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Saturday, March 10, 2018

GMPs for Small-Molecule Drugs in Early Development: Workshop Summary-Part VI

geopaul/E+/getty images The International Consortium on Innovation and Quality in Pharmaceutical Development (IQ Consortium) is a technically focused organization of pharmaceutical and biotechnology companies with a mission of advancing science-based and scientifically driven standards and regulations for pharmaceutical and biotechnology products worldwide. In previous issues of Pharmaceutical Technology, papers written by the IQ Consortium’s GMPs in Early Development Working Group described the desire and rationale for more clear and consolidated recommendations for GMPs in early development (Phase I through Phase IIa) (1-5). In this paper, the IQ Consortium presents a summary of key analytical method validation, stability, and manufacturing discussions that were part of the IQ Consortium’s recent workshop, “Best Practices and Applications of GMPs for Small Molecule Drugs in Early Development,” which was based on these earlier papers. The workshop was held on Feb. 4–5, 2014 in Washington, D.C. Attendees included more than 70 analytical; formulation development; quality assurance; and chemistry, manufacturing, and controls (CMC) regulatory scientists, representing more than 20 companies and FDA.

Workshop presentations consisted of industry representatives summarizing the previously published IQ Consortium papers (2–5) as well as FDA representatives who spoke on the same topics. The breakout sessions were designed to stimulate deeper discussion on specific topics and sharing of best practices across the industry. The presentation materials and key messages from general presentation sessions and the related breakout sessions are available on the IQ Consortium website (6). Although there were no specific agreements reached, there were constructive discussions throughout the workshop.

A summary of the key discussions related to analytical method validation, stability, and manufacturing is outlined in the following sections. A summary of the key discussions related to specifications in early development will be the subject of a future article.

Analytical method validation in early development workshop output

Workshop discussions regarding method validation in early development focused on validation parameters for compound-specific methods and general methods, as well as industry terminology. There was general agreement with phase-appropriate method validations as outlined in the position paper (2) as long as sound scientific judgment is used. The group recognized that method validation is not a singular event performed to satisfy a regulatory requirement. Rather, validation should be thought of as an ongoing exercise that evolves every time the method is used. Although there was agreement that evaluating robustness and intermediate precision did not have to be part of the method validation process in early development, consensus on some other validation elements was not reached. Specifically, there was some discussion that, even though it is routinely evaluated by most companies, linearity may not be a critical parameter to evaluate in early development since the criteria are almost always easily met. In addition, there was discussion regarding whether the use of system suitability in lieu of a separate method-validation process could ensure that the method performance (e.g., linearity, precision, specificity, sensitivity, etc.) was suitable for the intended use.

There was considerable discussion during the presentations and breakout session regarding the terminology used to describe validation activities. Specifically, the apparent interchangeable use of “validation” and “qualification” was discussed. The lack of consistency in the terminology has led to unnecessary debate and confusion across the industry and in communications with regulatory authorities. Harmonization of clarifying terminology such as Stage 1 validation, Stage 2 validation, or fit-for-purpose (FFP) validation might provide greater clarification on the stage of validation.

Approaches for validating general methods, such as gas chromatography (GC) residual solvent, heavy metal, and compendial methods varied within the industry. In most cases, compendial methods are evaluated to determine suitability of use, but are not validated. However, some companies performed validation of FFP general methods (e.g., GC residual solvents) for each drug substance (DS) and/or drug product (DP) sample matrix as compound specific methods. In contrast, other companies validated these methods for each individual analyte (e.g., solvent or metal), but did not perform additional validation for every DS and/or DP matrix.

Drug product manufacturing in early development workshop output

Results from the 2011 survey on early development manufacturing practices (3) highlight two areas that could benefit from open discussion: batch documentation and change-control systems. There was consensus at the workshop that batch records and change-control systems need to be designed to accommodate manufacturing flexibility in early development. Feedback from participants indicated that many companies have implemented approaches that allow this flexibility. The following are some examples of these approaches as well as discussion notes:

Only providing process parameter ranges in batch records when sufficient process knowledge has been accumulated. This approach reduces the number of process “deviations” that need to be addressed during or after a campaign. While health authorities would like to see some targets/ranges specified, they are mainly interested in knowing that the manufacturer has adequate controls and knows what steps must be taken to assure high quality product for the clinic. It is important, however, to provide enough instruction in the batch record such that actual set points or values observed during processing are recorded and deviations from expected performance are clear.

Several companies are moving away from having the quality unit preapprove batch records. In the 2011 survey, 100% of the 10 companies that responded indicated that their quality units preapprove batch records. Since the survey, one company has removed the requirement for packaging operations. Another company performs daily, concurrent batch record review with the quality unit during campaigns and is in the process of removing the preapproval requirement from their quality system.

Change control approaches vary between companies, but there was agreement that systems in early development must be able to quickly address deviations and changes. Several companies manufacture externally and rely heavily on the CMO’s quality systems for documenting deviations. In cases where the CMO manufactures both early- and late-phase/commercial supplies, it is advantageous to track the deviations separately for corrective action and preventive action (CAPA) purposes. It was noted during discussion that direct and timely quality involvement in early development should be encouraged to ensure that potential manufacturing concerns are quickly captured and addressed or dismissed.

A second breakout session focused on the practices of extemporaneous preparations (EP). On-site formulation preparation is an effective means of preparing early clinical supplies. In addition to shorter timelines, advantages of this approach include: lower DS demand, reduced analytical method and stability support, flexibility to quickly adjust dosing in response to clinical data, and less resource demand. According to an IQ working group survey, approximately 80% of companies already have the capability to do EP. This approach, however, is only being used in approximately 20% of applicable applications. Full results from this IQ survey will be published separately. Some obstacles companies have faced in implementing EP include: access to sites that can handle hazardous compounds or complex formulations, interpretation of regulatory requirements and regulatory authority expectations, and internal resistance toward “non-traditional” approaches.

The breakout session included three short presentations covering the history of EP, regulatory requirements/strategies and case studies of successful on-site preparation of immediate- and controlled-release dosage units.

While the preparation of EP material might not take place in traditional GMP manufacturing areas, it remains crucial that appropriate controls are in place to ensure subject safety and to safeguard product quality. Participants at the workshop agreed that safety is top-priority and that this responsibility ultimately resides with the study sponsor. The sponsor quality unit should audit the compounding site. Industry participants discussed the importance of carrying out one or more practice preparations at the compounding site. Industry participants discussed the practice of testing during and after these mock runs and using these data to validate preparation instructions, potentially eliminating the need to perform end-product testing on the actual preparations that will be given to study subjects. This approach allows for rapid dosing and de-risks changes that may occur in the product while waiting for analytical testing results. If this approach is taken, it is still important to perform stability studies on the mock preparations to support a practical “use-period” for the product. FDA representatives did not provide comment, but referred to the FDA guidance on testing expectations (7).

The EP approach is not limited to simple powder-in-bottle or solution/parenteral preparations for ADME and absolute bioavailability. Companies have successfully used EP to study the effects of drug release rate on pharmacokinetics using controlled-release preparations. Case studies from on-site preparations of matrix tablets as well as osmotic capsules were presented. Results of these types of EP studies can be used to quickly answer questions about food effect, colonic absorption, or potential for reducing adverse events—while using only a small amount of DS.

