Risk-Based Quality Control Strategies for Efficient Delivery of High-Quality Pharmacometric Datasets

Includes a Live Web Event on 09/05/2025 at 10:00 AM (EDT)

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This webinar explores strategies for implementing risk-based quality control (QC), emphasizing the use of peer-review QC to optimize robust validation. By tailoring the QC level to project-specific risk factors such as analysis purpose and data complexity, the delivery process for high-quality pharmacometric analysis datasets can be streamlined. The session will discuss differentiating between QC levels, such as self-QC, peer review, and double programming. Participants will discover practical methods for fostering collaboration, establishing clear data derivation rules, and utilizing comprehensive QC checklists, particularly for peer-review processes. Additionally, the webinar will highlight tools to support peer-review QC, enhancing QC efficiency and effectiveness.

Join us to build a stronger QC framework and adopt best practices in pharmacometric data validation.

Xiaobin Li, Programming Director, GSK

Programming Director

GSK

Xiaobin Li is the Programming Director of Clinical Pharmacology Modeling & Simulation Programming and Business Excellence at GSK, with over 20 years of experience in Pharmacometric Programming and tool development. Currently she is serving on the ISoP PMX Programming Special Interest Group (SIG) Steering Committee and co-leading its Data Visualization Working Group.

Srinivas Bachina

Director

AstraZeneca

Srinivas Bachina is currently working in AstraZeneca as Director CPQP programming, leading internal Pharmacometric programming. He has over 20 years of experience in Pharmacometric Programming and currently involved in ISOP Data Visualization working group.

Erin Dombrowsky

Director, Data Science – Pharmacometrics

Bristol Myers Squibb

Erin has over 17 years of experience in pharmacometric programming and currently leads a team at Bristol Myers Squibb, dedicated to supporting pharmacometric analysis dataset preparation. Her interests and expertise lie in creating and implementing efficiencies through standards and automation, and she enjoys training and developing new pharmacometric programmers. Erin's leadership extends to her co-lead roles in the Data Quality, Visualization and Reporting, and Introduction to Pharmacometrics Analysis Dataset Programming working groups within the ISOP PMx Data Programming Special Interest Group.