Process validation is the analysis of data gathered throughout the design and manufacturing of a product in order to confirm that the process can reliably output products of a determined standard. Regulatory authorities like EMA and FDA have published guidelines relating to process validation. [1] The purpose of process validation is to ensure varied inputs lead to consistent and high quality outputs. Process validation is an ongoing process that must be frequently adapted as manufacturing feedback is gathered. End-to-end validation of production processes is essential in determining product quality because quality cannot always be determined by finished-product inspection. Process validation can be broken down into 3 steps: process design (Stage 1a, Stage 1b), process qualification (Stage 2a, Stage 2b), and continued process verification (Stage 3a, Stage 3b).
In this stage, data from the development phase are gathered and analyzed to define the commercial manufacturing process. By understanding the commercial process, a framework for quality specifications can be established and used as the foundation of a control strategy. Process design [2] is the first of three stages of process validation. Data from the development phase is gathered and analyzed to understand end-to-end system processes. These data are used to establish benchmarks for quality and production control.
Design of experiments is used to discover possible relationships and sources of variation as quickly as possible. A cost-benefit analysis should be conducted to determine if such an operation is necessary. [3]
Quality by design is an approach to pharmaceutical manufacturing that stresses quality should be built into products rather than tested in products; that product quality should be considered at the earliest possible stage rather than at the end of the manufacturing process. Input variables are isolated in order to identify the root cause of potential quality issues and the manufacturing process is adapted accordingly.
Process analytical technology is used to measure critical process parameters (CPP) and critical quality attributes (CQA). PAT facilitates measurement of quantitative production variables in real time and allows access to relevant manufacturing feedback. PAT can also be used in the design process to generate a process qualification. [4]
Critical process parameters are operating parameters that are considered essential to maintaining product output within specified quality target guidelines. [5]
Critical quality attributes (CQA) are chemical, physical, biological, and microbiological attributes that can be defined, measured, and continually monitored to ensure final product outputs remain within acceptable quality limits. [6] CQA are an essential aspect of a manufacturing control strategy and should be identified in stage 1 of process validation: process design. During this stage, acceptable limits, baselines, and data collection and measurement protocols should be established. Data from the design process and data collected during production should be kept by the manufacturer and used to evaluate product quality and process control. [7] Historical data can also help manufacturers better understand operational process and input variables as well as better identify true deviations from quality standards compared to false positives. Should a serious product quality issue arise, historical data would be essential in identifying the sources of errors and implementing corrective measures.
In this stage, the process design is assessed to conclude if the process is able to meet determined manufacturing criteria. In this stage all production processes and manufacturing equipment is proofed to confirm quality and output capabilities. Critical quality attributes are evaluated, and critical process parameters taken into account, to confirm product quality. Once the process qualification stage has been successfully accomplished, production can begin. Process Performance Qualification [8] is the second phase of process validation.
Continued process verification is the ongoing monitoring of all aspects of the production cycle. [9] It aims to ensure that all levels of production are controlled and regulated. Deviations from prescribed output methods and final product irregularities are flagged by a process analytics database system. The FDA requires production data be recorded (FDA requirements (§ 211.180(e)). Continued process verification is stage 3 of process validation.
The European Medicines Agency defines a similar process known as ongoing process verification. This alternative method of process validation is recommended by the EMA for validating processes on a continuous basis. Continuous process verification analyses critical process parameters and critical quality attributes in real time to confirm production remains within acceptable levels and meets standards set by ICH Q8, Pharmaceutical Quality Systems, and Good manufacturing practice.
Validation may refer to:
Hazard analysis and critical control points, or HACCP, is a systematic preventive approach to food safety from biological, chemical, and physical hazards in production processes that can cause the finished product to be unsafe and designs measures to reduce these risks to a safe level. In this manner, HACCP attempts to avoid hazards rather than attempting to inspect finished products for the effects of those hazards. The HACCP system can be used at all stages of a food chain, from food production and preparation processes including packaging, distribution, etc. The Food and Drug Administration (FDA) and the United States Department of Agriculture (USDA) require mandatory HACCP programs for juice and meat as an effective approach to food safety and protecting public health. Meat HACCP systems are regulated by the USDA, while seafood and juice are regulated by the FDA. All other food companies in the United States that are required to register with the FDA under the Public Health Security and Bioterrorism Preparedness and Response Act of 2002, as well as firms outside the US that export food to the US, are transitioning to mandatory hazard analysis and risk-based preventive controls (HARPC) plans.
