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

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Presentation on theme: "1 Modeling and Simulation: Tool for Optimized Drug Development Martin Roessner Biostatistics sanofi aventis Bridgewater, NJ."— Presentation transcript:

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

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

3 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 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 – Preclinical Information – PK/PD data – Dose response information – Clinical outcome data (safety/efficacy) – Prior information: Historical data, information on related compounds, SBOAs, EPARs, etc. – Marketing and Financial projections

5 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 6 Integrated modeling and simulation can be used any time there is an important question impacting project value Whats the best dose and schedule? Is it worth developing a new dosage form? Is this treatment likely to be as good as the competitors? Whats the probability of success in Phase 3? 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 are the most important attributes of a 2 nd generation compound? Which indication should we go into first to maximize the value of the program? Should we in-license this compound?

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

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

9 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 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 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 CUI 0 1 CUI Distributions for Competing Treatments A B E(CUI ) B A Here, treatment B is expected to be superior to A P(CUI < X) Identify Critical Treatment Attributes and Relative Weights Identify Metrics and Relevant Response Levels for each Attribute Assign Preference Values for each Response Level CUI Framework Treatment- Response Models Probability of Individual Attribute Levels Expert Opinion Estimated Product Profile

12 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= 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 13 Possible responses and their clinical value for each attribute were defined AttributeResponsesPreference Ratio Efficacy on Bone Worse than Raloxifene Equivalent to Raloxifene Better than Raloxifene Endometrial Proliferation Worse than Raloxifene The same or better than Ralox Endometrial Lining Thickness Worse than Raloxifene The same or better than Ralox 1515 Cardiovascular Smaller effect on LDL than Ralox Same or larger effect on LDL vs. Ralox. Same effect on LDL + effect on HDL ….. Food Effect on PKPresence of food effect Absence of food effect 1212

14 14 Important attributes were ranked and their importance weighted AttributeRankRatingRelative Weight Efficacy on Bone Endometrial Proliferation Endometrial Lining Thickness Thromboembolic Disease Hot Flashes Breast Tenderness Cardiovascular Muscle Cramps Atrophic Vaginitis Food Effect on PK

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

16 16 Major Result: There was no dose for which SERM was expected to be considered equivalent or superior to Raloxifene Based on CUI and simulated drug response SERM Dose (mg) Clinical Utility Index CUI for Raloxifene

17 17 What if…… mg0.5 mg1 mg2.5 mg5 mg10 mg SERM Dose Clinical Utility Index Raloxifene SERM similar to Raloxifene i.e. no endometrial proliferation 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

18 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 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 20 Acknowledgement B. Korsan, K. Dykstra, T.J. Carrothers (Pharsight)


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