Regulatory/GMP Compliance

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How much do regulatory agencies know about nanotechnology or microfluidics? Yesterday, the answer was probably, "not much." Tomorrow, it may be "a lot." The reason is that new technologies push the agencies to expand their expertise.

Vagueness in the ICH Q2A and Q2B guidelines necessitates effective protocol design and data analysis. For specificity (detection in the presence of interfering substances), the goal is statistical differences with meaningful implications on assay performance. Linearity (results directly proportional to concentration of analyte in the sample) is typically demonstrated via least squares regression. Accuracy (difference between measured and true values) usually is presented as a percent of nominal. Precision analysis is vital because it supports claims of accuracy and linearity. A well-designed experiment and statistically relevant methods will facilitate method validation in accordance with ICH guidelines.

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Biopharmaceutical processes typically require a significant investment in equipment-often a substantial obstacle for start-up companies. The risk of drug development failure is often high, further limiting access to the required capital. Flexibility and lower capital outlays are required not only by start-up companies, but also by research organizations with multiple product lines and by companies requiring quick capacity increases. Disposable technologies offer the highest potential for these companies to meet their business requirements. With lower capital requirements and increased flexibility, disposables are an important part of these companies' risk management strategy.

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The adoption of single-use containers in the biopharmaceutical industry is becoming more frequent as the popularity and availability of the technologies increase. The choice of a solution for storage in single-use containers clearly depends on the application and the inherent risks associated with the application. A "one fits all" single-use system cannot respond to all the requirements of a particular step in a biopharmaceutical process, much less to all the steps of a process. The needs of an application will lead to very specific single-use solutions.

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In its early days, the biotech industry was almost entirely science driven, but it has since expanded from a laboratory environment to a sophisticated and dynamic manufacturing environment. As technological discoveries are increasingly translated into commercial products, biotech companies are realizing that they must generate a stronger return on assets.

This article shows how Probabilistic Tolerance Intervals of the form, "We are 99% confident that 99% of the measurements will fall within the calculated tolerance limits" can be used to set acceptance limits using production data that are approximately Normally distributed. If the production measurements are concentrations of residual compounds that are present in very low concentrations, it may be appropriate to set acceptance limits by fitting a Poisson or an Exponential Distribution.

The first part of this article, published in the September 2006 issue, discussed general strategies for validation extensions to other test method components, laboratories and even different test methods.1This second part provides practical tips on how to maintain test method suitability long after the formal completion of analytical method validation (AMV) studies.

Development reports document process development and support the design of validation experiments, yet in many firms training is not provided nor are expectations established. This article describes how project managers can help scientists master the art of report-writing.