Continued process verification

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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 [1] 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.

Contents

Its central purpose is to ensure that processes are in a constant state of control, thus ensuring final product quality. Central to effective CPV is a method with which to identify unwanted process inconsistencies in order to execute corrective or preventive measures. Once quality standards are set in place they must be monitored with regular frequency to confirm those parameters are being met. Continued process verification not only helps protect consumers from production faults, but business also see benefits in implementing a CPV program. Should product outputs not match target standards it can be very costly to investigate the problem source without existing CPV data.

Vital components of continued process verification

Data collection and analysis

Crucial in effective CPV implementation is an appropriate data collection procedure. Data must allow for statistical analytics and trend analysis of process consistency and capability. [3] A correctly implemented procedure will minimize overreactions to individual production outlier events and guarantee genuine process inconsistency are detected. While production variability can sometimes be obvious and even casually identified the FDA recommends using statistical tools to quantitatively detect problems and identify root causes. Initially, continued process verification should be based on quality standards established in the design phase. After a period of time variations can be detected by identifying deviation from historical data using statistical tools. Furthermore, these same tools can also be used to identify opportunities to optimize processes that may pre-emptively increase quality reliability. [4]

Related Research Articles

A quality management system (QMS) is a collection of business processes focused on consistently meeting customer requirements and enhancing their satisfaction. It is aligned with an organization's purpose and strategic direction. It is expressed as the organizational goals and aspirations, policies, processes, documented information, and resources needed to implement and maintain it. Early quality management systems emphasized predictable outcomes of an industrial product production line, using simple statistics and random sampling. By the 20th century, labor inputs were typically the most costly inputs in most industrialized societies, so focus shifted to team cooperation and dynamics, especially the early signaling of problems via a continual improvement cycle. In the 21st century, QMS has tended to converge with sustainability and transparency initiatives, as both investor and customer satisfaction and perceived quality are increasingly tied to these factors. Of QMS regimes, the ISO 9000 family of standards is probably the most widely implemented worldwide – the ISO 19011 audit regime applies to both and deals with quality and sustainability and their integration.

<span class="mw-page-title-main">Hazard analysis and critical control points</span> Systematic preventive approach to food safety

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.

<span class="mw-page-title-main">Good manufacturing practice</span> Manufacturing quality standards

Current good manufacturing practices (cGMP) are those conforming to the guidelines recommended by relevant agencies. Those agencies control the authorization and licensing of the manufacture and sale of food and beverages, cosmetics, pharmaceutical products, dietary supplements, and medical devices. These guidelines provide minimum requirements that a manufacturer must meet to assure that their products are consistently high in quality, from batch to batch, for their intended use. The rules that govern each industry may differ significantly; however, the main purpose of GMP is always to prevent harm from occurring to the end user. Additional tenets include ensuring the end product is free from contamination, that it is consistent in its manufacture, that its manufacture has been well documented, that personnel are well trained, and that the product has been checked for quality more than just at the end phase. GMP is typically ensured through the effective use of a quality management system (QMS).

In software project management, software testing, and software engineering, verification and validation (V&V) is the process of checking that a software 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?"

Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability describes the ability of a system or component to function under stated conditions for a specified period of time. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at a specified moment or interval of time.

Software assurance (SwA) is a critical process in software development that ensures the reliability, safety, and security of software products. It involves a variety of activities, including requirements analysis, design reviews, code inspections, testing, and formal verification. One crucial component of software assurance is secure coding practices, which follow industry-accepted standards and best practices, such as those outlined by the Software Engineering Institute (SEI) in their CERT Secure Coding Standards (SCS).

Environmental stress screening (ESS) refers to the process of exposing a newly manufactured or repaired product or component to stresses such as thermal cycling and vibration in order to force latent defects to manifest themselves by permanent or catastrophic failure during the screening process. The surviving population, upon completion of screening, can be assumed to have a higher reliability than a similar unscreened population.

In the experimental (non-clinical) research arena, good laboratory practice or GLP is a quality system of management controls for research laboratories and organizations to ensure the uniformity, consistency, reliability, reproducibility, quality, and integrity of products in development for human or animal health through non-clinical safety tests; from physio-chemical properties through acute to chronic toxicity tests.

Data cleansing or data cleaning is the process of detecting and correcting corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting or a data quality firewall.

Validation is 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.

Eight Disciplines Methodology (8D) is a method or model developed at Ford Motor Company used to approach and to resolve problems, typically employed by quality engineers or other professionals. Focused on product and process improvement, its purpose is to identify, correct, and eliminate recurring problems. It establishes a permanent corrective action based on statistical analysis of the problem and on the origin of the problem by determining the root causes. Although it originally comprised eight stages, or 'disciplines', it was later augmented by an initial planning stage. 8D follows the logic of the PDCA cycle. The disciplines are:

Corrective and preventive action consists of improvements to an organization's processes taken to eliminate causes of non-conformities or other undesirable situations. It is usually a set of actions, laws or regulations required by an organization to take in manufacturing, documentation, procedures, or systems to rectify and eliminate recurring non-conformance. Non-conformance is identified after systematic evaluation and analysis of the root cause of the non-conformance. Non-conformance may be a market complaint or customer complaint or failure of machinery or a quality management system, or misinterpretation of written instructions to carry out work. The corrective and preventive action is designed by a team that includes quality assurance personnel and personnel involved in the actual observation point of non-conformance. It must be systematically implemented and observed for its ability to eliminate further recurrence of such non-conformation. The Eight disciplines problem solving method, or 8D framework, can be used as an effective method of structuring a CAPA.

Cleaning validation is the methodology used to assure that a cleaning process removes chemical and microbial residues of the active, inactive or detergent ingredients of the product manufactured in a piece of equipment, the cleaning aids utilized in the cleaning process and the microbial attributes. All residues are removed to predetermined levels to ensure the quality of the next product manufactured is not compromised by residues from the previous product and the quality of future products using the equipment, to prevent cross-contamination and as a good manufacturing practice requirement.

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. "Integration verification and validation" can be abbreviated as "IV&V".

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.

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. 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, process qualification, and continued process verification.

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 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:

References

  1. "Process Validation: General Principles and Practices" (PDF). FDA. Retrieved 3 November 2014.
  2. "Trust but Verify (Continuously)" (PDF). Pharmaceutical Manufacturing. Retrieved 3 November 2014.
  3. "Continued Process Verification (CPV)". Atris Information Systems. Retrieved 3 November 2014.
  4. "A Case for Stage 3 Continued Process Verification". Pharmaceutical Manufacturing. Retrieved 3 November 2014.

Further reading