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Rajesh Krishna, PhD, FCP Clinical Pharmacology

Approaches to First-In-Man and Beyond: Early Evidence of Target Engagement with Biomarkers and Innovative Clinical Trial Designs. Rajesh Krishna, PhD, FCP Clinical Pharmacology. AGAH-ACCP Annual Meeting 2006 Transatlantic Strategies in Early Development Düsseldorf, Germany. Overview.

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Rajesh Krishna, PhD, FCP Clinical Pharmacology

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  1. Approaches to First-In-Man and Beyond: Early Evidence of Target Engagement with Biomarkers and Innovative Clinical Trial Designs Rajesh Krishna, PhD, FCP Clinical Pharmacology AGAH-ACCP Annual Meeting 2006 Transatlantic Strategies in Early Development Düsseldorf, Germany

  2. Overview • Part I • Experimental medicine and biomarkers for early evidence of concept and target engagement • Part II • Adaptive designs to maximize dose-response information and select the “winners”

  3. Part I: Experimental Medicine and Biomarkers

  4. Experimental Medicine • Scope: • Designed to provide a preliminary assessment of pharmacologic activity, efficacy, and/or safety of new compounds in early clinical development • Predictive of Phase III clinical efficacy / clinical outcomes • Approaches • Experimental medicine tools • Biomarkers and surrogate endpoints • Experimental models • Imaging • Molecular profiling • Unique role as experimental medicine tool and in biomarker discovery

  5. Experimental Medicine • Goals: • Increase efficiency of drug development • Accelerate and improve quality of drug development decisions • Augment understanding of test drugs, dose response, biology, and mechanisms of action • Aid in regulatory evaluation and, where possible, regulatory approval of test drugs

  6. DPP-IV Inhibitor Biomarkers Disease or distal biomarkers Meal bolus GI tract Skeletal muscle GLP-1 neuroendocrine cells in ileum Delayed gastric emptying Neural innervation Glucose Insulin ( cell) Active-GLP1 inactive GLP-1 DPP-IV Pancreatic islet Target engagement or proximal biomarkers Glucagon ( cell) CNS Food intake/body weight Hepatic glucoseproduction GI=gastrointestinal; CNS=central nervous system

  7. DPP-IV and Active GLP-1 levels ~2-fold increases in active GLP-1 levels >80% DPP-IV inhibition Placebo MK-0431 25 mg MK-0431 200 mg Placebo MK-0431 25 mg MK-0431 200 mg Herman et al., Diabetes 53(Suppl. 2): A82, 2004

  8. Insulin and glucose levels post-OGTT MK-0431 Enhanced Insulin Levels by ~22-23% MK-0431 Reduced Glycemic Excursion by ~22-26% OGTT Herman et al., Diabetes 53(Suppl. 2): A82, 2004

  9. DPP-IV Inhibitor Biomarkers Tie Mechanism of Action Together Disease or distal biomarkers Meal bolus GI tract Skeletal muscle GLP-1 neuroendocrine cells in ileum Delayed gastric emptying Neural innervation Glucose Insulin ( cell) Active-GLP1 inactive GLP-1 DPP-IV Pancreatic islet Target engagement or proximal biomarkers Glucagon ( cell) CNS Food intake/body weight Hepatic glucoseproduction GI=gastrointestinal; CNS=central nervous system

  10. DPP-IV Biomarkers Allow Assessment of Target Engagement EC50 ~26 nM EC80 ~100 nM Herman et al. Clin Pharmacol Ther 78:675-88, 2005

  11. DPP-IV Biomarkers Allow Assessment of Target Engagement Herman et al. Clin Pharmacol Ther 78:675-88, 2005

  12. Biomarker: PPARg MOA  FFA’s  FA uptake  FA release  specific gene expression in adipocytes  insulin sensitizing factor(s): Acrp30  expression / action of insulin resistance factor(s): TNFa PPARg ligand • Selection strategy: • Examine gene expression data • Select significantly up and down regulated genes • Select putative secreted proteins (derived from a search of databases containing annotation of "secreted or extracellular") • Derive MOA hypotheses for further testing Small-insulin sensitive adipocytes  visceral adiposity  insulin action in muscle / liver  hyperglycemia Reviewed in Wagner, 2002

  13. WAT gene expression in lean and db/db mice • Adiponectin is up regulated in lean mice by PPARg agonist treatment • Adiponectin is down regulated in db/db mice relative to lean, but not regulated by PPARg agonist treatment as assessed by microarray • Adiponectin is up regulated in db/db mice by RT-PCR C57B/6 db/db Lean vs db/db Rosi Gamma Rosi Gamma Rosi Gamma Alpha ACRP30 Reviewed in Wagner, J Clin Endocrinol Metab. 87:5362-6, 2002

  14. 100 75 ACRP30 ( ug/ml) 50 25 350 0 0 2 4 6 8 300 (mg/dl) 250 200 GLUCOSE * * 150 100 0 2 4 6 8 Biomarker: Adiponectin • Expression is correlated with glucose lowering in db/db mice • Recombinant ACRP30 has glucose lowering properties Reviewed in Wagner, J Clin Endocrinol Metab. 87:5362-6, 2002