There was considerable discussion during the breakout session about regulatory expectations and filing strategy. EP practices rely on standards of quality in a clinical pharmacy, which are governed by local laws and good clinical practices. Requirements for CMC submission vary country-to-country. For Singapore studies, no CMC information is typically provided to the Health Sciences Authority (HSA). Instead, someone from the HSA will visit the clinic or pharmacy to inspect preparation activities. For US studies, section P.3.3 of the investigational new drug (IND) application should include all of the key preparation steps and controls. It was noted that in Europe, all compounding pharmacies are cGMP compliant, and EP are released by a qualified person (QP). From a submission perspective, most companies treat EP clinical studies as “Phase I” even if the active ingredient itself is in later development or commercially available. The studies are short in duration, are closely monitored, and often use low or sub-therapeutic doses. The EP studies are also often the first time that a formulation has been evaluated, and usually do not represent the intended Phase III or commercial product.

Stability in early development workshop output

Presentations and breakout sessions on stability in early development followed the elements and recommendations of the IQ paper on the subject (4). Some participants acknowledged that the industry may be currently performing a lot of non-value-added stability studies, and that most of the resistance to reducing stability testing comes from within the companies rather than from regulatory authorities. It was pointed out that companies should focus on accumulating product/process knowledge and use risk assessment to design only necessary stability studies, while being mindful of regulatory environments.

Strategies in leveraging solid stress testing for drug substance and simple drug products like PiB (Powder in Bottle) and PiC (Powder in Capsule) were discussed. This practice is typically applied to stable and moderately stable DS, which is usually stressed at 70°C/75%RH for up to three weeks and at the 1X International Conference on Harmonization (ICH) Q1B photostability testing condition. Open containers to simulate the bulk (DS) least-protective packaging configuration are typically used, although some companies also stress the DS in closed containers to simulate packaged PiB and PiC configurations. Usually an initial DS retest period and an initial DP shelf life can be extrapolated to 15 months at 25 °C, with a range of 1218 months depending on companies’ internal policies and risk tolerance. The assigned retest period and shelf life (called “use period” for brevity) is then verified with reduced ICH long-term and accelerated stability testing of a “representative batch.” With this approach, one company has achieved seven successful clinical trial application (CTA)/IND submissions with an EU country and FDA.

Companies also shared their experiences in using the software ASAPprime, an Accelerated Stability Assessment Program (ASAP) modeling software, to enable rapid stability evaluations in early development. Employing several combinations of temperature and humidity conditions, ASAP is typically used to evaluate the chemical stability and thus to extrapolate a use period of DS and formulated DP. This model is also commonly used to assess the potential impact of packaging changes on material stability. Depending on the model data, it is possible to change to a less protective packaging without having to repeat stability testing. Physical changes are harder to predict with ASAP. Two companies have included ASAP stability data in regulatory filings with FDA and some EU countries. One company noted that some EU countries have expressed discomfort with ASAP-based extrapolation.

How stability data from representative batches of DS or DP are used differed among companies. Most companies use a non-GMP representative batch of DS or DP to get a more rapid assessment of the material’s stability. How stability studies are performed on the first GMP batch, however, varies across the industry. In some cases, when a representative non-GMP batch is placed on stability, GMP batches may be placed into stability chambers without testing. This approach would make the GMP materials on stability available for testing when there is a need to respond to regulatory queries, or if further development information gathered suggests that the batch is, in fact, not similar to the representative batch. Other companies conduct ICH long-term and accelerated-stability studies on the first GMP batches to use those batches as the stability representative batches.

It was also noted that while changes to DS or DP processes may affect the quality of a new batch, they may not affect its stability. When changes to processes or materials are made, any potential changes to the stability-related quality attributes should be considered to determine if stability studies are warranted for the new material. This is commonly done using a stability risk assessment (RA). In general, companies use RAs to make stability-testing decisions for new batches of DS and DP after changes. The formality of the procedures used to follow and capture RAs varies across the industry. RAs tend to be less formal for early-stage development and more formal for late-stage development.

Acknowledgements

The authors thank Linda Ng, Stephen Miller, Mahesh Ramanadham, and Ramesh Sood from FDA for their participation and contributions to the workshop and this summary.

References

1. A. Eylath et al., Pharm. Technol. 36 (6) 54-58 (2012).
2. D. Chambers et al., Pharm. Technol. 36 (7) 76-84 (2012).
3. R. Creekmore et al., Pharm. Technol. 36 (8) 56-61 (2012).
4. B. Acken et al., Pharm. Technol. 36 (9) 64-70 (2012).
5. M. Coutant et al., Pharm. Technol. 36 (10) 86-94 (2012).
6. www.iqconsortium.org
7. FDA, Guidance for Industry: cGMP for Phase 1 Investigational Drugs (CDER, July 2008).

About the Authors

Q. Chan Li, senior principal scientist, Boehringer Ingelheim
Jackson D. Pellett, scientist, Genentech
Michael Szulc, principal scientist, Biogen-Idec
Mark D. Trone, director, Alkermes
Kirby Wong-Moon, principal scientist, Amgen

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Downstream Processing: A Revalidation Study of Viral Clearance in the Purification of Monoclonal Antibody CB.Hep-1

ABSTRACT

This article revalidates the effectiveness of affinity chromatography, matrix sanitization, and storage procedures used in monoclonal antibody CB.Hep-1 purification to remove and inactivate viruses after process scale-up. The scale up of the CB.Hep-1 purification process demonstrated a similar removal factor for enveloped and nonenveloped viruses compared to the initial validation study. The HSV-1, HIV-1, and CPV viruses were sensitive to incubation with ethanol at 70% concentration (3.0–4.6 Logs). We found that 0.1N HCl is a robust chemical agent able to inactivate >6.13 Logs of nonenveloped high resistance viruses while ethanol at 20% concentration inactivated 3.7 Logs of enveloped viruses HSV-1 and HIV-1 but was unable to inactivate nonenveloped viruses HPV-1 and CPV.

Monoclonal antibodies (MAbs) are employed as immunoligands in the purification processes of biopharmaceutical products.^1,2 Virus transmission poses a high potential risk for patients who must be treated with these biopharmaceuticals, if MAbs come from human or animal sources.^3,4 It is necessary to validate the purification process capacity to remove and inactivate any potential viral contaminant.^5,6
Regardless of extreme virus controls, several instances of biological contamination have occurred. Research on virus contamination sources have shown that viruses can be introduced into the manufacturing process in different ways, illustrating the importance of viral clearance studies to guarantee the biopharmaceutical product safety.⁷

Acronym List

Validation of the purification method plays an essential role in establishing biological product safety, especially when there is a high risk for the source to be contaminated with known human pathogenic viruses. Since several contamination instances have occurred with agents whose presence was not known, validation also provides a high degree of confidence that these agents may also be removed.⁸

FDA defines validation as, "Establishing documented evidence, which provides a high degree of assurance that a specific process will consistently produce a product meeting its pre-determined specifications and quality attributes".⁹ The rationale is that if more effort is placed on validation at the beginning, then there will be less chance for failure during product life.¹⁰

Validation studies for purifications proceses involve the deliberate addition of a virus to one or more purification steps to measure the extent of its removal and inactivation capacity. It is not necessary to validate all purification steps, but only those that could contribute to virus removal or inactivation. To prevent the deliberate introduction of viruses into the manufacturing process, the validation studies should be done in a separate facility and in a scaled-down version of the manufacturing process. Validation at the small scale is an efficient way to perform viral clearance validation studies.¹¹

GENERAL PROCEDURE FOR VALIDATION

CB.Hep-1 MAb is a mouse IgG-2b, specific for HbsAg.¹² This MAb is used as an immunoligand in the antigen-purification process, which is one step in the manufacturing of the Hepatitis B vaccine for human use.^13,14 The main aim of our work was to investigate if the affinity chromatography used routinely in the purification of CB.Hep-1 shows the same virus removal factor after a scale-up process. We measured the virus inactivation factor of the column sanitization protocol using 70% ethanol and the matrix storage conditions in 20% ethanol. We also evaluated the column sanitization protocol with 0.1 N HCl to increase the inactivation factor for high resistance non-enveloped viruses.

