1. Problems of the Design and Interpretation of Very Early Clinical Trials in Hemato-Oncology Bruce D. Cheson, M.D. Georgetown University Hospital Lombardi Comprehensive Cancer Center Chair, CALGB Lymphoma Committee Washington, D.C., USA

2. Earliest Published Clinical Trials Daniel 1:11-20. Health of Hebrews fed a Kosher diet vs Babylonians fed on a state diet Scurvy on the HMS Salisbury: cider vs vinegar vs lemons

3. Phases of Clinical Trials Phase I - determine toxicity Phase II - determine activity Phase III - evaluate efficacy Phase IV - post-marketing

4. The Problem 6500 trials open to accrual in the U.S. (clinicaltrials.gov) 3% of patients go on studies Studies compete for same patients 63% of trials are ever completed

5. Why our trials fail Blame the design Blame the physicians Blame the patients Blame the wealth of new agents Rarely do we blame the science

6. Problems in New Drug Development Slow rate of accrual to clinical trials Lack of good preclinical models Lack of surrogate endpoints False negatives – missing an active agent False positives – waste resources on ineffective agent

7. High False Positive Rate Rely on a single study Unpredictability of intermediate endpoints Get excited by waterfall plots Short follow-up Response duration Toxicity Unplanned subset analyses

9. Will Rogers (1879-1935)

10. The Will Rogers Effect “When the Okies left Oklahoma and moved to California, they raised the average intelligence level in both states!”

13. S= (5, 6, 7, 8, 9) – Mean = 7

14. Moving 5 to R

15. Mean of R increases to 3

17. Moves false-positive advanced stage to early stage

19. Contrast enhanced CT - axial view

20. PET - axial view

21. PET-coronal

22. Reducing the False Negative Rate Recognize tumor diversity Understand tumor biology

23. Not All Patients or Their Diseases Are Created Equal

24. Lymphoma Cancer Facts Lymphomas represent the 5th most common form of cancer in the US 2011 projected >75,000 new cases in the US alone with ~ 25,000 deaths/yr ~ 60 morphologic/immunologic subtypes Many more by molecular-genetic assessment No two lymphomas are alike and treatments must be selected based on an individual’s tumor characteristics, by personalized medicine

25. Antoni van Leeuwenhoek (1632-1723) Invented the microscope around 1668 21

26. TreatmentAdvice Contrast of Appearance vs.Gene Expression Profiling Microscope DLBCL DLBCL High Risk Low Risk Microarray 22

27. Lenz et al., N. Engl. J. Med. 2008 A study of the Lymphoma Leukemia Molecular Profiling Project (LLMPP)

28. Survival curves in diffuse large B-cell lymphoma treated with Bortezomib-R-CHOP Ruan J et al. JCO 2011;29:690-697

29. Lenalidomide in DLBCL Hernandez-Ilizaliturri et al, Cancer (e-pub, 2011)

30. Lenalidomide in DLBCL (n=40) Response Rates GCB - 9% (4% CR) Non-GCB – 53% (5% CR) P = .006 Hernandez-Ilizaliturri et al, Cancer (e-pub, 2011)

31. Microvessel Density in DLBCL Cardesa-Salzmann et al, Haematol 2011 (e-pub ahead of print)

32. L H Cardesa-Salzmann et al, Haematol 2011 (e-pub ahead of print)

33. Clinical Factors: -FLIPI -F2 Biological Factors: -Histology -Molecular -Cytogenetic -Protein-mRNA Predictors of Clinical Behavior in FL Host factors?-FCR SNPs Microenvironment-Others

34. Overall survival based on lymphoma associated macrophage (LAM) content Farinha, P. et al. Blood 2005;106:2169-2174

35. . Weng W , Levy R JCO 2003;21:3940-3947 FcgRIII Polymorphisms and Response to Rituximab

36. CORAL maintenance: PFS by gender in maintenance and observation arms 1.0 1.0 0.8 0.8 0.6 0.6 Survival probability Survival probability 0.4 0.4 0.2 0.2 p = 0.0044 p = 0.5921 0.0 0.0 0 12 24 36 48 60 72 0 12 24 36 48 60 72 PFS (months) PFS (months) Female Female Male Male Rituximab Observation

38. Probability of Survival 100 80 60 40 20 0 0 24 48 72 96 120 144 168 Months 13q deletion Patients surviving (%) 12q trisomy 11q deletion Normal 17p deletion Döhner H, et al. N Engl J Med. 2000;343:1910-1916.

