(M-028) A Pharmacometrics Strategy for Ensuring Compatibility of Exposure-Response Analysis with Clinical Study Report: Enhancing Accuracy, Traceability, and Transferability Through Variable Mapping Specification (VMS)
Director, Clinical Pharmacology and Pharmacometrics AstraZeneca, Massachusetts, United States
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Objectives: Exposure-response (ER) analysis [1] is a critical component of the New Drug Application (NDA) process, providing insights to understand the relationship between drug concentration and its pharmacological or toxicological responses. These analyses are conducted using exposure-response datasets that integrates individual pharmacokinetic (PK) exposure metrics derived from empirical Bayes estimates in population PK modeling, with efficacy or safety endpoints. Pharmacometricians often face the challenge of ensuring quality control to maintain accuracy and alignment with Clinical Study Report’s (CSR) tables, figures, and listings (TFLs) derived from clinical study data. Furthermore, maintaining traceability and quality control (QC) particularly during transitions between team’s programmers or pharmacometricians remains a significant challenge. To address the current challenges and gaps, we propose a comprehensive strategy centered on the implementation of Variable Mapping Specification (VMS).
Methods: The workflow comprises four key components: (1) cross-functional communication, (2) data specification preparation, (3) VMS development, and (4) cross-validation of the ER dataset against the CSR’s TFL. The process begins with the pharmacometrician initiating the discussions in meetings with biostatistics, clinical, and safety study leads to ensure alignment on efficacy and safety endpoints, meticulously documenting the outcomes of these discussions. Following alignment, the pharmacometrician develops data specifications based on the Model Analysis Plan (MAP) and Statistical Analysis Plan (SAP). These specifications are then reviewed and endorsed by the relevant study function leads. In the next step, the pharmacometrics programmer collaborates with biostatisticians and study programmers to develop the Variable Mapping Specification (VMS), detailing guidelines for constructing ER datasets. The final ER dataset undergoes rigorous cross-validation against the CSR’s TFLs, ensuring consistency in subject numbers and key variables between the two sources.
Results: The VMS spreadsheet offers comprehensive details on data specifications for exposure-response (ER) analysis, covering variable names, labels, types, and mappings for each study. It clearly documents the derivation of each variable from the Study Data Tabulation Model (SDTM) and Analysis Data Model (ADaM) data domains. This structured, four-component workflow empowers the pharmacometrician to perform a swift and rigorous quality control during the submission period, while ensuring traceability and transferability.
Conclusions: This workflow streamlines the preparation of pharmacometrics submission deliverables by significantly improving quality control (QC) measures while ensuring transferability and traceability throughout the submission process.
Citations: [1] FDA Guidance for Industry: Exposure-Response Relationships — Study Design, Data Analysis, and Regulatory Applications.
