Pharmacodynamic Paradigms in Early-Phase Cancer Clinical Trials

1. Pharmacodynamic Paradigms in Early-Phase Cancer Clinical Trials Workshop Phase 0 Trials In Oncologic Drug Development Hilary Calvert Northern Institute for Cancer Research

2. Methodology for Phase I and Phase 0 (translational) Trials Develop trial methodology designed for targeted agents in trials with pharmacodynamic endpoints The use of pharmacodynamic or toxic endpoints present similar problems – magnitude, reproducibility, variability Endpoints • To develop methods that utilise continuously variable (scalar) endpoints rather than yes/no (Boolean) endpoints • To extend these techniques to combination Phase I trials

3. Traditional Starting dose Modified Fibonacci escalation Maximum Tolerated Dose (MTD) as an endpoint Disadvantages Patient inefficient Many patients at ineffective doses Safety risk as MTD is approached No built-in confidence intervals Pharmacokinetically-guided (Collins) Establish Target Area Under the Curve (AUC) from preclinical studies Monitor Pharmacokinetics at starting dose Escalate in large increments to achieve target AUC in patients Inter-patient variability in PKs Disadvantages Assumes linearity Metabolites May not be feasible Classical Methodology for Phase I and Translational Trials • Continual Reassessment (O’Quigley) • Stochastic model to predict probability of DLT vs dose • Starting dose • Dose doubling • Add data to model • Predict dose with desired probability of DLT • Disadvantages • Methodologically complex • Needs constraints for safety • May take time to converge • Accelerated Phase I Design (Simon) • Starting dose • Single patient dose doubling • Increase patients per cohort and reduce dose increments when mild (Grade II) toxicity is seen • Disadvantages • Could be hazardous with a steep dose/toxicity relationship • Little data at lower dose levels

4. Traditional Starting dose Modified Fibonacci escalation Maximum Tolerated Dose (MTD) as an endpoint Disadvantages Patient inefficient Many patients at ineffective doses Safety risk as MTD is approached No built-in confidence intervals Pharmacokinetically-guided (Collins) Establish Target Area Under the Curve (AUC) from preclinical studies Monitor Pharmacokinetics at starting dose Escalate in large increments to achieve target AUC in patients Disadvantages Inter-patient variability in PKs Assumes linearity Metabolites May not be feasible Classical Methodology for Phase I and Translational Trials • Continual Reassessment (O’Quigley) • Stochastic model to predict probability of DLT vs. dose • Starting dose • Dose doubling • Add data to model • Predict dose with desired probability of DLT • Disadvantages • Methodologically complex • Needs constraints for safety • May take time to converge • Accelerated Phase I Design (Simon) • Starting dose • Single patient dose doubling • Increase patients per cohort and reduce dose increments when mild (Grade II) toxicity is seen • Disadvantages • Could be hazardous with a steep dose/toxicity relationship • Little data at lower dose levels

5. CI-941 – DMP-941 - Losoxantrone • Similar to mitoxantrone • Animal models • Activity equal to or better than doxorubicin • No or little cardiotoxicity • One of 3 analogues submitted for clinical development by Warner Lambert • Candidate for AUC-based dose escalation • Preclinical pharmacology established “target” AUC and linearity up to 45 mg/m2

6. Target AUC Recommended Phase II dose Foster et al, Br J Cancer 28(213):463-469, 1992

7. Traditional Starting dose Modified Fibonacci escalation Maximum Tolerated Dose (MTD) as an endpoint Disadvantages Patient inefficient Many patients at ineffective doses Safety risk as MTD is approached No built-in confidence intervals Pharmacokinetically-guided (Collins) Establish Target Area Under the Curve (AUC) from preclinical studies Monitor Pharmacokinetics at starting dose Escalate in large increments to achieve target AUC in patients Disadvantages Inter-patient variability in PKs Assumes linearity Metabolites May not be feasible Classical Methodology for Phase I and Translational Trials • Continual Reassessment • Stochastic model to predict probability of DLT vs. dose • Starting dose • Dose doubling • Add data to model • Predict dose with desired probability of DLT • Disadvantages • Methodologically complex • Needs constraints for safety • May take time to converge • Accelerated Phase I Design (Simon) • Starting dose • Single patient dose doubling • Increase patients per cohort and reduce dose increments when mild (Grade II) toxicity is seen • Disadvantages • Could be hazardous with a steep dose/toxicity relationship • Little data at lower dose levels O'Quigley J et al: Biometrics, 46, 33-48, 1990

8. Comparison of mCRM1 Method with Traditional Method - Pemetrexed • Rinaldi DA et al: Cancer Chemotherapy and Pharmacology 44 (5): 372-380, 1999 • Rinaldi DA et al: Journal of Clinical Oncology 13 (11): 2842-2850, 1995 • McDonald AC et al: Clinical Cancer Research 4 (3): 605-610, 1998 • Faries D: J Biopharm Stat 4:147-164, 1994 Proc ASCO 1997, Abs no 733

