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Innovations in Drug Discovery - Novartis Institutes for BioMedical Research


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Sanjeev Thohan, Senior Research Fellow in Preclinical & Translational Sciences at the Novartis Institutes for BioMedical Research, discusses the most recent challenges and opportunities in the drug discovery industry, and provides insight into how the industry is progressing and its strategies to address demands. He also reviews areas ripe for innovation and disruption.

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Innovations in Drug Discovery - Novartis Institutes for BioMedical Research

  1. 1. Pharmaceutical Innovation – a personal perspective: how we got here and now where do we go? Sanjeev Thohan, PhD March 28, 2013
  2. 2. Overview… Historical perspective Target prosecution and safety Leverage Today and beyond… Cartoonstock.com2 Sthohan | March 2013 | Pharma Innovation | Confidential
  3. 3. 4000 years of medicine3 Sthohan | March 2013 | Pharma Innovation | Confidential
  4. 4. Serendipity to deliberate drug discovery….  In the past, drugs were at times discovered in a haphazard, or even accidental way, with pharmaceutical companies encouraging employees to take vacations in exotic locations and bring back dirt, fungus and other organic material, with tests then done on animals to see what the outcome would be… Gavin MacBeath, Harvard University, (2003).  Multidisciplinary efforts intersecting at a common ground of ―target-driven-drugs‖ that are a consequence of deliberate research and development…4 Sthohan | March 2013 | Pharma Innovation | Confidential
  5. 5. Historical perspective – influential pharmaceuticalsMedicine year ImportanceMorphine 1827 Commercialized by a pharmacy (Merck), pain management (Germany)Aspirin 1897 Synthetic salicylic acid was commercialized (Germany)Ether 1842 General anaesthetic, transformed surgery (US)Arsphenamine 1910 Syphillis Treatment (Hoechst, Germany)Insulin 1922 1st hormone therapy, transformed diabetes managementPenicillin 1929 Transformed the treatment of microbial diseasesChlorpromazine and 1950 Transformed management of psyschosis. (France) (Belgium)Haladol & 1958Estrogen+ Progestin 1961 Birth Control Pills, deep social impact (USA)Digoxin 1962 Changed treatment of heart failure and hypertension (Germany) (France)Furosemide 1993 Loop diuretic, effective treatment of hypertensionAtorvastatin 1996 Cholesterol lowering medicine (USA)HAART 1996-7 Transforming effect on AIDS patientsL-Dopa (Sweden); Hydrocortisone; Viagra (1996, USA); Ritalin 5 Sthohan | March 2013 | Pharma Innovation | Confidential
  6. 6. New Medicines Increase Longevity“They can mean an extra three months or five months or a year-another Christmas with the family, another season to plant a garden,another passage in the life of a child.”—Donna St. George on new targeted cancer therapies, The Washington Post, 2004 2.5 40% of Increase in Life Expectancy Increase in Longevity Due to New Drug Launches Number of Years Increased Longevity Total Increase in Longevity 1.96 2.0 1.65 1.5 1.37 1.07 1.0 0.76 0.79 0.70 0.57 0.62 0.56 0.45 0.5 0.30 0.23 0.12 0.0 1988 1990 1992 1994 1996 1998 2000 Data source: Lichtenberg. National Bureau of Economic Research Working Paper No. 9754 (Cambridge, MA: NBER, June 2003).6 Sthohan | March 2013 | Pharma Innovation | Confidential 11
  7. 7. Pharmaceutical Lifecyle7 Sthohan | March 2013 | Pharma Innovation | Confidential
  8. 8. Biotech: larger share of innovative approved drugsInnovativeness of FDA approved drugs (2001 – 2007) Source: USFDA 8 Sthohan | March 2013 | Pharma Innovation | Confidential
  9. 9. Drug Approvals 2012 Mullard, NatRev DD 2013  39 new drugs last year, marking a 15-year high. Most approvals since 1997 (↑33% over the last 20 years).  20 of 2012 approvals were first-in-class agents9 Sthohan | March 2013 | Pharma Innovation | Confidential
  10. 10. So how do we get there?It‘s a team effort……
  11. 11. Discovery processes: Target identification strategies Gene expression profiling Focused proteomics, e.g. activity-based protein profiling Pathway analysis – pathway databases, e.g. GeneGo Metacore & Ariadne Phenotype analysis – phenomic database Functional screening (siRNAs, shRNAs) Genetic association Scientific Literature11 Sthohan | March 2013 | Pharma Innovation | Confidential
  12. 12. Properties of an ideal drug target Target is disease-modifying and/or has a proven function in the pathophysiology of a disease. Modulation of the target is less important under physiological conditions or in other diseases. If the druggability is not obvious (e.g. as for kinases) a 3D-structure for the target protein or a close homolog should be available for a druggability assessment. Target has a favorable ‗assayability ‘ enabling high throughput screening. Target expression is not uniformly distributed throughout the body. A target/disease-specific biomarker exists to monitor therapeutic efficacy. Favorable prediction of potential side effects according to phenotype data (e.g. in k.o. mice or genetic mutation databases). Target has a favorable IP situation (no competitors on target, freedom to operate).12 Sthohan | March 2013 | Pharma Innovation | Confidential
