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Updated: May 27, 2026

A Quantitative Fitness Analysis Workflow

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Published on: August 13, 2012

Knowledge management for efficient quantitative analyses during regulatory reviews.

Kevin Krudys¹, Fang Li, Jeffry Florian

¹Division of Pharmacometrics, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993, USA.

Expert Review of Clinical Pharmacology

|November 25, 2011

Summary

This summary is machine-generated.

Effective knowledge management in pharmacometrics enhances drug development and public health. This involves robust infrastructure and collaboration for better data sharing and analysis at the US FDA.

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Area of Science:

Pharmacometrics
Drug Development
Public Health
Knowledge Management

Background:

Organizations employ strategies and methods to generate and leverage knowledge.
The Division of Pharmacometrics at the US Food and Drug Administration (FDA) implements knowledge management.
The goal is to improve drug development and advance public health.

Purpose of the Study:

To outline the activities within the Division of Pharmacometrics for effective knowledge management.
To illustrate principles of pharmacometric knowledge management with examples.
To highlight the benefits and future directions of knowledge management in drug development.

Main Methods:

Establishing infrastructure for pharmacometric knowledge management.
Implementing data standards, queryable databases, and libraries of modeling tools.
Archiving analysis results and utilizing reporting templates for communication.
Developing and showcasing two knowledge management systems.

Main Results:

Sound knowledge management increases productivity for reviewers.
Reviewers can focus on research questions for new drug applications.
Improved trial design and biomarker development are facilitated.
Knowledge management systems enhance efficiency and effectiveness.

Conclusions:

Effective knowledge management is crucial for improving drug development and public health.
Collaboration between the FDA and industry is essential for future advancements.
Implementing data and model standards will enhance knowledge sharing and dissemination.