1 / 23

Disease Models Overview and Case Studies

Disease Models Overview and Case Studies. Joga Gobburu Pharmacometrics Office Clinical Pharmacology, Office of Translational Sciences, CDER, FDA. Pharmacometrics Survey. Between 2000-2006, 72 NDAs needed Pharmacometrics Reviews/Analyses

dextra
Download Presentation

Disease Models Overview and Case Studies

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Disease ModelsOverview and Case Studies Joga Gobburu Pharmacometrics Office Clinical Pharmacology, Office of Translational Sciences, CDER, FDA

  2. Pharmacometrics Survey • Between 2000-2006, 72 NDAs needed Pharmacometrics Reviews/Analyses • For each of the Pharmacometrics Reviews, the ‘customers’ were asked to rate the impact on approval related and labeling decisions: • Pivotal: Decision would not have been the same without Pharmacometrics analysis • Supportive: Decision was well supported by the Pharmacometrics analysis • No Contribution: No need for the Pharmacometrics analysis

  3. Impact of Pharmacometrics Analyses 2000-2004 Pivotal: Regulatory decision will not be the same without PM reviewSupportive: Regulatory decision is supported by PM review Bhattaram et al. AAPS Journal.  2005; 7(3): Article 51. DOI:  10.1208/aapsj070351

  4. Pivotal: Regulatory decision will not be the same without PM reviewSupportive: Regulatory decision is supported by PM review Impact of Pharmacometrics Analyses 2005-2006 DCP=Division of Clinical Pharmacology @=survey pending in 1 case

  5. NDA#1: Approval of monotherapy oxcarbazepine in pediatrics for treating partial seizures using prior clinical data FDA/Sponsor pursued approaches to best utilize knowledge from the previous trials to assess if monotherapy in pediatrics can be approved without new controlled trials

  6. NDA#2: Establishment of biomarker-outcome relationship allowed more efficient future trial design • The sponsor was pursuing an accelerated approval, for drug to prevent a life-threatening disease, based on a biomarker even though clinical endpoint analysis failed in two pivotal trials

  7. 1.6 0.5 NDA#2: Establishment of biomarker-outcome relationship allowed more efficient future trial design Relative risk of the disease event Hazard ratio=10.0 (95% CI 2.5-30.0) p<0.001 Ratio of biomarker level to baseline

  8. NDA#3: Insights into trial failure reasons will lead to more efficient future trials Severe Baseline Disease Responders Mild Baseline Disease Non-Responders

  9. Females seem to be more sensitive to QT prolongation Slope Slope Slope Slope

  10. Need/Opportunities for Innovative Quantitative Methods in Drug Development Optimal design to show ‘disease modifying’ effects? Good marker(s) of survival benefit in cancer patients? Maximize the change of success of a 2yr obesity trial? Given 85% of depression trials fail, how to improve success? Best dose for a 26wk trial based on 12 wk data? Providing solutions for these issues calls for efficient use of prior knowledge

  11. Manage and Leverage Knowledge Information • Biomarker-Endpoint • Time course • Drop-out • Inclusion/Exclusion • criteria (Trial) Placebo & Disease Models • Parkinson’s • Obesity, Diabetes • Tumor-Survival • Rheumatologic condition • HIV • Epilepsy • Pain Knowledge We are referring to such diverse quantitative approach(es) as ‘Disease Modeling’

  12. Core Development Strategy for Testosterone Suppressants IC50 Reporter Gene Assay - Early screening of compounds based on IC50 value. - High thr’put method to filter thousands of compounds - Based on prior experience, a few potential entities will be selected for the next phase PKPD data Preclinical Disease Model - In vitro IC50 as a guide for preclinical dose selection - Animal models to measure all possible biomarkers e.g. GnRH, LH, T and Drug conc. Clinical Trial Simulation Dose optimization in cancer patients PKPD data - Invitro and preclinical data for clinical dose and regimen selection - Clinical development plan - Pilot study for dose optimization thr’ innovative trial designs Pivotal trial |----*2 mo-----| |----*2 mo-----| |----*2 mo-----| |----*3 mo-----| |---------*12 mo--------------| *Actual execution time.- it does account for time spent accumulating resources. From Pravin Jadhav, VCU/FDA

  13. Obesity • Obesity trials are large, over 1-2 yrs and fraught with challenges due to high drop-out rate Dr. Jenny J Zheng Dr. Wei Qiu Dr. Hae Young Ahn

  14. Obesity Model Qualification Baseline Body Weight 3000 patients

  15. Patients with small weight loss drop-out Drop-out patients Remaining patients 0-12 36-52 12-24 24-36

  16. Obesity: Time Course of Placebo Effect

  17. Value to Drug Development • Effective use of prior data for designing future registration trials • Might lead to alternative dosing considerations • Titration vs. fixed dose • Could lead to increased trial success • Allows of designing useful shorter duration trials for future compounds for screening and initial dose range selection

  18. Diabetes • How to reliably select doses for registration trials based on abbreviated dose finding trials • Need arose from an EOP2A meeting • Work in progress: No patient population and drop-out models yet. Drs. Vaidyanathan, Ahn, Yim, Zheng, Wang, Gobburu, Powell, Sahlroot, Orloff

  19. Pivotal Trial Dose Selection: Anti-Diabetic • Sponsor conducted 12 wk dose ranging trial in diabetics • Key Regulatory Question • What is a reasonable dose range and regimen for the pivotal trial(s)? • Challenge • Estimate of effect size on HbA1c at 26 wks not available. Effect size on FPG available.

  20. 1st order Oral Absorption FPG Cmt 1 Cmt 2 HbA1c FPG-HbA1c relationship from historic studies employed to estimate effects on HbA1c of the new compound Drug Conc. FPG HbAlc Time (Week) Jusko et al

  21. Biological relationship between FPG-HbA1c bridged information gap + = Drug X (other) in 28 patients Hybrid dataset in 100 patients Drug X (Sponsor) in 72 patients

  22. Value to Drug Development • More informed dose/regimen selection • Could lead to increased trial success • Quantitative analysis was critical • Effective use of prior data for predictions • Supports conduct of useful shorter duration trials for future compounds

  23. Disease Models: Challenges • Data Management • How to best maintain an efficient database? • Analysis • How to best conduct meta-analysis? • Identify and fill gaps (time-varying biomarkers in survival models)? • Inter-disciplinary collaboration • Biologists, Pharmacologists, Statisticians, Disease Experts, Quantitative Clinical Pharmacologists, Engineers need to come together to develop these models as a team.

More Related