Clinical Trial Simulations

Transcription

1 Clinical Trial Simulations Clinical Pharmacology meeting Flora T Musuamba

2 Outline Introduction Estimation vs Simulations Simulations as a diagnostic tool Simulation as a tool for quantitative decision making Clinical Trial Simulations Examples

3 Outline Introduction Estimation vs Simulations Simulations as a diagnostic tool Simulation as a tool for decision making and trial optimisation Clinical Trial Simulations Examples

4 INTRODUCTION Treatment outcome

5 INTRODUCTION Prior information/data Design experiment Collect data Develop model Evaluate fit to the data Simulate what if scenarios

6 INTRODUCTION Modeling and simulation can be used to address various questions during drug development and clinical practice What s the best dose and schedule? Is this treatment likely to be as good as the competitors? What is the optimal patient population for this drug? Is it worth developing a new dosage form? What s the probability of success in Phase 3? Should we continue this development program? 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? Should we in-license this compound? 6 Which indication should we go into first to maximize the value of the program?

7 INTRODUCTION

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

9 INTRODUCTION Clinical Utility Index (CUI) - a metric for the benefit/risk assessment 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. 9

10 P(CUI < X) INTRODUCTION The framework for the CUI should be combined to modeling and simulation to provide relative estimates of the patient benefit/risk Modeling and Simulation + 1 CUI Distributions for Competing Treatments E(CUI ) A A E(CUI ) B Benefit/Risk assessment 0 B CUI Here, treatment B is expected to be superior to A

11 Outline Introduction Estimation vs Simulations Simulations as a diagnostic tool Simulation as a tool for decision making and trial optimisation Clinical Trial Simulations Examples

12 ESTIMATION VS SIMULATION

13 ESTIMATION VS SIMULATION

14 ESTIMATION VS SIMULATION

15 ESTIMATION VS SIMULATION A model is a simplified presentation of system s behaviour or state. It consist of a series of equation or function that describe the relationship between variables in a precise way. Parameterization is the process by which the structure, the function or the behavior of the system are describd fn a model-based approach, instead of relaying on the experimental variables

16 Outline Introduction Estimation vs Simulations Simulations as a diagnostic tool Simulation as a tool for decision making and trial optimisation Clinical Trial Simulations Examples

17 Density FEV1 (L) FEV1 (L) SIMULATION-BASED DIAGNOSTIC TOOLS Visual predictive check DOSE == 0 DOSE == Time (days) Time (days) Normalized prediction distribution errors Histogram of data2$npde data2$npde

18 Outline Introduction Estimation vs Simulations Simulations as a diagnostic tool Simulation as a tool for decision making and trial optimisation Clinical Trial Simulations Examples

19 CLINICAL TRIAL SIMULATIONS

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36 Thank you for your attention!