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Risk-Based Approach to Lot Release.

Linas Mockus1, Gintaras Reklaitis1, Kenneth Morris2

  • 1Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907-2100.

Journal of Pharmaceutical Sciences
|October 15, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a new risk-based method for pharmaceutical lot release, improving quality assessment. The approach provides a probability of a drug batch meeting specifications, enhancing decision-making.

Keywords:
Bayesian methodsUSP monographsadaptive samplingin vitro dissolutioninter-lot variabilitylot releasepharmaceutical manufacturingprior knowledgerisk-based decision makingunit dose uniformity

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Area of Science:

  • Pharmaceutical manufacturing
  • Quality control
  • Risk assessment

Background:

  • Current lot release methods may not fully capture product quality risks.
  • A probabilistic approach is needed for robust risk-based decision-making in pharmaceutical quality control.

Purpose of the Study:

  • To propose a novel risk-based methodology for pharmaceutical lot release.
  • To assess the probability that a released lot meets product specifications.
  • To provide a probabilistic statement on the true quality of drug batches.

Main Methods:

  • The methodology integrates adaptive sample size determination.
  • It includes estimation of the probability of product compliance with specifications.
  • A clear lot-release decision framework is established based on probability estimates.

Main Results:

  • The proposed methodology was demonstrated using experimental data from 17 immediate-release solid oral drug products.
  • Data from multiple manufacturers and numerous lots were analyzed.
  • The approach yields a probabilistic statement regarding the true quality of each lot.

Conclusions:

  • The novel risk-based methodology offers a probabilistic framework for pharmaceutical lot release.
  • This enhances the assessment of risks associated with product quality and specification compliance.
  • The methodology supports more informed and reliable decision-making in pharmaceutical quality assurance.