer drug margetuximab as “treating approximately 25% of all breast cancer patients whose tumors overexpress HER2… This population of 25% of breast cancer patients represents 60.5% of the 42% of all patients who are HER2+.” Obfuscating language aside, this “42% of all patients” represents a considerable bump above other sources on the matter. The NIH National Cancer Institute, for example, put the figure at 25-30%, while WebMD, the Mayo Clinic and the Susan B. Komen For the Cure Foundation estimated that just 20% of all Figure 18: Macrogenics’ Forecasted Cash (Right Axis) and Shares Outstanding (Left Axis) Source: Analyst’s Calculations Figure 19: Macrogenics’ Estimated Market Potential for Margetuximab Source: Macrogenics Form S-1 Prospectus (2013) Figure 20: Margetuximab Potential Revenue at 30% vs. 42% HER2+ Market Potential Source: Analyst’s Calculations $0M $1000M $2000M $3000M $4000M $5000M 0M 10M 20M 30M 40M 50M 2015E 2017E 2019E 2021E 2023E 2025E 2027E 2029E Shares Outstanding Cash and Cash Equivalents $0M $500M $1000M $1500M $2000M $2500M $3000M 2020E 2022E 2024E 2026E 2028E 2030E 42% HER2+ 30% HER2+
- 8. UOIG 8 University ofOregon Investment Group January 29th , 2016 breast cancer patients overexpress HER2+. Not to be explained away by measurement error, scientists in the academic journal Breast Cancer Research concluded that current testing is “highly sensitive, accurately quantifies HER2 protein expression and correlates well with routine HER2 testing” before putting their estimate of HER2+ expression at 15-20% of total breast cancer patients. Holding forecasted market penetration rates fixed, the difference in patient estimates from Macrogenics and the upper end of NIH’s range would represent a difference of $4.5B in cumulative sales for their phase III drug, margetuximab (Figure 20). Macrogenics’ statements and associated charts (Figure 19) were redacted from subsequent filings describing margetuximab’s potential. Portfolio Strategy Original Investment Strategy Macrogenics was originally pitched to Tall Firs and (now-defunct) Svigals’ portfolios under the promise of “significant diversification benefits coupled with huge upside potential.” Since initiating a Tall Firs position for 195 shares of the firm in January 2014, Macrogenics’ stock is now down 69% (from a cost basis of $37.41). By comparison, shares of IBB, an industry ETF, are up 18% over the same period. As of January 22nd , 2015, Tall Firs is overweight healthcare and within 190 basis points of its small cap allocation benchmark (Figure 21-22). Portfolio Eligibility Tall Firs, which manages a portion of the University’s endowment, seeks to invest in “fundamentally undervalued companies.” In Security Analysis, the original text on value investing, Benjamin Graham defined investments as operations “in which, upon thorough analysis, promise safety of principal and a satisfactory return,” a measure Macrogenics has failed on both counts. Furthermore, Macrogenics fails to meet eligibility requirements for the Group’s other portfolios. The Alumni Fund, which seeks to buy companies with low valuation multiples and high returns on capital, describes the exact opposite situation Macrogenics is presently in. The DADCO fund, for its part, seeks to hold only the Group’s “highest conviction” picks, an unlikely label for a firm whose underlying business presents considerable difficulty even by leading industry specialists in predicting whether early-stage clinical drug trial results will ultimately translate to FDA approval. Recent News “Servier Severs $450M Oncology Deal with Macrogenics” Fierce Biotech, October 28, 2015 Following an early glimpse at the clinical data, French pharmaceutical firm Servier opted not to exercise an option for the international rights to enoblituzumab, Macrogenics’ phase I candidate with purported anti-tumor activity across a range of different cancers. The option, if exercised, would have entitled Macrogenics to clinical, regulatory and sales milestone payments of $430M in additional to the $20M received upfront when the agreement was signed in 2011. For their part, Servier was slated to gain commercial rights in all markets except North America, Japan, South Korea and India, pending successful approval by the FDA and its foreign equivalents. Servier continues to stand by Macrogenics for commercial rights to MGD006 and 007 in the same international regions. When pressed for details on the event, Macrogenics’ CEO Scott Koenig claimed ignorance to Servier’s exact reasoning, but mentioned the French firm’s recent Figure 21: Tall Firs’ Current Sector Allocations Source: UOIG Figure 22: Tall Firs’ Current Market Cap Allocations Source: UOIG Figure 23: Current DADCO Holdings Source: UOIG 0% 5% 10% 15% 20% 25% 30% Healthcare Technology Financials IME Consumer Cash Tall Firs Benchmark 0% 20% 40% 60% 80% 100% Small Mid Large Cash Tall Firs Benchmark Express Scripts MasTec SolarCity VASCO Data Security Alcoa Vanguard Scottsdale Funds Cash
- 9. UOIG 9 University ofOregon Investment Group January 29th , 2016 management overhaul as possible factor. In a later statement, Servier announced plans to lay 10% of its French workforce while re-orienting core focuses, “partly by increasing its emphasis on oncology.” Wasting little time in putting fresh capital from the severed enoblitzumab deal to use, Servier announced the following collaborations in the weeks after: ▪ The early exercising of an option with Pfizer for the co-development and worldwide (ex. US) rights to a novel phase I CAR-T immunotherapy treatment (a class in which Macrogenics’ phase I candidate MGD011 is positioned to compete against) ▪ A $130M deal to co-develop and market TAS-102 - Taiho Pharmaceutical’s colorectal cancer drug - in Europe ▪ A new partnership with Spectrum Pharmaceuticals to develop four hemato-oncology drugs in exchange for exclusive rights to the Canadian market ▪ The expansion of an existing collaboration with Novartis to include additional anticancer drug candidates in a co-development and commercialization agreement In passing, Macrogenics CEO Scott Koenig mentioned openness to new partnerships for enoblituzumab. “Macrogenics Teams Up with Merck for Cancer Drug” Washington Business Journal, October 26, 2015 Macrogenics announced plans to evaluate a combination treatment for margetuximab and pembrolizumab (Merck’s recently approved drug currently approved for advanced skin and lung cancer patients) against HER2+ gastric cancer in a combined phase I/II trial. The two-part open label trial will evaluate the safety of the combination in phase Ib testing while analyzing anti-tumor activity in phase II testing. While financial terms were not disclosed, an option for collaboration through phase III testing was made. Macrogenics expects patient enrollment for the current trial to continue through 2016. Catalysts Upside ▪ Novel, presently unanticipated disease indications for Macrogenics’ existing portfolio of pipeline candidates could broaden their estimated market potential, leading investors to bid up shares ▪ Better-than-expected clinical efficacy results could result in preferences among clinical oncology specialists shifting in Macrogenics’ favor as anticipation builds prior to future drug launches ▪ Robust evidence in support of the safety and efficacy of one or more of Macrogenics’ current pipeline candidates could lead to more attractive future partnership opportunities ▪ Additional equity investments and/or partnership arrangements could allow Macrogenics to make further investments in their clinical pipeline, increasing the likelihood of a successful approval Downside ▪ Failure of one or more clinical trials could result in a sudden decline in Macrogenics’ share price and intrinsic valuation ▪ Termination of existing partnerships might reduce future opportunities as Macrogenics’ perceived desirability as a collaborator wanes ▪ Unforeseen safety issues in Macrogenics’ clinical pipeline could lead to loss of credibility among prescribing physicians ▪ Amidst concerns over price inflation in the specialty drugs space, the failure to obtain formulary inclusion and/or unfavorable reimbursement Figure 24: Returns: Biotech ETF vs. Macrogenics Source: Yahoo! Finance Figure 25: Merck Annual Revenue Source: Yahoo! Finance Figure 26: Returns: Biotech ETF vs. Merck Source: Yahoo! Finance 50% 60% 70% 80% 90% 100% 110% 120% 130% 140% 150% 1/2015 4/2015 7/2015 10/2015 1/2016 MGNX IBB $39B $40B $41B $42B $43B $44B $45B $46B $47B $48B 2012A 2013A 2014A 70% 80% 90% 100% 110% 120% 130% 1/2015 4/2015 7/2015 10/2015 1/2016 MRK IBB
- 10. UOIG 10 University ofOregon Investment Group January 29th , 2016 rates from public and private payers could lead to physicians and patients opting for competing drugs over Macrogenics’ current candidates, especially as lower-priced biosimilars hit the market ▪ Legal disputes concerning the firm’s portfolio of intellectual property, of which Macrogenics has noted might be an issue for certain components of their Fc Optimization platform, could lead to lengthy patent litigation ▪ Declines in overall industry valuations and/or investor risk preferences could lead to shareholder dilution if Macrogenics’ stock declines materially before the planned issuance of additional equity ▪ With an average daily volume of <300K shares traded, any of the above downside catalysts could have an amplified effect on Macrogenics’ stock as lower liquidity levels inhibit the price discovery process Comparable Analysis Overview Because developmental biotech firms are valued on their estimated potential to generate outsized cash flows far into the future, relative valuation techniques are not generally awarded much importance when making investment decisions. Furthermore, as a majority of firms in the selection universe will not reach sustainable levels of profitability until after their first drug launch, both last twelve month (LTM) and one-year forward income statement estimates tend to be negative from the operating line down, rendering them useless for valuation purposes. To mitigate against these shortcomings, analyst estimates for sales, operating and net income were taken for the period of 2020, when a majority of selected comparable companies are expected to have at least one marketed drug. Screening Criteria The following criteria were taken into consideration when selecting comparable US-based biotechnology companies: ▪ Market capitalization below $1.5B to control for company maturation ▪ Gross margins of 100%, to account for a lack of marketed drugs ▪ Return on equity, return on assets and return on invested capital below 0% to account for firms’ current cash burn rates and lack of profitability ▪ A primary focus on cancer and oncology drug development ▪ The use of a hybrid platform/developmental pipeline business model ▪ At least one significant partnership agreement (to fulfill going concern requirements in the years preceding drug launches) The last criteria was given particular consideration, as 2 of the 5 companies used as comparables in Macrogenics’ original report are now trading for less than $1. Multiple and Company Weightings Because sales represent both the most important driver behind industry growth as well as the “cleanest” estimate, EV/Revenue was given a 50% weighting for valuation multiples, with the remainder divided evenly on EV/EBIT and P/E. Weightings for individual companies were assigned according to a weighting model based on the number of drugs in each clinical phase, along with employee headcount and enterprise value to control for business size, maturity and cash relative to market cap. Beta coefficients were also used as a proxy for the changing investor sentiment in each firm relative to the market. Implied prices were discounted to present value based on Macrogenics’ WACC. Celldex – 24.6% With a clinical portfolio biased towards phase I candidates and the closest beta to Macrogenics’, Celldex was weighted 24.65%. The firm’s two lead drug candidates, CDX-011 and CDX-110, are being evaluated in the treatment of breast cancer and glioblastoma (a form of brain cancer), respectively. The firm holds a Figure 27: Macrogenics Pipeline by Phase (Includes Drugs in Multiple Phases) Source: Macrogenics Investor Relations Figure 28: Proceeds from Stock Issuance (Right Axis) vs. Shares Outstanding (Left Axis) Source: Macrogenics 10-K Figure 29: Comparable Company Pipelines Source: SEC Filings 0 1 2 3 4 5 6 7 8 9 Phase III Phase II Phase I Preclinical $0M $50M $100M $150M $200M $250M 0M 5M 10M 15M 20M 25M 30M 35M 40M Q1-2014 Q2-2014 Q3-2014 Q4-2014 Q1-2015 Q2-2015 Q3-2015 Cumulative Proceeds from Issuance Shares Outstanding 0 2 4 6 8 10 12 14 16 18 Macrogenics Celldex ImmunoGen Merrimack OncoMed Xencor Phase I Phase II Phase III