9. Traditional Starting dose Modified Fibonacci escalation Maximum Tolerated Dose (MTD) as an endpoint Disadvantages Patient inefficient Many patients at ineffective doses Safety risk as MTD is approached No built-in confidence intervals Pharmacokinetically-guided (Collins) Establish Target Area Under the Curve (AUC) from preclinical studies Monitor Pharmacokinetics at starting dose Escalate in large increments to achieve target AUC in patients Disadvantages Inter-patient variability in PKs Assumes linearity Metabolites May not be feasible Classical Methodology for Phase I and Translational Trials • Accelerated Phase I Design (Simon) • Starting dose • Single patient dose doubling • Increase patients per cohort and reduce dose increments when mild (Grade II) toxicity is seen • Disadvantages • Could be hazardous with a steep dose/toxicity relationship • Little data at lower dose levels • Continual Reassessment (O’Quigley) • Stochastic model to predict probability of DLT vs. dose • Starting dose • Dose doubling • Add data to model • Predict dose with desired probability of DLT • Disadvantages • Methodologically complex • Needs constraints for safety • May take time to converge Simon R et al: Journal of the National Cancer Institute 89 (15): 1138-1147, 1997

10. Traditional Starting dose Modified Fibonacci escalation Maximum Tolerated Dose (MTD) as an endpoint Disadvantages Patient inefficient Many patients at ineffective doses Safety risk as MTD is approached No built-in confidence intervals Pharmacokinetically-guided (Collins) Establish Target Area Under the Curve (AUC) from preclinical studies Monitor Pharmacokinetics at starting dose Escalate in large increments to achieve target AUC in patients Disadvantages Inter-patient variability in PKs Assumes linearity Metabolites May not be feasible Methodology for Phase I and Translational Trials SLOW AND STEADY HARD TO GET • Continual Reassessment (O’Quigley) • Stochastic model to predict probability of DLT vs dose • Starting dose • Dose doubling • Add data to model • Predict dose with desired probability of DLT • Disadvantages • Methodologically complex • Needs constraints for safety • May take time to converge • Accelerated Phase I Design (Simon) • Starting dose • Single patient dose doubling • Increase patients per cohort and reduce dose increments when mild (Grade II) toxicity is seen • Disadvantages • Could be hazardous with a steep dose/toxicity relationship • Little data at lower dose levels CHEAP AND CHEERFUL FAST AND LOOSE

11. Almost always useful as a secondary endpoint Clinical “proof of principle” of an effect on the target May be useful as a primary endpoint if Target is known, is single and is known to mediate the therapeutic effect Level of target suppression needed is known (50%, 90%, 99%?) Required duration of target effect is known It is possible to measure all of the above Methodology required for trials with a Pharmacodynamic endpoint Requires definition of a dose where an effect of sufficient magnitude is present for sufficiently long in a sufficiently high proportion of the patients Endpoint is scalar (e.g., 95%) rather than Boolean (e.g., DLT present or not) Interpatient variability and confidence intervals Prediction of duration of effect Use of Pharmacodynamic Endpoints • Use of a scalar (continuously variable) methodology will also be of value where toxicity is used as an endpoint

12. PARP Inhibitor Phase 1 (0.5?) Trial: AG014699 • Potent inhibitor, IV administration • Not expected to be active as a single agent (BRCA data not known at the time of design) • Expected to potentiate monomethylating agents and Topoisomerase I active compounds • Tumour biopsies required for PD endpoint • Desire for single agent data on PARP inhibitor • Combination study with temozolomide undertaken • PARP inhibitors potentiate temozolomide • Temozolomide active in melanoma • Melanoma patients have multiple lesions, biopsies relatively easy • Single dose of AG14699 scheduled 1 week before combo

13. PARP Inhibitor – Clinical Plan Stage 1 – Phase 1 patients – dose escalation of PARP inhibitor Single agent PARP Inhibitor PARP Inhibitor + temozolomide 50% PD Assays - surrogate PD Assays - surrogate PARP Inhibition achieved: Stage 2 – Melanoma - dose escalation of temozolomide Single agent PARP Inhibitor PARP Inhibitor + temozolomide PD Assays - tumour PD Assays - surrogate

14. PD End point • PARP Inhibitory Dose (PID) • Dose of AG-014699 causing ≥50% inhibition on PARP-1 ex vivo in peripheral blood lymphocytes 24 hours after 1st dose, with a plateau in the degree of inhibition between dose levels. • Validated quantified immunoblot using monoclonal antibody against PAR

15. (SW620 xenografts)

17. PARP immunoblot assay with grateful thanks and credit to Alex Bürkle and Ruth Plummer permeabilised cell suspension expose to NAD+ and oligonucleotide for 6 min PAR formed stop reaction with ice-cold 12.5µM 699 blot known number of cells on to nylon membrane probe with 1° anti-PAR antibody probe with 2° HRP-conjugated antibody expose to ECL and measure luminescence