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Validating Analytical Methods for Biopharmaceuticals, Part 1: Development and Optimization

Regulatory guidance documents are written by committees, resulting in statements that are both exact and generic. Meeting regulatory requirements involves not only interpreting these documents correctly but also addressing their omissions. This article provides practical guidance on issues that are not thoroughly covered by current guidance documents regarding validation of analytical methods for biopharmaceuticals.

Figure 1: Process Map of Analytical Method Development and Validation

Four of the key regulatory guidance documents on methods validation state, "Methods validation is the process of demonstrating that analytical procedures are suitable for their intended use."^1-4 We have all read, and likely used, this phrase many times when summarizing method-validation results. However, according to Muire-Sluis, development scientists often point out that "validated methods may not be valid."⁵ The question therefore arises, what exactly makes a validated method valid? According to CBER, "the acceptability of analytical data corresponds directly to the criteria used to validate the method."⁴

We can generate evidence for the validity of analytical data in the formal method-validation program where all critical parameters are extensively tested under a detailed protocol that includes scientifically justified and logical step-by-step experimental approaches. All planned data sets must fall within pre-established protocol acceptance criteria (limits). These criteria should be derived from and justified in relation to historical data and product specifications. Once evidence for all critical elements is provided, the validated method will become the official, licensed procedure for that particular product and process step, and it will then support production and product release. The relationship between "valid" or "suitable and validated" is often overlooked, but there is a high price when "validated" test systems are simply inappropriate.

Incentives to replace existing licensed test procedures may come from regulatory agencies, or they could be motivated by potential cost savings, ease of use (automation), and the opportunity to generate more accurate and reliable results.

The International Conference on Harmonisation (ICH)'s Q2A and Q2B^1,2 and the United States Pharmacopoeia's USP 27 <1225>⁶ should be used for basic guidance. However, following just these guidelines will not necessarily produce a "valid" method and may not provide sufficient evidence that this method is suitable for product release. FDA provides guidance on some of the scientific issues that are not covered by Q2A and Q2B or USP 27.^3,4,6

Process Map. A process map showing the recommended steps for the selection, development, validation, and potential transfer of analytical methods, illustrating all functional responsibilities was developed. Frequently, larger companies have separate functional units for method development, validation, and testing. The process flow in Figure 1 describes an ideal sequence of steps for better analytical method validation (AMV).

The rigorous standards suggested here are ideal, but they are not necessarily required or followed during method development. Methods can be developed without strict adherence to GMP regulations if adequate documentation systems are used.

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FDA's Draft Guidance for Process Validation: Can It Be Applied Universally?

In November 2008, the US Food and Drug Administration issued Draft Guidance for Industry—Process Validation: General Principles and Practices (1). The guidance outlines regulatory expectations for process validation following a "life-cycle concept" that describes a "cradle-to-grave" approach for validating pharmaceutical processes (2). The life-cycle approach builds upon the results of experimental activities during development to define operating parameters and product specifications that are used in initial and ongoing process qualification. The life-cycle concept provides a robust means for the development, manufacture, and control of pharmaceutical products.

The guidance document covers validation largely at a conceptual level and avoids narrow precepts and specific examples. This approach is appropriate because the document addresses the subject from active pharmaceutical ingredient (API) production (by either chemical synthesis or biological processes) through drug-product production for all pharmaceutical dosage forms. The intended breadth of coverage embraces a myriad of unit operations in the preparation and manufacture of these products. Unstated is whether the draft guidance is intended to be applied to supportive processes that are not an inherent part of the formulation process. Among the support processes are cleaning, inspection, sterilization, and aseptic processing. Each of these processes can be an essential part of pharmaceutical manufacture that requires validation.

Basics of the draft guidance

The draft guidance recommends a defined and structured approach for process-validation activities within an organization. During the design and development stage, experiments should define the relationship between the independent process parameters and the dependent product attributes. These studies should be conducted in a predefined manner, and the results should be documented for later reference. The goal of process development is the attainment of knowledge regarding the process–product relationships to support later commercial production. The greater the knowledge accumulated at this early period, the more assurance the firm will have that it can successfully launch and maintain the process at a commercial scale. From a compliance perspective, this approach makes excellent sense; the knowledge gained during preclinical and clinical-stage experimentation provides a way to link clinical data obtained at the smaller scales with data from the later production process. A well-developed process is one for which the critical process parameters have been identified and control ranges for each have been established (3). The development experiments should evaluate the interaction between the independent and dependent variables until the results of the process are predictable and routinely acceptable. Multifactorial experiments can assess the relationships between the variables and build knowledge about the process's limitations. The experiments performed at a smaller scale establish the acceptable ranges for the various independent process parameters. Thus, when the process is operated under the appropriate conditions, operators have substantially greater confidence that the desired quality attributes of the product will be realized. The acceptability of the end result is ascertained using samples of the completed materials.

Initial and ongoing qualification of production processes are the means for establishing and confirming the experimental experience at significantly larger scales of operation. Knowledge gleaned from the development simplifies later activities. Production processes are always operated within the defined operating ranges because there is no reason to experiment with conditions at the extreme ends of the ranges on this larger scale. Challenges during these stages are primarily in the number of tests performed on the produced materials. Qualification lots are customarily sampled at a substantially higher rate than are routine production lots, and testing of these expanded samples is the challenge of the commercial process. The guidance recommends using appropriate statistical tools in the full-scale qualification efforts to provide the desired confidence in process and product acceptability and thus attain the desired validated state. The expectations for statistical evidence in process validation are well founded; sampling batches at the modest levels associated with pharmacopeial tests provide little, if any, proof of end-product quality. Although those tests may be legally binding, they have only limited value. Industry has largely ignored the levels of "real quality" needed to support its claims for patient welfare (4).

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Keep It Clean | Pharmaceutical Technology

Cleaning and Cleaning Validation—Volume 1, Paul Pluta, Ed., PDA, Bethesda, MD, 2009, 470 pp., ISBN: 978-1933722375

Cleaning and Cleaning Validation–Volume 1 is presented as an all-inclusive reference manual for cleaning-validation. The editor's goal is ambitious, and the result is impressive. This book covers the gamut of cleaning-validation topics in substantial detail, thus helping to equip the reader with a single source of general scientific understanding. It is the first and most general in a series of volumes detailing "current knowledge and approaches to cleaning and validation of cleaning processes," as editor Paul Pluta states in the introduction. Subsequent volumes will offer increasingly detailed, specific information, and the series will aim "to address three fundamental questions of cleaning and cleaning validation: why, what and how," according to Pluta.

The book is logically arranged into four major sections that cover cleaning-validation basics, cleaning chemistry and engineering, residues, and specific residues for cleaning. This organization allows readers to find specific information and related topics.

The book's first section lays a strong framework for its subsequent sections. It first provides insight into process validation in general, and then into cleaning validation in particular. The text details regulatory standards and companies' cleaning-validation policies, and offers guidance for the development of a cleaning-validation master plan. The section's detailed information should prove informative, regardless of the reader's experience level in cleaning validation.

