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Equipment grouping is an essential aspect of cleaning validation in pharmaceutical and biopharmaceutical manufacturing. The objective of equipment grouping is to categorize equipment based on their similarities in terms of design, function, and cleaning requirements. This process allows for the development of cleaning validation protocols that can be applied to a group of equipment with similar cleaning requirements, rather than testing each individual piece of equipment. Equipment grouping for cleaning validation involves the following steps: Step 1: Identification of Equipment The first step is to identify all the equipment that needs to be cleaned and validated. This includes all the manufacturing equipment, such as tanks, reactors, filters, and filling machines, as well as the support equipment, such as hoses, gaskets, and valves. Step 2: Classification of Equipment The next step is to classify the equipment based on their design and function. This involves grouping equipment with similar design and function together. For example, all the mixing tanks could be grouped together, while all the filling machines could be grouped together. Step 3: Determination of Cleaning Requirements The third step is to determine the cleaning requirements for each equipment group. This involves identifying the cleaning agents and procedures required to effectively clean the equipment. The cleaning requirements may vary based on the equipment design, material of construction, product contact surfaces, and cleaning agents used. Step 4: Development of Cleaning Validation Protocol The final step is to develop a cleaning validation protocol for each equipment group. This involves specifying the sampling locations, acceptance criteria, analytical methods, and documentation requirements for each equipment group. There are several benefits to equipment grouping for cleaning validation. Firstly, it saves time and resources by reducing the number of validation studies required. Instead of validating each individual piece of equipment, validation can be performed on a representative sample from each equipment group. This allows for a more efficient validation process and reduces the overall validation workload. Secondly, equipment grouping allows for a more robust validation process. By grouping equipment with similar cleaning requirements, the validation protocol can be optimized to ensure that all equipment within the group is effectively cleaned and validated. This helps to ensure that product quality is not compromised by equipment contamination. Thirdly, equipment grouping helps to minimize the risk of cross-contamination. By grouping equipment with similar cleaning requirements, the risk of cross-contamination between different products is reduced. This is particularly important in multi-product facilities, where equipment may be used for different products. In order to ensure effective equipment grouping for cleaning validation, it is important to consider the following factors: Equipment Design: Equipment with similar design and construction should be grouped together. This includes equipment that is made of similar materials, has similar product contact surfaces, and has similar cleaning requirements. Function: Equipment that performs similar functions should also be grouped together. This includes equipment that is used for mixing, filling, and packaging. Cleaning Requirements: Equipment with similar cleaning requirements should be grouped together. This includes equipment that requires similar cleaning agents and procedures. Product Contact: Equipment that comes into contact with similar products should also be grouped together. This includes equipment that is used for the same product or products with similar characteristics. In conclusion, equipment grouping is an essential aspect of cleaning validation in pharmaceutical and biopharmaceutical manufacturing. By grouping equipment with similar cleaning requirements, the validation process can be optimized to ensure that all equipment is effectively cleaned and validated. This helps to ensure product quality, reduce the risk of cross-contamination, and save time and resources. When considering equipment grouping for cleaning validation, it is important to consider equipment design, function, cleaning requirements, and product contact.

Cross-contamination is a major concern in the pharmaceutical industry. It occurs when one product or material comes into contact with another product or material, resulting in contamination. This can have serious consequences, including compromised product quality, safety concerns, and regulatory non-compliance. In this article, we will explore the causes, effects, and prevention of cross-contamination in the pharmaceutical industry. Causes of Cross Contamination There are several causes of cross-contamination in the pharmaceutical industry. One of the most common causes is inadequate cleaning and sanitation procedures. If equipment and surfaces are not properly cleaned between batches or products, residual materials can remain and contaminate subsequent batches. Another cause of cross-contamination is the use of shared equipment or facilities. If different products are manufactured in the same equipment or facility, there is a risk of cross-contamination (unless appropriate controls are in place). Other causes of cross-contamination include human error, improper handling and storage of materials, and environmental factors such as airflow and temperature. Effects of Cross Contamination The effects of cross-contamination can be serious and far-reaching. In terms of product quality, cross-contamination can result in compromised potency, purity, and identity of drug products. This can lead to adverse effects on patients, including reduced efficacy or even harm. Cross-contamination can also have financial consequences for pharmaceutical companies. If contaminated products are identified, they may need to be recalled, resulting in significant costs and damage to the company's reputation. In addition, cross-contamination can lead to regulatory non-compliance, resulting in fines and penalties, as well as damage to the company's reputation. Prevention of Cross Contamination Prevention of cross-contamination is critical in the pharmaceutical industry. Several steps can be taken to minimize the risk of cross-contamination. The first step is to establish and implement a robust cleaning and sanitation program. This program should include procedures for cleaning and sanitizing equipment and surfaces between batches, as well as procedures for