4.5 Article

Verification and Validation of Computational Models Used in Biopharmaceutical Manufacturing: Potential Application of the ASME Verification and Validation 40 Standard and FDA Proposed AI/ML Model Life Cycle Management Framework

Journal

JOURNAL OF PHARMACEUTICAL SCIENCES
Volume 110, Issue 4, Pages 1540-1544

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.xphs.2021.01.016

Keywords

Verification and validation; Computational models; Machine learning; Digital twins; Biopharmaceutical manufacturing; GMLP

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This study explores the credibility and standardized frameworks for computational models in biopharmaceutical manufacturing, aiming to facilitate consistent decision making and alignment with existing good practices.
A wide variety of computational models covering statistical, mechanistic, and machine learning (locked and adaptive) methods are explored for use in biopharmaceutical manufacturing. Limited discussion exists on how to establish the credibility of a computational model for application in biopharmaceutical manufacturing. In this work, we tried to use the American Society of Mechanical Engineers (ASME) Verification and Validation 40 (V&V 40) standard and FDA proposed Al/ML model life cycle management framework for Software as a Medical Device (SaMD) in biopharmaceutical manufacturing use cases, by applying to a set of curated hypothetical examples. We discussed the need for standardized frameworks to facilitate consistent decision making to enable efficient adoption of computational models in biopharmaceutical manufacturing and alignment of existing good practices with existing frameworks. In the study of our examples, we anticipate existing frameworks like V&V 40 can be adopted. (C) 2021 American Pharmacists Association s . Published by Elsevier Inc. All rights reserved.

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