  13. 13. Therapeutic approaches: target modulationTraditional Novel – Good IP position Small Molecules  Antibody drug conjugates • Enzymes, receptors, transcription  Stapled or stabilized factors, ion channels, transport proteins, protein-protein interfaces proteins Biologics  Nanotechnology • Extracellular proteins, trans-  Repurposed/repositioned membrane receptors, cell surface drugs receptors, substrates and metabolites  Patent extension Nucleic Acids • RNAi13 Sthohan | March 2013 | Pharma Innovation | Confidential
  14. 14. Discovery Processes: Lead Optimization14 Sthohan | March 2013 | Pharma Innovation | Confidential
  15. 15. Drug Failures in Ph II-IIIPhase II failures 2008-2010 Phase III failures 2007-2010 Nature Reviews Drug Discovery 10, 328-329 (May 2011) Nature Reviews Drug Discovery 10, 87 (February 2011) Leading reasons for adverse events: • cardiovascular toxicity • hepatotoxicity 15 Sthohan | March 2013 | Pharma Innovation | Confidential
  16. 16. Population Responses What we use in research models Intrinsic variability • Drug-target or metabolite target interaction • Type of target transduction • Access at the biophase • Delivery and input rate • Metabolism and pheno/genotype • Disease and homeostasis What is • Placebo response Extrinsic Variability • Drug-drug interactions • Interactions with endogenous substances16 Sthohan | March 2013 | Pharma Innovation | Confidential
  17. 17. Elements of early safety assessment• In vitro Safety Pharmacology: – Human target based: associated with clinical adverse reactions • GPCRs • Nuclear hormone receptors • Ion channels  Risk Assessment and Mitigation • Transporters • Kinases - Integration with ADME and PK data - Computer-assisted Drug Design (SAR) • Proteases -Clinical annotation • Other enzymes -Bioinformatics and network prosecution• Phenotypic and Organ-toxicity – Cell- & tissue-based • Cardiomyocyte-based assays • Hepatotoxicity • Hematotoxicity • Neurotoxicity • Genotoxicity 17 Sthohan | March 2013 | Pharma Innovation | Confidential
  18. 18. How to identify targets for safety profiling?Reverse translation Therapeutic effect A Relevance to EFPC Common ADR Molecular target Cmax AC50 General application Therapeutic effect B Define coverage EFPC: effective free plasma concentration AC50: concentration necessary to achieve 50% activity @ off-target, in vitro 18 Sthohan | March 2013 | Pharma Innovation | Confidential
  19. 19. Predicting targets based on ADRs Requirements • Large-scale computational effort to predict the activity of marketed drugs against adverse drug reaction (ADR) targets • In vitro profile of marketed drugs • Biomarker for the off-target related ADRs a d • Extrapolation to drug candidates to predict ADRs in silico a Side effect profile of d Side effect profile of Pr chlorotrianisene synthetic estrogens Prenylamine Chlorotrianisene Chlorotrianisene e e Domperidone Lounkine et al. Nature (2012) b19 Sthohan | March 2013 | Pharma Innovation | Confidential b
  20. 20. Prescription drug cocktails?There is a chance to enhance side effects by taking several promiscuous compounds Do we take this into account?20 Sthohan | March 2013 | Pharma Innovation | Confidential
  21. 21. Proof of Target – ADR link: 5HT2b agonism - VHD Common feature: 5HT2b agonism Clinical landscape of VHD Restrictions Withdrawn Withdrawn 30 Fen- Phen Dose dependent effect! Kvernmo, 2006 Specifics of 5HT2b-related VHD Long latency development, but irreversible* Hard to detect/diagnose in the clinic No signal in short regulatory animal studies Needs special in vivo experimental design to confirm manifestation 21 Sthohan | March 2013 | Pharma Innovation | Confidential
  22. 22. Combination therapy profiles Look for caution signals and common pathwaysPimozide Risperidone Zolpidem Alprazolam Fluphenazine Haloperidol22 Sthohan | March 2013 | Pharma Innovation | Confidential
  23. 23. Type 2 Diabetes mellitus treatment landscape Monotherapy add add Obese metformin sulfonylurea exenatide or Insulin or glitazone Non-obese Sulfonylurea exenatide or Insulin or or metformin glitazone elderly Low dose secretagogue Switch to simple insulin --- regimen Asian glitazone metformin Sulfonylurea or Insulin or Exenatide* (*not approved w glitazone) Multidrug regimen for diabetes can become more complex with atherogenic dyslipidemia, hypertension, and prothorombotic/proinflammatory states • Cholesterol management (simvastatin) • ACE inhibitors (enalapril) • Low dose aspirin 23 Sthohan | March 2013 | Pharma Innovation | Confidential