cleaning and sanitizing shared equipment and facilities. Another important step is to establish clear segregation and separation between different products and materials. This can be achieved through the use of dedicated equipment and facilities, as well as through the use of physical barriers such as airlocks and isolators. In addition, it is important to establish clear procedures for handling and storing materials. This includes procedures for transferring materials between equipment and facilities, as well as procedures for storing materials to prevent cross-contamination. Human factors are also an important consideration in preventing cross-contamination. It is important to provide adequate training to employees on the proper handling and storage of materials, as well as on the importance of cleaning and sanitation procedures. Finally, regular monitoring and testing of equipment and surfaces can help to identify any potential sources of cross-contamination. This can include swab testing and other analytical techniques to detect residual materials. Conclusion Cross-contamination is a serious concern in the pharmaceutical industry. It can have serious consequences for product quality, patient safety, and regulatory compliance. The causes of cross-contamination are varied but can be mitigated through the establishment of robust cleaning and sanitation programs, clear segregation and separation of materials, proper handling and storage procedures, and regular monitoring and testing. By taking proactive steps to prevent cross-contamination, pharmaceutical companies can ensure that their products are safe and effective for patients, while also avoiding financial and reputational damage.

#cleaningvalidation #pharmaceutical Cleaning validation is an essential process in the pharmaceutical industry to ensure that drug products are safe and effective for patients. Over the years, cleaning validation has evolved from a basic visual inspection to a complex and highly regulated process. In this article, we will explore the history of cleaning validation in the pharmaceutical industry. Early Days of Cleaning Validation In the early days of the pharmaceutical industry, cleaning validation was a simple process that involved visually inspecting equipment after cleaning to ensure that there was no visible residue. This was a subjective process that relied heavily on the experience and judgment of the cleaning personnel. However, as the pharmaceutical industry grew, the need for a more objective and scientific approach to cleaning validation became apparent. 1960s and 1970s In the 1960s and 1970s, the United States Food and Drug Administration (FDA) began to develop regulations for the pharmaceutical industry. These regulations included requirements for cleaning validation to ensure that equipment was properly cleaned between batches of drug products. During this time, the pharmaceutical industry began to use analytical methods to detect trace amounts of residual drug products and cleaning agents on equipment surfaces. These methods included chromatography, spectrophotometry, and titration. These analytical methods allowed for a more objective and precise approach to cleaning validation. 1980s and 1990s In the 1980s and 1990s, the FDA increased its focus on cleaning validation and issued guidance documents that provided more detailed requirements for the process. The FDA's in 1993 issued a guidance document, " Guide To Inspections Validation Of Cleaning Processes" included the FDA expectations with regard to cleaning validation and outlined the key elements of a successful cleaning validation program. During this time, the pharmaceutical industry began to use swabbing and rinsing techniques to collect samples from equipment surfaces for analysis. These techniques provided more accurate and reliable results than visual inspection alone. 2000s and Beyond In the 2000s and beyond, the FDA continued to increase its focus on cleaning validation and issued additional guidance documents that provided more specific requirements for the process. The concept of Health Based Exposure Limits (HBEL) and Permitted Daily Exposure became adopted by major regulatory bodies in place of less science and risk based approaches that was suggested earlier (e.g. 10 ppm limit or 1/1000 of therapeutic dose). In 2014, EMA issued it is Guideline on setting health-based exposure limits for use in risk identification in the manufacture of different medicinal products in shared facilities. ISPE issued also the Risk-Based Manufacture of Pharmaceutical Products (Risk-MaPP) guide with further details on managing the cross-contamination risk in multi-product facilities. This was followed by the ISPE Cleaning Validation Lifecycle guide in 2020 offering a comprehensive approach for establishing a compliant cleaning validation program. The pharmaceutical industry has continued to develop new and innovative methods for cleaning validation, including the use of advanced analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy. These techniques allow for the detection and quantification of even trace amounts of residual drug products and cleaning agents. The Future of Cleaning Validation As the pharmaceutical industry continues to evolve, so too will the process of cleaning validation. New technologies and techniques will be developed that will make the process more efficient, effective, and reliable. One area of focus for the future of cleaning validation is the use of automated cleaning systems. These systems can provide a more consistent and reliable approach to cleaning validation, reducing the risk of errors and variability. Another area of focus is the development of more sensitive and specific analytical methods for detecting residual drug products and cleaning agents. These methods will allow for the detection of even lower levels of residual contaminants, improving the safety and efficacy of drug products. Conclusion The history of cleaning validation in the pharmaceutical industry has been marked by a gradual evolution from a basic visual inspection to a complex and highly regulated process. The use of analytical methods, swabbing and rinsing techniques, and automated cleaning systems has made the process more objective, reliable, and efficient. As the pharmaceutical industry continues to evolve, so too will the process of cleaning validation. New technologies and techniques will be developed that will make the process even more effective and efficient. By staying up-to-date with these developments, the pharmaceutical industry can ensure that its products are safe and effective for patients.