- 11. UOIG 11 University ofOregon Investment Group January 29th , 2016 number of partnerships, including licensing agreements with Amgen and Seattle Genetics. ImmunoGen – 27.2% ImmunoGen’s enterprise value, headcount and clinical pipeline were the closest among comparables to Macrogenics’ among comparable companies, suggesting the most similar stage of business development. Kadcyla, a currently marketed antibody-based HER2+ breast cancer treatment similar to Macrogenics’ margetuximab, was developed using their technology platform and out-licensed to Roche. ImmunoGen’s entire pipeline is devoted to oncology candidates, and they hold partnerships with Novartis, Bayer, Eli Lilly and Amgen. For these reasons, the firm was given a 27.21% weighting. Merrimack – 15.6 % With a pipeline tilted towards phase II candidates and an unusual amount of debt on their balance sheet given their stage of development, Merrimack was given the lowest weighting. The firm holds partnerships with Baxter and Sanofi, and has a portfolio devoted purely to oncology drugs, including a mid-stage candidate for advanced HER2+ breast cancer. OncoMed – 15.7 % Like Macrogenics, OncoMed has targeted the use of cancer stem cells to discover and develop novel treatments. The firm has strategic alliances with Bayer, Celgene and GlaskoSmithKline. While their pipeline is slanted towards phase I, ImmunoGen’s lower beta and lack of phase III candidates yielded a 15.65% weighting. Xencor – 16.9% Xencor develops antibody-based treatments to target cancer and autoimmune diseases. Their lead candidate, XmAb5574, is in phase II trials for the treatment of B-cell cancers. Xencor has licensing agreements with Novo Nordisk and Amgen. However, their lower beta and lack of phase III candidates resulted in a 16.93% weighting. Intrinsic Valuation Probability-Adjusted Discounted Cash Flow Overview Given the inherent uncertainties involved in forecasting cash flows for early-stage biotechnology firms, a probability-adjusted DCF was implemented. The model seeks to overcome the binary nature of clinical trial progression and FDA approval by accounting for the likelihood a developmental drug will reach the commercial stage given its current phase in clinical testing. As this uncertainty affects both firms’ decisions on which drugs to progress through trials as well as anticipated future sales, R&D expenses are probability-adjusted in addition to sales. Phase success probabilities were taken from a 2014 Nature Biotechnology article featuring the most comprehensive industry study to date. Revenue Model Market Potential Forecasting future revenues for drugs in current development requires the use of a bottom-up market potential estimation. First, current year incidence rates (i.e., new diagnoses) for a drug’s disease target are used to assess the maximum market size. Data for these rates was accessed from the National Cancer Institute, a government-backed component of the National Institute of Health. Following this, forecasts must be made for each disease in question. Estimates for disease Figure 30: Quantitative Metric Weightings Source: Analyst’s Calculations Figure 31: Relative Valuation Source: Analyst’s Calculations Figure 32: Comparables – Headcount (Left Axis) vs. Enterprise Value (Right Axis) Source: Yahoo! Finance Figure 33: Returns: Macrogenics vs. Biotech ETF vs. Healthcare ETF vs. Russell 2000 Source: Yahoo! Finance Criteria Importance Weighting Beta 20.00% Phase I 20.00% Phase II 20.00% Phase III 25.00% Headcount 5.00% Enterprise Value 10.00% Multiple Implied Price Weighting EV/Revenue $14.50 50.00% EV/EBIT $14.72 25.00% P/E $13.03 25.00% $0M $200M $400M $600M $800M $1000M $1200M $1400M 0 50 100 150 200 250 300 350 MGNX CLDX IMGN MACK OMED XNCR Headcount Enterprise Value $25 $75 $125 $175 Jan-14 Apr-14 Jul-14 Oct-14 Jan-15 Apr-15 Jul-15 Oct-15 Jan-16 Macrogenics Biotech ETF Healthcare ETF Russell 2K
- 12. UOIG 12 University ofOregon Investment Group January 29th , 2016 rates in 2020, 2025 and 2030 were accessed from the World Health with linear interpolation between the stated dates. After forecasting incidence, market potential is narrowed down according to each drug’s stated patient type. Macrogenics’ oncology candidates are being evaluated for advanced (metastatic) cancer progression in patients who have already or are concurrently undergoing surgery, chemotherapy and radiation therapy, including those who have failed previous biologic-based treatments. Current rates for said patients were found in various academic sources and held fixed as a percentage of total patients across the forecast. Drug Pricing For drug pricing, sticker prices are non-representative of the actual dollars going to a manufacturer. Consequently, the wholesale acquisition cost (WAC) – the price paid by pharmacies to drug makers– has to be gathered or estimated. Because WACs are generally confidential, estimation is common. Fortunately, gross sales figures are reported by firms such as IMS Health while net sales are reported by manufacturers, leading to viable estimates. The WACs of comparable currently-marketed antibody-based oncology drugs were compiled from academic sources (when available), or estimated from sticker prices otherwise. The general estimate for gross-to-net pricing is 83%. In cases where one of Macrogenics’ pipeline candidates had a direct comparable, the corresponding WAC was used; otherwise, an average was taken across the data. Given patent protection and inelastic demand, manufacturers do not generally set prices according to market equilibrium, but instead estimate the maximum price a payer will bear while still offering formulary status and reimbursement. Drug prices – especially for specialty pharmaceuticals - have experienced considerable inflation in the past decade; Express Scripts’ Specialty Prescription Drug Index has nearly doubled (!) from 2007 to 2014. The author feels that this trend has its upper limits on Medicare and Medicaid budgets, public perceptions of the biopharmaceutical industry and budgetary pressure from politicians. Consequently, price inflation from current levels was forecasted to only double over the next 15 year period. Inflation was forecasted according to this rate for the WACs of all drugs in the revenue model. Market Penetration Developmental pipeline drugs must be evaluated not only against presently- marketed comparables (if they exist), but also the future potential of the current pipelines of other firms in the industry. Because a drug’s proof of concept in humans does not have to be established until the end of phase II testing, assigning any reasonable conviction to such estimates for sales decades away would be an exercise in deceit. Consequently, rules of thumb were used. Launch year penetration rates are not generally high for cancer drugs given patients’ aversion to immediately switching from current treatments unless a truly innovative product is entering the market. Consequently, launch penetration rates were kept at 5% for all drug forecasts. Following launch, drug sales tend to follow a predictable life cycle – with increasing market penetration until “peak sales”, whereby new competition erodes excess returns and sales growth declines before dramatically falling off after patent expiration gives generic competition. While increased difficulties in the biologic manufacturing process have generally insulated biotech firms from patent erosion, the emergence of more biosimilars into the US market in upcoming years is expected to lower this lead against traditional pharmaceuticals, including Figure 34: Oncology Drug Clinical Probabilities for Phase Transition and Launch Success Source: Nature Biotechnology Figure 35: Bottom-Up Sales Forecasting Process Source: Analyst’s Illustration Figure 36: Comparable Antibody-Based Drug Wholesale Acquisition Costs Source: Journal of Clinical Oncology Figure 37: Drug Sales Forecast Source: Analyst’s Forecast Phase Transition Launch I 68.90% 13.20% II 42.30% 19.16% III 54.70% 45.29% BLA 82.80% 82.80% Newly Diagnosed Patients Eligible Subgroups Market Penetration Brand Name Generic Name WAC Avastin bevacizumab $27,805 Erbitux cetuximab $59,526 Herceptin trastuzumab $48,792 Mylotarg gemtuzumab $17,496 Rituxan rituximab $15,670 $0M $500M $1000M $1500M $2000M $2500M 2020E 2022E 2024E 2026E 2028E 2030E Margetuximab Enoblituzumab MGD006 MGD007 MGD009