A particularly strong inclusion is a chapter on a quality-by-design template for the development of an efficient and effective cleaning program. A cleaning program can be designed to achieve performance requirements consistently by identifying worst-case operating conditions through small-scale characterization studies, and transferring the knowledge obtained to the full-scale cleaning process. The quality-by-design approach uses a strong scientific rationale to build quality into a cleaning-validation program. The approach, therefore, could significantly enhance the program's robustness and capability.

In the second section, readers will find a brief treatise on cleaning-agent chemistry and mechanisms. In addition to providing a basic understanding of various cleaning agents, this section could help readers choose the most appropriate cleaning agent for their equipment and its materials of construction, thereby optimizing their cleaning effectiveness and consistency. This section is relatively short, but it discusses all key considerations for cleaning-agent selection properly.

The book passes from the general to the specific in its third section, which offers much more detail. Various passages explore residues and residue-grouping strategies, and also present an in-depth discussion of visual cleanliness and its employment in cleaning programs. The discussion of microbial and endotoxin residue helps readers understand regulatory requirements and technical issues associated with the microbial aspects of cleaning validation.

The final section features interesting insights into removing specific residues. For example, the section discusses biotech residues in depth, providing basic biologics and a case study. The section also examines manual cleaning processes and procedures, which are common in the pharmaceutical industry. It is important to understand and control the variability associated with manual cleaning to ensure the quality of a cleaning-validation program.

One of this book's outstanding strengths is its list of contributors, which includes a range of experts in various cleaning-validation disciplines. Individual parts of the book were written by respected academics, product manufacturers, detergent manufacturers, consultants, and regulatory investigators, and their contributions provide a balanced and comprehensive perspective. Each author has many years of experience in his or her field, and most are previously published subject-matter experts.

Cleaning and Cleaning Validation–Volume 1 is a comprehensive general text that would make a great stand-alone reference manual for cleaning validation. Most chapters include many references to current literature, regulatory guidelines, and requirements for cleaning-process validation. Practical information and case-study examples throughout the chapters reinforce the book's technical discussions. This book is a valuable resource for employees involved in developing pharmaceutical cleaning-validation programs.

Richard Hwang, PhD, is senior director of pharmaceutical sciences at Pfizer Worldwide R&D, Eastern Point Rd., Groton, CT 06340, tel. 860.715.0296, fax 860.686.8198, [email protected]
. He is also a member of Pharmaceutical Technology's editorial advisory board.

Jack N. Duranto is principal pharmaceutical scientist at Pfizer Worldwide R&D.

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Radiation Sterilization of Parenterals | Pharmaceutical Technology

Drug makers have sterilized pharmaceuticals by gamma irradiation for more than 40 years. High-energy gamma irradiation is used mainly in the healthcare industries to sterilize disposable medical devices. Over the years, however, the number of radiation-sterilized pharmaceuticals has gradually increased. Pharmaceutical companies now radiation sterilize drugs such as ophthalmic preparations, topical ointments, veterinary products, and parenterals. Regulatory pressure to adopt terminal-sterilization processes has promoted radiation sterilization.

Radiation sterilization may be performed using either gamma rays from a radioisotope source (usually cobalt-60) or electron-beam or X-ray irradiation. Gamma-ray irradiation, however, is by far the more common method.

Like all methods of sterilization, irradiation involves a compromise between inactivation of the contaminating microorganisms and damage to the product being sterilized. The imparted energy, in the form of gamma photons or electrons, does not always differentiate between molecules of the contaminating microorganism and those of the pharmaceutical substrate.

The interaction between high-energy gamma radiation and matter forms ion pairs by ejecting electrons, leading to free-radical formation and excitation. The free radicals are extremely reactive because each has an unpaired electron on one of its outer orbitals. Free-radical reactions may involve gas liberation, double-bond formation and scission, exchange reactions, electron migration, and cross-linking. In fact, any chemical bond may be broken and any potential chemical reaction may take place. In crystalline materials, this may result in vacancies, interstitial atoms, collisions, thermal spurs, and ionizing effects. Polymerization is a particularly common result in unsaturated compounds. In microorganisms, radiation-induced damage may express itself in various biological changes that may lead to cell death. Although DNA generally is considered the major subject of cellular damage, membrane damage also may contribute significantly to reproductive-cell death. In solutions, a molecule may receive energy directly from the incident radiation (the "direct effect") or, in aqueous solutions such as parenterals, by the transfer of energy from the radiolysis products of water (e.g., hydrogen and hydroxyl radicals and the hydrated electron) to the solute molecule (the "indirect effect"). In dilute solutions, most of the energy is imparted to the water, as is the case with many parenteral solutions. The indirect radiation effect therefore would account for most of the resulting possible radiation damage.

The process of radiation-induced damage by electrons is similar to that for gamma photons. In electron irradiation, the high-energy electrons produced outside the target molecule ionize the molecular species as they pass through the medium and release their energy. The ionization process leads to the production of secondary electrons with a range of energies capable of breaking bonds in the medium near the ionization event. The high-energy electrons usually are produced either by accelerating them across a large drop in potential in a direct-current machine or by a linear or circular electron accelerator.

X-rays are electromagnetic photons emitted when high-energy electrons strike any material. X-rays therefore can be produced by an electron accelerator. X-ray sterilization is not as fast as electron-beam irradiation. Since electron-beam and X-ray machines are powered electrically, the handling, shipping, and disposal of radioisotopes is not necessary. A disadvantage of electron-beam irradiation is its low penetration power, although more modern machines have overcome this problem. X-ray machines may penetrate even more than gamma-ray machines.

The chapters about gamma-radiation and electron-beam sterilization in the Encyclopedia of Pharmaceutical Technology contain general reviews of radiation sterilization (1, 2).

Contract sterilizers usually perform irradiation (1, 3). Though the contract sterilizer usually assumes many process-validation duties, the drug manufacturer bears final responsibility for the product's sterility. The contract sterilizer essentially is responsible for guaranteeing the delivered radiation dose.

The effect of radiation on pharmaceuticals

Any processing such as sterilization in the manufacture of a pharmaceutical product must cause minimal degradation. This requirement applies to radiation processing. Data on the feasibility of irradiating final pharmaceutical products (parenteral products in particular), active ingredients, or excipients can be obtained from the scientific literature. Reviews on the effects of gamma and electron-beam irradiation are readily available (4–17). Although many of the cited investigations offer only a superficial examination of the irradiated drugs, the reported data give useful insights into the overall radiation stability of these products and indicate whether more extensive testing of the products should be undertaken.

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Correlation of Visible-Residue Limits with Swab Results for Cleaning Validation

The use of visual inspection as a criterion for equipment cleanliness has always been a component of cleaning validation programs. Mendenhall proposed the use of only visual examination to determine equipment cleanliness as long ago as 1989 (1). He concluded that visible cleanliness criteria were more rigid than quantitative calculations and clearly adequate. The US Food and Drug Administration limited the use of visually clean criterion between lots of the same product (2). LeBlanc raised the question of whether a visible limit as the sole acceptance criterion could be justified (3).

A visible-residue limit (VRL) currently is used in a clinical pilot plant for the introduction of new compounds (4, 5) in cases for which the VRL is lower than the acceptable-residue limit (ARL). The ARL is the amount of a formulation component that can be carried over to the next formulation with no pharmacological or adulteration concerns. The initial use of an active pharmaceutical ingredient (API) in the facility is followed by cleaning and a visual inspection against the previously determined VRL. Visually clean equipment means the current cleaning procedure is effective and the new API is not a new worst case that would require cleaning validation.

