BIO International Convention


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Boston Biotech Clinical Research (BBCR) Presentations at the BIO International Convention.

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  • A qualified biomarker must link a biomarker with biology and clinical end points.Wagner, Webster, 2007, Nature
  • SMs are therapies that are matched to patient subpopulations with the aid of clinical biomarkers that predict with some reliability patient differential response – be it in efficacy or safety. Our notion of clinical biomarkers is not limited to genotyping – also includes imaging, clinical observation, or even patient self-report (urge vs. stress incontinence, self-identified black person).
  • BIO International Convention

    1. 1. Rare Diseases Experience as a Model to Critically Affect Innovation in Biomarker Strategy and Precision Medicine<br />Moderator<br />Candida Fratazzi MD <br />Speakers<br />Claudio Carini, PhD, FRCPath<br />GioraFeuerstein MD, MSc. F.A.H.A. <br />Mark TrusheimPhD <br />Colin Williams PhD <br />
    2. 2. Precision Medicine The Time is now<br />Claudio Carini, MD, PhD, FRCPathPfizer Inc.<br />
    3. 3. Drug Development is a lengthy, high- attrition process<br />More Spending – Less Apparent Productivity and Innovation?<br />
    4. 4.
    5. 5. What is missing?<br />Biomarkers<br />
    6. 6. Biomarker Definition<br />A molecule that indicates an alteration of<br />the physiological state of an individual in <br />relationship to health or disease state, <br />drug treatment, toxins etc<br />Biomarkers are by virtue of their short<br />term availability predictors of long term <br />events<br />
    7. 7. Why Biomarkers are Important in Medicine?<br />Staging or Severityof Disease<br />Patient/Subject Selection<br />Safety/Prediction of AE<br />Prognosis of TX intervention<br />Patient/Subject Selection<br />Discriminate Health from Disease Stage<br />Monitoring ClinicalResponse to Therapy<br />
    8. 8. The Elephant in the Room<br />Putting it all together<br />Understanding <br />A multi<br />-<br />”<br />omics<br />”<br />Qualified<br />Biology<br />Strategy<br />Biomarkers<br />Genechip<br />Target<br />n<br />It<br />’<br />s<br />It<br />’<br />s<br />UC<br />UC<br />Efficacy<br />n<br />RT<br />-<br />PCR<br />PK/PD<br />n<br />It<br />’<br />s<br />It<br />’<br />s<br />IHC<br />RA<br />RA<br />Safety/<br />/Tox<br />It<br />’<br />s<br />It<br />’<br />s<br />n<br />It<br />’<br />s<br />It<br />’<br />s<br />SLE<br />SLE<br />AS<br />AS<br />Flow <br />Mechanism<br />n<br />cytometry<br />Pharmacology<br />n<br />Molecular <br />imaging<br />Disease progression<br />n<br />It<br />’<br />s<br />It<br />’<br />s<br />It<br />’<br />s<br />It<br />’<br />s<br />Classification<br />Protein <br />n<br />JIA<br />JIA<br />analysis<br />CD<br />CD<br />Precision Medicine<br />n<br />Mass <br />Understanding <br />Spectrometry<br />Drug PK/PD<br />Proteomics <br />profiling<br />
    9. 9. Biomarkers: Potential Guides to Effectiveness and Safety<br />The -omics<br />Clinical<br />New study paradigms*<br />Experimental human biology<br />Imaging<br />An Integrated Approach<br />Proteomics<br />Pharmacogenetics<br />Metabonomics<br />
    10. 10. Building Bridges Between Research and Clinical Development<br />Exchange of Information<br />Biomarkers - PK - PG - Experimental CP<br />
    11. 11. Preclinical<br />Animal <br />Testing<br />Biomarkers<br />Compounds<br />Biomarkers Connect Discovery and Clinical Research<br />Clinical <br />Medicine<br />Clinical Research <br />Phases<br />Discovery & Preclinical Phases<br /><ul><li> Better </li></ul>Qualified <br />Compounds<br /><ul><li> Patient </li></ul>Enrichment<br />Strategies<br />Omics, <br />Screening <br />Based on <br />Cellular , <br />Physiologic<br />Models,<br />Driven by <br />Target<br />Population<br />Analysis<br />Diagnostic <br />tests<br />Patient samples<br />Missing? Impact on clinical medicine<br />Bench to Bedside<br />