- 13. UOIG 13 University ofOregon Investment Group January 29th , 2016 those expected to compete against margetuximab. In cases where a drug did not have current existing competition (e.g., MGD006 for acute myeloid leukemia), peak penetration rates were forecasted to be higher than instances where both currently marketed drugs and upcoming biosimilars are projected to launch. For declines in penetration rates through the terminal year, 60-80% of peak sales penetration was used as a general range. It is important to note that this relates more to the limitations of the DCF in biotech valuation rather than underlying fundamentals. Modeling in a decline through terminal year has the effect of making terminal free cash flow growth negative, violating the “going concern” assumption of the model. Consequently, intermediate growth rates were used to project FCF growth back within range of the Group-mandated 3%. Revenue from Collaborative Research Macrogenics currently generates sales by out-licensing their technology platforms, performing pre-clinical R&D for larger firms, and licensing sales rights for pipeline candidates to outside firms. These services incur upfront payments followed by maintenance and milestone payments pending fulfillment of agreed- upon clinical, regulatory, and commercial milestones. Financial terms for these arrangements were accessed from Macrogenics’ most recent 10-Q and probability-adjusted according to clinical phase. Macrogenics holds options with certain firms to exercise for the arrangement of profit-sharing and co-marketing agreements following successful completion of a milestone (typically, entrance into phase III testing). Given the lack of available contractual terms and the marked lack of specific disease indications to forecast market potential, these options were not projected in the model. Preclinical Drugs Drugs currently in preclinical testing are not generally projected by biotech analysts. Not only are their disease indications and proof of concepts uncertain, but miniscule probability-to-market metrics and heavy discount rates from expected cash flows far in the future render such revenue streams nearly immaterial from a valuation perspective. However, because the advancement of preclinical-to-clinical products represents a cost of doing business for Macrogenics, preclinical R&D expenses were projected and probability-adjusted appropriately. (This includes expenses for MGD012, MGD013 and MGD014.) Cost of Goods Sold (COGS) Given a lack of commercial products, developmental biotech firms do not have COGS expenses until their initial drug launches. As such, COGS was projected to be in line with a 10 year historic industry average based on FactSet data. General and Administrative (G&A) Macrogenics’ current G&A expense consists of salaries and benefits for support- related employees. However, the firm is in the preparatory stages of building a salesforce in anticipation of future drug launches. Consequently, in recent quarters, G&A expenses have been above trailing annual averages seen in 2011- 2013. Caution was taken against overestimating expenses going forward, as oncology drugs require fewer sales representatives than industry averages given their work focuses on specialist rather than general practitioners. Research and Development (R&D) R&D expenses are generated from the discovery, manufacturing, and advancement of pipeline candidates through the preclinical and clinical testing process. Forecasts were based on the number of drugs Macrogenics has in each major clinical testing phase, estimated transition dates following completion of Figure 38: Revenue from Collaborative Research Source: Macrogenics 10-K Figure 39: Preclinical Drug Phase Transition Date Estimates Source: Analyst’s Calculations Figure 40: Clinical Pipeline Launch Date Estimates Source: Analyst’s Calculations $0M $20M $40M $60M $80M 2011A 2012A 2013A 2014A Boehringer Eli Lilly Government Agencies Gilead Green Cross Janssen Pfizer Servier Takeda Drug Phase Start Date End Date MGD012 Preclinical 10/1/2015 9/30/2018 MGD012 I 10/1/2018 7/31/2020 II 8/1/2020 1/30/2023 MGD012 III 1/31/2023 1/30/2027 MGD013 Preclinical 10/1/2015 9/30/2018 MGD013 I 10/1/2018 7/31/2020 II 8/1/2020 1/30/2023 MGD013 III 1/31/2023 1/30/2027 MGD014 Preclinical 10/1/2015 9/30/2018 MGD014 I 10/1/2018 7/31/2020 II 8/1/2020 1/30/2023 MGD014 III 1/31/2023 1/30/2027 Drug and Phase Indication Expected Launch Enoblituzumab - I Solid Tumors (+ipi) 7/2024 Enoblituzumab - I Solid Tumors (mono) 10/2022 Enoblituzumab - I Solid Tumors (+pembro) 5/2025 Margetuximab - III Breast (3+) 6/2020 Margetuximab - II Breast (1-2+) 4/2023 Margetuximab - I/II Gastric 11/2022 MGD006 - I AML 10/2024 MGD007 - I Colorectal 1/2025 MGD009 - I Solid Tumors 1/2025 MGD010 - I Autoimmune Disorders 5/2024 MGD011 - I B-Cell Malignancies 10/2024
- 14. UOIG 14 University ofOregon Investment Group January 29th , 2016 current clinical phases, and average cost per phase. Because little transparency exists on cost components of Macrogenics’ R&D expense, data for average drug trial costs and durations was taken from Karl Keegan’s Biotechnology Valuation to aid in forecasting the above. Expenses were probability-adjusted based on phase success rates. For current trials, additional adjustments were made for each drugs’ projected total phase expense versus costs already incurred. To account for future drug development outside their existing pipeline, additional expenses were projected on the “Other Preclinical Drugs” line. This, in part, falls in line with management’s desire to mature to a large-scale, fully integrated firm with a deep pipeline. As such expenses are fundamental to long-term business sustainability, and because pre-clinicals do not require rigorous approval prior to testing, these costs were not probability-adjusted. Finally, headcount-related expenses were projected according to current salaries for biotech research analysts found on Payscale and Glassdoor, and then adjusted according to an expected long-term salary inflation rate. Capital Expenditures and Depreciation Macrogenics’ management has stated plans to increase manufacturing capacity to produce drugs at the increased throughput required in phase III and commercial environments. Moreover, while their current manufacturing is adequate to handle margetuximab’s transition into phase III, management has stated that this will not be sufficient for additional late-stage candidates. Consequently, capital expenditures were projected to experience significant growth in anticipation of the firm’s first drug launch by 2020. Because Macrogenics’ plants are under operating lease agreements, projections for increased manufacturing needs were accounted for on the “Leaseholds Improvement” line. Gross leasehold improvements were then projected to decline to 0% growth by the terminal year. Depreciation was forecasted based on useful life assumptions from Macrogenics’ most recent10-K. Working Capital Working capital items were projected using their associated drivers listen on Macrogenics’ 10-K and slated to evolve from current levels to those seen in more mature biopharmaceutical firms. To define mature levels, a composite was computed from the largest firms in the industry – Gilead, Amgen, Celgene, and Biogen. Following their expected first drug launch, inventory was added to current assets. For AR, days sales outstanding was projected to peak in the interim period between first and additional drug launches (2020-2022) as the firm remains relatively new among drug wholesalers before declining following the expectation of increased bargaining power on payment terms. Deferred revenue arises from partnership agreements and represent upfront payments for licenses that are deemed not to have stand-alone value until further R&D has been conducted. Because current deferred revenue flows to the income statement in later periods, this was modeled in, with the new current balance becoming the change in long-term deferred revenue from the previous period. Adjustments to deferred revenue had a negligible impact on valuation. Tax Rate As of 2014, Macrogenics had $288.6M in federal and state net operating loss (NOL) carryforwards, and R&D tax credits. Expirations for these carryforwards are slated to take place from 2020 through 2035. Under the model, Macrogenics Figure 41: Research and Development Expense Forecast Source: Analyst’s Calculations Figure 42: Capital Expenditures and Depreciation Forecast Source: Analyst’s Calculations Figure 43: Gross PP&E Forecast Source: Analyst’s Calculations (300%) (200%) (100%) 0% 100% 200% 300% 400% 500% 600% $0M $20M $40M $60M $80M $100M $120M $140M $160M $180M 2015E 2017E 2019E 2021E 2023E 2025E 2027E 2029E Research and Development % Revenue $0M $5M $10M $15M $20M $25M $30M $35M 2015E 2017E 2019E 2021E 2023E 2025E 2027E 2029E Depreciation Capital Expenditures $0M $50M $100M $150M $200M 2015E 2017E 2019E 2021E 2023E 2025E 2027E 2029E Computer Equipment Furniture and Office Equipment Laboratory Equipment Leasehold Improvements Software
- 15. UOIG 15 University ofOregon Investment Group January 29th , 2016 will have exhausted current NOLs by 2025. After that, the tax rate was forecasted to increase to the US corporate marginal rate of 35% in line with Group standards. Beta Because shares of Macrogenics have been trading for less than 3 years, beta was calculated starting from the firm’s IPO date in October 2013. A terminal beta consisting of industry and comparable companies’ Hamada and Vasicek betas was also used to account for lowered capital costs following a forecasted maturation. Weighted Average Cost of Capital (WACC) A small cap premium of 100 basis points was added to Macrogenics’ WACC to account for operational risks. Even taking this into account, the final WACC of 14% in context to what is used among early stage biotech analysts when evaluating potential capital returns. According to Avance, a biotechnology valuation firm, WACCs between 15-20% are the industry norm for clinical stage firms. With that said, return on invested capital into perpetuity stood just below Macrogenics’ cost of capital in the model, suggesting a reasonable figure. Shareholder’s Equity Model To mitigate against negative cash balances in the years preceding drug approval and estimate dates of future stock issuance, an equity schedule was implemented. Current year prices for equity issuance were computed by taking Macrogenics’ volume-weighted average price (VWAP) since IPO. From there, the firm’s implied price-to-earnings multiple was projected to converge to current industry levels by the terminal year (an admittedly generous supposition). Assuming no additional non-dilutive financing, Macrogenics is estimated to issue at least 5M equity shares through 2019 to fund their pipeline and scale existing operations. Recommendation Macrogenics has no place in the portfolio of a long-term value-oriented investment fund. The firm has failed on each of its four original investment thesis points, and is overvalued on both relative and intrinsic measures. For these reasons, the author recommends a SELL in the Tall Firs portfolio. Final Valuation Price Weighting Discounted Cash Flow $17.45 90.00% Forward Comparables $14.28 10.00% Implied Price $17.13 Current Price $20.54 Overvalued (16.59%) Figure 44: Beta Estimates Source: Analyst’s Calculations Figure 45: Proceeds from Equity Issuance (Right Axis) vs. Total Shares Offered (Left Axis) Source: Macrogenics 10-K Figure 46: DCF Assumptions Source: Analyst’s Calculations Period Beta SE Weighting 1 Year Daily 1.54 0.21 0.00% Since IPO Daily 1.69 0.18 100.00% Since IPO Weekly 1.78 0.39 0.00% Macrogenics Beta 1.69 $0M $30M $60M $90M $120M $150M $180M 0M 1M 2M 3M 4M 5M 6M 7M 10/2013 2/2014 7/2015 Total Shares Offered Proceeds from Issuance TaxRate 35.00% Terminal Growth Rate 3.00% Risk Free Rate 2.13% Terminal Value 153,067 Beta 1.69 PVof Terminal Value 20,651 Market Risk Premium 6.45% Sumof PVFCF 599,537 % Equity 100.00% FirmValue 620,188 % Debt - Total Debt - CAPM/WACC 14.04% Minority Interests - Terminal Risk Free Rate 2.95% Market Capitalization 620,188 Terminal Beta 1.36 Fully Diluted Shares 35,539 Terminal % Equity 100.00% Implied Price $17.45 Terminal % Debt - Current Price $20.54 Terminal CAPM/WACC 12.74% Overvalued (15.04%) DiscountedFree Cash FlowAssumptions
