Stability modeling methodologies to enable earlier patient access.

Over recent years, confidence has been gained that predictive stability modeling approaches using statistical tools, prior knowledge and industry experience enable, in many instances, a robust and reliable shelf-life/expiry or retest period prediction for medicinal products. These science and risk-based approaches can compensate for not having a complete real-time stability data set to be included in regulatory applications at the time of initial submission and, thereby, accelerate the availability of new medicines. Examples of predictive stability modeling include accelerated stability assessment procedure (ASAP), advanced kinetic modeling (AKM), and novel modeling approaches that involve the use of Bayesian statistics and Artificial Intelligence (AI) applications such as Machine Learning (ML), with applicability to both synthetic and biological molecules.

Science- and Risk-Based Stability Strategies to Support Product Lifecycle Changes.

ICH Q12 asserts that science- and risk-based approaches are applicable to stability studies supporting Chemistry, Manufacturing and Controls (CMC) post-approval changes (PAC) to enable more timely implementation; however, no guidance or specific examples are provided to demonstrate how prior knowledge of the product can inform the risk assessment for the proposed change(s). Ten diverse case studies are presented in this manuscript to demonstrate how science- and risk-based stability strategies were used to support drug substance and product CMC PAC and lifecycle management activities. The accumulated stability knowledge held by original manufacturers of marketed products is substantial, and different elements of this knowledge base were used to assess the risks and impact of the proposed changes for confident change management.

Risk-based approach to setting sterile filtration microbial bioburden limits - Focus on biotech-derived products.

Holistic concepts should be applied that reduce risks prior to final bioburden testing and sterile filtration, based on enhanced process and product attribute understanding, which could be key to successful bioburden risk management. Key findings of this paper include.

Dynamic Regulatory Assessment: Unpacking the Process Reveals Readiness to Pilot for Europe-An EFPIA View.

The medicines regulatory network of the European Economic Area comprises 30 countries, their National Competent Authorities (NCA), and the European Medicines Agency (EMA). The NCAs and EMA are involved at different stages of the medicine life cycle; not all are engaged in a particular medicine's development discussions. As a result, knowledge management (ie, acquisition and transfer between medicine developer and the NCAs) is fragmented and inefficient.

Compliance and regulatory considerations for the implementation of the multi-attribute-method by mass spectrometry in a quality control laboratory.

Multi-attribute methods employing mass spectrometry are applied throughout the biopharmaceutical industry for product and process characterization purposes but are not yet widely accepted as a method for batch release and stability testing under the good manufacturing practice (GMP) regime, due to limited experience and level of comfort with the technical, compliance and regulatory aspects of its implementation at quality control (QC) laboratories. This article is the second part of a two-tiered publication aiming at providing guidance for implementation of the multi-attribute method by peptide mapping liquid chromatography mass spectrometry (MAM) in a QC laboratory. The first part [1] focuses on technical considerations, while this second part provides considerations related to GMP compliance and regulatory aspects.