18. PARP Assay Validation • Minimise / explain variability • Enzyme stable with freezing?? • Inhibition stable with freezing • Can inhibition be measured in PBMCs? • Establish procedures for handling samples • Does sampling and transport affect result? • Consistency of assay reagents • Provide standards for acceptability of results • Control samples • Intra- and inter-assay variability • Thanks to Ruth Plummer • Probably 1-2 person years

19. Schedule: 28 day cycle :Temozolomide :AG014699 Day: -10 to -4 1 4 8 15 22 28 ↑↑ ↑ PK PK PK PD PD PD PK PK Comet Comet PK (plasma) and PD (lymphocytes) in Part 1 (any tumour) and 2 (melanoma) First cycle only Biopsy Biopsy in Part 2 (melanoma patients) only

20. Patient Demographics

21. Dosing and toxicity

24. Mean tumour PARP activity at 6 hoursafter a single dose of AG014699

25. AG14699 Phase 0/1 TrialInterpretation • 12 mg/m2 AG14699 causes profound inhibition of PARP in PBMCs and ~90% inhibition in melanoma • 12 mg/m2 AG14699 can be given with a “full” dose of temozolomide • Protocol criteria have been met, but: • Might 18 mg/m2 with a dose-reduction for temozolomide work better? • What would be the variability of the level and duration of tumour inhibition? • Do we need a longer period of inhibition for single agent treatment of BRCA tumours? • What might the effects on PARP homologues be?

26. PARP Homologues • PARP-1 most prevalent most of existing data relates to PARP-1 • PARP-2 responsible for residual PARP activity in PARP-1 knockouts PARP-2 knockouts are also viable Double knockouts not viable • PARP-3 Unknown • PARP-4 V-PARP - drug resistance • PARP-5 Tankyrase 1 - involved in telomerase activity • PARP-6 Tankyrase 2 • PARP 7.. upwards ? function

27. Two Dimensional CRM MethodDeveloped in house by James Wright • New targeted agents will be used in combination with both traditional cytotoxics and other targeted agents • “Multikinase inhibitors” • For every single agent Phase I there will be many combination Phase Is • Toxicities may potentiate or antagonise • For any two drugs, there is a range of maximum tolerated dose pairs MTD of Drug B Toxic Antagonism Toxic Additivity Toxic Synergy MTD of Drug A

28. Two Dimensional CRM MethodDeveloped by James Wright, PhD Student, 1997-2000 • CRM Methodology requires that the probability of DLT at each level is estimated before the start of the trial (priors) • A model relating the probability of DLT to dose is created using the estimated data points • As real data accumulate during the course of the trial they are used to modify the model • A problem for single agent studies is that the initial estimates may be way out • For combination Phase I studies, single agent data are already available, facilitating the estimation of priors • Hypothetical example: Priors are constructed showing the probability of dose limiting toxicity for each pair of doses Data derived from single agent Phase I Studies Data estimated from mechanistic knowledge and experience

29. CRM Method – Illustration with Completed Trial OSI 211 in combination Phase I with carboplatin OSI211 – Liposomal Lurtotecan Carboplatin

30. Combination Continual Reassessment Method of OSI 211 + Carboplatin.Probabilities of Dose Limiting Toxicity (DLT) Based on Priors Carboplatin AUC is expressed in µg/ml × min Increasing Risk of DLT Decreasing Risk of DLT Confidence intervals were calculated but are not shown

31. Proposed Enhancements of 2-Dimensional Phase I Methodology • Use a scalar rather than a Boolean endpoint (e.g., reduction in neutrophil count rather than MTD) • Modify for use with Pharmacodynamic endpoints

32. Mean Tumour PARP Activity at 6 Hoursafter a Single Dose of AG-014699 100 We want this 80 60 Predicted curve Tumour PARP Activity (% pre-treatment) Instead of this 40 95% Confidence intervals ▲ 20 ▲ ▲ 0 5 10 15 20 25 0 AG014699 Dose (mg/m2)

33. Methodology for Phase I and Translational Trials - Needs • Trial methodology designed for targeted agents in trials with pharmacodynamic endpoints methods that utilise continuously variable (scalar) endpoints rather than yes/no (Boolean) endpoints • Extension of these techniques to combination Phase I trials • Models to detect trends may be more appropriate than hypothesis-testing • We need to use these methods where available and develop new mathematical models where they are not • Early investment in PD assay development and validation

34. Acknowledgements Newcastle Patients Research nurses Ruth Plummer Nicola Curtin Herbie Newell Roger Griffin Chris Jones Alan Boddy Barbara Durkacz Bernard Golding Plus the other clinical investigators Agouron/Pfizer Heidi Steinfeldt Zdenek Hostomsky Raz Dweji Gerrit Los Cancer Research UK