- 16. UOIG 16 January 29th ,2016University of Oregon Investment Group Appendix 1 – Relative Valuation Comparables Analysis ($ in thousands) Macrogenics Celldex ImmunoGen Merrimack OncoMed Xencor Stock Characteristics Max Min Median Weight Avg. 24.65% 27.21% 15.57% 15.65% 16.93% Current Price $20.54 $6.31 $9.49 $9.14 $20.54 $9.60 $8.64 $6.31 $9.49 $11.57 Beta 1.89 1.34 1.43 1.52 1.69 1.89 1.43 1.45 1.34 1.36 Size Short-TermDebt - - - - - - - - - - Long-TermDebt 39,653 - - 6,174 - - - 39,653 - - Cash and Cash Equivalent 365,767 31,280 57,738 107,387 365,767 66,971 247,843 56,350 31,280 57,738 Non-Controlling Interest 481 - - 75 - - - 481 - - Preferred Stock - - - - - - - - - - Diluted Basic Shares 131,649 30,109 86,985 80,195 35,539 98,646 86,985 131,649 30,109 41,382 Market Capitalization 946,999 285,732 751,547 692,993 729,979 946,999 751,547 830,706 285,732 478,790 Enterprise Value 880,028 254,452 503,704 591,854 364,212 880,028 503,704 814,490 254,452 421,052 Growth Expectations % Revenue Growth 2019E 86.70% (26.40%) 67.90% 47.23% 55.10% 67.90% 69.90% 15.30% 86.70% (26.40%) % Revenue Growth 2020E 335.10% (28.60%) 56.20% 85.80% 175.00% 56.20% 60.50% 20.80% (28.60%) 335.10% % EBIT Growth 2019E 1375.70% 14.00% 253.60% 303.09% 14.00% 253.60% NM 162.80% 1375.70% NM % EBIT Growth 2020E 307.10% 49.60% 104.90% 135.98% NM 132.10% 307.10% 77.70% 49.60% NM % EPS Growth 2019E 1086.70% 21.80% 337.50% 258.95% 21.80% 147.60% NM 337.50% 1086.70% NM % EPS Growth 2020E 1041.30% 14.30% 144.65% 341.07% NM 115.00% 1041.30% 174.30% 14.30% NM Profitability Margins EBIT Margin 48.87% 12.33% 40.26% 35.96% 23.91% 48.87% 40.26% 28.73% 40.88% 12.33% Net Margin 37.39% 10.75% 23.25% 25.92% 23.52% 35.56% 23.25% 20.27% 37.39% 10.75% Qualitative Metrics Drugs in Phase I 13 2 5 8 8 11 13 2 5 5 Drugs in Phase II 5 2 3 3 2 5 2 3 2 3 Drugs in Phase III 1 - - .5 1 1 1 - - - Employee Headcount 317 108 306 241 246 156 317 306 108 306 Operating Results Revenue (2020E) 908,830 189,140 469,770 534,835 411,600 908,830 454,650 524,180 469,770 189,140 EBIT (2020E) 444,170 23,320 183,060 216,726 98,400 444,170 183,060 150,600 192,050 23,320 Net Income (2020E) 323,150 20,340 106,260 155,871 96,800 323,150 105,690 106,260 175,640 20,340 Multiples 1000 EV/Revenue 2.23x 0.54x 1.11x 1.24x 0.88x 0.97x 1.11x 1.55x 0.54x 2.23x EV/EBIT 18.06x 1.32x 2.75x 5.34x 3.70x 1.98x 2.75x 5.41x 1.32x 18.06x Market Cap/Net Income = P/E 23.54x 1.63x 7.11x 8.11x 7.54x 2.93x 7.11x 7.82x 1.63x 23.54x Multiple Implied Price Discounted Price Weight EV/Revenue $24.69 $14.60 50.00% EV/EBIT $25.08 $14.83 25.00% P/E $22.10 $13.07 25.00% Price Target $14.28 Current Price $20.54 Overvalued (30.50%)
- 17. UOIG 17 January 29th ,2016University of Oregon Investment Group Appendix 2 – Discounted Cash Flow Valuation DiscountedCash FlowAnalysis ($ in thousands) 2011A 2012A 2013A 2014A 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Total Revenue 57,207 63,826 58,035 47,797 128,147 98,046 43,243 49,666 16,455 22,181 53,783 88,515 295,805 503,269 914,120 1,393,148 1,764,342 2,041,918 2,326,689 1,758,352 % YoY Growth 0.00% 11.57% (9.07%) (17.64%) 168.11% (23.49%) (55.90%) 14.85% (66.87%) 34.80% 142.47% 64.58% 234.19% 70.14% 81.64% 52.40% 26.64% 15.73% 13.95% (24.43%) Cost of Goods Sold - - - - - - - - - 2,235 9,508 17,642 66,867 114,731 206,493 317,033 402,754 466,888 532,685 401,370 % Revenue - - - - - - - - - 10.08% 17.68% 19.93% 22.61% 22.80% 22.59% 22.76% 22.83% 22.87% 22.89% 22.83% Gross Profit $57,207 $63,826 $58,035 $47,797 $128,147 $98,046 $43,243 $49,666 $16,455 $19,946 $44,275 $70,873 $228,938 $388,539 $707,627 $1,076,116 $1,361,588 $1,575,030 $1,794,004 $1,356,982 Gross Margin 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 89.92% 82.32% 80.07% 77.39% 77.20% 77.41% 77.24% 77.17% 77.13% 77.11% 77.17% Depreciation and Amortization 1,147 960 1,193 1,822 2,602 3,906 5,431 6,658 8,547 8,687 9,979 11,316 12,656 13,944 15,090 16,112 16,940 17,529 17,841 17,846 % Revenue 2.01% 1.50% 2.06% 3.81% 2.03% 3.98% 12.56% 13.41% 51.94% 39.16% 18.55% 12.78% 4.28% 2.77% 1.65% 1.16% .96% .86% .77% 1.01% Research and Development 39,942 44,473 45,389 68,364 82,575 62,191 79,526 76,936 77,128 73,875 82,671 85,276 89,574 91,349 100,768 110,596 119,553 129,878 140,680 151,939 % Revenue 69.82% 69.68% 78.21% 143.03% 64.44% 63.43% 183.91% 154.91% 468.71% 333.06% 153.71% 96.34% 30.28% 18.15% 11.02% 7.94% 6.78% 6.36% 6.05% 8.64% General and Administrative 10,869 10,188 11,087 15,926 31,088 21,419 9,328 10,577 3,459 4,602 11,011 17,878 58,934 98,884 177,099 266,077 332,123 378,765 425,196 316,503 % Revenue 19.00% 15.96% 19.10% 33.32% 24.26% 21.85% 21.57% 21.30% 21.02% 20.75% 20.47% 20.20% 19.92% 19.65% 19.37% 19.10% 18.82% 18.55% 18.27% 18.00% Earnings Before Interest & Taxes $5,250 $8,205 $366 ($38,315) $11,882 $10,530 ($51,043) ($44,505) ($72,679) ($67,218) ($59,386) ($43,596) $67,773 $184,362 $414,671 $683,331 $892,971 $1,048,858 $1,210,287 $870,694 % Revenue 9.18% 12.86% .63% (80.16%) 9.27% 10.74% (118.04%) (89.61%) (441.67%) (303.05%) (110.42%) (49.25%) 22.91% 36.63% 45.36% 49.05% 50.61% 51.37% 52.02% 49.52% Other Expense (Income) (1,467) (157) 627 (2) 88 - - - - - - - - - - - - - - - % Revenue (2.57%) (.25%) 1.08% (.00%) .07% - - - - - - - - - - - - - - - Earnings Before Taxes 6,717 8,362 (261) (38,313) 11,794 10,530 (51,043) (44,505) (72,679) (67,218) (59,386) (43,596) 67,773 184,362 414,671 683,331 892,971 1,048,858 1,210,287 870,694 % Revenue 11.74% 13.10% (.45%) (80.16%) 9.20% 10.74% (118.04%) (89.61%) (441.67%) (303.05%) (110.42%) (49.25%) 22.91% 36.63% 45.36% 49.05% 50.61% 51.37% 52.02% 49.52% Less Taxes (Benefits) - - - - - - - - - - - - - - 21,736 239,166 312,540 367,100 423,600 304,743 TaxRate - - - - - - - - - - - - - - 5.24% 35.00% 35.00% 35.00% 35.00% 35.00% Net Income $6,717 $8,362 ($261) ($38,313) $11,794 $10,530 ($51,043) ($44,505) ($72,679) ($67,218) ($59,386) ($43,596) $67,773 $184,362 $392,935 $444,165 $580,431 $681,758 $786,686 $565,951 Net Margin 11.74% 13.10% (.45%) (80.16%) 9.20% 10.74% (118.04%) (89.61%) (441.67%) (303.05%) (110.42%) (49.25%) 22.91% 36.63% 42.99% 31.88% 32.90% 33.39% 33.81% 32.19% Add Back: Depreciation and Amortization 1,147 960 1,193 1,822 2,602 3,906 5,431 6,658 8,547 8,687 9,979 11,316 12,656 13,944 15,090 16,112 16,940 17,529 17,841 17,846 Operating Cash Flow $7,864 $9,322 $932 ($36,491) $14,396 $14,436 ($45,612) ($37,847) ($64,132) ($58,532) ($49,407) ($32,281) $80,430 $198,306 $408,025 $460,277 $597,372 $699,287 $804,527 $583,797 % Revenue 13.75% 14.61% 1.61% (76.35%) 11.23% 14.72% (105.48%) (76.20%) (389.73%) (263.88%) (91.86%) (36.47%) 27.19% 39.40% 44.64% 33.04% 33.86% 34.25% 34.58% 33.20% Current Assets 3,444 2,184 2,976 7,146 11,559 15,010 7,453 9,506 3,463 6,198 18,119 32,501 108,840 179,077 313,229 460,976 562,186 624,597 683,497 671,059 % Revenue 6.02% 3.42% 5.13% 14.95% 9.02% 15.31% 17.24% 19.14% 21.04% 27.94% 33.69% 36.72% 36.79% 35.58% 34.27% 33.09% 31.86% 30.59% 29.38% 38.16% Current Liabilities 44,289 29,728 28,822 27,094 19,542 38,625 49,359 49,379 51,964 53,668 66,547 77,218 115,451 156,809 241,990 351,109 450,421 540,589 639,167 551,732 % Revenue 77.42% 46.58% 49.66% 56.69% 15.25% 39.39% 114.15% 99.42% 315.79% 241.96% 123.73% 87.24% 39.03% 31.16% 26.47% 25.20% 25.53% 26.47% 27.47% 31.38% Net Working Capital ($40,845) ($27,544) ($25,846) ($19,948) ($7,983) ($23,614) ($41,906) ($39,873) ($48,501) ($47,471) ($48,428) ($44,717) ($6,611) $22,268 $71,239 $109,867 $111,765 $84,009 $44,330 $119,327 % Revenue (71.40%) (43.16%) (44.54%) (41.73%) (6.23%) (24.09%) (96.91%) (80.28%) (294.74%) (214.02%) (90.04%) (50.52%) (2.23%) 4.42% 7.79% 7.89% 6.33% 4.11% 1.91% 6.79% Change in Working Capital - 13,301 1,698 5,898 11,965 (15,631) (18,292) 2,033 (8,628) 1,030 (957) 3,711 38,106 28,879 48,970 38,628 1,898 (27,756) (39,679) 74,997 Capital Expenditures 500 940 2,961 3,572 5,281 6,259 7,358 8,577 9,907 11,337 12,690 14,003 15,225 16,301 17,180 17,811 18,154 18,179 17,867 17,215 % Revenue .87% 1.47% 5.10% 7.47% 4.12% 6.38% 17.02% 17.27% 60.21% 51.11% 23.60% 15.82% 5.15% 3.24% 1.88% 1.28% 1.03% .89% .77% .98% UnleveredFree Cash Flow $7,364 ($4,919) ($3,727) ($45,961) ($2,849) $23,808 ($34,678) ($48,457) ($65,412) ($70,899) ($61,140) ($49,995) $27,099 $153,125 $341,875 $403,838 $577,320 $708,864 $826,339 $491,586 DiscountedFree Cash Flow $20,203 ($25,805) ($31,620) ($37,429) ($35,575) ($26,902) ($19,291) $9,169 $45,433 $88,951 $92,139 $115,507 $124,368 $127,133 $66,321 Excess Returns on Capital Considerations x Return on Invested Capital 36.52% 34.81% (.27%) (26.10%) 7.51% 6.10% (16.24%) (16.07%) (14.07%) (14.74%) (14.65%) (11.98%) 15.58% 29.54% 38.36% 30.04% 28.02% 24.64% 22.04% 13.65% Weighted Average Cost of Capital 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% 14.04% Excess Returns 22.49% 20.78% (14.31%) (40.14%) (6.53%) (7.93%) (30.28%) (30.11%) (28.11%) (28.77%) (28.69%) (26.02%) 1.54% 15.50% 24.32% 16.00% 13.99% 10.60% 8.01% (.39%)
- 18. UOIG 18 January 29th ,2016University of Oregon Investment Group Appendix 3 – Three Statement ConsolidatedStatement of Income ($ in thousands) 2011A 2012A 2013A 2014A 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Revenue fromDrug Sales - - - - - - - - - 9,674 41,153 76,355 289,406 496,560 893,712 1,372,134 1,743,139 2,020,714 2,305,485 1,737,149 % Growth - - - - - - - - - - 325.39% 85.54% 279.03% 71.58% 79.98% 53.53% 27.04% 15.92% 14.09% (24.65%) Revenue FromCollaborative Research 47,054 59,646 56,753 47,264 126,915 90,883 42,450 48,874 15,663 11,714 11,838 11,368 5,607 5,917 19,616 20,222 20,411 20,411 20,411 20,411 % Growth - 26.76% (4.85%) (16.72%) 168.52% (28.39%) (53.29%) 15.13% (67.95%) (25.21%) 1.05% (3.97%) (50.68%) 5.53% 231.53% 3.09% .94% - - - Grant Revenue 10,153 4,180 1,282 533 1,232 - - - - - - - - - - - - - - - % Growth - (58.83%) (69.33%) (58.42%) 131.14% (100.00%) - - - - - - - - - - - - - - Total Revenue 57,207 63,826 58,035 47,797 128,147 98,046 43,243 49,666 16,455 22,181 53,783 88,515 295,805 503,269 914,120 1,393,148 1,764,342 2,041,918 2,326,689 1,758,352 % Growth - 11.57% (9.07%) (17.64%) 168.11% (23.49%) (55.90%) 14.85% (66.87%) 34.80% 142.47% 64.58% 234.19% 70.14% 81.64% 52.40% 26.64% 15.73% 13.95% (24.43%) Cost of Goods Sold - - - - - - - - - 2,235 9,508 17,642 66,867 114,731 206,493 317,033 402,754 466,888 532,685 401,370 % Revenue from Drug Sales - - - - - - - - - 23.11% 23.11% 23.11% 23.11% 23.11% 23.11% 23.11% 23.11% 23.11% 23.11% 23.11% Gross Income 57,207 63,826 58,035 47,797 128,147 98,046 43,243 49,666 16,455 19,946 44,275 70,873 228,938 388,539 707,627 1,076,116 1,361,588 1,575,030 1,794,004 1,356,982 Gross Margin 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 89.92% 82.32% 80.07% 77.39% 77.20% 77.41% 77.24% 77.17% 77.13% 77.11% 77.17% Research and Development 41,089 45,433 46,582 70,186 85,177 66,096 84,957 83,594 85,675 82,562 92,650 96,592 102,231 105,293 115,857 126,708 136,494 147,407 158,521 169,785 % Total Revenue 71.82% 71.18% 80.27% 146.84% 66.47% 67.41% 196.47% 168.31% 520.65% 372.22% 172.27% 109.12% 34.56% 20.92% 12.67% 9.10% 7.74% 7.22% 6.81% 9.66% General and Administrative 10,869 10,188 11,087 15,926 31,088 21,419 9,328 10,577 3,459 4,602 11,011 17,878 58,934 98,884 177,099 266,077 332,123 378,765 425,196 316,503 % Total Revenue 19.00% 15.96% 19.10% 33.32% 24.26% 21.85% 21.57% 21.30% 21.02% 20.75% 20.47% 20.20% 19.92% 19.65% 19.37% 19.10% 18.82% 18.55% 18.27% 18.00% Operating Income 5,250 8,205 366 (38,315) 11,882 10,530 (51,043) (44,505) (72,679) (67,218) (59,386) (43,596) 67,773 184,362 414,671 683,331 892,971 1,048,858 1,210,287 870,694 Operating Margin 9.18% 12.86% .63% (80.16%) 9.27% 10.74% (118.04%) (89.61%) (441.67%) (303.05%) (110.42%) (49.25%) 22.91% 36.63% 45.36% 49.05% 50.61% 51.37% 52.02% 49.52% Other Expense (Income) (1,467) (157) 627 (2) 88 - - - - - - - - - - - - - - - % Total Revenue (2.57%) (.25%) 1.08% (.00%) .07% - - - - - - - - - - - - - - - Pre-TaxIncome 6,717 8,362 (261) (38,313) 11,794 10,530 (51,043) (44,505) (72,679) (67,218) (59,386) (43,596) 67,773 184,362 414,671 683,331 892,971 1,048,858 1,210,287 870,694 % Total Revenue 11.74% 13.10% (.45%) (80.16%) 9.20% 10.74% (118.04%) (89.61%) (441.67%) (303.05%) (110.42%) (49.25%) 22.91% 36.63% 45.36% 49.05% 50.61% 51.37% 52.02% 49.52% Provision for Income Taxes - - - - - - - - - - - - - - 21,736 239,166 312,540 367,100 423,600 304,743 Tax Rate - - - - - - - - - - - - - - 5.24% 35.00% 35.00% 35.00% 35.00% 35.00% Net Income (Loss) 6,717 8,362 (261) (38,313) 11,794 10,530 (51,043) (44,505) (72,679) (67,218) (59,386) (43,596) 67,773 184,362 392,935 444,165 580,431 681,758 786,686 565,951 Net Margin 11.74% 13.10% (.45%) (80.16%) 9.20% 10.74% (118.04%) (89.61%) (441.67%) (303.05%) (110.42%) (49.25%) 22.91% 36.63% 42.99% 31.88% 32.90% 33.39% 33.81% 32.19% ConsolidatedBalance Sheet ($ in thousands) 2011A 2012A 2013A 2014A 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Assets Cash and Cash Equivalents 55,219 47,744 116,481 157,591 153,513 182,306 340,388 299,123 545,863 481,914 429,220 381,405 411,992 569,807 918,899 1,332,801 1,922,347 2,645,079 3,486,936 3,991,231 Restricted Cash 582 405 405 300 - - - - - - - - - - - - - - - - Accounts Receivable 3,398 2,046 2,004 2,935 9,086 8,174 4,438 6,043 2,315 3,533 9,615 17,509 54,785 86,628 146,259 205,346 237,824 248,824 254,980 347,817 Prepaid Expenses 46 138 972 4,211 2,473 6,836 3,015 3,463 1,147 1,546 3,750 6,171 20,622 35,084 63,723 97,113 122,985 142,330 162,175 122,557 Inventories - - - - - - - - - 1,118 4,754 8,821 33,434 57,365 103,246 158,516 201,377 233,444 266,342 200,685 Total Current Assets 59,245 50,332 119,862 165,037 165,072 197,316 347,841 308,629 549,325 488,111 447,339 413,906 520,832 748,884 1,232,127 1,793,777 2,484,533 3,269,677 4,170,432 4,662,289 Property, Plant and Equipment, Net 3,288 3,268 5,035 6,785 9,464 11,817 13,744 15,663 17,024 19,674 22,385 25,073 27,642 29,999 32,089 33,787 35,001 35,650 35,676 35,045 Other Long-TermAssets 148 147 885 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 2,064 Total Long-Term Assets 3,436 3,415 5,920 8,849 11,528 13,881 15,808 17,727 19,088 21,738 24,449 27,137 29,706 32,063 34,153 35,851 37,065 37,714 37,740 37,109 Total Assets $62,681 $53,747 $125,782 $173,886 $176,600 $211,197 $363,650 $326,356 $568,413 $509,849 $471,788 $441,043 $550,538 $780,947 $1,266,280 $1,829,628 $2,521,597 $3,307,391 $4,208,173 $4,699,398 Liabilities Accounts Payable 11,052 3,739 3,169 1,669 2,857 10,503 14,212 17,087 18,910 21,712 30,961 40,201 76,393 116,632 197,999 303,197 398,967 485,183 579,733 488,212 Accrued Expenses 1,052 1,237 3,584 7,930 6,052 23,611 30,365 29,894 30,656 29,558 33,188 34,619 36,661 37,780 41,594 45,514 49,056 53,008 57,036 61,122 Lease Exit Liability 534 629 1,439 1,642 1,866 2,113 2,385 - - - - - - - - - - - - - Deferred Revenue 31,653 24,123 20,267 14,248 7,163 793 793 793 793 793 793 793 793 793 793 793 793 793 793 793 Other Liabilities - - 363 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 1,605 Total Current Liabilities 44,289 29,728 28,822 27,094 19,542 38,625 49,359 49,379 51,964 53,668 66,547 77,218 115,451 156,809 241,990 351,109 450,421 540,589 639,167 551,732 Lease Exit Liability, Net Of Current Portion 10,074 9,445 8,006 6,364 4,498 2,385 0 - - - - - - - - - - - - - Deferred Rent Liability 2,361 2,802 2,904 2,670 6,079 4,887 3,694 2,501 1,309 116 - - - - - - - - - - Deferred Revenue, Net Of Current Portion 23,237 19,956 7,136 16,472 11,889 11,096 10,304 9,511 8,719 7,926 7,133 6,341 5,548 4,756 3,963 3,170 2,378 1,585 793 - Total Long-Term Liabilities 35,875 32,256 18,046 25,506 22,466 18,368 13,998 12,013 10,027 8,042 7,133 6,341 5,548 4,756 3,963 3,170 2,378 1,585 793 - Total Liabilities $80,165 $61,984 $46,868 $52,600 $42,009 $56,993 $63,357 $61,391 $61,991 $61,710 $73,680 $83,559 $120,999 $161,565 $245,953 $354,279 $452,799 $542,174 $639,959 $551,732 Total Equity ($17,484) ($8,237) $78,914 $121,286 $134,591 $154,205 $300,292 $264,965 $506,422 $448,139 $398,108 $357,485 $429,538 $619,383 $1,020,327 $1,475,349 $2,068,799 $2,765,217 $3,568,213 $4,147,667
- 19. UOIG 19 January 29th ,2016University of Oregon Investment Group Appendix 3 – Three Statement (Continued) ConsolidatedStatement of Cash Flows ($ in thousands) 2011A 2012A 2013A 2014A 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Cash Provided by (Used in) Operating Activities Net Income 6,717 8,362 (261) (38,313) 11,794 10,530 (51,043) (44,505) (72,679) (67,218) (59,386) (43,596) 67,773 184,362 392,935 444,165 580,431 681,758 786,686 565,951 Adjustments to Reconcile Net Income to Cash Providedby Operating Activities Depreciation 1,147 960 1,193 1,822 2,602 3,906 5,431 6,658 8,547 8,687 9,979 11,316 12,656 13,944 15,090 16,112 16,940 17,529 17,841 17,846 Stock-Based Compensation 2,348 838 862 3,244 847 2,410 2,561 2,522 2,323 2,262 2,700 2,973 4,280 5,483 8,009 10,857 13,019 14,660 16,310 13,502 Fair Value Adjustment Of Warrant Liability (1,459) (151) 626 - - - - - - - - - - - - - - - - - Changes In Operating Assets AndLiabilities: Accounts Receivable 12,551 1,352 42 (931) (6,151) 912 3,736 (1,605) 3,727 (1,218) (6,082) (7,894) (37,276) (31,844) (59,631) (59,087) (32,477) (11,000) (6,156) (92,837) Prepaid Expenses 77 (91) (834) (3,239) 1,738 (4,363) 3,821 (448) 2,316 (399) (2,203) (2,421) (14,451) (14,462) (28,639) (33,390) (25,872) (19,345) (19,845) 39,618 Restricted Cash (1) 177 - 105 300 - - - - - - - - - - - - - - - Inventories - - - - - - - - - (1,118) (3,637) (4,067) (24,613) (23,932) (45,881) (55,270) (42,860) (32,067) (32,898) 65,657 Accounts Payable (10,271) (7,312) (570) (1,500) 1,188 7,647 3,708 2,875 1,824 2,802 9,249 9,240 36,192 40,239 81,367 105,198 95,770 86,216 94,550 (91,521) Accrued Expenses 273 185 2,347 4,346 (1,878) 17,559 6,754 (471) 761 (1,097) 3,630 1,431 2,041 1,119 3,814 3,921 3,542 3,952 4,028 4,086 Lease Exit Liability (447) (534) (629) (1,439) (1,642) (1,866) (2,113) (2,385) - - - - - - - - - - - - Deferred Revenue (4,276) (10,810) (16,676) 3,317 (11,668) (7,163) (793) (793) (793) (793) (793) (793) (793) (793) (793) (793) (793) (793) (793) (793) Deferred Rent 232 441 102 (234) 3,409 (1,193) (1,193) (1,193) (1,193) (1,193) (116) - - - - - - - - - Net Cash UsedIn Operating Activities $6,758 ($6,582) ($14,173) ($32,759) $539 $28,379 ($29,129) ($39,343) ($55,167) ($59,285) ($46,658) ($33,811) $45,811 $174,117 $366,271 $431,713 $607,700 $740,911 $859,723 $521,510 Cash Provided by (Used in) Investing Activities Purchases of Property and Equipment (500) (940) (2,961) (3,572) (5,281) (6,259) (7,358) (8,577) (9,907) (11,337) (12,690) (14,003) (15,225) (16,301) (17,180) (17,811) (18,154) (18,179) (17,867) (17,215) Net Cash Providedby (Usedin) Investing Activities ($500) ($940) ($2,961) ($3,572) ($5,281) ($6,259) ($7,358) ($8,577) ($9,907) ($11,337) ($12,690) ($14,003) ($15,225) ($16,301) ($17,180) ($17,811) ($18,154) ($18,179) ($17,867) ($17,215) Cash Provided by (Used in) Financing Activities Proceeds FromIssuance Of Common Stock, Net Of Offering Costs 70 47 84,771 76,716 - - 187,915 - 305,158 - - - - - - - - - - - Proceeds FromStock Option Exercises - - 1,100 744 664 6,673 6,655 6,655 6,655 6,673 6,655 - - - - - - - - - Net Cash Providedby (Usedin) Financing Activities $12,085 $47 $85,871 $77,441 $664 $6,673 $194,569 $6,655 $311,813 $6,673 $6,655 - - - - - - - - - Net Change in Cash Position Net Change in Cash and Cash Equivalents 18,343 (7,475) 68,738 41,110 (4,078) 28,793 158,082 (41,265) 246,739 (63,949) (52,694) (47,815) 30,586 157,815 349,092 413,902 589,546 722,732 841,856 504,295 Cash and Cash Equivalents at Beginning of Period 36,876 55,219 47,744 116,481 157,591 153,513 182,306 340,388 299,123 545,863 481,914 429,220 381,405 411,992 569,807 918,899 1,332,801 1,922,347 2,645,079 3,486,936 Cash and Cash Equivalents at End of Period 55,219 47,744 116,481 157,591 153,513 182,306 340,388 299,123 545,863 481,914 429,220 381,405 411,992 569,807 918,899 1,332,801 1,922,347 2,645,079 3,486,936 3,991,231
- 20. UOIG 20 January 29th ,2016University of Oregon Investment Group Appendix 4 – Stockholder’s Equity Model Stockholders' Equity Model x ($ in thousands) 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Beginning Equity Balance 121,286 134,591 154,205 300,292 264,965 506,422 448,139 398,108 357,485 429,538 619,383 1,020,327 1,475,349 2,068,799 2,765,217 3,568,213 Net Income 11,794 10,530 (51,043) (44,505) (72,679) (67,218) (59,386) (43,596) 67,773 184,362 392,935 444,165 580,431 681,758 786,686 565,951 Stock-Based Compensation 847 2,410 2,561 2,522 2,323 2,262 2,700 2,973 4,280 5,483 8,009 10,857 13,019 14,660 16,310 13,502 Proceeds fromIssuance of Common Stock - - 187,915 - 305,158 - - - - - - - - - - - Option Proceeds 664 6,673 6,655 6,655 6,655 6,673 6,655 - - - - - - - - - New Shares Issued fromOptions 277 503 502 502 502 503 502 - - - - - - - - - Average Strike Price $2.40 $13.26 $13.26 $13.26 $13.26 $13.26 $13.26 $13.26 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 $0.00 Ending Equity Balance 134,591 154,205 300,292 264,965 506,422 448,139 398,108 357,485 429,538 619,383 1,020,327 1,475,349 2,068,799 2,765,217 3,568,213 4,147,667 Shares Outstanding Schedule x ($ in thousands) 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Beginning Basic Shares Outstanding 34,312 34,589 35,092 38,094 38,596 41,598 42,101 42,603 42,603 42,603 42,603 42,603 42,603 42,603 42,603 42,603 Shares Issued fromOptions 277 503 502 502 502 503 502 - - - - - - - - - Shares Issued for Capital Funds - - 2,500 - 2,500 - - - - - - - - - - - Ending Basic Shares Outstanding 34,589 35,092 38,094 38,596 41,598 42,101 42,603 42,603 42,603 42,603 42,603 42,603 42,603 42,603 42,603 42,603 Effect of Dilutive Securities - - - - - - - - - - - - - - - - Ending Diluted Shares Outstanding 34,589 35,092 38,094 38,596 41,598 42,101 42,603 42,603 42,603 42,603 42,603 42,603 42,603 42,603 42,603 42,603 Share Issuance Assumptions x $USD, Shares in Thousand 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Current Year EPS ($ USD) $0.34 $0.30 ($1.34) ($1.15) ($1.75) ($1.60) ($1.39) ($1.02) $1.59 $4.33 $9.22 $10.43 $13.62 $16.00 $18.47 $13.28 Implied P/E Multiple 82.9x 172.3x (56.1x) (85.5x) (69.9x) (91.1x) (121.2x) (188.0x) 135.7x 55.3x 28.5x 27.5x 22.7x 20.8x 19.3x 28.6x Projected Share Price ($ USD) $28.27 $51.72 $75.17 $98.61 $122.06 $145.51 $168.96 $192.41 $215.86 $239.31 $262.76 $286.20 $309.65 $333.10 $356.55 $380.00 Shares Issued (Repurchased) - - 2,500 - 2,500 - - - - - - - - - - - Total Shares Unissued fromCharter 90,411 89,908 86,906 86,404 83,402 82,899 82,397 82,397 82,397 82,397 82,397 82,397 82,397 82,397 82,397 82,397 Cash and Cash Equivalents ($ Thousands) 153,513 182,306 340,388 299,123 545,863 481,914 429,220 381,405 411,992 569,807 918,899 1,332,801 1,922,347 2,645,079 3,486,936 3,991,231