The same scientific rationale supports the use of VRLs in a manufacturing facility. The main difference between pilot plant and commercial manufacturing facilities is equipment size. Acceptable viewing parameters for the larger manufacturing equipment, including distance, viewing angle, and light level, consistently detect VRLs for several marketed formulations (6).

The implementation of VRLs in the pilot plant and their potential use in the manufacturing facility were additions to established cleaning programs. The cleaning programs in both the pilot plant and manufacturing facilities established validation based on swab sample data using high-performance liquid chromatography (HPLC) for analysis. Visual inspections were part of the validation, but were qualitative determinations only.

It should be possible to demonstrate the correlation between the quantitatively determined VRL of either the API or formulation on the manufacturing equipment and the analytically determined swab recovery data. The data from the two determinations should be mutually supportive as part of a cleaning process validation. Therefore, a retroactive analysis of the pilot-plant validation study compared the previously obtained swab results with the more recently generated VRLs for the subject compounds.

In addition, a current cleaning validation study conducted in a clinical packaging area included VRL as an integral part of the study. The study used documented worst-case formulations to soil the equipment, followed by cleaning according to a standard operating procedure. Visual inspection used experimentally determined VRLs. Swab samples for the appropriate compound confirmed the equipment's cleanliness. Testing for each formulation was repeated twice to validate the cleaning procedure. The final report includes a comparison between the VRLs and the swab sample results.

Although the cleaning validation passed testing (i.e., all swab results were lower than the ARL), the swab results for several metformin samples assayed higher than the experimentally determined VRL. An investigation reconciled the discrepancy.

Retrospective analysis

The cleaning-validation study for the pilot plant selected worst-case formulations. One formulation was validated for a dry-granulation equipment train and another for the wet-granulation process. Each piece of cleaned equipment was visually inspected before swab testing and both formulations were tested three times for validation.

The compounds tested were simvastatin and rofecoxib (Whitehouse Station, NJ, Merck & Co., Inc.). Four observers viewed dried solution spots of known concentrations to determine the VRLs. The experimentally derived VRLs for the compounds were 0.485 and 0.871 μg/cm² , respectively (4). For a swab area of 25 cm² , the limits were 12.1 and 21.8 μg/swab. The VRLs for the base and neutral detergents used to clean the equipment were <0.37 and <0.56 μg/cm² (<9.3 and <14 μg/swab).

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Scaling Down of Biopharmaceutical Unit Operations — Part 1: Fermentation

The fermentation process can be challenging to scale down and several factors must be evaluated for each step.

Mar 01, 2005

BioPharm International

Volume 18, Issue 3

Anurag Rathore

Creation and qualification of scale-down models are essential for performing several critical activities that support process validation and commercial manufacturing. As shown in Figure 1, these activities include process characterization and production support studies that are performed to evaluate column and membrane lifetimes, demonstrate clearance of host-cell impurities and viruses, and troubleshoot manufacturing issues. While the underlying fundamentals are relatively the same as those when scaling up, some unique considerations should be taken when scaling unit operations down.^1-4 The goal when scaling down is to create a small-scale or lab-scale system that mimics the performance of its large-scale (pilot or manufacturing) counterpart, when both the process parameters are varied within their operating ranges and also when a process parameter deviates outside its operating range. Before it can be used for lab studies, the scale-down model needs to be qualified and its equivalence to large-scale examined. Data from an inaccurate scale-down model could result in conclusions that may not be applicable to large-scale, resulting in an unsuccessful process-validation campaign or continued lot failures in a manufacturing campaign.

This article is divided into two segments. The first part focuses on an upstream unit operation — fermentation. The next segment will cover two downstream unit operations — chromatography and filtration. The combined article is the fifth in the "Elements of Biopharmaceutical Production" series.

Figure 1. Scale-down Models are Best Utilized for Process Characterization and Production Support

HARDWARE SCALE-DOWN GUIDELINES
Fermentation processes often involve several scales of operation, encompassing inoculum development, seed expansion, and production fermentation. The differences in volumes between the steps in a single fermentation process can be 10X to 100X for the pilot scale, and 1,000 to 100,000X for the production scale. This may cause the fermentation processes to be challenging to scale down and the specific process parameters, vessel geometries, and operational control strategies must be evaluated for each step. Some general guidelines to consider in developing a representative scale-down model follow.

Practitioners use the terms "similar reactor" or "similar vessel geometries" to describe optimal conditions for a scale-down strategy. However, similarity in vessel geometry does not necessarily imply identical systems, although this would be the most attractive option. Instead, geometric similarity means that the overall aspect ratios of each vessel (small vs. large) are close enough to not impact performance. More importantly, the impeller and sparger designs and placements within the vessel are nearly identical.

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Technology Improvements Drive Capacity Gains for Biologics Fill/Finish

Until recently, the handling of sterile liquids in the pharmaceutical industry has relied on decades-old techniques and technologies. During the past 10 years, however, biologics have taken a prominent role in the drug-development pipeline. The value of these drugs, sometimes measured in tens of thousands of dollars per dose, has put greater pressure on biologics downstream fill and finish operations. The increased scrutiny from regulators and the greater product value have initiated industry improvements so that quality, safety, and cost-efficiency remain high at this crucial late stage in manufacturing.

BioPlan recently prepared a white paper identifying trends among in-house fill and finish operations for recombinant therapeutics (1). This research excluded outsourced operations and CMOs. BioPlan found significant differences between industry capacity and capacity use for these large-molecule facilities, compared with the constraints currently being experienced in small-molecule fill and finish, which have in some cases even led to drug shortages at the hospital level.

In biologics in-house operations, BioPlan found trends that include the increased use of isolator technologies, more high-speed operations, and other innovative approaches. Findings regarding capacity use indicate that in-house manufacturers, on average, continue to have additional available fill-and-finish vialing, pre-filled device, and lyophilization capacity:

Utilization averaged 55% for lyophilization

58% for pre-filled devices

70% for vialing.

At present, there is sufficient capacity, even without adding shifts or additional equipment. This finding is in contrast to the situation with small molecules, where some facilities are working at near-capacity, and facility consolidation, regulatory actions, closures, and the use of less efficient legacy equipment have created bottlenecks and even serious drug shortages at the hospital level.

The state of in-house fill/finish capacity
BioPlan’s in-house biologics fill/finish market analysis evaluated the capacity for recombinant biologics and compiled information from 89 candidate facilities in the US and Europe. More than 50 industry participants were surveyed at facilities, equipment suppliers, and consulting groups.

Regarding vialing, capacity utilization averaged 70%; this figure represents the average for biopharmaceutical in-house manufacturers, which generally produce at most a few products at each facility. While this indicates that a relatively large flex or expansion vialing capacity may be available among current primary manufacturers, in-house facilities are not designed for, nor are they capable of, running at maximum capacity, due to down-time, maintenance, and cleaning/validation.

For pre-filled devices and syringes (PFS), an even greater amount of flex capacity was found. Pre-filled syringe and cartridges fill-finish capacity averaged 6.75 million per shift; the average PFS fill/finish capacity utilization was 55%, suggesting considerable expansion capacity potential among those facilities doing in-house PFS fill-finish.