    12. 12. What Patients Expect Today and More So in The Future?<br />BIOMARKERS<br />Drugs that work<br />Drugs that are safe<br />Doses that are right <br /> for me<br />12<br />
    13. 13. A fit-for-Purpose Biomarker<br />Qualified Biomarker<br />Clinical endpoints <br />Biology<br />A qualified biomarker must link a biomarker with biology and clinical end-points<br />13<br />
    14. 14. Why Do we Need Biomarkers?<br />To treat diseases more effectively: Disease Biomarkers<br />Disease BM will enable the:<br />1. Differentiation/stratification of otherwise similar disease states<br />2. Better identifies which disease states are more responsible to the study drug<br />3. Evaluation of disease susceptibility<br />4. Treat high risk pts before the onset of symptoms<br />5. Tracking disease progression<br />To predict clinical efficacy: Patient Selection BM<br />Patient BM will provide:<br />1. Explain why Pts are responding differently to different drugs<br />2. Basis for differentiating “high responders” from “low responders”<br />3. To target “ high responders” who stand better chances of success<br />
    15. 15. What is Personalized Medicine?<br />15<br />
    16. 16. Major Drugs Ineffective for Many…<br />Beneficial to Some<br />16<br />
    17. 17. Harmful to Others<br />17<br />
    18. 18. <ul><li>Why do individuals respond differently to the same drug?
    19. 19. Why do individuals require different doses?
    20. 20. Why do some experience AE after taking the drug?
    21. 21. Genetic variation of the drug target gene
    22. 22. Genetic variation in the biochemical pathways affected by the drug
    23. 23. Genetic and genomic factors related to the etiology of the disorder
    24. 24. Other factors (age, sex, diet, environment ...)</li></ul>Pharmacogeneticslooks at inherited factors that may influence these differences.<br />
    25. 25. Responders<br />Non-Responders<br />Adverse Drug <br />Events<br />Current Treatments Take Little Account of Human Variation<br />
    26. 26. Personalized Medicine Foresees Greater Use of Diagnostics in Therapeutic Decision Making<br />Responders<br />Non-Responders<br />Adverse Drug Events<br />Choose the RIGHT DRUGat the RIGHT DOSEfor the RIGHT PERSON<br />A<br />B<br />Dx<br />Test<br />C<br />
    27. 27. 21<br />Why is Personalized Medicine Important?<br /><ul><li>To avoid adverse events:
    28. 28. 2.2 million people are hospitalized and 100,000 deaths occur each year due to adverse effects of prescription drugs
    29. 29. To better treat disease:
    30. 30. Development of predictive markers would allow for earlier treatment
    31. 31. To identify novel drug targets:
    32. 32. Current drugs are based on less than 500 targets. </li></li></ul><li>Why we Need Personalized Medicine in Research and Drug Development? Safer and more Effective Drugs<br />22<br />
    33. 33. Six Blinded Scientists Examining an Elephant<br />Translational Medicine: the lacking piece of the puzzle<br />23<br />
    34. 34. 24<br />Thank You<br />Questions?<br />
    35. 35. Gene discovery and genomic prediction of Atherosclerosis disease states and susceptibility<br />
    36. 36. 26<br />
    37. 37. Biomarkers In Drug Discovery and Development: Orphan Diseases and Orphan Therapeutics<br />Giora Feuerstein MD<br />FARMACON LLC<br /> Washington DC<br />June 28, 2011<br />
    38. 38. …and its getting worse<br />Translational Medicine in Pharmaceutical Industry:<br /> from “nice to have” to “do or die”<br />
    39. 39. Translational Medicine in Pharmaceutical Industry: from “nice to have” to “do or die”<br /><ul><li>Aims at reducing the Attrition Rate – Increase Successful Deliveries by Rigorous Science
    40. 40. From “Bench to Bed and Bed to Bench” (BB2)
    41. 41. Identification, validation and implementation of Biomarkersin lieu of clinical end-points
    42. 42. Harmonize and Rationalize Pre-clinical Research, Safety/ADME and Early Clinical Development </li></li></ul><li>Target Validation<br /><ul><li>Biomarkers that validate the importance of the target in human disease