The Health-Based Exposure Limits (HBEL) approach is a method used to calculate cleaning limits in pharmaceutical manufacturing facilities. Cleaning limits are the maximum allowable levels of residual drug product and cleaning agents that can remain on equipment surfaces after cleaning. The HBEL approach uses scientific data and risk assessments to determine safe cleaning limits that protect patients from harmful exposure to residual drug products. The HBEL approach consists of three primary steps: setting a permitted daily exposure (PDE), calculating a safety factor (SF), and determining a cleaning limit based on the PDE and SF. Setting the Permitted Daily Exposure (PDE) The PDE is the maximum amount of a drug substance that a patient can be exposed to on a daily basis without experiencing harmful effects. To determine the PDE, toxicologists conduct a thorough risk assessment that considers the toxicity of the drug, its intended use, and the patient population. The PDE is expressed in milligrams per day. Calculating the Safety Factor (SF) The SF is a multiplier applied to the NOAEL (No Observed Adverse Effect Level) to account for uncertainties in the risk assessment and to provide an additional margin of safety. The SF is typically calculated based on factors such as the quality of the toxicology data, the severity of the drug’s toxicity, and the variability of patient response. A typical SF is 10, meaning that the cleaning limit should be set at one-tenth of the PDE. Determining the Cleaning Limit The cleaning limit is calculated by multiplying the PDE by the number of therapeutic doses (the worst-case scenario) in the next product. For example, if the PDE is 50 mg/day and the number of therapeutic doses is 100, the cleaning limit would be 5 g per equipment surface area. This means that after cleaning, no more than 5 g of residual drug product or cleaning agent can remain on any given equipment surface. To calculate the number of therapeutic doses, the minimum batch size of the next product should be divided by the maximum daily dose of this product. The cleaning limit is typically expressed in micrograms per square centimeter (µg/cm2) or parts per million (ppm). The limit may vary depending on the equipment and the cleaning process. In general, equipment surfaces that come into direct contact with the drug product will have lower cleaning limits than those that do not. The cleaning limit calculation must take into account the surface area of the equipment being cleaned. For example, a large mixing tank may have a higher cleaning limit than a small piece of equipment that is used to dispense the drug product. However, usually drug products are manufactured on a train of equipment so the sum of surface areas of all product-contact equipment is used to calculated the swab limit (remember: carryover is cumulative). Verification of Cleaning Limits Once the cleaning limit has been calculated, it is important to verify that it can be achieved using the cleaning process that is used in the facility. This may involve conducting cleaning validation studies to demonstrate that the cleaning process can consistently achieve the desired cleaning limit. If the cleaning limit cannot be achieved using the current cleaning process, changes to the process may be necessary. This may involve using different cleaning agents or adjusting the cleaning parameters such as the temperature, time, or pressure. Conclusion The HBEL approach is an effective method for determining cleaning limits in pharmaceutical manufacturing facilities. It is based on scientific data and risk assessments and provides a margin of safety to protect patients from harmful exposure to residual drug products. It is important for pharmaceutical manufacturers to use the HBEL approach when setting cleaning limits to ensure that their products are safe for patients. The cleaning limit calculation must take into account the surface area of the equipment being cleaned, and the cleaning process must be validated to ensure that it can consistently achieve the desired cleaning limit. By following the HBEL approach, pharmaceutical manufacturers can ensure that their products meet regulatory requirements and are safe for patients to use. References: - EMA Guideline on setting health-based exposure limits for use in risk identification in the manufacture of different medicinal products in shared facilities. - EMA Questions and answers on implementation of risk-based prevention of cross-contamination in production and ‘Guideline on setting health-based exposure limits for use in risk identification in the manufacture of different medicinal products in shared facilities’ - ASTM E3219-20 Guide For Derivation Of Health-Based Exposure Limits (HBELs).

