Process Development: Maximizing Process Data from Development to Manufacturing

Jul 01, 2007
Volume 20, Issue 7


Process development and manufacturing for biopharmaceuticals are often disjointed activities. Disconnects among groups are aggravated by a lack of common terminology and poor data management practices. A UK biotech consortium has initiated a collaborative development effort to address data management issues. The proposed outcome is a data model, based on the ISA-88 Standard for Batch Control, to capture process and facility data throughout the product lifecycle. A data framework that follows the ISA-88 model can simplify process scale up and enable early views of project costs and facility fit.

Sartorius North America Inc.
The biopharmaceutical industry shows signs of maturity, and increasing competitive pressure is driving the need for faster, cheaper development and production processes. Companies are actively looking for solutions that speed progress from lab to pilot-scale manufacture and that promote cost-effective production processes. Progress toward these goals is hindered by the complexity and variability of biological product manufacturing, however, and current initiatives, such as quality by design, are a reflection of how much the industry has yet to learn about bioprocesses.

Product development lifecycles typically range from five to eight years for biopharmaceuticals;1 the long lag times between development and manufacture make it difficult for companies to learn from past experience. Furthermore, investigational process-development activities usually take second place to the main objective of producing product as quickly as possible. The organizational divides that frequently separate development and manufacturing activities only aggravate the situation, particularly when companies lack effective data management.

A survey of pharmaceutical companies conducted by Ken Morris, PhD, of Purdue University, and Sam Venugopal and Michael Eckstut of Conformia Software, Inc., revealed that few companies can track data and decision-making processes during the development lifecycle, and that most are dissatisfied with the ability of their existing IT systems to capture and manage drug development information.2 Survey results indicate that drug development specialists spend five hours a week, on average, looking for data, and about two-thirds of respondents reported they couldn't find 10–20% of the data they needed. It is virtually impossible to achieve continuous improvement in such an environment, and the cost of lost time and rework during development can be significant. The average cost to develop a new pharmaceutical is more than $800 million,3 and development costs continue to rise.

To manufacturers from other industries, the solution seems obvious: implement a new, comprehensive IT solution, or make better use of existing systems. Even though there are many sophisticated IT solutions available, ranging from enterprise resource planning (ERP) systems to electronic lab notebooks (ELNs), adoption has been slow and problematic in the biopharmaceutical industry. There are several reasons for this. First, the widespread presence of paper lab notebooks and uncertainties about electronic records and signatures have caused many organizations to be reluctant to abandon paper-based systems. Companies that do make the switch often go through an awkward transition period where both paper and electronic systems are in use. This doubles the workload of end users and can increase resistance to change. Second, software vendors tend to adopt a "one size fits all" approach, often a flawed practice because it ignores the fact that different users can have different ways of working, and there is a wide range of business models in the biopharmaceutical industry. Small companies may focus on discovery and outsource their manufacturing requirements, large companies may buy in new processes, and so on. Third, in some cases the issues go beyond data management and reflect more fundamental disconnects in communication. Adding a level of automation to ineffective business processes often makes the problems worse.


To address some of these issues, a research consortium was formed in 2006 to collaboratively develop a knowledge-management model and supporting applications. End users are from research, process development, technology transfer, and manufacturing. The consortium received a grant from the UK Department of Trade and Industry (DTI) for a three-year project. The consortium is led by BioPharm Services Ltd., a technical consultancy with experience in bioprocess simulation and design, in collaboration with Avecia and Cambridge Antibody Technology (CAT). BioPharm Services has created process simulation models for Avecia and CAT in the past, and each company offers a unique perspective on the biopharmaceutical industry. In addition, the collaborative agreement enables the model to be tested with sample process data and scenarios early in development. The following sections outline the approach taken and the progress to date.

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