    43. 43. Biomarkers that define the direct interaction of the compound with its discrete target
    44. 44. Biomarkers that define consequencesof compound interaction with the target relative to PK
    45. 45. Biomarkers that correlatewith disease </li></ul> (initiation, progression, regression, remission, relapse or modification)<br /><ul><li> Biomarkers that define likelihood of patients to respond (or not) to the compound</li></ul>Target/Compound<br />Interaction<br />Pharmacodynamic Activity (PK/PD)<br />Disease Biomarker<br />& Disease Modification<br />Patient selection and<br />Stratification<br />Biomarkers: A Utilitarian Classification<br />
    46. 46. PK/PD Biomarkers in Orphan Disease <br />show the way<br /><ul><li> Case Study 1: Muckle–Wells syndrome
    47. 47. Rare genetic disorder provides biomarkers that ‘pave the way’ for target validation
    48. 48. The case of anti-IL-1b development for RA
    49. 49. PK/PD- Biomarkers
    50. 50. Bayesian methodology
    51. 51. Target validation in M-W syndrome
    52. 52. Registration for Rheumatoid arthritis</li></li></ul><li>                      <br />Website for this image<br /><br /><ul><li>Full-size image - Same sizex larger</li></ul>This image may be subject to copyright.<br />Target Validation: When Biology Trumps Chemistry<br /><ul><li> Case Study 2: Diabetes
    53. 53. Diabetes drugs are available but unmet medical need high
    54. 54. Insulin injection is the ultimate treatment in chronic diabetes
    55. 55. Insulin sensitivity drugs (TZDs) of limited efficacy and carry safety issues
    56. 56. 11beta-HSD-1 inhibitors have the potential to improve insulin sensitivity
    57. 57. Neuro-endocrine liabilities observed with all HSD-1 inhibitors</li></li></ul><li>~<br />-<br />Hypothalamus<br />Tissue<br />Plasma<br />~<br />Pituitary<br />[Drug]<br />[Drug]<br />~<br />Adrenal<br />[HSD-1]act<br />~<br />[cortisol]n<br />[cortisol]<br />~<br />Cortisol<br />~<br />IR<br />Translational Medicine Case Study:When Biology “trumps” the compound, The 11bHSD1 Inhibitor saga <br />PK<br />PD<br />Plasma AdiposeTissues<br />Liver<br />
    58. 58. Visceral Fat<br />SubQ Fat<br />D4-Cortisol/D3-Cortisol<br />Translational Medicine Issue: Can 11beta-HSD-1 inhibitors reduce peripheral tissue local cortisol and reduce tissue IR w/o activating the HPA<br />The “Killer Study”<br />HSD1 inhibitors can reduce IR w/o change in plasma cortisol<br /><ul><li>Translational Medicine study (Univ Edinburgh, B walker)
    59. 59. Tissue cortisol production is significant
    60. 60. In non-diabetics:
    61. 61. Liver: Major source (~90%) of splanchniccortisol release into the circulation
    62. 62. SubQ fat: Account for ~10% of cortisol release
    63. 63. Visceral fat: does not appear to contribute to net cortisol output</li></li></ul><li>Rare Diseases as Stratified Medicine Economic Models<br />Mark Trusheim<br />Visiting Scientist, MIT<br /><br />President, Co-Bio Consulting<br />
    64. 64. What We Mean by Stratified Medicine<br />Matching therapies to patient sub-populations with clinical biomarkers<br />Objective: Do more good (efficacy) or avoid ill (adverse reactions)<br />Clinical Biomarkers -- beyond genotyping<br />Molecular (gene expression, proteomic, biochemical)<br />Imaging<br />Clinical observation<br />Patient self-reporting<br />Clinical Biomarkers: Any information which shows a reliable, predictive correlation to differential patient responses<br />
    65. 65. The Patient Therapeutic Continuum: Stratified Medicines are not “Personalized”<br />Nature Reviews Drug Discovery: April 2007<br />
    66. 66. Orphan Drugs Demonstrate Economic Potential<br />Stratified<br />Medicines<br />Increasingly<br />Approaching<br />Orphan sizes<br />(thousands of patients, average yearly price in $thousands)<br />
    67. 67. Comparing Orphan and Stratified Medicines<br />Orphan<br />Stratified<br />Known mechanism & marker<br />Small population<br />Strong patient and provider networks<br />Modest payer impact<br />Known mechanism & marker<br />May be small or large population<br />Perhaps unrecognized strata and no networks<br />Modest payer impact for one, but large if entire field (like oncology) stratifies<br />