In software project management, software testing, and software engineering, verification and validation is the process of checking that a software engineer system meets specifications and requirements so that it fulfills its intended purpose. It may also be referred to as software quality control. It is normally the responsibility of software testers as part of the software development lifecycle. In simple terms, software verification is: "Assuming we should build X, does our software achieve its goals without any bugs or gaps?" On the other hand, software validation is: "Was X what we should have built? Does X meet the high-level requirements?"
Bioequivalence is a term in pharmacokinetics used to assess the expected in vivo biological equivalence of two proprietary preparations of a drug. If two products are said to be bioequivalent it means that they would be expected to be, for all intents and purposes, the same.
An approved drug is a medicinal preparation that has been validated for a therapeutic use by a ruling authority of a government. This process is usually specific by country, unless specified otherwise.
The process of establishing documentary evidence demonstrating that a procedure, process, or activity carried out in testing and then production maintains the desired level of compliance at all stages. In the pharmaceutical industry, it is very important that in addition to final testing and compliance of products, it is also assured that the process will consistently produce the expected results. The desired results are established in terms of specifications for outcome of the process. Qualification of systems and equipment is therefore a part of the process of validation. Validation is a requirement of food, drug and pharmaceutical regulating agencies such as the US FDA and their good manufacturing practices guidelines. Since a wide variety of procedures, processes, and activities need to be validated, the field of validation is divided into a number of subsections including the following:
Process analytical technology (PAT) has been defined by the United States Food and Drug Administration (FDA) as a mechanism to design, analyze, and control pharmaceutical manufacturing processes through the measurement of critical process parameters (CPP) which affect the critical quality attributes (CQA).
A design history file is a compilation of documentation that describes the design history of a finished medical device. The design history file, or DHF, is part of regulation introduced in 1990 when the U.S. Congress passed the Safe Medical Devices Act, which established new standards for medical devices that can cause or contribute to the death, serious illness, or injury of a patient. Prior to this legislation, U.S. Food and Drug Administration (FDA) auditors were limited to examining the production and quality control records of the device.
Good automated manufacturing practice (GAMP) is both a technical subcommittee of the International Society for Pharmaceutical Engineering (ISPE) and a set of guidelines for manufacturers and users of automated systems in the pharmaceutical industry. More specifically, the ISPE's guide The Good Automated Manufacturing Practice (GAMP) Guide for Validation of Automated Systems in Pharmaceutical Manufacture describes a set of principles and procedures that help ensure that pharmaceutical products have the required quality. One of the core principles of GAMP is that quality cannot be tested into a batch of product but must be built into each stage of the manufacturing process. As a result, GAMP covers all aspects of production; from the raw materials, facility and equipment to the training and hygiene of staff. Standard operating procedures (SOPs) are essential for processes that can affect the quality of the finished product.
In the pharmaceutical industry, drug dissolution testing is routinely used to provide critical in vitro drug release information for both quality control purposes, i.e., to assess batch-to-batch consistency of solid oral dosage forms such as tablets, and drug development, i.e., to predict in vivo drug release profiles. There are three typical situations where dissolution testing plays a vital role: (i) formulation and optimization decisions: during product development, for products where dissolution performance is a critical quality attribute, both the product formulation and the manufacturing process are optimized based on achieving specific dissolution targets. (ii) Equivalence decisions: during generic product development, and also when implementing post-approval process or formulation changes, similarity of in vitro dissolution profiles between the reference product and its generic or modified version are one of the key requirements for regulatory approval decisions. (iii) Product compliance and release decisions: during routine manufacturing, dissolution outcomes are very often one of the criteria used to make product release decisions.
