Quality/GMPs

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Digitalization of QbD Risk Assessments

The digital transformation of quality-by-design assessment workflows can improve efficiency, reduce human errors, and facilitate integration within a much broader digital ecosystem.

Digitalization of QbD Risk Assessments

Subjectivity in Quality Risk Management

The authors discuss subjectivity in the ICH Q9 (R1) guidance document.

Subjectivity in Quality Risk Management

Phase-appropriate Compliance for Cell and Gene Therapies

Understanding how to apply phase-appropriate GMPs is crucial for achieving successful regulatory approval.

Phase-appropriate Compliance for Cell and Gene Therapies

From the earliest days of the biotechnology industry, companies have grappled with the complexities of making innovative biopharmaceuticals on a large scale. Success in manufacturing begins with process science, since biotech production requires perfection in maintaining living organisms in a sterile environment under controlled physiological conditions. But unless companies can solve the challenge of planning for and managing manufacturing capacity, they will not be able to achieve the full potential of promising biotech products.

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Understanding the end-to-end management of chemistry, manufacturing, and controls (CMC) resources provides the opportunity to enhance long-term planning, leverage development options, manage resource trade offs, and track progress against plans. The goal is to improve the pharmaceutical development process to deliver the pipeline. This article provides an overview of the organizational structure of Process Research and Development (PR&D) and the CMC teams at Genentech; the alignment of resources based on CMC contracts, process development activity maps and project resource plans; and the business economic analysis for evaluating development options.

The US Pharmacopeia (Rockville, MD, USP, www.usp.org) recently announced that the implementation period for its USP­–NF general notices statement requiring all manufacturers to conform to recently revised residual solvent standards in General Chapter <467> has been extended from July 1, 2007 to July 1, 2008.

One goal of process characterization is establishing representative performance parameter ranges that can be used to set validation acceptance criteria (VAC). Characterization studies yield varying numbers of data points from multiple experiments, and may also include data generated at different scales (e.g., bench, pilot, and commercial), which add complexity to the analysis. Many statistical approaches can be used to set ranges from large data sets. As an example, we present the statistical considerations and techniques for setting validation acceptance ranges for a chromatography step used in purifying a recombinant protein. Performance parameter data from a combined data set consisting of 67 bench, six pilot, and three full-scale runs were analyzed using the statistical analysis software JMP (SAS Institute). The combined data set was used to compute tolerance intervals, so that sources such as scale and column feed material could be properly modeled. The resulting ranges were used to establish..