Finally, with regards to lyophilization capacity, which averaged 760 square feet among those facilities with these data available, utilization averaged 58%, again indicating room for expanding manufacturing output.

Overall, the largest scale manufacturing operations tend to be concentrated among just a few companies, with this the case for in-house fill/finish. Most of those largest-capacity facilities are based in Europe.

Activities outsourced by biomanufacturers
Although BioPlan’s white paper analysis focused on in-house fill-finish capacity, other BioPlan research found that eight in 10 biopharmaceutical manufacturers worldwide outsource at least some fill/finish operations today, up from 6 in 10 in 2010 (2). In fact, fill/finish operations are one of the most commonly outsourced activities, behind only toxicity testing (86.8% outsourcing to some degree) and analytical testing of other bioassays (89% outsourcing).

The results of BioPlan’s annual report also show that, in volume terms, fill/finish operations are one of the most heavily outsourced activities: Respondents estimated outsourcing (on average) 37.9% of the fill/finish operations at their facilities, ahead of areas like toxicity testing (35.4%) and validation services (19.9%) (see Figure 1).

Figure 1: Top five activities outsourced to some degree by biomanufacturers.

Available in-house capacity implications
The excess capacity available to in-house manufacturers of biologics may allow expansion of in-house fill/finish operations without adding shifts or equipment. Capacity, however, is commonly misrepresented as being related to machine speed or lyophilizer chamber capacity in vials. In-house fill/finish operators also note that equipment turnaround time, cleaning, and sterilization (in situ and ex situ) also need to be considered when calculating efficiencies. In this analysis, capacity utilization was defined as the “typical estimated usage of fill/finish capacity per shift”/“maximum capacity per shift”, using current number of shifts, and production equipment. As noted, a facility could significantly increase capacity by adding shifts, if needed.

Future trends
The fill/finish industry will likely depend on ramp-up of technologies and capabilities both in-house and at CMOs. Future trends will include:

Fill and finish CMOs are becoming larger, through mergers and acquisitions.

CMOs will continue to install state-of-the-art fill/finish equipment, mostly to support clinical manufacturing. Biopharmaceutical CMOs will do less sub-contracting of their fill and finish to specialized CMOs.

Fill-Finish CMOs in India and rapidly developing countries are handling increasing amounts of biopharmaceutical products, mostly for domestic and lesser-regulated international commerce.

Conclusion
In-house biologics fill/finish operations are unique from contract manufacturers’ business strategies. In addition, comparing small molecule in-house vs large molecule/recombinant biologics leads to significantly different conclusions. The lower capacity use rates for biologics can be partly explained by the more recent installation of higher technology equipment, RABS/isolators, and automation. The effect of end-product value is likely also a factor.

Newer technology adoption will impact utilization rates at both in-house and outsourced service providers (CMOs) as legacy equipment is replaced; however, this area requires further research. Fill/finish operations represent one of the top activities projected to be outsourced at significantly greater levels in the future. In fact, nearly 28% of global industry respondents to BioPlan’s annual study indicate they will be outsourcing more of their fill/finish projects over the next 24 months.

Decisions in this area are likely to be based on efficiency, cost effectiveness, and capacity availability as the industry makes critical in-house vs outsource decisions. For CMOs to compete for fill/finish business, data indicate that it’s increasingly important that they position themselves as having state-of-the art equipment, especially in fill/finish services.

References
1. BioPlan Associates, Trends in Aseptic Bioprocessing Capacity for the Fill and Finish of Recombinant Biologics: An Analysis of US and European In-house Capacity and Capacity Utilization (BioPlan Associates, December 2014).
2. BioPlan Associates, 11th Annual Report and Survey of Biopharmaceutical Manufacturing Capacity and Production (Rockville, MD, April 2014), www.bioplanassociates.com/11th.

Article Details
Pharmaceutical Technology
Vol. 39, Issue 1
Pages: 66-68
Citation: When referring to this article, please cite it as E. Langer, "Fill/Finish Capacity Use for Biologics," Pharmaceutical Technology 39 (1) 2015.

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FDA Publishes Revised Process-Validation Guidance

FDA published its long-awaited guidance titled Process Validation: General Principles and Practices this week. The document, which revises and replaces the 1987 guidance titled Guideline on General Principles of Process Validation, explains the components of process validation for the manufacture of human and animal drug and biological products, including active pharmaceutical ingredients. The guidance emphasizes the importance of risk-based decision making and recommends that the degree of control over attributes be commensurate with their risk to the process or output.

The new guidance categorizes process-validation activities into three stages.
During Stage 1, process design, a company defines the commercial process based on what it has learned throughout development and scale-up activities. The document recommends that companies use design-of-experiment studies and risk-analysis tools to understand process variables. In Stage 1, a company should develop strategies to control processes by reducing the variation of inputs, adjusting equipment to compensate for input variation, or both tactics. Process design must be based in science, and decisions about design should be documented, according to the guidance.

During Stage 2, process qualification, a company should evaluate its process design. This evaluation should include an examination of the facility and the qualification of equipment and utilities, according to the guidance. In addition, personnel should carry out process-performance qualification (PPQ) to confirm the process design and demonstrate that the commercial manufacturing process performs as expected. “The approach to PPQ should be based on sound science and the manufacturer’s overall level of product and process understanding and demonstrable control,” according to the document. PPQ requires a written protocol that describes items, such as manufacturing conditions, data to be collected, tests to be performed, and the sampling plan. The ultimate decision to begin commercial distribution should be supported by data from commercial-scale batches, according to the guidance.

Stage 3, continued process verification, provides ongoing assurance during routine production that the process remains in a state of control. This goal requires a system for detecting deviations from the process. “Adherence to the CGMP [current good manufacturing practice] requirements, specifically, the collection and evaluation of information and data about the performance of the process, will allow detection of undesired process variability” and help personnel determine whether action must be taken to correct, anticipate, and prevent problems so that the process remains in control, according to the guidance.

During this stage, a company should establish an ongoing program to collect and analyze product and process data that relate to product quality. Trained personnel should statistically trend and review the data, and the information collected should verify that the quality attributes are appropriately controlled throughout the process, according to the guidance.

See related Pharm Tech articles:

The Importance of Equivalence in the Execution and Maintenance of Validation Activities (Pharm Tech)

The New FDA Process Validation Guideline (Pharm Tech)

Is FDA's Draft Process-Validation Guidance a Mixed Blessing? (Equipment & Processing Report)

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Fill/Finish Capacity Use for Biologics

Utilization averaged 55% for lyophilization

58% for pre-filled devices

70% for vialing.

Figure 1: Top five activities outsourced to some degree by biomanufacturers.

Future trends
The fill/finish industry will likely depend on ramp-up of technologies and capabilities both in-house and at CMOs. Future trends will include:

Fill and finish CMOs are becoming larger, through mergers and acquisitions.

CMOs will continue to install state-of-the-art fill/finish equipment, mostly to support clinical manufacturing. Biopharmaceutical CMOs will do less sub-contracting of their fill and finish to specialized CMOs.

Fill-Finish CMOs in India and rapidly developing countries are handling increasing amounts of biopharmaceutical products, mostly for domestic and lesser-regulated international commerce.

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Is FDA's Draft Process-Validation Guidance a Mixed Blessing?

The US Food and Drug Administration’s Draft Guidance for Industry—Process Validation: General Principles and Practices provides a life-cycle approach for validating pharmaceutical processes and aims to help pharmaceutical companies achieve consistently high product quality. The document includes several concepts that are familiar to the industry but also contains ambiguities and recommendations that might be difficult for some drugmakers to follow.

