This document provides an introduction to forecasting methods used in healthcare. It discusses what forecasting is, different types of forecast models, and key steps to develop a forecast model including epidemiology, defining the target patient population, and accounting for future events. Examples of forecasting projects are also listed. The document outlines KantarHealth's standard approach of combining patient- and prescription-based forecasting. It describes key aspects of the methodology like defining the target patient population, calculating treated patients, and incorporating future events like new product launches through diffusion curves.

1. An Introduction to ForecastingAn Introduction to Forecasting
Presented by Stephen Potts Managing Director AP & MEAPresented by Stephen Potts – Managing Director, AP & MEA
Yong Huey Ling – Associate Director, AP & MEA
15th April 2010

2. I would like to cover…
– What is Forecasting?
• What are the different types of forecast models available?
– What are the key steps to develop a Forecast Model?
• Epidemiology
• Defining your patient target
• The concept of the ‘treated patient’
• Allowing for future events
Examples– Examples
2

3. What is Forecasting?What is Forecasting?
Confidential
3

4. What is Forecasting?
4

5. What is Forecasting?
CommercialCommercial
Development
Promotional
Forecasting
Todd Johnson
Promotional
Response
Modeling
Advanced
Applications
Kevin Norell
William Serad
Kevin Norell
Industry
Experts
Proprietary
Software
Proven
Methods
Established
databases
5

6. Forecasting covers many different disciplines
• Forecast Architect Based on transparent market assumptions to
project future patients, units,
prescriptions and/or revenues for brand
and market forecasting
• Integrative Forecasting Calibrated to in-market data• Integrative Forecasting Calibrated to in-market data
• Patient flow models Suitable for complex markets
(e.g. oncology, biologics, HIV, Hepatitis C)
• Promotional response model To evaluate promotional programs and marketing
mix. Usually involves econometric
modeling Tend to focus on in-line products to forecastmodeling. Tend to focus on in line products to forecast
short-term (18-24 months) volume
changes.
6

7. General Forecasting Approaches
– Patient Based Forecast
• Population
• Prevalence
• IncidenceIncidence
• Patient Flow (Oncology, HIV, Biologics, etc.)
– Volume Based Forecast
• Sales Revenue
• Units
• PrescriptionsPrescriptions
• Days of Therapy
– Combination Patient/Volume Based Forecast
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8. KantarHealth Standard Forecasting Approach
A combination of patient- and prescription-based forecasting that applies to currently
marketed products or compounds in development
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9. Combination Approach to Modeling: Patient-Based and
Prescription-Based
– Use Patients to...
• Capture the POTENTIAL market
– Use Doctor / Prescription Data to…
Better define a market (Example: which doctors are using the drug)• Better define a market (Example: which doctors are using the drug)
• Determine the size of the TREATED market
• Calculate treated patients and market shares of existing drugs
• Calculate current pricing
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10. A Special Case: Patient Flow Modeling
P ti t Fl / T kiPatient Flow / Tracking
Positives
– Incorporates time dependency in methodology
U d i id i l i l i t t i f di t• Used in epidemiologic analysis to capture progression from disease onset
– Used in drug treatment analysis to capture movement of patients from one therapeutic regimen to another
• Provides the greatest means of understanding the relationships and dependencies between therapies or disease segments
– Best used for:
f f ( )• Epidemiological analysis of diseases with changes in onset of disease or survival (diabetes, HIV)
• Evaluating opportunities in the pharmaceutical sector related to lines of therapy or resistance to therapy
Shortcomings
– Complex and time-consuming – extremely data-driven that may require primary market research
Key question: Are survival, disease progression, length of therapy, and therapeutic history of each
patient important to the forecast?
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11. Methodology: EpidemiologyMethodology: Epidemiology

12. Defining the Patient Population
T t l P lTotal Prevalence
(Diagnosed and Undiagnosed)
DiagnosedDiagnosed
Treatedeated
Drug Therapy
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13. Target Patients
– Target patients are identified based upon the product profile and the current
phase of product development.
T t ti t b ifi ibl– Target patients – be as specific as possible
• Overall indication
• Are there clinically relevant subgroups? (mild, moderate, severe; age; sex)
• Include / exclude comorbid conditions
• Halo effect: Similar indication for which the drug might be used
Mutually Exclusive, Collectively Exhaustive
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14. Methodology: Treated PatientsMethodology: Treated Patients