39. Outcome With Alemtuzumab in CLL Cytogenetic Subgroups. Stilgenbauer S et al. JCO 2009;27:3994-4001

40. 100 100 80 80 Surviving (%) 60 60 Surviving (%) P=0.0008 P=0.001 40 40 20 20 0 0 50 100 150 200 250 300 0 0 50 100 150 200 250 300 Months Months Survival of CLL Patients With Mutated vsUnmutated VH Genes Stage-A CLL patients (n=62) All patients (n=84) Mutated Mutated Unmutated Unmutated Damle RN, et al. Blood. 1999;94:1840-1847. Hamblin TJ, et al. Blood. 1999;94:1848-1854

41. Genes That Best Discriminate Ig-Unmutated and Ig-mutated CLL Ig-Unmut Ig-Mut

42. Kaplan-Meier Estimates Based on Level of ZAP-70 Expression Likelihood of survival Risk of disease progression 100 90 80 70 60 50 40 30 20 10 0 100 90 80 70 60 50 40 30 20 10 0 <20% ZAP-70–positive cells 20% ZAP-70–positive cells % Progression % surviving <20% ZAP-70–positive cells 20% ZAP-70–positive cells P=0.009 P=0.01 0 2 4 6 8 10 12 14 16 0 4 8 12 16 20 24 28 32 36 Years after diagnosis Years after diagnosis Crespo M, et al. N Engl J Med. 2003;348:1764-1775.

43. The Nature of the Disease

44. Pathway vs. Network signaling Pathway “Newtonian” Network “Chaotic” A. Friedman and N. Perrimon, Cell 128, January 26, 2007

45. Shc Grb2 PI3-K Sos-1 Ras AKT Raf MEKK-1 MEK mTOR MKK-7 ERK JNK Which Target?

46. Sos-1 PI3-K Ras Grb2 Shc Raf MEK MEKK-1 JNK MKK-7 ERK AKT The Target Interactome Where’s the target? Courtesy of I. Serebriiskii and E. Golemis, Fox Chase Cancer Center

47. Cheson’s Rule “The efficacy of a new drug is directly proportional to its negative impact on clinical research”

48. Victims of Our Own Successes: The Disease Front-line HL Front-line DLBCL Front-line FL Front-line CLL

49. Victims of Our Own Successes: The Drug New drug B is very active in relapsed/refractory disease Rapidly adopted as front-line Problems No drug B naïve pts against which to compare drug C No data on other drugs in B-relapsed pts Results in relapse too good to improve upon Results in front-line too good to improve upon

50. Examples TK inhibitors in CML B(R) in F/LG NHL B(R) in CLL Brentuximabvedotin in HL

51. Solutions Drug B +/- drug C in relapsed-refractory pts Takes a randomized trial Long time for answer Drug C in B-refractory pts No data with other agents Risky

52. Do We Have Surrogate Endpoints?

53. 1.0 0.8 0.6 0.4 0.2 0.0 0 12 24 36 48 84 60 72 Time (months) MRD Response and Treatment-Free Survival After Alemtuzumab Treatment (N=91) MRD-negative CR/PR (n=18) P<0.0001 Cumulative probability MRD-positive CR (n=14) MRD-positive PR (n=17) Nonresponders (n=42) Moreton P et al. J Clin Oncol. 2005;23:2971-2979.

54. PRIMA: Primary endpoint (PFS): 36 months’ follow-up after randomisation 1.0 0.8 75% Rituximab maintenance 0.6 Event-free rate 58% 0.4 Observation Stratified HR = 0.55 95% CI: 0.44–0.68 p < 0.0001 0.2 0.0 0 6 12 18 24 30 36 42 48 54 60 Time (months) Patients at risk 505 472 445 423 404 307 207 84 17 0 – 513 469 415 367 334 247 161 70 16 0 – GA Salles et al. ASH 2010, Abstract 1788

55. Progression-free survival(from study registration)Conventional response assessment 1.0 CR/CRu PR 0.8 SD/PD 0.6 Probability of PFS 0.4 0.2 p < 0.0001 0.0 0 6 12 18 24 30 36 42 48 54 60 Time (months) No. of subjects Event Censored Median PFS (months) CR/CRu 89 35% (31) 65% (58) 52 PR 27 44% (12) 56% (15) NR SD/PD 8 88% (7) 13% (1) 7

56. Progression-free survival(from study registration) Post-treatment PET-CT based assessment 1.0 PET negative PET positive 74% 0.8 0.6 Probability of PFS 0.4 32% HR = 3.5 (95% CI 2.0-6.1) p < 0.0001 0.2 0.0 0 6 12 18 24 30 36 42 48 54 60 Time (months) Event Censored Median PFS (months) No. of subjects PET negative 31% (28) 69% (63) NR 91 PET positive 33% (11) 19 33 67% (22)

57. Progression-free survival according to IPS group and PET results after two cycles of ABVD Gallamini, A. et al. J Clin Oncol; 25:3746-3752 2007

