To demonstrate that a dose-determining assay is fit for purpose, the measurement uncertainty associated with a reported release test result must be suitably small. The establishment of a corresponding product specification is inextricably linked to the tolerance for error in assigning a dose value for a vector lot. By adopting an equivalence-based lot release model which includes a total error approach to assay qualification, specific testing strategies can be evaluated quantitatively for dose error and lot release decision risks throughout the drug development process. This article aims to reinforce how the concepts tied to an equivalence-based lot release model are interrelated and applied in practice. It provides in-depth explanations of fundamental concepts and clarifies common misunderstandings for quality control, quality assurance, and regulatory affairs personnel held accountable for decisions made in vector dose assignment and product lot release.
Tag: <span>dose-determining assay</span>
NOTE: Page 7 of this article has been revised to correct an error in the original article which stated that “..the probability of failing a lot when it actually is not equivalent, becomes 1-2*α.” The correct equation, 1-α, has replaced the errant one and a single sentence following it was added to further clarify this concept.
ABSTRACT: Pre-clinical and clinical trials conducted to establish the minimum effective dose and the maximum tolerated dose of a viral vector assume that the assigned dose values are comparable across studies. Toxicity has been associated with high dose administration of both adenovirus and adeno-associated virus-based vectors, and increased attention must be paid to assays used to measure dose. High assay variability can be mitigated by replication and the reporting of a mean value for product lot release. The establishment of a dose specification and a testing strategy must take into account the risk of errant quality control decisions. This can be accomplished by linking assay qualification information to measurement uncertainty through a statistical framework. By adopting an equivalence approach, the risk of releasing lots with unacceptably high or low dose values is minimized by reducing measurement uncertainty. This article provides a worked-through example to introduce applicable statistical concepts and the equations necessary to facilitate their implementation in the field.