15. Treated Patients
Allocate
historical data
to the defined
Apply
conversion
Start with
Historical Data
Calculate Tx
Patients
to the defined
market
segment
factors
(Sales, Rx, Units,
Days of Therapy)
(at the
product level)
Total Days of Therapy
Days per Period * ComplianceTreated Patients =
* Concomitant drug usage data: Adjust the total patients treated to account for patients taking multiple agents
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16. Now that the market is properly defined and sized… establish
baseline trends.
Project the existing trends in the market to their natural conclusion under the assumption
th t thi h i th f t Thi ll th k t t h ilib i hi h ithat nothing changes in the future. This allows the market to reach equilibrium, which is
considered the “default forecast.”
Treatment Rate
60%
70%
40%
50%
60%
20%
30%
Historical Period Forecasting Period
0%
10%
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
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17. Methodology: Future EventsMethodology: Future Events

18. What are future events?
– Anything that can affect the course of a market.
F t t i l dFuture events include:
• New product launches
• Changes in labeling for existing products
• New clinical study publications
• Changes in price
• Changes in promotion
Loss of patent protection• Loss of patent protection
• Off-label use
• Etc.
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19. The Diffusion Curve
– Modeled by Frank Bass around 1960, the Bass Diffusion Model describes the
diffusion of new technologies into consumer markets.
– In the Bass Model, there are two characteristic types of consumers:
• Innovators who make purchasing decisions based on their own evaluation of the pros and• Innovators, who make purchasing decisions based on their own evaluation of the pros and
cons of the new technology. They are described as being “Internally Influenced.”
• Imitators, who make purchasing decisions based on the example of others and who adopt a
new product only when their contemporaries have deemed it valuable. They are described asp y p y
being “Externally Influenced.”
– Each type of consumer has a characteristic uptake curve.
The o erall adoption c r e is a blend of the t o c r es based on the relati e– The overall adoption curve is a blend of the two curves, based on the relative
preponderance of each consumer type.
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20. The Diffusion Curve
Diffusion Curves
80%
90%
100%
Uptake Types
60%
70%
80%
Type 1
Peak Share
(Max)
30%
40%
50% Curve A
Curve B
Curve C
Type 2
Launch
10%
20%
30%
Years to Achieve Peak (Max) = TMax
0%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
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21. Example of Uptake Analogies:
Tekturna (aliskiren) – Novartis Oral Solid / Hypertension
Tekturna Tekturna Trend
120000
140000
160000
180000
60000
80000
100000
120000
0
20000
40000
ar-07
n-07
p-07
c-07
ar-08
n-08
p-08
c-08
ar-09
n-09
p-09
c-09
ar-10
n-10
p-10
c-10
ar-11
n-11
p-11
c-11
ar-12
n-12
p-12
c-12
ar-13
Ma
Ju
Sep
De
Ma
Ju
Sep
De
Ma
Ju
Sep
De
Ma
Ju
Sep
De
Ma
Ju
Sep
De
Ma
Ju
Sep
De
Ma
Tekturna Parameters:
TMax: 4.6 Years (54 months)
Curve: 1.82 (~Rapid)
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22. The Forecast: Launch of a New Product
Market Share
60%
40%
50%
30%
10%
20%
0%
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
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23. Examples of Forecasting Projects
Evaluation of the incremental ROI for a Phase IV clinical program.
Development of a patient flow model for a new biologic product by line of therapy across several
indications.
Forecast of an oncology portfolio of future and existing products for a potential merger or acquisition.
Global market forecast for future CNS products with multiple indications and phased approvals.
Forecast of a line extension including primary market research to ascertain the level of
cannibalization of reference product.
Development of scenario tool to analyze the effects of various reimbursement programs on existing
product sales.
Pre-launch forecast of orphan drug with limited availability of market data.
Independent third party assessment of commercial potential for an early stage product to assist in
raising capital.
Annual forecast and reconciliation for product portfolio planning process.
Review of existing forecast model with recommendations for enhancement.

24. Contact
Karim Ben MaïzKarim Ben Maïz
Business Development Director – Maghreb Cluster
Mob Morocco+212 (0) 6 71 82 51 05
karim.benmaiz@kantarhealth.com
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