Quality Control/Quality Assurance

Now is a good time for companies to know their suppliers well.

A comprehensive process and analytical transfer package can speed up your product's time to market and save costs.

Emerging therapies pose challenges for standardizing QC.

The expanding globalization of the industry poses a challenge for international enforcement.

Need a standard to follow? Just ask, What would Genentech do?

Contrary to popular belief, the out-of-specification problem started years before the Barr Decision.

Regulatory agencies have evolved along with the biotechnology industry to define quality standards.

Multivariate data analysis can help biotech manufacturers deepen their process understanding.

The corruption of China's food and drug sectors is not limited to one man. Likewise, real reform will require the efforts of many.

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.

The US FDA (Rockville, MD, www.fda.gov) recently announced the availability of a draft guidance, entitled, Q10 Pharmaceutical Quality System.

The FDA issued MedImmune, Inc. (Gaithersburg, MD, www.medimmune.com), a warning letter for violating the agency's manufacturing rules and held off approving the company's influenza vaccine for use in children younger than age five until the problems are resolved.

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..

Process monitoring ensures that the process performs within the defined acceptable variability that served as the basis for the filed design space.

The biopharmaceutical industry has gained a lot of experience in monitoring glycosylation, but still has a lot to learn about the structure–function relationship.

The United States Pharmacopeia (USP, Rockville, MD, www.usp.org) and the UK's National Institute for Biological Standards and Control (NIBSC, Hertfordshire, UK, www.nibsc.ac.uk) are seeking participants in a study of analytical methods used by the industry to characterize and quantify oligosaccharides.

ABSTRACT

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.

Conducting an analysis of the 4 Ms-man, machine, methods, and materials-enables companies to identify the true root causes of deviations.

The many benefits of disposable technologies, such as significant savings in time, labor and capital, as well as ease of scalability and flexibility, have led to the growing trend of adopting disposable technologies in bioprocess manufacturing processes.

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.

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.

Federal regulations are broad and open to interpretation. Most have not caught up with advancements in technology.