- 21. UOIG 21 January 29th ,2016University of Oregon Investment Group Appendix 5 – Property, Plant and Equipment Model Net PP&EModel x ($ in thousands) 2012A 2013A 2014A 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Fixed Tangible Assets Computer Equipment 2,004 2,379 2,596 2,856 3,127 3,408 3,698 3,994 4,293 4,605 4,927 5,260 5,601 5,952 6,309 6,671 7,038 7,408 7,778 % Growth - 18.73% 9.12% 10.00% 9.50% 9.00% 8.50% 8.00% 7.50% 7.25% 7.00% 6.75% 6.50% 6.25% 6.00% 5.75% 5.50% 5.25% 5.00% % Gross PP&E 11.38% 11.57% 10.75% 9.71% 8.76% 7.92% 7.16% 6.49% 5.89% 5.38% 4.95% 4.58% 4.27% 4.01% 3.80% 3.62% 3.48% 3.36% 3.28% % Revenue 3.14% 4.10% 5.43% 2.23% 3.19% 7.88% 7.45% 24.27% 19.36% 8.56% 5.57% 1.78% 1.11% .65% .45% .38% .34% .32% .44% Furniture and Office Equipment 651 651 751 826 905 986 1,070 1,155 1,242 1,332 1,425 1,522 1,620 1,722 1,825 1,930 2,036 2,143 2,250 % Growth - (0.00%) 15.36% 10.00% 9.50% 9.00% 8.50% 8.00% 7.50% 7.25% 7.00% 6.75% 6.50% 6.25% 6.00% 5.75% 5.50% 5.25% 5.00% % Gross PP&E 3.70% 3.17% 3.11% 2.81% 2.54% 2.29% 2.07% 1.88% 1.70% 1.56% 1.43% 1.33% 1.24% 1.16% 1.10% 1.05% 1.01% .97% .95% % Revenue 1.02% 1.12% 1.57% .64% .92% 2.28% 2.15% 7.02% 5.60% 2.48% 1.61% .51% .32% .19% .13% .11% .10% .09% .13% Laboratory Equipment 8,748 11,166 13,917 17,396 21,571 26,533 32,370 39,168 47,001 55,931 65,999 77,219 89,574 103,010 117,431 132,698 148,621 164,970 181,467 % Growth - 27.64% 24.64% 25.00% 24.00% 23.00% 22.00% 21.00% 20.00% 19.00% 18.00% 17.00% 16.00% 15.00% 14.00% 13.00% 12.00% 11.00% 10.00% % Gross PP&E 49.68% 54.29% 57.65% 59.13% 60.46% 61.65% 62.72% 63.67% 64.51% 65.38% 66.30% 67.28% 68.34% 69.48% 70.71% 72.03% 73.43% 74.89% 76.41% % Revenue 13.71% 19.24% 29.12% 13.58% 22.00% 61.36% 65.18% 238.02% 211.90% 103.99% 74.56% 26.10% 17.80% 11.27% 8.43% 7.52% 7.28% 7.09% 10.32% Leasehold Improvements 4,882 4,895 5,193 6,491 8,049 9,900 12,079 14,615 17,538 20,695 24,006 27,367 30,651 33,716 36,413 38,598 40,142 40,945 40,945 % Growth - 0.27% 6.09% 25.00% 24.00% 23.00% 22.00% 21.00% 20.00% 18.00% 16.00% 14.00% 12.00% 10.00% 8.00% 6.00% 4.00% 2.00% 0.00% % Gross PP&E 27.73% 23.80% 21.51% 22.06% 22.56% 23.00% 23.40% 23.76% 24.07% 24.19% 24.11% 23.84% 23.38% 22.74% 21.93% 20.95% 19.83% 18.59% 17.24% % Revenue 7.65% 8.43% 10.86% 5.07% 8.21% 22.90% 24.32% 88.82% 79.07% 38.48% 27.12% 9.25% 6.09% 3.69% 2.61% 2.19% 1.97% 1.76% 2.33% Software 1,323 1,477 1,683 1,851 2,027 2,210 2,397 2,589 2,783 2,985 3,194 3,410 3,631 3,858 4,090 4,325 4,563 4,803 5,043 % Growth - 11.63% - 10.00% 9.50% 9.00% 8.50% 8.00% 7.50% 7.25% 7.00% 6.75% 6.50% 6.25% 6.00% 5.75% 5.50% 5.25% 5.00% % Gross PP&E 7.51% 7.18% 6.97% 6.29% 5.68% 5.13% 4.64% 4.21% 3.82% 3.49% 3.21% 2.97% 2.77% 2.60% 2.46% 2.35% 2.25% 2.18% 2.12% % Revenue 2.07% 2.55% 3.52% 1.44% 2.07% 5.11% 4.83% 15.73% 12.55% 5.55% 3.61% 1.15% .72% .42% .29% .25% .22% .21% .29% Gross PP&E 17,607 20,568 24,140 29,421 35,679 43,037 51,614 61,521 72,858 85,548 99,552 114,777 131,078 148,258 166,068 184,222 202,401 220,268 237,482 % Growth - 16.82% 17.37% 21.87% 21.27% 20.62% 19.93% 19.20% 18.43% 17.42% 16.37% 15.29% 14.20% 13.11% 12.01% 10.93% 9.87% 8.83% 7.82% % Revenue 27.59% 35.44% 50.51% 22.96% 36.39% 99.52% 103.92% 373.87% 328.47% 159.06% 112.47% 38.80% 26.05% 16.22% 11.92% 10.44% 9.91% 9.47% 13.51% Less Accumulated Depreciation 14,339 15,532 17,354 19,957 23,862 29,293 35,951 44,497 53,184 63,163 74,478 87,135 101,079 116,169 132,281 149,221 166,751 184,591 202,437 % Gross PP&E 81.44% 75.52% 71.89% 67.83% 66.88% 68.06% 69.65% 72.33% 73.00% 73.83% 74.81% 75.92% 77.11% 78.36% 79.65% 81.00% 82.39% 83.80% 85.24% Total Net PP&E 3,268 5,036 6,786 9,464 11,817 13,744 15,663 17,024 19,674 22,385 25,073 27,642 29,999 32,089 33,787 35,001 35,650 35,677 35,045 % Growth - 54.09% 34.75% 39.47% 24.86% 16.31% 13.96% 8.69% 15.57% 13.78% 12.01% 10.24% 8.53% 6.97% 5.29% 3.59% 1.86% .07% (1.77%) % Revenue 5.12% 8.68% 14.20% 7.39% 12.05% 31.78% 31.54% 103.45% 88.70% 41.62% 28.33% 9.34% 5.96% 3.51% 2.43% 1.98% 1.75% 1.53% 1.99% Depreciation 960 1,193 1,822 2,602 3,906 5,431 6,658 8,547 8,687 9,979 11,316 12,656 13,944 15,090 16,112 16,940 17,529 17,841 17,846 % Gross PP&E 29.38% 23.69% 26.85% 27.49% 33.05% 39.51% 42.51% 50.20% 44.15% 44.58% 45.13% 45.79% 46.48% 47.03% 47.69% 48.40% 49.17% 50.01% 50.92% Capital Expenditures 940 2,961 3,572 5,281 6,259 7,358 8,577 9,907 11,337 12,690 14,003 15,225 16,301 17,180 17,811 18,154 18,179 17,867 17,215 % Revenue 1.47% 5.10% 7.47% 4.12% 6.38% 17.02% 17.27% 60.21% 51.11% 23.60% 15.82% 5.15% 3.24% 1.88% 1.28% 1.03% .89% .77% .98%
- 22. UOIG 22 January 29th ,2016University of Oregon Investment Group Appendix 6 – Depreciation Schedule Depreciation Schedule 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E 1,496 1,496 1,496 1,095 1,095 21 21 21 21 21 - - - - - - 1,106 1,106 1,106 963 963 8 8 8 8 8 - - - - - - 1,303 1,303 1,303 1,154 1,154 8 8 8 8 8 - - - - - 1,525 1,525 1,525 1,371 1,371 8 8 8 8 8 - - - - 1,771 1,771 1,771 1,611 1,611 8 8 8 8 8 - - - 2,038 2,038 2,038 1,875 1,875 9 9 9 9 9 - - 2,325 2,325 2,325 2,160 2,160 9 9 9 9 9 - 2,597 2,597 2,597 2,426 2,426 9 9 9 9 9 2,862 2,862 2,862 2,685 2,685 9 9 9 9 3,108 3,108 3,108 2,926 2,926 10 10 10 3,326 3,326 3,326 3,138 3,138 10 10 3,503 3,503 3,503 3,310 3,310 10 3,630 3,630 3,630 3,434 3,434 3,700 3,700 3,700 3,501 3,706 3,706 3,706 3,644 3,644 3,514 Period 5 Period 16 Period 15 Period 14 Period 13 Period 12 Period 11 Period 10 Period 9 Period 8 Period 7 Period 6 Period 4 Period 3 Period 2 Period 1 Asset Base
- 23. UOIG 23 January 29th ,2016University of Oregon Investment Group Appendix 7 –Consolidated Revenue from Drug Sales Drug Sales ($ in thousands) 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Margetuximab 9,674 41,153 65,800 135,970 242,513 309,285 380,348 455,624 416,077 371,304 321,642 % Growth - 325.39% 59.89% 106.64% 78.36% 27.53% 22.98% 19.79% (8.68%) (10.76%) (13.38%) % of Total Revenue 100.00% 100.00% 86.18% 46.98% 48.84% 34.61% 27.72% 26.14% 20.59% 16.11% 18.52% Enoblituzumab (MGA-271) - - 10,554 153,436 253,863 364,939 485,085 466,027 442,221 413,749 380,779 % Growth - - - 1353.78% 65.45% 43.75% 32.92% (3.93%) (5.11%) (6.44%) (7.97%) % of Total Revenue - - 13.82% 53.02% 51.12% 40.83% 35.35% 26.73% 21.88% 17.95% 21.92% MGD006 - - - - 184 3,784 6,773 10,055 13,616 10,320 11,816 % Growth - - - - - 1960.66% 78.98% 48.45% 35.41% (24.21%) 14.50% % of Total Revenue - - - - .04% .42% .49% .58% .67% .45% .68% MGD007 - - - - - 45,098 95,371 150,680 210,797 275,402 171,424 % Growth - - - - - - 111.47% 57.99% 39.90% 30.65% (37.75%) % of Total Revenue - - - - - 5.05% 6.95% 8.64% 10.43% 11.95% 9.87% MGD009 - - - - - 170,605 404,557 660,753 938,004 1,234,710 851,488 % Growth - - - - - - 137.13% 63.33% 41.96% 31.63% (31.04%) % of Total Revenue - - - - - 19.09% 29.48% 37.91% 46.42% 53.56% 49.02% Total Revenue from Drug Sales $9,674 $41,153 $76,355 $289,406 $496,560 $893,712 $1,372,134 $1,743,139 $2,020,714 $2,305,485 $1,737,149 % Growth - 325.39% 85.54% 279.03% 71.58% 79.98% 53.53% 27.04% 15.92% 14.09% (24.65%)
- 24. UOIG 24 January 29th ,2016University of Oregon Investment Group Appendix 8 – Consolidate Revenue from Partnerships Revenue from Collaborative Research Funding ($ in thousands) 2011A 2012A 2013A 2014A 2015A 2016A 2017A 2018A 2019A 2020A 2021A 2022A 2023A 2024A 2025A 2026A 2027A 2028A 2029A 2030A Boehringer 7,340 10,975 14,075 13,518 11,112 4,112 2,369 1,771 551 551 674 205 205 205 205 285 474 474 474 474 % Total 15.60% 18.40% 24.80% 28.60% (17.80%) (63.00%) (42.39%) (25.24%) (68.90%) - 22.42% (69.66%) - - - 39.27% 66.43% - - - Green Cross - - 7,832 5,388 600 - - - - - - - - - - - - - - - % Total - - 13.80% 11.40% (88.86%) - - - - - - - - - - - - - - - Janssen - - 7,832 5,388 79,520 31,240 13,502 19,637 11,647 5,739 5,739 5,739 3,605 451 3,225 3,225 3,225 3,225 3,225 3,225 % Total - - 13.80% 11.40% 1375.84% (60.71%) (56.78%) 45.43% (40.69%) (50.72%) - - (37.19%) (87.49%) 615.33% - - - - - Pfizer 5,082 5,189 3,405 - - - - - - - - - - - - - - - - - % Total 10.80% 8.70% 6.00% - - - - - - - - - - - - - - - - - Servier - 10,319 29,285 17,204 11,138 49,226 22,629 23,516 2,049 4,106 4,106 4,106 1,460 631 8,697 9,222 9,222 9,222 9,222 9,222 % Total - 17.30% 51.60% 36.40% (35.26%) 341.97% (54.03%) 3.92% (91.29%) 100.41% - - (64.44%) (56.77%) 1278.00% 6.04% - - - - Takeda - - - 7,940 22,223 6,306 3,950 3,950 1,416 1,318 1,318 1,318 338 4,630 7,489 7,489 7,489 7,489 7,489 7,489 % Total - - - 16.80% 179.87% (71.63%) (37.35%) - (64.15%) (6.94%) - - (74.38%) 1271.56% 61.75% - - - - - Other 894 119 114 2,789 2,323 - - - - - - - - - - - - - - - % Total 1.90% .20% .20% 5.90% - - - - - - - - - - - - - - - - Total Revenue from Collaborative Research $47,054 $59,646 $56,753 $47,264 $126,915 $90,883 $42,450 $48,874 $15,663 $11,714 $11,838 $11,368 $5,607 $5,917 $19,616 $20,222 $20,411 $20,411 $20,411 $20,411 % Growth - 26.76% (4.85%) (16.72%) 168.52% (28.39%) (53.29%) 15.13% (67.95%) (25.21%) 1.05% (3.97%) (50.68%) 5.53% 231.53% 3.09% .94% - - -
- 25. UOIG 25 January 29th ,2016University of Oregon Investment Group PartnershipRevenue 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E ($ in thousands) 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Boehringer 11,112 4,112 2,369 1,771 551 551 674 205 205 205 205 285 474 474 474 474 Preclinical Milestone Payments 20,650 20,650 - - - - - - - - - - - - - - Probability-Adjusted 11,112 4,112 - - - - - - - - - - - - - - Phase I Milestone Payments - - 17,265 12,402 - - - - - - - - - - - - Probability-Adjusted - - 2,369 1,701 - - - - - - - - - - - - Phase II Milestone Payments - - - 1,195 9,490 9,490 9,490 - - - - - - - - - Probability-Adjusted - - - 69 551 551 551 - - - - - - - - - Phase III Milestone Payments - - - - - - 3,891 6,444 6,444 6,444 6,444 - - - - - Probability-Adjusted - - - - - - 124 205 205 205 205 - - - - - Commercial Milestone Payments - - - - - - - - - - - 10,839 18,040 18,040 18,040 18,040 Probability-Adjusted - - - - - - - - - - - 285 474 474 474 474 Janssen 79,520 31,240 13,502 19,637 11,647 5,739 5,739 5,739 3,605 451 3,225 3,225 3,225 3,225 3,225 3,225 Phase I Milestone Payments 10,479 45,341 6,881 - - - - - - - - - - - - - Probability-Adjusted 79,520 31,240 4,741 - - - - - - - - - - - - - Phase II Milestone Payments - - 30,062 67,377 37,562 - - - - - - - - - - - Probability-Adjusted - - 8,761 19,637 10,947 - - - - - - - - - - - Phase III Milestone Payments - - - - 4,389 36,000 36,000 36,000 22,611 - - - - - - - Probability-Adjusted - - - - 700 5,739 5,739 5,739 3,605 - - - - - - - Commercial Milestone Payments - - - - - - - - - 3,415 24,431 24,431 24,431 24,431 24,431 24,431 Probability-Adjusted - - - - - - - - - 451 3,225 3,225 3,225 3,225 3,225 3,225 Servier 11,138 49,226 22,629 23,516 2,049 4,106 4,106 4,106 1,460 631 8,697 9,222 9,222 9,222 9,222 9,222 Phase I Milestone Payments 12,361 71,446 14,993 - - - - - - - - - - - - - Probability-Adjusted 11,138 49,226 10,330 - - - - - - - - - - - - - Phase II Milestone Payments - - 17,850 80,686 263 - - - - - - - - - - - Probability-Adjusted - - 12,299 23,516 77 - - - - - - - - - - - Phase III Milestone Payments - 12,370 25,757 25,757 25,757 9,158 - - - - - - - Probability-Adjusted - - - - 1,972 4,106 4,106 4,106 1,460 - - - - - - - Commercial Milestone Payments - - - - - - - - - 4,781 65,888 69,866 69,866 69,866 69,866 69,866 Probability-Adjusted - - - - - - - - - 631 8,697 9,222 9,222 9,222 9,222 9,222 Takeda 22,223 6,306 3,950 3,950 1,416 1,318 1,318 1,318 338 4,630 7,489 7,489 7,489 7,489 7,489 7,489 Phase I Milestone Payments 22,384 8,616 - - - - - - - - - - - - - - Probability-Adjusted 22,223 5,936 - - - - - - - - - - - - - - Phase II Milestone Payments - 1,267 13,554 13,554 2,626 - - - - - - - - - - - Probability-Adjusted - 369 3,950 3,950 765 - - - - - - - - - - - Phase III Milestone Payments - - - - 4,082 8,267 8,267 8,267 2,118 - - - - - - - Probability-Adjusted - - - - 651 1,318 1,318 1,318 338 - - - - - - - Commercial Milestone Payments - - - - - - - - - 35,078 56,737 56,737 56,737 56,737 56,737 56,737 Probability-Adjusted - - - - - - - - - 4,630 7,489 7,489 7,489 7,489 7,489 7,489 Appendix 9 –Partnership Revenue Model