The draft guidance suggests manufacturers establish links from their clinical process to their commercial-manufacturing process. This approach is similar to the one FDA has used in its preapproval inspections. If the guidance becomes final as it currently stands, manufacturers may be expected to use the data that they gain during formulation and development to define a product’s critical attributes, which would be the basis for the manufacturing-process parameters.

The agency points out that development and formulation data can improve a company’s understanding of its processes during scale-up and commercial manufacturing. This understanding would help companies control variability and increase product quality, says Chris Ames, director of global validation at Catalent Pharma Solutions (Somerset, NJ). Companies would submit these data to FDA to establish links between clinical and commercial processes.

But the draft guidance does not advise manufacturers about how to identify the most important characteristics of its product or manufacturing process, or about how to demonstrate links from the clinical to commercial process. “They’ve left it completely open to interpretation as to what data you provide and what format you use,” says Jim Agalloco, president of Agalloco and Associates. This ambiguity would suit Big Pharma because it frees companies to use their experience and discretion in deciding how to follow the guidance, says Agalloco. Small and emerging drugmakers, however, would likely be confused because they don’t have the depth of knowledge that would help them define critical attributes.

Some elements of the draft guidance resemble a Six Sigma approach to manufacturing, which is familiar to the pharmaceutical industry. The main similarity is the draft guidance’s recommendation of a statistical link that demonstrates that variability remains constant from the clinical through the commercial manufacturing stages. The statistical link is intended to confirm that processes are the same throughout all phases.

Although the draft guidance suggests statistical analysis, it leaves industry with only a broad understanding of what that means. FDA does not explicitly suggest that manufacturers use particular statistical tools, the agency simply recommends that companies apply good statistics to establish the links, says Agalloco.

The draft guidance suggests manufacturers define a process that can be measured, analyzed, improved, and controlled, and this approach is closely related to Six Sigma. The benefit of the Six Sigma technique is that it provides a mechanism for scientific review of a process, for assessing variability, and for identifying improvements, says Ames.

On the other hand, it is unclear whether the draft guidance recommends a product be refined in the way that a Six Sigma approach would. “To me, Six Sigma implies an acceptance by FDA that you might not have done a sufficient job in development and scale-up and are allowed to improve product and process while it is in operation,” says Agalloco. Patients’ experiences with a product might persuade a manufacturer that it should adjust one of the drug’s parameters to improve it. Six Sigma would allow postcommercialization changes to a product, but the draft guidance may not be compatible with them, Agalloco says.

Before it could submit a regulatory filing, a company would have to spend a great deal of time and money to better understand its ingredients, its product, its manufacturing process, its material handling, and associated variables. Pharmaceutical companies might object to the draft guidance’s approach because it suggests this expensive work be completed before commercialization, but the costs would not be recoverable before commercial-scale manufacturing began.

Although it is based on good science, if the final guidance is approved as drafted, it could easily increase drug-development time by one or two years, thus costing a manufacturer millions of dollars, says Warren Charlton, a consultant at WHC Bio Pharma Technical Services. Manufacturers would need to use smart strategies to shorten development time, but not knowing how much data regulators expect in a submission would make this strategy difficult.

The draft guidance inspired a huge volume of comments that will likely take FDA a long time to review, says Agalloco. Even though the guidance might not be final for at least a year, manufacturers would be wise to study it now and seek advice about interpreting it. In this difficult time for the pharmaceutical industry, no company can afford to ignore regulators’ recommendations, and advance preparation would be to a manufacturer’s benefit.

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Cleaning Validation in Continuous Manufacturing

Now Design/Shutterstock.comIt is now possible, as demonstrated by Janssen (1), for drug manufacturers to convert their processes to adopt continuous production of oral solid-dosage forms produced in compact, closed units, with a higher level of automation and minimal manual interventions. In continuous manufacturing, the sequential production steps that are part of a classic batch process are integrated into a continuous process. To ensure GMP compliance, cleaning is required on some frequency between batches of the same product and when switching between different products.

What is continuous manufacturing?

It is important to define continuous manufacturing and to understand the characteristics that differentiate it from a typical batch process. The classical definition involves the following:

All crucial steps involved to produce something from its starting materials to the end-product must be integrated into a steady uninterrupted process.

The systems should operate continuously (non-stop) targeting at least 50 weeks per year.

There should be no significant downtime in product or process changeover.

Some variations of this processing mode may be foreseen over the years. Processes that do not fit the above definition, such as infrequent manufacture (e.g., operates only once or twice per year) or a multi-product process train (i.e., same equipment used for many different products), are generally not considered continuous manufacturing (2).

Cleaning concerns

Although most companies do not have immediate plans for implementation of continuous manufacturing, many GMP professionals have questions concerning the impact of this type of process on cleaning and cleaning validation. People involved in quality, engineering, operations, and validations are asking about applying cleaning validation to pharmaceuticals produced in a continuous manufacturing process. The purpose of this article is to provide a review of the regulatory expectations on cleaning and cleaning validation and to help drive efficiency by rethinking the design of the cleaning process in continuous manufacturing.

Professionals interested in understanding cleaning and continuous manufacturing must become familiar with the following aspects:

The regulatory perspective on cleaning validation and applicability to continuous manufacturing

The importance of the lifecycle model and risk assessment tools to successfully design and implement a cleaning procedure for continuous manufacturing

Testing, sampling, process analytical technology (PAT), and equipment design concepts that should be reviewed and considered to optimize cleaning in continuous manufacturing

How to establish cleaning residue limits explicitly for continuous manufacturing.

Regulatory perspective

In the United States, the regulatory expectation is that equipment be cleaned prior to manufacturing to prevent contamination or adulteration of products (3). Similarly, in Europe, Canada, Asia, Latin America, and other territories, equipment cleaning is a regulatory requirement cited in their applicable GMPs. According to 21 Code of Federal Regulations (CFR) Part 211.67 Equipment cleaning and maintenance, “Equipment and utensils shall be cleaned, maintained, and sanitized at appropriate intervals to prevent malfunctions or contamination that would alter the safety, identity, strength, quality, or purity of the drug product beyond the official or other established requirements” (3). Also, in 1993, FDA issued the Guide to Inspections of Validation of Cleaning Processes to assist the industry in compliance with GMP requirements (4). The European Medicine Agency (EMA), Health Canada, and others subsequently issued similar guides to assist the industry in complying with the relevant regulations (5–6).

Based on these guidance documents, cleaning validation is clearly a necessity when the equipment is used to manufacture more than one drug product due to cross-contamination concerns. A question remains as to whether cleaning validation is required for dedicated equipment, which may be the case for most continuous manufacturing processes. The need to validate the cleaning procedure when the equipment is dedicated to one product is generally left to the company’s discretion, and it must be supported with proper justification. Nevertheless, cleaning validation of dedicated equipment has been discussed in other publications, and the rationale behind this can also be applied to continuous manufacturing (7). In the case of continuous manufacturing, cleaning validation of dedicated equipment should be done to demonstrate that the cleaning procedure can effectively remove residue build-up and undesirable residues (including microbial) produced during a specific length of manufacturing (i.e., campaign) that may compromise product quality and patient safety.