21 CFR part 11 has been considered for many years the corner stone of computer systems validation and the basis for regulating electronic records and electronic signatures in GMP environment. Part 11 is available in approximately 6 pages that detail the general expectations of the US FDA regarding the submitted electronic records and signatures. Secure time-stamped audit trail is typically required to track any modification or deletion of electronic records. The agency requires also the validation of computer systems to ensure accurate, reliable and consistent system that are able to identify invalid or altered electronic records. In order to achieve this, computer systems are generally tested against the user requirements and challenged to verify its reliability, security and integrity. Management of passwords, unique identification and generally the access to the computer system is required during the lifecycle of any computer system in the GMP environment. In addition, risk assessments can be employed to assess the possible failure modes of a system and suggest mitigation actions. Disaster recovery plan should be in place to ensure that the electronic records can be retrieved throughout the retention period. Business continuity plans should be in place in case of temporary failure of a particular computer system. Despite the established validation requirements for many years in the pharmaceutical industry, computer-system validation (CSV) is still widely seen by the industry practitioners as the topic that should be avoided as possible. In many organizations, CSV is a highly tedious process that is preserved to big computer system and automation projects. External resources may be utilized in many cases to conduct the required validation. On the other hand, smaller business-driven automation projects may lack the required expertise for the development and validation. For example, many pharmaceutical organizations use rudimentary spreadsheets as database to manage GMP processes from document numbering to inventory management. Automation (including visual basic macros and MS power automate flows) are usually discouraged not to be in a situation that CSV is mandatory. This results in a situation where a formal manual process is presented to inspectors and a hidden digital process is relied on in the day to day business activities. The aim of this article is to solve the mystery of CSV and provide a basic guidance for validating simple automation solutions in GMP environment. The following is a high-level process for validating a configured or custom-made software. Create the user requirements: either if the automation solution is home-made or developed by a third-party, user requirements are usually needed to define the functional , security and other features related to data processing. Each requirement is usually assigned a unique number and are tested as will be explained in the next sections. In the light of the user requirements, the automation solution is developed. Design document, system description or a technical specification may be created to explain how the IT developer addressed the user requirements. The importance of this step comes from the fact that there are different ways to meet a user requirement and hence, different potential failure modes. Based on the understanding of the user requirements and the technical specification, testing phase is established. Quality risk management: It may needed to assess the potential failure modes at system and component level before creating the testing protocol. Code review: it is particularly required for customized software (GAMP category 5) where a customized code script is written for a particular software. From the name, code review implies expert-review of the written codes to ensure they are free from bugs. Testing: installation and operation qualification (IOQ) needs to be implemented to test that the computer system meet all the computer system requirements. Traceability matrix can be required for bigger projects to confirm that each user requirement has been covered by at least one test. Business continuity plan: In the case of failure of the computer system, alternative process needs to be in place to keep the business running. The contingency process can be either manual or another digital system. Disaster recovery plan: As per the 21 CFR part 11 requirements, electronic records must be protected and readily retrievable throughout their life-cycle. This document basically explain the process to be followed in case of destruction of the electronic records due to a disaster (e.g. fire) or any other accident causing file corruption (e.g. cyber attack). The plan usually explain a process of regular back-up of data. The frequency and location of back-up servers must be justified through a risk assessment. If the generated electronic records are printed to paper (e.g. the calculated results in a validated spreadsheet), they may not be handled anymore as electronic records and physical archiving process be in place. Security plan: This document addresses the virtual and physical security of the computer system. Also, different access levels should be described if applicable. Security administration procedure: There should be a procedure in place to grant access to the authorized personnel and to revoke the access if needed. Also, the procedure can manage passwords and access roster reviews. Periodic review: In order to monitor the validated state of the computer system, regular periodic reviews may be conducted to assess the performance of the computer system and provide recommendations. Finally, it is important to note that the level of complexity of the CSV process is directly proportional to the criticality and complexity of the computer system. In may cases, one document can include all the required validation documentation.