- 26. UOIG 26 January 29th ,2016University of Oregon Investment Group Appendix 9 –Partnership Revenue Model (Continued) EstimatedTime andMilestone Payment By Trial Drug Name Indication Phase Phase Start Date Phase End Date Milestone Payment Partner MGD006 AML I 7/1/2015 4/30/2017 49,400 Servier II 5/1/2017 10/30/2019 49,400 Partner III 10/31/2019 10/30/2023 49,400 Servier BLA 10/31/2023 10/30/2024 210,000 Servier MGD007 Colorectal I 10/1/2015 7/31/2017 49,400 Servier II 8/1/2017 1/30/2020 49,400 Servier III 1/31/2020 1/30/2024 49,400 Servier BLA 1/31/2024 1/30/2025 210,000 Servier MGD010 Autoimmune Disorders I 1/1/2015 10/31/2016 31,000 Takeda II 11/1/2016 5/2/2019 31,000 Takeda III 5/3/2019 5/2/2023 31,000 Takeda BLA 5/3/2023 5/2/2024 375,500 Takeda MGD011 B-Cell Malignancies I 7/1/2015 4/30/2017 62,700 Janssen II 5/1/2017 10/30/2019 135,000 Janssen III 10/31/2019 10/30/2023 135,000 Janssen BLA 10/31/2023 10/30/2024 150,000 Janssen Undisclosed DART NA 0 1/1/2014 12/31/2016 41,300 Boehringer I 1/1/2017 11/1/2018 29,667 Boehringer II 11/2/2018 5/2/2021 29,667 Boehringer III 5/3/2021 5/2/2025 29,667 Boehringer BLA 5/3/2025 5/3/2026 83,000 Boehringer
- 27. UOIG 27 January 29th ,2016University of Oregon Investment Group Appendix 10 –Margetuximab Revenue Model US Breast Cancer Market Potential x All numbers in thousands unless noted otherwise 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Breast Cancer Incidence 266 270 273 277 280 284 287 290 293 296 299 % Growth 2.48% 1.32% 1.30% 1.28% 1.27% 1.25% 1.08% 1.07% 1.06% 1.05% 1.04% % Female Population: 50+ .42% .42% .42% .42% .42% .42% .43% .43% .43% .43% .43% Breast Cancer Patients HER2+ 80 81 82 83 84 85 86 87 88 89 90 % Total Breast Cancer Incidence 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% Breast Cancer HER2+ 3+ Patients 40 40 41 42 42 43 43 44 44 44 45 % Total Breast Cancer HER2+ Patients 15.00% 15.00% 15.00% 15.00% 15.00% 15.00% 15.00% 15.00% 15.00% 15.00% 15.00% Breast Cancer HER2+ 1-2 Patients 226 229 232 235 238 241 244 247 249 252 254 % Total Breast Cancer HER2+ Patients 85.00% 85.00% 85.00% 85.00% 85.00% 85.00% 85.00% 85.00% 85.00% 85.00% 85.00% Patients Eligible for Margetuximab (3+) 12 12 12 12 13 13 13 13 13 13 13 Patients Eligible for Margetuximab (1-2) 68 69 70 71 72 72 73 74 75 76 76 US Gastric Cancer Market Potential All numbers in thousands unless noted otherwise 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Gastric Cancer Incidence 26 26.17 27 27.34 28 29 29.07 30 30.17 31 31 % Growth .79% 2.29% 2.24% 2.19% 2.14% 2.10% 1.94% 1.90% 1.86% 1.83% 1.80% % Population: 50+ .02% .02% .02% .02% .02% .02% .02% .02% .02% .02% .02% Gastric Cancer HER2+ Patients 6 6 6 6 6 6 6 7 7 7 7 % Total Gastric Cancer Incidence 22.00% 22.00% 22.00% 22.00% 22.00% 22.00% 22.00% 22.00% 22.00% 22.00% 22.00% Gastric Cancer HER2+ Patients 4 4 4 4 4 4 4 4 4 4 4 % Total Gastric Cancer HER2+ Patients 14.00% 14.00% 14.00% 14.00% 14.00% 14.00% 14.00% 14.00% 14.00% 14.00% 14.00% Patients Eligible for Margetuximab 1 1 1 1 1 1 1 1 1 1 1 MargetuximabRevenue (HER2+ 3+ Breast Cancer) x All numbers in thousands unless noted otherwise 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Total Patients Treated 1 1 2 2 3 3 3 3 2 2 2 % Market Share 5.00% 10.00% 15.00% 20.00% 25.00% 23.33% 21.67% 20.00% 18.33% 16.67% 15.00% Net Price Per Year ($USD) $70,895 $74,820 $78,668 $82,404 $85,995 $89,404 $92,597 $95,540 $98,202 $100,552 $102,563 Annual Price Inflation 5.93% 5.54% 5.14% 4.75% 4.36% 3.96% 3.57% 3.18% 2.79% 2.39% 2.00% Unadjusted Revenue (HER2+ 3+ Breast Cancer) 21,360 90,862 145,168 205,357 271,278 266,528 259,107 249,424 237,501 223,397 207,209 % Growth - 325.39% 59.77% 41.46% 32.10% (1.75%) (2.78%) (3.74%) (4.78%) (5.94%) (7.25%) Probability-AdjustedRevenue (HER2+ 3+ Breast Cancer) 9,674 41,153 65,749 93,009 122,866 120,715 117,354 112,968 107,568 101,180 93,848 Probability-to-Market 45.29% 45.29% 45.29% 45.29% 45.29% 45.29% 45.29% 45.29% 45.29% 45.29% 45.29% MargetuximabRevenue (HER2+ 1-2 Breast Cancer) x All numbers in thousands unless noted otherwise 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Total Patients Treated - - - 4 7 11 15 18 16 14 11 % Market Share - - - 5.00% 10.00% 15.00% 20.00% 25.00% 21.67% 18.33% 15.00% Net Price Per Year ($USD) $70,895 $74,820 $78,668 $82,404 $85,995 $89,404 $92,597 $95,540 $98,202 $100,552 $102,563 Annual Price Inflation 5.93% 5.54% 5.14% 4.75% 4.36% 3.96% 3.57% 3.18% 2.79% 2.39% 2.00% Unadjusted Revenue (1-2 HER2+ Breast Cancer) - - - 217,992 614,897 970,922 1,355,329 1,766,754 1,590,537 1,392,508 1,174,183 % Growth - - - - 182.07% 57.90% 39.59% 30.36% (9.97%) (12.45%) (15.68%) Probability-AdjustedRevenue (HER2+ 1-2 Breast Cancer) - - - 41,764 117,804 186,013 259,659 338,481 304,721 266,782 224,954 Probability-to-Market - - - 19.16% 19.16% 19.16% 19.16% 19.16% 19.16% 19.16% 19.16% MargetuximabRevenue (Late Stage HER2+ Gastric Cancer) x All numbers in thousands unless noted otherwise 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Total Patients Treated - - 0 0 0 0 0 0 0 0 0 % Market Share - - 5.00% 9.00% 13.00% 17.00% 21.00% 25.00% 21.67% 18.33% 15.00% Net Price Per Year ($USD) $70,895 $74,820 $78,668 $82,404 $85,995 $89,404 $92,597 $95,540 $98,202 $100,552 $102,563 Annual Price Inflation 5.93% 5.54% 5.14% 4.75% 4.36% 3.96% 3.57% 3.18% 2.79% 2.39% 2.00% Unadjusted Revenue (Late Stage HER2+ Gastric Cancer) - - 268 6,246 9,617 13,349 17,410 21,791 19,773 17,445 14,821 % Growth - - - 2231.29% 53.97% 38.80% 30.42% 25.17% (9.26%) (11.77%) (15.05%) Probability-AdjustedRevenue (Late Stage HER2+ Gastric Cancer) - - 51 1,197 1,842 2,557 3,335 4,175 3,788 3,342 2,839 Probability-to-Market - - 19.16% 19.16% 19.16% 19.16% 19.16% 19.16% 19.16% 19.16% 19.16%
- 28. UOIG 28 January 29th ,2016University of Oregon Investment Group Appendix 11 –Enoblituzumab Revenue Model US SolidTumor Market Potential x All numbers in thousands unless noted otherwise 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Bladder Cancer Incidence 91 93 96 98 100 103 105 107 110 % Growth 2.74% 2.67% 2.60% 2.53% 2.36% 2.30% 2.25% 2.20% 2.15% % Population: 50+ .07% .08% .08% .08% .08% .08% .08% .08% .08% Breast Cancer Incidence (Triple-Negative) 48 48 49 50 50 51 51 52 52 % Growth 1.30% 1.28% 1.27% 1.25% 1.08% 1.07% 1.06% 1.05% 1.04% % Female Population: 50+ .07% .07% .07% .07% .07% .07% .07% .08% .08% Kidney Cancer Incidence 71 72 73 74 75 76 77 78 79 % Growth 1.61% 1.58% 1.56% 1.54% 1.33% 1.32% 1.30% 1.28% 1.27% % Population: 50+ .06% .06% .06% .06% .06% .06% .06% .06% .06% Lung Cancer Incidence 278 285 291 297 303 308 314 320 325 % Growth 2.34% 2.28% 2.23% 2.18% 1.89% 1.86% 1.82% 1.79% 1.76% % Population: 50+ .23% .23% .23% .23% .24% .24% .24% .24% .25% Melanoma Incidence 85 86 87 89 90 91 93 94 95 % Growth 1.58% 1.56% 1.53% 1.51% 1.55% 1.53% 1.51% 1.49% 1.46% % Population: 50+ .07% .07% .07% .07% .07% .07% .07% .07% .07% Prostate Cancer Incidence 301 306 311 317 321 325 328 332 336 % Growth 1.78% 1.75% 1.72% 1.69% 1.25% 1.23% 1.22% 1.20% 1.19% % Male Population: 50+ .52% .52% .52% .52% .53% .53% .53% .53% .53% Total Incidence 873 890 907 924 939 954 969 984 998 % Growth 2.00% 1.96% 1.92% 1.89% 1.60% 1.58% 1.55% 1.53% 1.51% % Population: 50+ .71% .72% .72% .73% .73% .74% .74% .75% .75% Late Stage Cancer Patients 262 267 272 277 282 286 291 295 300 % Total Cancer Incidence 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% Refractory Late Stage Cancer Patients 183 187 191 194 197 200 203 207 210 % Late Stage Patients 70.00% 70.00% 70.00% 70.00% 70.00% 70.00% 70.00% 70.00% 70.00% BH-73+ Patients Eligible for Enoblituzumab 162 165 168 171 174 177 180 182 185 % Late Stage Patients 88.25% 88.25% 88.25% 88.25% 88.25% 88.25% 88.25% 88.25% 88.25% EnoblituzumabRevenue (SolidTumor) x All numbers in thousands unless noted otherwise 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Total Patients Treated 8 19 29 41 52 49 45 41 37 % Market Share 5.00% 11.25% 17.50% 23.75% 30.00% 27.50% 25.00% 22.50% 20.00% Net Price Per Year ($USD) $59,789 $62,629 $65,358 $67,949 $70,375 $72,612 $74,635 $76,421 $77,949 Annual Price Inflation 5.14% 4.75% 4.36% 3.96% 3.57% 3.18% 2.79% 2.39% 2.00% Unadjusted Revenue (Enoblituzumab) 79,956 1,162,386 1,923,193 2,764,668 3,674,860 3,530,482 3,350,130 3,134,441 2,884,666 % Growth - 1353.78% 65.45% 43.75% 32.92% (3.93%) (5.11%) (6.44%) (7.97%) Probability-AdjustedRevenue (Enoblituzumab) 10,554 153,436 253,863 364,939 485,085 466,027 442,221 413,749 380,779 Probability-to-Market 13.20% 13.20% 13.20% 13.20% 13.20% 13.20% 13.20% 13.20% 13.20%
- 29. UOIG 29 January 29th ,2016University of Oregon Investment Group Appendix 12 –MGD006 Revenue Model US Acute MyeloidLeukemia (AML) Market Potential x All numbers in thousands unless noted otherwise 2024E 2025E 2026E 2027E 2028E 2029E 2030E Leukemia Incidence 51 52 53 54 55 56 57 % Growth 2.01% 1.97% 1.86% 1.82% 1.79% 1.76% 1.73% % Population: 50+ .04% .04% .04% .04% .04% .04% .04% AML Patients 19 20 20 21 21 21 22 % Total Leukemia Incidence 38.38% 38.38% 38.38% 38.38% 38.38% 38.38% 38.38% Recurrent Patients Eligible for MGD006 5 5 5 5 5 5 5 % Total AML Patients 25.00% 25.00% 25.00% 25.00% 25.00% 25.00% 25.00% MGD006 Revenue (Recurrent AML) x All numbers in thousands unless noted otherwise 2024E 2025E 2026E 2027E 2028E 2029E 2030E Total Patients Treated 0 1 1 2 3 2 2 % Market Share 5.00% 16.25% 27.50% 38.75% 50.00% 36.25% 40.00% Net Price Per Year ($USD) $34,078 $35,509 $36,870 $38,148 $39,331 $40,406 $41,214 Annual Price Inflation 4.57% 4.20% 3.83% 3.47% 3.10% 2.73% 2.00% Unadjusted Revenue (MGD006) 1,391 28,670 51,314 76,176 103,153 78,182 89,516 % Growth - 1960.66% 78.98% 48.45% 35.41% (24.21%) 14.50% Probability-AdjustedRevenue (MGD006) 184 3,784 6,773 10,055 13,616 10,320 11,816 Probability-to-Market 13.20% 13.20% 13.20% 13.20% 13.20% 13.20% 13.20%
- 30. UOIG 30 January 29th ,2016University of Oregon Investment Group Appendix 13 –MGD007 Revenue Model US Colorectal Cancer Market Potential x All numbers in thousands unless noted otherwise 2025E 2026E 2027E 2028E 2029E 2030E Colorectal Cancer Incidence 177 180 183 187 190 193 % Growth 1.96% 1.83% 1.80% 1.77% 1.74% 1.71% % Population: 50+ .14% .14% .14% .14% .14% .15% Stage IVPatients Eligible for MGD007 62 63 64 65 66 68 % Total Colorectal Cancer Incidence 35.00% 35.00% 35.00% 35.00% 35.00% 35.00% MGD007 Revenue (Colorectal Cancer) x All numbers in thousands unless noted otherwise 2025E 2026E 2027E 2028E 2029E 2030E Total Patients Treated 3 6 10 13 17 10 % Market Share 5.00% 10.00% 15.00% 20.00% 25.00% 15.00% Net Price Per Year ($USD) $110,303 $114,532 $118,502 $122,176 $125,515 $128,026 Annual Price Inflation 4.20% 3.83% 3.47% 3.10% 2.73% 2.00% Unadjusted Revenue (MGD007) 341,652 722,501 1,141,505 1,596,934 2,086,359 1,298,657 % Growth - 111.47% 57.99% 39.90% 30.65% (37.75%) Probability-AdjustedRevenue (MGD007) 45,098 95,371 150,680 210,797 275,402 171,424 Probability-to-Market 13.20% 13.20% 13.20% 13.20% 13.20% 13.20%
