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Rapid Learning Precision Oncology

Rapid Learning Precision Oncology. Rapid Learning Precision Oncology. Part I: Patient’s Perspective. Part II: Industry Perspective. Part III: Aligning Incentives. Part I: Patient’s Perspective. clinical trials. chemotherapy. experimental methods. radiation. surgery.

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Rapid Learning Precision Oncology

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  1. Rapid Learning Precision Oncology

  2. Rapid Learning Precision Oncology Part I: Patient’s Perspective Part II: Industry Perspective Part III: Aligning Incentives

  3. Part I: Patient’s Perspective clinical trials chemotherapy experimentalmethods radiation surgery • Thousands of rare molecular subtypes • Tens of thousands of treatment combinations • Traditional RCTs become problematic

  4. Precision Oncology 2.0 (Today) Normal skin cell Scans Original cancer cell Biopsy Monitor Sequence Biomarkers Sequencing Machines Treated cell Treat Compare Patient Chromosomes Test Target Cancer cell Normal cell In vivo In silico In vitro Adapted from NY Times

  5. Precision Oncology 3.0 Normal skin cell Scans Original cancer cell Biopsy Biopsies Serum Markers Panomics Monitor Sequence Biomarkers Sequencing Machines Treated cell Combo Therapies Treat Compare Network Analysis Patient Networks Chromosomes Test Target TreatmentPlanning Cancer cell Normal cell In vivo In silico In vitro Adapted from NY Times

  6. Molecular Tumor Board Medical, surgical and radiation oncologists, biostatisticians, radiologists, and pathologists + clinical geneticists and specialists in cancer pathways, pharmacology, bioinformatics

  7. Case Reports

  8. No Learning

  9. Rapid Learning Precision Oncology A rapid learning community for cancer • Help each patient obtain the best possible outcome • Learn as much as possible • Disseminate rapidly Model Learn Treat Analyze

  10. Melanoma Molecular Subtypes Cell Signaling Pathways Subtypes MAPK 1 NRAS Responders 2 PTEN MITF 3 NRAS PI3K BRAF PI3K 4 AKT MEK CDK 5 Non- Responders c-KIT mTOR 6 ERK Bcl-2 Bcl-2, Bcl-xL, Mcl-1 7 MITF MAPK/ PI3K 8 8 NOXA, PUMA BIM, BID, BAD BAK p53 BAX Cyclin D MAPK/ CDK 9 9 MDM2 CDK4/6 p16 p14ARF NRAS/ MAPK/ PI3K 10 10 10

  11. Human-Machine Knowledge System Physicians Scientists Clinical Researchers Patients Patient Models Reference Models Specimens Labs Hospitals Payers Pharma Clinical Trials

  12. What It Means To Do Our Best “Although our ability to exploit knowledge of cancer pathways is in its infancy, we must do our best for today's cancer patients and, in the process, learn as much as possible for the patients of tomorrow.” Tony Blau MD, U. Washington ITOMIC: Intensive Trial of OMics in Cancer NCT01957514: Collecting, Analyzing, and Storing Samples From Patients With Metastatic, Triple Negative Breast Cancer Receiving Cisplatin (ITOMIC) University of Washington & NCI

  13. Rapid Learning Network Mitesh Borad Mayo Clinic George Demetri Dana Farber Tony Blau U. Washington Lincoln Nadauld Intermountain Health Joel Neal Stanford Andrea Califano Columbia U. Keith Flaherty MGH Heinz Josef Lenz, USC Ravi Salgia U. Chicago Beth Karlan Cedars Sinai

  14. Global Cumulative Treatment Analysis

  15. Part II: Industry Perspective Year 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 DrugDiscovery TrialsPhase 1 TrialsPhase 2 TrialsPhase 3 FDAApproval

  16. Replace Large Trials With… Year 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 DrugDiscovery TrialsPhase 1 TrialsPhase 2 TrialsPhase 3 FDAApproval

  17. N-of-1 Studies Year 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 DrugDiscovery FDAApproval

  18. Replace Discovery With… Year 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 DrugDiscovery FDAApproval

  19. All Approved + Investigational Drugs Year 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 DrugDiscovery FDAApproval

  20. Years To Months Month 1 1.5 2 2.5 3 Precision Oncology 3.0

  21. GCTA: Many Parallel N-of-1 Trials Month 1 1.5 2 2.5 3 Precision Oncology 3.0

  22. The Search For Cures

  23. Succeed Slowly 9 yrs 5 yrs 3 yrs 1 yr

  24. Fail Fast 5 yrs 3 yrs 1 yr

  25. Fail Fast 5 yrs 3 yrs 1 yr

  26. Bed to Bench 5 yrs 3 yrs 1 yr

  27. Bed to Bench 5 yrs 3 yrs 1 yr

  28. Tightly Integrate Research and Care “Although our ability to exploit knowledge of cancer pathways is in its infancy, we must do our best for today's cancer patients and, in the process, learn as much as possible for the patients of tomorrow.” Tony Blau MD, U. Washington “…There are still no curative treatments for castration-resistant prostate cancer (CRPC) and, therefore, it remains fatal….Our findings suggest that dual targeting of the Akt and mTOR signaling pathways using MK-2206 and MK-8669 may be effective for treatment of CRPC, particularly for patients with deregulated Rb pathway activity. “ Andrea Califano, PhD, Columbia

  29. Part III. Aligning Incentives Drug Fails • Lose cost of pills • Save years Physician applies for compassionate use Drug Works • Health plan pays • Replicate-small n • Fast track approval Pharma provides drug

  30. Toolkit Licensing

  31. Rapid LearningPrecision Oncology Tightly integrating cancer research, drug development, and clinical care will improve outcomes, accelerate research, and slash time to clinic. Trials are for validation, not discovery. GCTA-like studies are the only way to efficiently search the vast space of targeted therapies x subtypes. Managing an individual’s cancer, and then generalizing to other patients, is much more achievable than “Curing Cancer”. Barriers such as drug access and reimbursement can be overcome by aligning industry’s interests with the those of patients. The FDA has a critical role in predictive pharmacology, toolkit licensing, and single subject INDs for testing rational combination therapies.

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