Communicating the Value of Pharmacodynamic Modelling in Drug ...

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… and from a clinical perspective: What is the expected clinical response for a treatment in a particular patient population? What is the level of certainty surrounding predicted response? How do different treatment strategies and target patient subpopulations impact response? What is the probability that response is less or greater than a specific target? What dose is required to achieve a target response? What is the probability of achieving a specific efficacy target while keeping probability for adverse events below a certain level? How do the attributes for the compound compare to competitors? What is optimal positioning strategy versus competitors to balance safety and efficacy? slide 10 30 May 2008, ARCS © Pharsight Corporation All Rights Reserved
To simulate drug development scenarios of interest, a number of sub-models are developed and integrated Pharmacotherapeutics Pharmacodynamics Pharmacokinetics Dosing Regimes Exposures Efficacy & tolerability endpoints Clinical Profile Clinical Events 1 or more drugs Information Sources • Preclinical data • Early-phase trial results • Late phase results • In-house experts • Public information Financial Value Market economics slide 11 30 May 2008, ARCS © Pharsight Corporation All Rights Reserved
Page 1 and 2: Communicating the Value of Pharmaco
Page 3 and 4: FDA Perspective There is a clear em
Page 5 and 6: …. And What Can Be Done About It?
Page 7 and 8: Examples of Applications of MBDD Hi
Page 9: PK/PD applications in MBDD ● Mid-
Page 13 and 14: Public-Source Data ● Public-sourc
Page 15 and 16: Case Studies Example 1. How can pre
Page 17 and 18: Comparisons across regimens and dru
Page 19 and 20: Example 2: How can M&S be used to s
Page 21 and 22: Docetaxel model Side effects Dose E
Page 23 and 24: There was a clinically meaningful i
Page 25 and 26: Contribution of this approach to fi
Page 27 and 28: Strategy: Efficient Model-Based Dev
Page 29 and 30: Results: The Model Described Mono-
Page 31 and 32: Summary of process so far …. Pre-
Page 33 and 34: Models provide answers to important
Page 35 and 36: Our purpose is to view and query mo
Page 37 and 38: Q1: What is the probability that ge
Page 39 and 40: Q2: What is the probability that, i
Page 41 and 42: Q3: Given the magnitude of LDL-C lo
Page 43 and 44: Value of MBDD approach for gemcaben

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