One of the common misconceptions about cleaning that visually clean surfaces are by default clean. While any equipment need to be visibly clean to be considered clean, this condition is not by itself a sufficient evidence of reduction of product residues to safe limits. Visible residue limit studies provide guidance for manufacturers on the minimum visible surface concentration of a specific product on a particular material of construction. Once this visually detectable threshold is established, it can be compared to health based exposure limits (calculated utilizing the PDE) to assess if appropriate visual inspection can prove that a piece of equipment is clean and safe to be used in a GMP process. In 1993, Fourman and Mullen suggested only 4 ug/cm2 as the visible residue limit of many materials used in pharmaceuticals. Subsequent studies brought this threshold below 1 ug/cm2. This shows the ability of visual inspection to detect product residues at very low concentrations. Moreover, the ability to visually detect very low surface residues encouraged some researchers to recommend visible residue limits as a replacement of chemical analysis. In 2018, EMA Q&A publication on health-based exposure limits and cross contamination justified the use of visual inspection as an alternative to analytical testing at each change over conditional that a documented risk assessment can prove that the visible residue limit is higher than the established health-based exposure limits. However, the determination of the visible residue limit is a problematic process. In the lab setting, it is possible to spike known quantities of product on the surface of a coupon then determine the minimum concentration that is visibly detectable. In manufacturing settings, many variables can affect the ability to visually detect certain residues in equipment. The solvent in use, surface material of construction, lighting condition, inspection distance, inspection angle, and the light color (light temperature). While in the lab, inspecting a soiled coupon can be a hassle-free, it is usually difficult to provide similar inspection condition to dirty manufacturing equipment or to specific parts of these equipment which brings the same question again, is visually clean = clean? from what we presented above, this can only be a valid assumption once a robust quality risk assessment has been completed based on the outcome of a controlled visible residue limit study. References G.L. Fourman and M.V. Mullen, "Determining Cleaning Validation Acceptance Limits for Pharmaceutical Manufacturing Operations," Pharm. Technol. 17 (4), 54–60 (1993). EMA Questions and answers on implementation of risk-based prevention of cross-contamination in production and ‘Guideline on setting health-based exposure limits for use in risk identification in the manufacture of different medicinal products in shared facilities’ 2018 R.J. Forsyth, V. Van Nostrand, and G. Martin, "Visible-Residue Limit for Cleaning Validation and its Potential Application in a Pharmaceutical Research Facility," Pharm. Technol. 28 (10), 58–72 (2004). K.M. Jenkins and A.J. Vanderwielen, "Cleaning Validation: An Overall Perspective," Pharm. Technol. 18 (4), 60–73 (1994).

One of the common debates that arises from time to time where continuous cleaning verification is adopted that why do we need cleaning validation if we test after each product change?! Cleaning validation refers to the process of providing a documented evidence that the cleaning process is capable of reducing the residue to safe limits effectively and consistently. Early US FDA guidelines on cleaning validation (e.g. guide to inspections validation of cleaning process in 1993) discouraged testing until clean practices where equipment are tested, resampled and retested until acceptable cleaning results are achieved. This was considered an indicator of cleaning ineffectiveness and that the cleaning method is not validated. Such practices were only allowed in rare cases (e.g. cleaning of clinical drugs where cleaning validation is not required) as the dependence on ineffective cleaning methods poses an unacceptable risk of cross contamination even with continuous cleaning verification (i.e. swabbing after each product change). Cleaning samples is an isolated time-point that was collected "hopefully" from the most difficult to clean spots of a piece of equipment. Considering that the swab to equipment surface area is significantly small ratio, it might not be a wise decision to rely solely on few sporadic cleaning swab results without considering the cleaning process design and the history of effective cleaning process that has been established through reproducible cleaning results of reasonably justified swab locations. Only a well crafted cleaning validation study can provide this evidence of robust cleaning process where routine cleaning verification adds another layer of confidence in the validity of equipment cleaning. Moreover, the nature of equipment staining is usually not homogenous i.e. residues are not equally distributed on the surfaces which limits the value of swab sampling even if the most difficult to clean locations were selected as the residue can still exist in easy to access and clean spots if the cleaning method is badly designed (e.g. inefficient spray ball). In contrast, repeatable and acceptable cleaning results in a cleaning validation study can prove the effectiveness of the cleaning process (three successful runs). However, someone can argue that while swab samples are limited to significantly small surface area, rinse samples can represent most of the equipment surface, hence no need for the cleaning validation. Rinse samples are indirect sampling technique that require two elements to prove effective cleaning: Recovery study so that the rinse solvent is able to recover the residues to acceptable percentage. Ensure that the rinse solvent will contact all product contact surface area. Both of the two conditions raises some challenges considering that as rinse sample lack the physical scrubbing effect provided by direct swabbing, usually rinses fail to recover the sticky residues and hence might not be the most accurate method to verify cleaning (depending on the nature of the expected residues). However, the confidence in the rinse results can be significantly improved in light of a successful cleaning validation study.