  15. Biomarker: Adiponectin At the protein level, ACRP30 is robustly regulated by PPARg treatment in db/db mice PPAR Agonist Full (Rosi) Reviewed in Wagner, J Clin Endocrinol Metab. 87:5362-6, 2002

  16. g a Biomarker: Adiponectin • Pilot Study • 14 day treatments • Placebo, • Fenofibrate • Fenofibrate + rosiglitazone • Rosiglitazone • Plasma levels increased in healthy volunteers treated with PPARg but not PPARa agonists • Supports use as biomarker Wagner et al, J Clin Pharmacol. 45:504-13, 2005

  17. Biomarker: Adiponectin 500 In patients with type 2 diabetes, ACRP30 rises with PPARg treatment TRIPOD Study, Tom Buchanan,UCLA 400 300 200 % Change in insulin sensitivity (Dsi) 100 0 -100 -100 0 100 200 300 400 % Change in total Adiponectin Pajvani et al. JBC 279:12152-62, 2004

  18. 500 400 300 % Change in insulin sensitivity (Dsi) 200 100 0 -100 -100 0 100 200 300 400 % Change in total Adiponectin Biomarker: Adiponectin • But, some patients will: • Increase ACRP30 • Without Concomitant • Increase in Insulin • Sensitivity • Improve Insulin • Sensitivity Without • Concomitant • Increase in • ACRP30 Pajvani et al. JBC 279:12152-62, 2004

  19. Pajvani et al. JBC 279:12152-62, 2004

  20. Change in Insulin Sensitivity vs. Change in HMW/Total Adiponectin Pre- vs. Post-TZD Treatment (TRIPOD Study, Tom Buchanan) 500 n=40 400 300 % Change in insulin sensitivity (Dsi) 200 100 0 -100 -50 0 50 100 % Change in HMW/Total Pajvani et al. JBC 279:12152-62, 2004

  21. 125/80 40/25 375/125 100 90 80 70 60 50 40 30 20 10 0 0 1 10 100 1000 10000 Tracer Binding Low High Imaging as a BiomarkerTarget Engagement and Dose of Aprepitant Mean (± SE) Plasma Trough Concentrations of Aprepitant Binding of PET tracer to NK1 receptors Brain NK1 Receptor Occupancy (%) Blockade of NK1 receptorsafter aprepitant dosing Aprepitant Plasma Trough Concentration (ng/mL) Hargreaves J Clin Psych 63: (suppl 11): 18-24, 2003

  22. Imaging as a BiomarkerAprepitant: CINV Dose Finding Study Time to First Emesis or Rescue

  23. Part II: Novel Clinical Trial Designs

  24. Issues in Dose SelectionStandard Parallel Group Design Response Dose

  25. Issues in Dose SelectionIncreased Number of Doses to Confirm ED95 ED95 Response Wasted Doses Wasted Doses Dose

  26. Bayesian Adaptive Designs • Increase number of doses • placebo + a large number of actives • Adaptive learning about dose response • Prevent allocating patients to ineffective doses • Borrowing strength from neighbouring doses and insuring continuity of response • Stop dose-ranging trial when response at ED95 is known reasonably well

  27. Issues in Dose SelectionIncreased Number of Doses and Adaptation ED95 Response Dose

  28. Up and Down Design • Yields distribution of doses clustered around dose with 50% responders (ED50) • 1st subject receives dose chosen based on prior information • Subsequent subjects receive next lower dose if previous subject responded, next higher dose if no response • Inference based on conditional distribution of response given the doses yielded by the dosing scheme

  29. Up & Down DesignSimulated from Past Trial Results • Single-dose dental pain study (total 399 patients) • 51 placebo patients • 75 Dose 1 patients • 76 Dose 2 patients • 74 Dose 3 patients • 76 Dose 4 patients • 47 ibuprofen patients • Primary endpoint is Total Pain Relief (AUC) during 0-8 hours post dose (TOPAR8) • Up & Down design in sequential groups of 12 patients sampled from study results.

  30. Simulated Up & Down DesignCompleted Dental Pain Study • Sequential groups of 12 patients (3 placebo, 6 test drug, 3 ibuprofen) • First group receives Dose 2 • Subsequent group receives next higher dose if previous group is non-response, next lower dose if response • Response (both conditions satisfied): • Mean test drug – mean placebo ≥ 15 units TOPAR8 • Mean test drug – mean ibuprofen > 0 • Algorithm continues until all ibuprofen data exhausted • originally planned precision for ibuprofen vs placebo • (16 groups = 191 total patients)

  31. Dental Pain Randomized Design vs Up & Down Design Results

  32. Dental Pain Randomized Design vs Up & Down Design Results

  33. Key Conclusions Simulated Up & Down Design in Dental Pain • Up & Down design is viable for dose-ranging in dental pain • yields similar dose-response information as parallel group design • Can use substantially fewer patients than parallel group design • Logistics of implementation more complicated than usual parallel group design • Can be accomplished in single center or small number of centers

  34. Acknowledgements • John Wagner • James Bolognese • Gary Herman

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