    68. 68. When are Orphan Drugs Good Models for Stratified Economics?<br />Stratification creates a small population<br />Strong patient advocacy exists<br />Clinical trial and regulatory models for small populationsBUT<br />Market exclusivity and lower competition may not apply<br />Payer concern that a large stratified condition is not ‘rare’10% of all Alzheimer’s patients is a lot of patients, and cost.<br />
    69. 69. Orphans Modeling Stratified Medicines: Expect Price and Profitability Premiums?<br />Supporting Arguments<br />Stratified medicines will perform substantially better for their target populations than alternative treatments (assumption)<br />Recently introduced therapies have commanded price premiums: biologics, stratified medicines, adjuvant therapies<br />Payers have formal or informal policies to “pay for performance”<br />Counter Arguments<br />Limited payer ability to afford increased costs<br />Diagnostics will siphon profitability<br />Multiple entrants in new “stratified” drug classes will lower prices<br />Analytical Task<br />Develop a Performance Differential/Price Premium curve by examining price premiums obtained in the market today by “classic” therapies LIKE ORPHAN DRUGS<br />Price<br />Premium<br />Performance Differential<br />
    70. 70. Orphans Modeling Stratified Medicines: Development Processes<br />Opportunities<br />Strong patient and provider networks to enable clinical trials<br />Novel clinical trial designs to accommodate few patients available can speed development and lower costs<br />Potentially more rapid entry into man based on strong mechanism understanding and high need<br />Challenges<br />Need to develop and validate biomarker lower since embedded in diagnosis<br />Regulatory skepticism that stratification is tactic to avoid ‘gold standard’ clinical trials<br />Clinical<br />Trial<br />Size<br />Biomarker Driven Performance Differential<br />Potential: Lower Cost and Higher Success<br />Probability of<br />Regulatory<br />Approval<br />
    71. 71. Orphans Modeling Stratified Medicines: Public Policy and Incentives?<br />Federal Research and Development Support<br />NIH grants for research, and even development (Bench to Bedside Awards)<br />Expedited regulatory pathways<br />Federal Financial Incentives<br />Market exclusivity grants to INDICATION<br />High value reimbursement<br />R&D support above<br />Registries to identify, monitor and involve patients and samples<br />Role for Disease Foundations<br />Awareness, network creation and dissemination<br />Direct research support<br />Expert science panels validates early, small company science<br />
    72. 72. Orphan Learnings in Stratified Medicine Examples<br />Tysabri re-introduction for Multiple Sclerosis enabled by patient advocacy, patient registries and now, a biomarker<br />Rare oncology sub-populations receiving Orphan level reimbursement<br />Provenge autologous stem cell therapy: $93,000 for 3 course regimen<br />Erbitux and Vectibis: Up to $80,000 for 18 week regimen<br />Revlimid: Up to $10,000 per month for multiple myeloma<br />Gleevec: Up to $54,000 per year for CML<br />High market shares (>80%) are possible<br />
    73. 73. Conclusions<br />Rare diseases and orphan drugs have blazed the trail for stratified medicine economic models<br />From clinical development through regulatory to reimbursement and public policy, the lessons of rare diseases are being translated to stratified medicine<br />However, the aggregate size of some stratified medicine markets may strain payers and induce skepticism by regulators that special treatment is appropriate<br />An ‘integrated stakeholder chain” from research foundations to companies, regulators, payers and advocates is critical<br />
    74. 74. Information in Biomarker discovery<br />How effective use of information resources can support innovation<br />Dr. Colin Williams<br />Thomson Reuters<br />
    75. 75.