  24. 24. Combination therapy profilesmetformin sitagliptin pioglitazone simvastatin enalapril24 Sthohan | March 2013 | Pharma Innovation | Confidential
  25. 25. Drug Innovation – ―the new‖ New tools to do things • reagents to explore biological phenomena or new types of drugs, such as aptamers, chimeric proteins, peptidomimetics, multi-valent antibodies, etc. New ways to measure things • techniques of scientific observation and measurement, including new visualization methods, multiplexed assays, real-time biological kinetics measurements and others. New ‗things‘ themselves • devices, including the use of new materials with novel properties. New ways to handle and extract insights from experimental observations • advances in bioinformatics, data integration, knowledge management, artificial intelligence and others.25 Sthohan | March 2013 | Pharma Innovation | Confidential
  26. 26. Leveraging the existingNew IP?....
  27. 27. Repositioning"New technologies however enable the systematic evaluation of any drug or mechanism of action against any disease." Aris Persidis of Biovista is in the process of filing for novel use patents for 12 drugs with potential in Parkinsons, Alzheimers, epilepsy, depression and sleep disorders. Clive Morris, head of the new opportunities division at AstraZeneca, existing medicines that have already been in clinical trials can skip the early phase of drug development and go straight into phase two (mid-stage) trials, which can save three to five years. AstraZeneca is now testing a failed diabetes and obesity drug for use as a glaucoma treatment. AstraZeneca (October 2012) made 22 failed medicines available to academics through a partnership with the Medical Research Council and it also struck a £180m partnership with its bigger rival GlaxoSmithKline in May to boost the faltering development of new antibiotics, dubbed NewDrugs4BadBugs. "Typically, repositioning is done by accident, or in a limited way,― -between 2007 and 2009, 30% of all newly marketed medicines were either existing drugs or new formulations of old drugs. - - Aris Persidis (Biovista - 2012).27 Sthohan | March 2013 | Pharma Innovation | Confidential
  28. 28. Repositioning The safety advantage. • Existing drugs that are either approved or have been shown to be safe in late-stage trials, but have failed to meet end points of their originally-targeted indications, can leverage their inherently reduced development risk into potentially new indications. Since safety accounts for approximately 30% of drug failures in clinical trials, this is a significant development advantage that repositioned drugs enjoy. The money savings advantage. • Relaunching a repositioned drug averages $8.4 million, whereas to relaunch a new formulation of an existing drug in its original indication costs an average $41.3 million. NCE/NME development averages more than $1.3 billion (160 million times less investment). Repositioning is in a completely different league of investment needed to create a new drug product in the market. The market potential advantage. • Potential for market success depends on numerous factors, including market need, competition, differentiation, an excellent product, IP barriers, payer acceptance, compliance and a successful market strategy. These factors apply for repositioned drugs in the same way as they do for NCE/NME drugs as well. The return on investment potential. • Portfolio strategy: it is prudent to have a reasonable stable of repositioned drugs under development as a portfolio, to allow for attrition due to potential lack of efficacy (but not safety), when any drug is tested in clinical trials. The out-licensing potential. • Pharmaceutical companies are said to be exploring new models to out-license some of their clinical drug candidates that may have been shelved for whatever reason. Benefits: met end points and have proven themselves to be safe. Repositioning grants a pharmaceutical company specific and novel business development possibilities for out-licensing.28 Sthohan | March 2013 | Pharma Innovation | Confidential
  29. 29. Repositioning Original Use RepurposedAspirin (Bayer) - 1897 Inflammation and pain antiplatelet drug for treating and preventing heart attacks and strokesIbuprofen (Boots) -1960 Anti-inflammatory Hangovers, rheumatoid arthritis, and Parkinsons disease prevention?Galantamine (Sopharma) Plio paralysis/ Alzheimers1960’s - USSR anesthesiaZidovudine (GSK) 1964 Oncology HIV/ AIDSRogaine (Pfizer) - 1976 High blood pressure hair lossMifepristone (RU486) - 1980 Pregnancy termination Antipsychotic, major depressionGemzar (Lilly) - 1980s Antiviral cancer drugCymbalta (Lilly) - 1990 Antidepressant fibromyalgiaFinasteride (Merck) -1993 Benign prostatic Hair loss hyperplasiaTopiramate (JNJ) - 1996 Epilepsy ObesityViagra (Pfizer) -1996 Heart disease Erectile dysfunction Pulmonary Arterial Hypertension 29 Sthohan | March 2013 | Pharma Innovation | Confidential
  30. 30. Today and Beyond…..
