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ACoP10 Post-Meeting Workshop: Integration of PHM and Stat Analyses Using CTS, October 24, 2019

From: Ken Kowalski <kgkowalski58>
Date: Mon, 10 Jun 2019 10:07:33 -0400

Dear NMUsers,


On Thursday, October 24, 2019, I will be giving an ACoP10 post-meeting
workshop in Orlando, FL. This workshop will be a 3-hour didactic lecture
based on my recently published paper:


Kowalski, K.G. "Integration of Pharmacometric and Statistical Analyses Using
Clinical Trial Simulations to Enhance Quantitative Decision Making in
Clinical Drug Development". Statistics in Biopharmaceutical Research
2019;11:85 - 103.


See below for a description of the workshop. To register for the workshop
please visit the ACoP10 registration website:


I hope to see you there.






Kenneth G. Kowalski

Kowalski PMetrics Consulting, LLC

Email: kgkowalski58

Cell: 248-207-5082


Integration of Pharmacometric and Statistical Analyses using Clinical Trial
Simulations to Enhance Quantitative Decision Making in Clinical Drug


Workshop Description

This workshop outlines a general framework in which clinical trial
simulations are employed integrating both pharmacometric and statistical
analyses to support trial design and quantitative decision making in drug
development. Specifically, predictive pharmacometric models are used as
data-generation models to simulate data, while data-analytic models as
specified in the statistical analysis plan are used to analyze the simulated
data, and to apply a quantitative data-analytic decision rule. Various
probability metrics including probability of achieving the target value
(PTV), probability of success (POS), and probability of a correct decision
(POCD) are proposed to support study design recommendations and quantitative
decision-making. A case study is presented to illustrate the clinical trial
simulation methods and procedures described in this article.


Training Objectives

1. Learn how to formulate quantitative decision rules using confidence
interval criteria.


2. Understand the concept of assurance or probability of success and how
it differs from statistical power.


3. Understand the distinction between confidence intervals and
prediction intervals and how to perform stochastic simulations using
pharmacometric models to construct such statistical intervals.


4. Learn how to apply clinical trial simulation procedures to evaluate
various probability metrics including PTV, POS, and POCD to support study
design recommendations and quantitative decision-making.



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Received on Mon Jun 10 2019 - 10:07:33 EDT

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