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  1. FDA STEM Outreach, Education and Engagement

Modernizing Drug Labeling Presentation Related to Quantitative Clinical Pharmacology

Authors:
Poster Author(s)
Pernati, Chenchu Vignesh, FDA/CDER (Student); Yao, Kevin, FDA/CDER (Student): Liu, Jiang, FDA/CDER (Mentor)
Center:
Contributing Office
Center for Drug Evaluation and Research

Abstract

Poster Abstract

Background

Optimal pharmacotherapy is driven by an understanding of a drug’s clinical pharmacology and the clinical context in which the drug will be used. Appropriate inclusion of clinical pharmacology information in a drug’s labeling can be directly translated to prescribing decisions. Important clinical pharmacology attributes to consider in therapeutic decision making should be quantitative and clinically meaningful. Those quantitative information include, but are not limited to, Pharmacodynamics (PD) (section 12.2), and Pharmacokinetics (PK) (section 12.3) in a variety of settings and specific populations. However, we have noticed some inconsistency and gaps in the presentation of quantitative clinical pharmacology information in drug labeling thus leading to inefficient communication. Those gaps include: the misrepresentation of ADME parameters such as (terminal/elimination half-life vs effective half-life), inconsistent use of clearance vs. body-size normalized clearance, mis-presentation of population variability vs. parameter precision, inclusion of incomplete PK information of specific population, and inadequacies in the presentation of exposure-response relationships that might be useful for health care providers.

Objective

1) systematically evaluate how the quantitative clinical pharmacology information is derived and presented in drug labeling; 2) identify the inconsistency and gaps in the current labeling practice; 3) propose solutions to the identified gaps and potential best practice to improve the quantitative clinical pharmacology labeling process.

Methods

Clinical pharmacology labeling and their corresponding submissions and reviews were surveyed, and inconsistencies were identified in the quantitative clinical pharmacology labeling practice. ADME parameters were examined and analyses were revisited if an issue was identified. For specific population, we evaluated the utility of population pharmacokinetics approach in assessing the impacts of intrinsic and extrinsic factors on drug exposure.

Results

The study performs a comprehensive analysis through evaluation of criteria based on clinical pharmacology guidance regarding the labeling for human prescription drugs and biological products. A comprehensive database of quantitative clinical pharmacology labeling information for drugs approved recently is constructed. Inconsistency and gaps in the current labeling practice were found. Instances of adequate information vs inadequate information regarding exposure-response relationships were also identified. Solutions and best labeling practice were proposed.

Conclusion

This project will help the agency modernize quantitative clinical pharmacology information in drug labeling and guide health care provider using the product more efficiently.


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