Verification and validation are independent procedures that are used together for checking that a product, service, or system meets requirements and specifications and that it fulfills its intended purpose. These are critical components of a quality management system such as ISO 9000. The words "verification" and "validation" are sometimes preceded with "independent", indicating that the verification and validation is to be performed by a disinterested third party. "Independent verification and validation" can be abbreviated as "IV&V".
Design controls designates the application of a formal methodology to the conduct of product development activities. It is often mandatory to implement such practice when designing and developing products within regulated industries.
Quality by design (QbD) is a concept first outlined by quality expert Joseph M. Juran in publications, most notably Juran on Quality by Design. Designing for quality and innovation is one of the three universal processes of the Juran Trilogy, in which Juran describes what is required to achieve breakthroughs in new products, services, and processes. Juran believed that quality could be planned, and that most quality crises and problems relate to the way in which quality was planned.
The Drug Quality and Security Act is a law that amended the Federal Food, Drug, and Cosmetic Act to grant the Food and Drug Administration more authority to regulate and monitor the manufacturing of compounded drugs. The bill was written in response to the New England Compounding Center meningitis outbreak that took place in 2012, which killed 64 people. The bill was signed by President Obama on November 27, 2013.
Continued process verification (CPV) is the collection and analysis of end-to-end production components and processes data to ensure product outputs are within predetermined quality limits. In 2011 the Food and Drug Administration published a report outlining best practices regarding business process validation in the pharmaceutical industry. Continued process verification is outlined in this report as the third stage in Process Validation.
Critical process parameters (CPP) in pharmaceutical manufacturing are key variables affecting the production process. CPPs are attributes that are monitored to detect deviations in standardized production operations and product output quality or changes in critical quality attributes. Those attributes with a higher impact on CQAs should be prioritized and held in a stricter state of control. The manufacturer should conduct tests to set acceptable range limits of the determined CPPs and define acceptable process variable variability. Operational conditions within this range are considered acceptable operational standards. Any deviation from the acceptable range will be indicative of issues within the process and the subsequent production of substandard products. Data relating to CPP should be recorded, stored, and analyzed by the manufacturer. CPP variables and ranges should be reevaluated after careful analysis of historical CPP data. Identifying CPPs is done in stage one of process validation: process design are an essential part of a manufacturing control strategy.
Process qualification is the qualification of manufacturing and production processes to confirm they are able to operate at a certain standard during sustained commercial manufacturing. Data covering critical process parameters must be recorded and analyzed to ensure critical quality attributes can be guaranteed throughout production. This may include testing equipment at maximum operating capacity to show quantity demands can be met. Once all processes have been qualified the manufacturer should have a complete understanding of the process design and have a framework in place to routinely monitor operations. Only after process qualification has been completed can the manufacturing process begin production for commercial use. Equally important as qualifying processes and equipment is qualifying software and personnel. A well trained staff and accurate, thorough records helps ensure ongoing protection from process faults and quick recovery from otherwise costly process malfunctions. In many countries qualification measures are also required, especially in the pharmaceutical manufacturing field.
Process performance qualification protocol is a component of process validation: process qualification. This step is vital in maintaining ongoing production quality by recording and having available for review essential conditions, controls, testing, and expected manufacturing outcome of a production process. The Food and Drug Administration recommends the following criteria be included in a PPQ protocol:
Design space verification is defined by the European Medicines Agency as the verification that material inputs and processes are able to scale to commercial manufacturing levels while maintaining a standard of quality. Therefore, it is difficult to conduct design space verification while not operating at target levels and should be conducted over the manufacturing lifecycle. Changes in manufacturing output within the design space should not present any risks. Should the manufacturing load exceed the boundaries defined as normal operating ranges unanticipated scale-dependent issues can occur.
Predictive engineering analytics (PEA) is a development approach for the manufacturing industry that helps with the design of complex products. It concerns the introduction of new software tools, the integration between those, and a refinement of simulation and testing processes to improve collaboration between analysis teams that handle different applications. This is combined with intelligent reporting and data analytics. The objective is to let simulation drive the design, to predict product behavior rather than to react on issues which may arise, and to install a process that lets design continue after product delivery.