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Process Validation of Existing Processes and Systems Using Statistically Significant Retrospective Analysis - Part One of Three

by Andrew W. Jones, Technical Manager, KMI/PAREXEL LLC
January 2001

The FDA defined Process Validation in 1987 by the following: “Process Validation is establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its predetermined specification and quality attributes.” 1The purpose of this article is to discuss how to validate a process by introducing some basic statistical concepts to use when analyzing historical data from Batch Records and Quality Control Release documents to establish specifications and quality attributes for an existing process. In an ideal world, the qualification of processing equipment, utilities, facilities, and controls would commence at the start up of a new plant or the implementation of a new system. This would be followed by the validation of the process based on developmental data and used to establish the product ranges for in process and final release testing. However, the ideal case may not exist and thus there are incidences where commissioning of facilities or new systems occurs concurrently with the qualification and process validation; or the facility and equipment are “existing” and there is no such documentation. Some facilities, equipment, or processes pre-date the above definition by many years and therefore have never been validated on qualified equipment, utilities, facilities, and controls. Additionally, in some cases, no developmental data exists to establish the product ranges for in process and release testing.

Basics of Process Validation

Before examining the existing processes, it is important to first understand the basic concepts of Process Validation. Figure 1 is a flow chart defining Process Validation from the developmental stage to the plant floor. As a simplistic example, a process begins with the raw materials being released, then the raw materials are mixed, pH is adjusted, purification occurs by gel chromatography, excipients are added for final formulation, and the product is filled and terminally sterilized. Each of these steps has defined functions and therefore would have a designed goal. For example, purification would not begin until the desired pH is reached in the previous step. Therefore, the desired pH is an in process attribute of the pH adjustment stage and the amount of buffer used to adjust the pH is a processing parameter. Each of these steps has attributes that one would want to monitor to determine that the product is being produced acceptably at that step such that the next process step can start. The ranges for these attributes are generally determined by process development data so that if the process attributes are met, then there is a high degree of confidence that the final container is filled with a product of acceptable attributes as determined by the developmental data.

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During Process Validation, there needs to be approved Standard Operating Procedures (SOPs) in place that Plant Operators have been trained on. Analytical testing should be performed by SOPs and the Quality Control (QC) analysts should be trained in these SOPs as well. The analytical tests should have been previously validated by normal analytical methods validation and documented as such. Also, the equipment used to prepare product must be documented to be qualified for its installation, operation, and performance, commonly referred to as IQ, OQ, and PQ. There are methods for performing such qualification retrospectively, but for the purpose of this discussion, it is only important to note that the equipment must be qualified.

Relating Process Validation to Existing Processes

Existing processes may lack developmental data for in process ranges and release testing. If a retrospective analysis of existing data is used to establish process ranges, including input, output, and in process testing parameters, then the process can be treated like a new process by following the basics of Prospective Process Validation. The difference between traditional Prospective Process Validation and Prospective Process Validation based on retrospective analysis is that in place of developmental data to establish ranges, the retrospective analysis reviews data from past Batch Production Records, QC test reports, product specs, etc. Thus the items that need to be in place are: approved SOPs, and Batch Records with personnel training, equipment qualification (IQ, OQ, PQ), QC methods validated, approved SOPs and training for QC personnel. With these in place, all that is missing is a Process Validation Protocol with defined ranges. The best sources of this information are approved completed batch records, process deviation reports, QC Release data, and small-scale studies. From these, the following items must be completed:

  • Critical parameters and input and output parameters must be defined.
  • A statistically valid time frame or number of batches must be determined.
  • The data used to establish the parameters must be extracted from controlled documents.
  • The data extracted from the controlled documents will be analyzed to establish ranges.

Each one of these steps will be examined in the following sections to describe them in further detail.

Critical parameters and input and output parameters defined.

In The Guidelines on General Principles of Process Validation, 15 MAY 1987, it states that:

The validity of acceptance specifications should be verified through testing and challenge of the product on a sound scientific basis during the initial development and production phase.1

It is important to determine which parameters in your process are critical to the final product. When determining these parameters and attributes a variety of personnel with different expertise should be utilized. Assembling a team of professionals is a starting point and this committee should be a multi-disciplined team including Quality, Validation, Systems Engineering, Facility Engineering, Pharmaceutical Sciences (or R&D), and Manufacturing. When determining the parameters and attributes which are critical, it is important to consider those which if they were not controlled or achieved, then the result would have an adverse effect on the product. A risk assessment should be performed to analyze what the risk is and what the results are if a specific parameter or attribute is not controlled or achieved (e.g. the resulting product would be flawed). Risk assessment is defined by The Ontario Ministry of Agriculture, Food and Rural Affairs as:

  1. the probability of the negative event occurring because of the identified hazard,
  2. the magnitude of the impact of the negative advent, and
  3. consideration of the uncertainty of the data used to assess the probability and the impact of the components. 2

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Figure 2 is a list of general questions to consider when assessing risk while Figure 3 is an example of Fault Tree Analysis - a formal approach to evaluating risk, where a Top Level Event is observed and through questions and observations the cause of the event can be determined.

National Center for Drugs and Biologics and National Center for Devices and Radiological Health, “Guidelines on General Principles of Process Validation,” Rockville MD. 15 MAY 1987.National Center for Drugs and Biologics and National Center for Devices and Radiological Health, “Guidelines on General Principles of Process Validation,” Rockville MD. 15 MAY 1987.Ontario Ministry of Agriculture, Food and Rural Affairs (2000), Queen’s Printer for Ontario, Last Updated March 22, 2000; WEB: http://www.gov.on.ca/omafra/english/research/risk/assum1b.html.

Page last updated: 5 March 2009