- 31. UOIG 31 January 29th ,2016University of Oregon Investment Group Appendix 14 –MGD009 Revenue Model US SolidTumor Market Potential x All numbers in thousands unless noted otherwise 2025E 2026E 2027E 2028E 2029E 2030E Bladder Cancer Incidence 98 100 103 105 107 110 % Growth 2.53% 2.36% 2.30% 2.25% 2.20% 2.15% % Population: 50+ .08% .08% .08% .08% .08% .08% Breast Cancer Incidence 284 287 290 293 296 299 % Growth 1.25% 1.08% 1.07% 1.06% 1.05% 1.04% % Female Population: 50+ .42% .43% .43% .43% .43% .43% Colorectal Cancer Incidence 177 180 183 187 190 193 % Growth 1.96% 1.83% 1.80% 1.77% 1.74% 1.71% % Population: 50+ .14% .14% .14% .14% .14% .15% Kidney Cancer Incidence 74 75 76 77 78 79 % Growth 1.54% 1.33% 1.32% 1.30% 1.28% 1.27% % Population: 50+ .06% .06% .06% .06% .06% .06% Lung Cancer Incidence 297 303 308 314 320 325 % Growth 2.18% 1.89% 1.86% 1.82% 1.79% 1.76% % Population: 50+ .23% .24% .24% .24% .24% .25% Melanoma Incidence 89 90 91 93 94 95 % Growth 1.51% 1.55% 1.53% 1.51% 1.49% 1.46% % Population: 50+ .07% .07% .07% .07% .07% .07% Ovarian Cancer Incidence 26 26 27 27 27 28 % Growth 1.46% 1.32% 1.30% 1.28% 1.27% 1.25% % Female Population: 50+ .04% .04% .04% .04% .04% .04% Prostate Cancer Incidence 317 321 325 328 332 336 % Growth 1.69% 1.25% 1.23% 1.22% 1.20% 1.19% % Male Population: 50+ .52% .53% .53% .53% .53% .53% Thyroid Cancer Incidence 59 60 60 61 61 61 % Growth .74% .66% .66% .65% .65% .64% % Population: 50+ .05% .05% .05% .05% .05% .05% Total Incidence 1,421 1,442 1,464 1,485 1,506 1,527 % Growth 1.73% 1.50% 1.48% 1.46% 1.44% 1.42% % Population: 50+ 1.12% 1.12% 1.13% 1.14% 1.15% 1.15% Late Stage Cancer Patients 426 433 439 445 452 458 % Total Cancer Incidence 30.00% 30.00% 30.00% 30.00% 30.00% 30.00% BH-73+ Patients Eligible for MGD009 376 382 387 393 399 404 % Late Stage Patients 88.25% 88.25% 88.25% 88.25% 88.25% 88.25% MGD009 Revenue (SolidTumor) x All numbers in thousands unless noted otherwise 2025E 2026E 2027E 2028E 2029E 2030E Total Patients Treated 19 43 68 93 120 81 % Market Share 5.00% 11.25% 17.50% 23.75% 30.00% 20.00% Net Price Per Year ($USD) $68,715 $71,349 $73,822 $76,111 $78,191 $79,755 Annual Price Inflation 4.20% 3.83% 3.47% 3.10% 2.73% 2.00% Unadjusted Revenue (MGD009) 1,292,454 3,064,803 5,005,666 7,106,033 9,353,795 6,450,618 % Growth - 137.13% 63.33% 41.96% 31.63% (31.04%) Probability-AdjustedRevenue (MGD009) 170,605 404,557 660,753 938,004 1,234,710 851,488 Probability-to-Market 13.20% 13.20% 13.20% 13.20% 13.20% 13.20%
- 32. UOIG 32 January 29th ,2016University of Oregon Investment Group Currently MarketedComparable Biologics x Name Comparable WAC Premium Final WAC Generic Name Brand Name Application AWP WAC Margetuximab $48,792 5.00% $51,231 bevacizumab Avastin Anti-Angiogenic Cancer Therapy $33,500 $27,805 Enoblituzumab $33,858 15.00% $38,937 cetuximab Erbitux Squamous Cell and Colorectal Carcinoma $71,718 $59,526 MGD006 $17,496 15.00% $20,121 gemtuzumab Mylotarg Relapsed Acute Myeloid Leukemia $21,080 $17,496 MGD007 $59,526 5.00% $62,502 rituximab Rituxan Non-Hodgkin's Lymphoma, Rheumatoid Arthritis $18,880 $15,670 MGD009 $33,858 15.00% $38,937 trastuzumab Herceptin HER2+ Breast Cancer $58,785 $48,792 Macrogenics Drug Pricing Appendix 15 –Drug Pricing Model
- 33. UOIG 33 January 29th ,2016University of Oregon Investment Group Research andDevelopment Model 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E ($ in thousands) 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022E 2023E 2024E 2025E 2026E 2027E 2028E 2029E 2030E Margetuximab 33,446 16,436 19,463 9,908 10,851 6,873 7,095 2,472 1,460 1,789 1,789 1,789 1,789 1,789 1,789 1,789 % Growth 73.30% (50.86%) 18.41% (49.09%) 9.52% (36.66%) 3.22% (65.16%) (40.96%) 22.55% - - - - - - % of Total R&D 34.63% 24.87% 22.91% 11.85% 12.67% 8.32% 7.66% 2.56% 1.43% 1.70% 1.54% 1.41% 1.31% 1.21% 1.13% 1.05% MGA271 (Enoblituzumab) 13,884 11,127 11,726 10,454 10,008 6,496 6,243 4,705 4,057 1,678 1,068 1,232 1,232 1,232 1,232 1,232 % Growth 2.09% (19.86%) 5.38% (10.85%) (4.26%) (35.09%) (3.89%) (24.64%) (13.77%) (58.63%) (36.37%) 15.40% - - - - % of Total R&D 14.38% 16.83% 13.80% 12.51% 11.68% 7.87% 6.74% 4.87% 3.97% 1.59% .92% .97% .90% .84% .78% .73% MGD006 3,017 2,227 3,495 4,134 3,801 2,186 2,186 2,186 1,871 364 596 596 596 596 596 596 % Growth (13.80%) (26.18%) 56.93% 18.29% (8.06%) (42.49%) - - (14.39%) (80.56%) 63.93% - - - - - % of Total R&D 3.12% 3.37% 4.11% 4.95% 4.44% 2.65% 2.36% 2.26% 1.83% .35% .51% .47% .44% .40% .38% .35% MGD007 3,518 2,881 3,394 4,134 4,134 2,343 2,186 2,186 2,186 474 571 596 596 596 596 596 % Growth (12.05%) (18.10%) 17.82% 21.79% - (43.32%) (6.71%) - - (78.30%) 20.42% 4.37% - - - - % of Total R&D 3.64% 4.36% 4.00% 4.95% 4.83% 2.84% 2.36% 2.26% 2.14% .45% .49% .47% .44% .40% .38% .35% MGD010 6,840 1,294 4,134 4,134 2,835 2,186 2,186 2,186 945 501 596 596 596 596 596 596 % Growth 75.38% (81.08%) 219.39% - (31.43%) (22.89%) - - (56.75%) (47.02%) 19.04% - - - - - % of Total R&D 7.08% 1.96% 4.87% 4.95% 3.31% 2.65% 2.36% 2.26% .92% .48% .51% .47% .44% .40% .38% .35% MGD011 3,003 2,399 3,551 4,134 3,801 2,186 2,186 2,186 1,871 364 596 596 596 596 596 596 % Growth (41.13%) (20.11%) 48.06% 16.41% (8.06%) (42.49%) - - (14.39%) (80.56%) 63.93% - - - - - % of Total R&D 3.11% 3.63% 4.18% 4.95% 4.44% 2.65% 2.36% 2.26% 1.83% .35% .51% .47% .44% .40% .38% .35% MGD012 848 3,400 3,400 2,705 652 721 823 823 467 435 435 435 95 80 82 82 % Growth - 301.10% - (20.43%) (75.91%) 10.64% 14.16% - (43.31%) (6.73%) - - (78.28%) (15.40%) 2.26% - % of Total R&D .88% 5.14% 4.00% 3.24% .76% .87% .89% .85% .46% .41% .38% .34% .07% .05% .05% .05% MGD013 848 3,400 3,400 2,705 652 721 823 823 467 435 435 435 95 80 82 82 % Growth - 301.10% - (20.43%) (75.91%) 10.64% 14.16% - (43.31%) (6.73%) - - (78.28%) (15.40%) 2.26% - % of Total R&D .88% 5.14% 4.00% 3.24% .76% .87% .89% .85% .46% .41% .38% .34% .07% .05% .05% .05% MGD014 848 3,400 3,400 2,705 652 721 823 823 467 435 435 435 95 80 82 82 % Growth - 301.10% - (20.43%) (75.91%) 10.64% 14.16% - (43.31%) (6.73%) - - (78.28%) (15.40%) 2.26% - % of Total R&D .88% 5.14% 4.00% 3.24% .76% .87% .89% .85% .46% .41% .38% .34% .07% .05% .05% .05% Other Preclinical Drugs 18,927 3,400 8,014 12,629 17,243 21,857 26,471 31,086 35,700 40,314 44,929 49,543 54,157 58,771 63,386 68,000 % Growth (8.94%) (82.04%) 135.71% 57.58% 36.54% 26.76% 21.11% 17.43% 14.84% 12.93% 11.45% 10.27% 9.31% 8.52% 7.85% 7.28% % of Total R&D 19.60% 5.14% 9.43% 15.11% 20.13% 26.47% 28.57% 32.18% 34.92% 38.29% 38.78% 39.10% 39.68% 39.87% 39.99% 40.05% Research and Development Salaries 11,405 16,132 20,980 25,951 31,047 36,272 41,628 47,116 52,741 58,503 64,407 70,454 76,647 82,990 89,484 96,133 % Growth - 39.63% 28.38% 22.11% 18.10% 15.33% 13.29% 11.73% 10.50% 9.50% 8.68% 7.99% 7.39% 6.89% 6.44% 6.05% % of Total R&D 11.81% 24.41% 24.69% 31.04% 36.24% 43.93% 44.93% 48.78% 51.59% 55.56% 55.59% 55.60% 56.15% 56.30% 56.45% 56.62% Total Research AndDevelopment Expense (Probability-Adjusted) 96,582 66,096 84,957 83,594 85,675 82,562 92,650 96,592 102,231 105,293 115,857 126,708 136,494 147,407 158,521 169,785 % Growth 37.61% (31.56%) 28.54% (1.60%) 2.49% (3.63%) 12.22% 4.25% 5.84% 3.00% 10.03% 9.37% 7.72% 8.00% 7.54% 7.11% % Revenue 75.37% 67.41% 196.47% 168.31% 520.65% 372.22% 172.27% 109.12% 34.56% 20.92% 12.67% 9.10% 7.74% 7.22% 6.81% 9.66% Appendix 16 –Research and Development Model
- 34. UOIG 34 January 29th ,2016University of Oregon Investment Group Drug Name Indication Platform Phase Phase Start Date Expected Launch Partner Margetuximab Breast (3+) Fc Optimization III 7/2015 6/2020 Green Cross Margetuximab Breast (1-2+) Fc Optimization II 10/2015 4/2023 Green Cross Margetuximab Gastric Fc Optimization I/II 10/2015 11/2022 Green Cross MGA271 (Enoblituzumab) Solid Tumors (+ipi) Fc Optimization I 4/2015 7/2024 None MGA271 (Enoblituzumab) Solid Tumors (Mono) Fc Optimization I 7/2013 10/2022 None MGA271 (Enoblituzumab) Solid Tumors (+pembro) Fc Optimization I 1/2016 5/2025 None MGD006 AML DART I 7/2015 10/2024 Servier MGD007 Colorectal DART I 10/2015 1/2025 Servier MGD009 Solid Tumors DART I 10/2015 1/2025 None MGD010 Autoimmune Disorders DART I 1/2015 5/2024 Takeda MGD011 B-Cell Malignancies DART I 7/2015 10/2024 Janssen MGD012 NA Fc Optimization 0 10/2015 1/2028 None MGD013 NA DART 0 10/2015 1/2028 None MGD014 NA DART 0 10/2015 1/2028 None Drug Development Pipeline Phase Average Years in Phase Average Cost in Phase % Total Clinical Cost Probability of Advancing Pre-Clinical 3.00 10,200 - 19.91% Phase I 1.83 6,000 11.76% 68.90% Phase II 2.50 15,000 29.41% 42.30% Phase III 4.00 30,000 58.82% 54.70% BLA 1.00 2,000 - 82.80% Phase IV(Post-Market) 12.50 38,900 - - Clinical Development Considerations Appendix 16 –Research and Development Model (Continued)
- 35. UOIG 35 January 29th ,2016University of Oregon Investment Group Considerations TaxRate 35.00% Terminal Growth Rate 3.00% Current Reinvestment Rate NM Risk Free Rate 2.13% Terminal Value 153,067 Reinvestment Rate in Year 2030 13.14% Beta 1.69 PVof Terminal Value 20,651 Implied Return on Capital in Perpetuity 13.65% Market Risk Premium 6.45% Sumof PVFCF 599,537 WACC 14.04% % Equity 100.00% FirmValue 620,188 Implied Excess Returns on Capital in Perpetuity (39bps) % Debt - Total Debt - Terminal Value as a % of Total 3.33% CAPM/WACC 14.04% Minority Interests - Implied 2015 EBITDA Multiple 4.94x Terminal Risk Free Rate 2.95% Market Capitalization 620,188 Implied Multiple in Year 2030 0.46x Terminal Beta 1.36 Fully Diluted Shares 35,539 Free Cash Flow Growth Rate in Terminal (40.51%) Terminal % Equity 100.00% Implied Price $17.45 Terminal % Debt - Current Price $20.54 Terminal CAPM/WACC 12.74% Overvalued (15.04%) Final Valuation Price Weighting Discounted Cash Flow $17.45 90.00% Forward Comparables $14.28 10.00% Implied Price 17.13 Current Price 20.54 Overvalued (16.59%) DiscountedFree Cash FlowAssumptions Appendix 17 – Discounted Cash Flow Considerations and Assumptions
- 36. University of OregonInvestment Group January 29th , 2016 Appendix 18 – Sources American Society of Clinical Oncology (ASCO) ASimpleModel.com Avalanche Biotechnology UOIG Equity Research Report (Hanston Nguyen) Biotechnology Valuation: An Introductory Guide (Karl Keegan) Cancer.gov Cancer.org Centers for Medicare & Medicaid Services ClinicalTrials.gov Deutsche Bank Global Pharmaceuticals Industry Report (2012) Drug Pricing Overview (Larry Cross) FactSet FDAReview.org Fierce Biotech.com Genentech Investor Relations Glassdoor.com Goldman Sachs Biotechnology Industry Report (2006) IBISWorld International Journal of Cancer Research and Treatment Journal of Clinical Oncology Macrogenics Investor Relations Macrogenics SEC Filings Medscape National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Program National Health Statistics Group National Institute of Health Nature International Weekly Journal of Science New York Times Payscale.com Pharmaceutical Research and Manufacturers of America (PhRMA) Roche Investor Relations S&P Capital IQ SEC Filings Security Analysis (Benjamin Graham) St. Louis Federal Reserve Economic Data (FRED) Susan G. Komen (Breast Cancer Foundation) Wall Street Journal Washington Business Journal World Bank World Health Organization International Agency for Research on Cancer (WHO IARC) Yahoo! Finance