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Modeling and Simulation: Tool for Optimized Drug Development

Martin Roessner Biostatistics sanofi aventis Bridgewater, NJ. Modeling and Simulation: Tool for Optimized Drug Development . Outline. Background Modeling and Simulation (M&S) approach Clinical Utility Index (CUI) Example: SERM Conclusion. Industry challenge .

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Modeling and Simulation: Tool for Optimized Drug Development

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  1. Martin Roessner Biostatistics sanofi aventis Bridgewater, NJ Modeling and Simulation:Tool for Optimized Drug Development

  2. Outline • Background • Modeling and Simulation (M&S) approach • Clinical Utility Index (CUI) • Example: SERM • Conclusion

  3. Industry challenge • Drug development process not much changed over the last 25 years • Drug development cost continue to increase ($802 Mill +) • Time to market, attrition rates and the number of late stage failures remain unchanged • The industry needs to radically rethink the drug development process to remain competitive • The industry needs to work smarter not harder

  4. Modeling and Simulation is a tool for quantitative decision-making • It is a methodology that uses mathematical/statistical models and simulations in a predictive manner • M&S provides an integrated framework to use this information to optimize the drug development process

  5. Implementation of M&S • Development and broad adoption of M&S will help create value • Benefits • Optimized development strategies • Early termination of unpromising compounds • Reduction in late stage attrition • Shorter development time earlier to approval and launch • Increase number of drugs to market • Enhanced labeling • More accurate and dynamic risk assessment along the development

  6. Integrated modeling and simulation can be used any time there is an important question impacting project value “Is it worth developing a new dosage form?” “What’s the best dose and schedule?” “Should we continue this development program?” “What is the optimal patient population for this drug?” “Is there a clinical trial design that will show PoC and find the best dose?” “What’s the probability of success in Phase 3?” “Is this treatment likely to be as good as the competitors?” “Which indication should we go into first to maximize the value of the program?” “Should we in-license this compound?” “What are the most important attributes of a 2nd generation compound?”

  7. Clinical and Preclinical Data Physician Market Research Exploratory Data Analysis Clinical Utility Model Efficacy Dose-Response Model Safety Dose-Response Model Simulation Integration A modeling approach to decision-making involves integration of information from a number of sources

  8. Clinical and Preclinical Data Physician Market Research Exploratory Data Analysis Clinical Utility Model Efficacy Dose-Response Model Safety Dose-Response Model Simulation Integration A modeling approach to decision-making involves integration of information from a number of sources

  9. Clinical Utility Index (CUI) - a metric for the benefit of treatment to the patient (1) • Every drug has benefits and risks. • The relative importance of these characteristics depend on the disease the drug is intended to treat • They also change with dosage, patient population, etc. • Trade-offs must often be made among the drug effects comprising the product profile, balancing the benefits and risks.

  10. Clinical Utility Index (CUI) - a metric for the benefit of treatment to the patient (2) • The CUI quantifies trade-offs by providing a single metric for the multiple dimensions of benefit and risk. • It is… • a systematic approach to understand subjective preferences • a transparent way of weighing tradeoffs • knowledge-driven; available data are used; if not available, rely on expert opinion • closely related to the Target Product Profile • It is not … • an “objective” measure in the sense of a physiological measurement

  11. The framework for the CUI is elicited from the project team; when combined with models of response, it provides a relative estimate of the patient benefit Identify Metrics Identify Critical Assign and Relevant CUI Treatment Preference CUI Distributions for Response Framework Attributes and Values for each Levels for each Competing Treatments Relative Weights Response Level Attribute 1 A E(CUI ) A P(CUI < X) E(CUI ) B B Treatment- 0 Response CUI Models Probability of Estimated Here, treatment B is Individual Product expected to be superior to A Attribute Levels Profile Expert Opinion

  12. Example • SERM, a Selective Estrogen Receptor Modifier for the Treatment of Osteoporosis in Post-Menopausal Women • Two Phase II studies: • 1. Placebo, SERM (2.5mg, 10mg, 50mg) and Raloxifene, n=118 • 2. Placebo, SERM (0.5mg, 5mg) n=79 • Primary efficacy endpoint was % change from baseline U-CTX • Included additional safety and activity endpoints • How does the efficacy, safety and tolerability of SERM compare with its major competitor drug and at which dose • Explorative analysis • Clinical Utility Index (CUI) • Simulation results and sensitivity analysis • Is it worthwhile to continue development

  13. Possible responses and their clinical value for each attribute were defined

  14. Important attributes were ranked and their importance weighted

  15. Models of dose-response provided estimates of attribute level and uncertainty in these estimates Dose-Response for Urinary CTX(measure of bone turnover) Baseline-adjusted week-12 % Difference from Placebo • Clear dose response • Log-Linear model adequately describe available data

  16. Major Result: There was no dose for which SERM was expected to be considered equivalent or superior to Raloxifene 60 Based on CUI and simulated drug response CUI for Raloxifene 50 40 Clinical Utility Index 30 20 10 0 0.25 0.5 1 2.5 5 10 SERM Dose (mg)

  17. What if……. If SERM did not cause endometrial proliferation, available data support effects of SERM would be similar or better at doses of 1 mg and higher 100 SERM similar to Raloxifene i.e. no endometrial proliferation 80 60 Clinical Utility Index Raloxifene 40 20 0 0.25 mg 0.5 mg 1 mg 2.5 mg 5 mg 10 mg SERM Dose

  18. Impact: Further development of SERM was halted, saving $50-100M in development costs • SERM fails to show equivalent clinical utility to Raloxifene at all doses examined • “Based on that simulation, ‘we stopped funding development of the compound,’ says Frank Douglas… the ratio between the therapeutic benefit and the side effect demonstrated that this [compound] was not as beneficial as Evista.’… Douglas estimates that the … computer model … saved the company $50 million to $100 million, the cost of later-stage clinical trials. ‘We also avoided exposing a lot of women to a drug that ultimately would have failed,’ he adds. ‘And we were able to switch to another project with a greater chance of success.’ “ • —Forbes 10/7/02

  19. Conclusion • Industry needs to operate smarter • M&S provides a framework to optimize drug development at various levels • Clinical Utility Index can be used to assess the potential success of a product in the market

  20. Acknowledgement B. Korsan, K. Dykstra, T.J. Carrothers (Pharsight)

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