Introduction
Foundations of process validation
Key elements of process validation
Challenges and solutions
Future directions and conclusions
References
Further Reading
Process validation is crucial for ensuring the quality of final products and the safety of these processes for manufacturing personnel and consumers in the pharmaceutical, medical device, and biotechnology industries.
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Introduction
According to the United States Food and Drug Administration (FDA), process validation is collecting and evaluating data obtained throughout a product's entire lifecycle, including the initial drug development process and its commercial manufacturing1.
Although process validation is a regulatory standard, it has an important role in maintaining control of the manufacturing process.
The rapid identification and subsequent resolution of any variation allows the manufacturer to continually improve their processes and be confident that the final product meets all quality attributes.
Foundations of process validation
Process validation can be classified into three distinct stages: process design, process qualification (PQ), and continued process verification.
During the first process design stage, the commercial manufacturing process will be defined to ensure it consistently delivers a high-quality product. Product quality and manufacturing data must be reviewed periodically to determine whether any changes to these processes are needed.
Subsequently, PQ involves assessing whether the process design can effectively produce the commercial product in a reliable and reproducible manner. PQ can be further divided into two stages, the first involves designing the facility, which also includes selecting equipment and utilities that will be needed during the manufacturing process1.
The second element of PQ involves process performance qualification (PPQ), during which each aspect of the manufacturing process, including the actual facility, utilities, equipment, and trained personnel, are combined and confirmed to perform as expected.
The final validation stage is designed to allow for the continual monitoring of the commercial manufacturing process. This stage typically involves establishing systems capable of collecting and evaluating data on the performance of manufacturing processes in real-time.
Key elements of process validation
Many regulatory agencies worldwide, including the FDA, can legally enforce process validation procedures to ensure that final drug products consistently and reliably meet pre-determined quality standards.
These regulations also indicate that written production and process control procedures are essential to ensure that drug protects have the identity, strength, quality, and purity they are reported to possess.
To meet these standards, the FDA recommends an interdisciplinary approach to process validation, in which professionals from various industries work together to generate appropriate procedures and best practices2.
A successful process validation process requires continuous monitoring of data on each attribute and parameter of the manufacturing process.
This information allows manufacturers to quickly identify the sources of any variation and the extent to which this variation is causing issues, as well as understand the impact of this variation on the manufacturing process and, ultimately, product attributes.
Critical process parameters (CPPs) are variables within the pharmaceutical manufacturing process that can impact critical quality attributes (CQA), thus demonstrating the importance of closely monitoring CPPs in process validation.
Both physical and chemical CPPs are often monitored through in-line/online process sensors, some of which include pH, dissolved oxygen (pO2), dissolved carbon dioxide (pCO2), exhaust O2 and CO2, nutrient and metabolite concentrations, temperature, pressure, and oxidation-reduction potential (ORP)3.
Challenges and solutions
Despite the crucial role of process validation in supporting the safe production of high-quality pharmaceutical products, there are various challenges associated with the execution of this approach.
For example, many complex processes are involved in the production of pharmaceutical agents and biotechnology products, thus increasing the number of variables that can affect the quality of the final product.
In addition to the inherent challenges associated with managing and validating these complex processes, regulatory standards continue to evolve, which can make it increasingly difficult for pharmaceutical industries to maintain their compliance with new industry requirements.
Process validation involves collecting, analyzing, and managing vast data. Thus, manufacturing companies must design standardized procedures that are easy to follow while adhering to regulatory requirements4.
The implementation of advanced data management and analytics tools can also improve the efficiency of data collection processes and reduce unnecessary costs. Automating different aspects of the validation process may also accelerate data collection and analysis procedures while reducing the risk of human error.
Effective cleaning validation processes are crucial for producing regulated products, including vaccines and pharmaceutical agents.
In fact, the U.S. FDA, the European Medicines Agency (EMA), and the Pharmaceutical Inspection Co-operation Scheme (PIC/S) have cleaning validation guidelines that all pharmaceutical products must comply with before they can be released to the public.
Compliance with these regulations involves consistently removing residues below established acceptance levels, necessitating meticulous cleaning methods that are thoroughly documented.
ValGenesis, a smart solutions life sciences company, offers Process Manager, a cleaning validation software that guarantees regulatory compliance through the automated electronic documentation of cleaning processes5.
Future directions and conclusions
Process validation is integral to the safe production of pharmaceutical agents. As artificial intelligence (AI) capabilities continue to advance, its incorporation into process validation, particularly in continued process verification, is expected to reduce the time to act on variation alerts while simultaneously providing the manufacturer with potential solutions in real-time.
As these variations and their responses are recorded, machine learning (ML) models can also be created to provide a data-driven approach based on historical information to understand and manage manufacturing processes over time.
References
- “Process Validation: General Principles and Practices” [Online]. Available from: https://www.fda.gov/files/drugs/published/Process-Validation--General-Principles-and-Practices.pdf.
- “A Basic Guide to Process Validation in the Pharmaceutical Industry” [Online]. Available from: https://www.thefdagroup.com/blog/process-validation-pharmaceutical-industry.
- “What are Critical Process Parameters (CPPs)?” [Online]. Available from: https://www.hamiltoncompany.com/process-analytics/process-analytical-technology/critical-process-parameters.
- “Navigating the Challenges of Process Validation: 10 Strategies for Success” [Online]. Available from: https://kneat.com/article/process-validation-challenges-and-solutions/.
- “ValGenesis Process Manager” [Online]. Available from: https://www.valgenesis.com/product/process-manager.
Further Reading