  31. 31. Repositioning: explore alternative indications for existing drugsBioinformatics-based approaches have the potential to offer systematicinsights into the complex relationships among drugs, targets anddiseases necessary for successful repositioning.  Network modeling links repositioning objects in a network format.  The network biological relevance is measured by the purity of identified modules and topological parameters such as ―betweenness centrality and closeness.‖  The network can be used to predict novel repositioning opportunities. Liu,, DDT 2012 31 Sthohan | March 2013 | Pharma Innovation | Confidential
  32. 32. Biologics: 907 medicines and vaccines in development - 2013 338 cancer therapeutics that target several different types of solid tumors, leukemia and lymphoma. Monoclonal antibodies account for 170 of the 338 products in development. 176 candidates in development for an array of infectious diseases, including 134 PhRMA Productivity report 2013 vaccines. 71 medicines for autoimmune diseases, such as lupus, multiple sclerosis and rheumatoid arthritis. 58 treatments for cardiovascular diseases, such as congestive heart failure and stroke. Other diseases include diabetes, digestive disorders, genetic disorders, neurologic and respiratory disorders 32 Sthohan | March 2013 | Pharma Innovation | Confidential
  33. 33. Protein-protein interactionsToday: high-quality interaction networks of reasonable coverage are available for only a small number of interaction types and model organisms, thus limiting the evolutionary trajectories. Limiting our understanding. Yama and Burk. Nat rev mol cell biol 2009Future opportunities: shift from static 2D to comparative spatiotemporalnetwork.Higher density data with greater resolution means more opportunity. 33 Sthohan | March 2013 | Pharma Innovation | Confidential
  34. 34. Tools of nanotechnology Liposomes Nanoparticles Polymeric micelles Dendrimers Nanocantilever Carbon nanotubes Quantum dots Misra, 2010, DDT34 Sthohan | March 2013 | Pharma Innovation | Confidential
  35. 35. Stapled peptidesCan stapled peptides solve the ―undruggable space?‖ Historical perspective: • Not orally available in active form • Lack the ability to enter cells • Inactivated by proteases, filtered from the blood by the kidneys within minutes. A stabilized α-helix (pink) binds to a key portion of the HIV capsid (blue), as shown in an NMR structure. A hydrocarbon side-chain cross-link (yellow) helps this helix enter cells. Drahl, CEN. Volume 86 Issue 22 (2008) 35 Sthohan | March 2013 | Pharma Innovation | Confidential
  36. 36. New Technology: Histopathology imaging Whole slide images of histology sections resolved into distinct patches (e.g., viable tumor, necrosis) so that each patch can be linked with the outcome. Computed code, from the learned representation, is then utilized to classify patches from a curated library of images. Evaluation over 1400 and 2500 samples of glioblastoma multiforme and clear cell kidney carcinoma indicates a performance of 84% and 81%, respectively.Color coding is black(tumor), pink (necrosis),and green (transition to Processes are computationally demandingnecrosis). Solutions may be in High Perfomance Computing – AI learning. 36 Sthohan | March 2013 | Pharma Innovation | Confidential
  37. 37. Opportunities for innovation FIPNet (fully integrated pharmaceutical network) model of drug development, in which the core capabilities of different stakeholders in the development process are leveraged. CRO, contract research organization Katin, Clin Pharmacol Ther. 2010 March; 87(3): 356–361.37 Sthohan | March 2013 | Pharma Innovation | Confidential
  38. 38. Sharing? Securely profile every compound ever synthesized against every assay with multiple computational models in a collaborative manner, using standard technologies without structural disclosure. There is a need for a universal platform for collaborative drug discovery and development that will allow researchers to collaborate, while retaining refined IP rights. Bunin & Ekins, DDT 2011―Integrated specialization‖Operate within natural workflows or with minimal interruption to research individuals/teams.Securely and selectively collaborate with anyone or any organization with trulycomplementary and best in class capabilities… Bunn and Ekins DDT 2011 38 Sthohan | March 2013 | Pharma Innovation | Confidential
  39. 39. Questions and thoughts39 Sthohan | March 2013 | Pharma Innovation | Confidential