58. BEACOPP treatment for 154 PET-2- positive advanced-stage HL patients PET2-neg All pts PET2+ Gallamini A. et al, Br J Haematol, 152:551, 2011

59. CALGB Risk-Adapted Studies in HL

60. Variables Influencing Interim PET Results Disease Stage Therapy Method of interpretation

61. Accelerate Completion of Clinical Trials Activate fewer studies Consider alternative funding sources Identify surrogate endpoints Novel statistical designs

62. Is There Still a Role For Traditional Phase I Studies in Haematologic Malignancies?

63. Dose Escalation of Rituximab in CLL Dose Patients with toxicity 2 (mg/m ) No. No. Grade 500 3 0 - 650 3 1 1+ nausea 825 3 0 - 1000 3 2 1+ malaise, nausea 1500 4 1 dyspnea, dose 2 2250 10 5 2+ fever, chills 1+ nausea, fatigue $LT O’Brien et al, JCO 19:2165-70, 2001

64. Need to Consider Novel Study Designs

66. Tumour growth may be slow

67. Single arm study cannot identify improved PFSEnrichment design Select/randomize relatively homogenous patients

68. . Rosner G L et al. JCO 2002;20:4478-4484 Randomized Discontuation Design

69. A Proposal for New Drug Development in Cancer Small Phase II Trials Molecular Enrichment Molecular Enrichment Repeat

70. I-SPY2 TRIAL* ADAPTIVELY RANDOMIZE Experimental arm 1 Experimental arm 2 Outcome: Complete Response Population of patients Experimental arm 3 Experimental arm 4 Experimental arm 5 Standard therapy *Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis 2

71. Sometimes We Are Misled By Rigid Response Criteria CLL Cheson, et al, Am J Hematol 29:72, 1988 Cheson, et al, Blood 87:4990, 1996 Hallek, Cheson, et al, Blood 111:5446, 2008 AML Cheson, et al, JCO 8:813, 1990 Cheson et al, JCO 21:4642, 2003 MDS Cheson, et al, Blood 96:3671, 2000 Cheson, et a, Blood 108:419, 2006 NHL Cheson, et al, JCO 17:1244, 1999 Cheson, et al, JCO 25:579, 2007 MM – Don’t blame me!

73. Bone pain

75. The Road to Individualized Therapy Starts With Science

76. CALGB Current/Planned Protocols in Untreated Follicular NHL Low-Intermediate FLIPI 50402 - Rituximab + galiximab (completed) 50404 - Rituximab + oblimersen (RIP) 50701 - Rituximab + epratuzumab (completed) 50803 - Rituximab + lenalidamide (near completion) 50901 – Ofatumumab (500 mg vs 1000 mg) 511XX – Rituximab/Lenalidomide +/- PCI32765

77. Correlative Studies PET scans Molecular profiling, gene expression TMAs collected on all patients Studies of effector cell number/function FOXP3, T-Regs Microenvironmental factors, LAMs SNPs MicroRNAs

79. GCB v ABC DLBCL Analysis

80. Discovery

81. Whole Genome Sequencing

82. Germ line and Tumor

83. Discovery 6 9 15 0 18 3 21 25 12 Time Line (weeks)

84. Regulatory Problems

85. Study Design: Relapsed/Refractory CLL Fludarabine/Cyclophosphamide Eligible Patients Fludarabine/Cyclophosphamide Oblimersen Dosing regimen: Oblimersen 3 mg/kg/d d1-7 Fludarabine 25 mg/m2/d d5-7 Cyclophosphamide 250 mg/m2/d d5-7 O’Brien et al, JCO 27:5208, 2009

86. Primary Endpoint Major Response 25 CR 17% nPR 20 Percent Major Response 15 P=0.025 9 7% 10 2 5 8 5 0 FC Oblimersen/ FC O’Brien et al, JCO 27:5208, 2009

87. Survival curves by treatment arm with 5 yrs follow-up ITT population CR or PR patients Patients with fludarabine- sensitive disease O'Brien S et al. JCO 2009;27:5208-5212

88. FC +/- Oblimersen in R/R CLL: PFS O'Brien S et al. JCO 2007;25:1114-1120

89. Reasons for FDA Rejection PFS better than OS in relapsed setting PFS secondary endpoint No PFS difference between arms Small benefit outweighed by adverse effects Could not identify pts likely to benefit

90. Safety and Efficacy Value FDA EMEA

91. Challenge to Trigger Paradigm Shift CURE FOR CANCER Paradigm Shift Mind Shift Patients & Advocates Pharma. & Biotech Co. Insurance & Guidelines $$$ Science & Medical Government & Policy Makers

92. Life Cycle of Drug Development Drug Discovery Rebirth Epiphany Clinical Trial Crisis (inactive, toxic) Safety + Efficacy Approval!! Pharmacoptosis (Programmed drug death)