    76. 76. Why information?<br />“In 1990, all the necessary data for the concept of feedback control of p53 function were available, although this function was recognized only recently.”<br />Conceptual biology: Unearthing the gems, Nature 416, 373; 2001 Blagosklonny, M and Pardee, A<br /><ul><li> Knowledge differentiates organizations and delivers competitive advantage
    77. 77. Decreases risk
    78. 78. Enhances project level decision making
    79. 79. Focuses resource allocation
    80. 80. Empowers scientists to drive innovation
    81. 81. Creates efficiencies by preventing wasted experimentation</li></li></ul><li>The information challenge<br /><ul><li>Information overload
    82. 82. Wide range of sources - Literature, Patents, Conferences and medical meetings, Press releases, Clinical trial reports
    83. 83. Google 425k hits – Her2 and biomarker
    84. 84. Highly variable terminology in Biology
    85. 85. Lack of standard or Universal criteria on Biomarker development
    86. 86. Variation in protocols, statistical analysis
    87. 87. So many parameters not enough subjects
    88. 88. It is estimated scientists spend ~35% time dealing with information</li></li></ul><li>Mesothelioma<br /><ul><li>Mesothelioma is a form of cancer that affects the Mesothelium and can affect:
    89. 89. the inner surface of the chest wall where it is known as the pleura
    90. 90. the abdomen, where it is known as the peritoneum.
    91. 91. Organs within those cavities eg lung, heart
    92. 92. New diagnoses in US ~2,500 annually</li></li></ul><li>
    93. 93. <ul><li>Mesothelioma drug pipeline – 52
    94. 94. Compared to 1104 drugs under development for Obesity
    95. 95. Source: Thomson Reuters Integrity</li></li></ul><li><ul><li> Reported Biomarkers of Mesothelioma - 430
    96. 96. 3,400 hits in Google search
    97. 97. PubMed 1143 results</li></li></ul><li>
    98. 98. Proof of efficacy with mesothelioma markers<br /><ul><li>Ranpirnase (activation of Caspase)
    99. 99. Cisplatin
    100. 100. Gemcitabine hydrochloride
    101. 101. Pemetrexed disodium
    102. 102. Troglitazone
    103. 103. PPAT agonist inhibitors
    104. 104. LenvatinibMesylate
    105. 105. BEZ-235 (Novartis Phase I/II breast cancer, mTor inhibitor)
    106. 106. Celecoxib
    107. 107. AZD-1152-HQPA
    108. 108. Do the targets associated to these drugs have a role in other disease?</li></li></ul><li>
    109. 109.
    110. 110. The Core cell cycle, Source MetaCore<br />
    111. 111. Gene Expression and Mesothelioma<br /><ul><li>Developing insights from experimental information is also a critical
    112. 112. Analyzing gene expression data from mesothelioma can give a glance in to the mechanism of the disease
    113. 113. Analyse publically available dataset from Geo (GDS2604)
    114. 114. Explore expression profile in responders to previously identified drugs and identify differentially expressed genes</li></li></ul><li>
    115. 115.
    116. 116. Summary<br /><ul><li>Knowledge enhances decision making
    117. 117. Improve efficiency in project design through researching the area
    118. 118. Biomarker information is:
    119. 119. published in a non standard way
    120. 120. is fragmented way
    121. 121. is expanding rapidly
    122. 122. Disease segmentation based on molecular characteristics is going to create many new orphan diseases.
    123. 123. Will the ophan disease ‘model’ become the life blood of pharmaceutical research
    124. 124. There are many biomarkers available which can prove efficacy of a compound.
    125. 125. Using Mesothlioma (or other orphan diseases) as a model can prove efficacy against a target quickly.
    126. 126. Understanding the biological function of that target can open new indications for a therapeutic</li>