Process validation has been described as just another chore to satisfy regulatory authorities. In biotechnology, some of the problematic issues were, and still are, related to differences in worldwide regulatory reviewers' expectations and differences even within a single regulatory agency. Although those differences still exist, it has been demonstrated time and again that a downstream process validation plan complying with worldwide expectations can be developed and implemented.Validation should not be considered as just 3 to 5 consecutive conformance batches. Validation begins in development and includes a life-cycle approach. Validation can be thought of as a multistep, structured effort that starts in process development with a risk assessment and the use of risk mitigation tools that enable quality by design (QbD).1 After the initial design phase, characterization (also called robustness) studies that use Design of Experiments (DoE) plus further experimental work enable the establishment of ranges in which the process always delivers the requisite active pharmaceutical ingredient (API) quality. Conformance or validation batches confirm that the entire process can be run consecutively at least three times.
Designing Validation and Quality into a Chromatographic Process
Risk assessment and mitigation are described in ICH Q9.2 For biotechnology, Failure Modes and Effects Analysis (FMEA) is probably the most commonly described risk management tool.3–5 All risk management requires that experts from multiple disciplines ask the following questions:
The information obtained from the risk analysis will only be useful, however, if the input is appropriate. For downstream processing, it is essential to have additional input from the upstream processing, manufacturing, and analytical departments. The results from the risk assessment often dictate the number of chromatographic or other downstream steps needed to reduce specific risks to acceptable levels.
Risk management is an iterative process and empirical data gathered in development may alter process design. For example, column load for initial steps often is increased during early development as cell culture conditions are modified to increase productivity. An overloaded column is not likely to provide expected purity levels and can alter the outcome of subsequent downstream process steps. Optimizing column size or even adding another step may be necessary to achieve the expected product quality. Changes during cell culture that alter metabolism and rates of protein expression have been shown to increase the rate of retrovirus production. Such changes may necessitate the need for greater virus clearance capability to be designed into the downstream process to mitigate patient safety risks.6