As of the time of publication, no specific regulation or guidance document for continuous manufacturing has been released. FDA authorities have presented a general perspective on continuous manufacturing, which addresses the concerns around “lot” and “batch” definitions (8). According to the CFR, “batch” and “lot” refer to a quantity of material with uniform characteristics and do not specify mode of manufacture; no regulations or guidance documents forbid the adoption of continuous manufacturing. In fact, continuous manufacturing seems to be consistent with philosophies, such as quality by design (QbD) and the lifecycle approach to process validation, found in current guidance documents (9–12).

Lifecycle approach

In 2011, FDA issued a process validation guide (12) focusing on three main elements:

Quality needs to be built into the process

Quality is not guaranteed by in-process or final process testing

A manufacturing process needs to be defined and continuously monitored to ensure consistent quality.

The elements of the lifecycle model are the building blocks to a harmonized approach to process validation and subsequently, cleaning validation. The lifecycle elements of design, validation, and monitoring are also the building blocks to make continuous processing an efficacious mode of manufacturing. The process lifecycle approach as discussed in the guidance document focuses on understanding the processes and ensuring that they are meeting the requirements set forth in the design stage. The elements of the lifecycle approach should not be limited to manufacturing since they may also be applied to other processes including cleaning. With this in mind, the lifecycle model can be used to improve or optimize cleaning procedures by having a better understanding of the input variables and the output attributes.

Designing the cleaning process

Process efficiency is important in continuous manufacturing and cleaning is not an exception. For example, at some pre-established schedule, the continuous manufacturing facility must be shutdown to perform equipment cleaning and maintenance. Cleaning procedures are expected to be done quickly and correctly the first time in order to meet the optimum changeover time as established in the production schedule. Also cleaning procedures should be systematically designed to reduce waste within the cleaning process.

Figure 1: CLICK TO ENLARGE. Typical equipment of oral solid-dose (OSD) batch process and a continuous manufacturing (CM) process flow with soil type considerations for cleaning evaluations. SOP is standard operating procedure; CIP is clean in place. All images are courtesy of the authors.The design stage of the lifecycle model (Stage 1) is of particular importance because the cleaning process is defined based on knowledge gained through development and scale-up activities. This stage ensures that the variables are identified and their criticality to the cleaning process is assessed. For example, the design inputs or critical cleaning process parameters for the wash step include the cleaning agent, concentration, temperature, time, cleaning method, water quality, and environmental factors (13–14). Laboratory, pilot, or field studies should be used to help define the cleaning process and identify conditions that would lead to the desired fast, effective, and lean cleaning process (see Table I). These studies may involve cleaning evaluations with wet, baked-on residue found in the drier as well as dry, compacted residue for tablet pressing equipment (see Figure 1).

A formal risk assessment for the cleaning process is also recommended using a system for identifying and managing risk such as fault tree analysis (FTA), hazard analysis and critical control point (HACCP), or failure modes and effect analysis (FMEA) (15–16). Risk assessment should be based on the knowledge gained through the design stage and focus should be placed on the issues that have potential impact on product quality and patient safety. Table II includes items to consider for building a cleaning process knowledge base. A design of experiments could be used to identify those parameters that have a significant impact to cleaning within a specified range (17).

Monitoring technology

Cleaning processes are often viewed as time- and resource-consuming activities that only add to the operational costs of product manufacturing. Delays in equipment readiness due to cleaning failures, lengthy manual cleaning procedures, or off-line sampling wait times can challenge continuous manufacturing schedules and result in costly production delays.

Table I: Design space considerations for continuous manufacturing.

Manufacturers using batch processing, including cleaning processes, perform laboratory testing conducted on pulled samples to evaluate quality attributes. PAT, however, can be used in continuous manufacturing to provide real-time continuous analysis and release of the cleaned equipment. PAT is a system for designing, analyzing, and controlling manufacturing through timely measurements, process understanding, and process control (18). In cleaning applications, PAT may be applied to complement the cleaning performance qualification and later, to support continued verification. For example, concentration-versus-conductivity plots are pre-established to monitor the final water rinse for residual cleaning agent (19). Total organic carbon (TOC) analysis can also be correlated to process residues. In a published case study, a cleaning process was evaluated using an on-line TOC analyzer integrated into the return line of a clean-in-place (CIP) system (20).

Table II: Cleaning process knowledge base.

There are sampling options (e.g., rinse and swab) universally acceptable for monitoring the cleaning performance of the targeted residues; each option has advantages and disadvantages to consider. For most cleaning applications, rinse sampling is typically expected to be faster and easier compared to swab sampling, which may require access to equipment locations through disassembly or confined-space entry and consequently compromises personnel safety.

Analytical methods can be specific or non-specific to determine the amount of residue on the surface through direct and indirect sampling methods. Non-specific detection methods, such as pH, conductivity, or TOC, can be used to measure multiple residue types. These types of methods are preferred due to the quick turnaround time, minimum waste generation, and simplicity of the assay. Ultra high-pressure liquid chromatography (UHPLC) instruments measure residue based on detection of a specific analyte and is a faster alternative over traditional HPLC (21).

Table III: Faster testing technologies commonly used for cleaning monitoring.

Table III lists examples of at-line and in-line methods that could be used for detection of residual cleaning agent. For continuous manufacturing, it is recommended to review testing technologies and select one that makes the most sense given the analytical resources, type of residue and carry-over risk, speed of analysis, and/or adaptability to PAT.

Cleaning equipment design

Batch pharmaceutical processes employ a variety of methods to clean process equipment. Manual cleaning methods using wipes and brushes are common in legacy batch-mode processes while CIP systems are popular at newer facilities. Even though both manual and automatic cleaning methods are accepted by drug regulatory agencies around the globe, companies considering continuous manufacturing processes should opt for CIP systems because they are effective, consistent, and reliable. Consistent cleaning results are achieved because there is minimal operator intervention, reduced likelihood of human error, and consistent control of critical parameters when combined with PAT technologies. The principal objective of a CIP system is to achieve the desired cleanliness level without disassembling the process equipment. Generally, CIP cleaning is done by circulating cleaning solutions through pipes, pumps, valves, and spray devices that distribute the cleaning agent over the surface areas of the equipment. PAT technology can be used to monitor cleaning steps, such as the preparation of cleaning solution to a pre-established concentration and the rinsing of the equipment down to pre-established residue limits.

With adequate sanitary design, such as coverage, diaphragm valves, pitch, and dead-leg orientation, CIP systems can deliver faster and lean cleaning processes suitable for continuous manufacturing. All sanitary design concepts must be thoroughly reviewed to ensure equipment cleanability and minimize water consumption. Multiple sources provide details on sanitary options (22–24). In summary, a laboratory evaluation to determine critical cleaning parameters combined with a review of equipment design concepts should help improve speed of the cleaning procedure, reduce waste generated during cleaning execution, minimize cleaning agent and water consumption, and reduce human interventions.

Establishing cleaning residue limits

In setting acceptable residue limits within continuous manufacturing, two situations should be considered (25). In the first situation, the manufacturing process for Product A is interrupted (a scheduled or unscheduled stoppage) due to a minor maintenance event or light cleaning such as vacuuming or dry wiping the work surfaces; when complete, the manufacturing line is back up and running. In this situation, there is no concern of residual carry-over of the active ingredient because only one product is being manufactured; therefore, cleaning validation is not applicable. If a product impurity, cleaning agent, equipment lubricant, or similar processing aid was introduced, however, a cleaning procedure should be performed to remove those residues to safe levels prior to resuming production. This type of interruption will fall into the second situation.

In the second situation, Product A production has stopped and change-out is occurring to begin continuous manufacturing of Product B. In this scenario, there is a need to perform an in-depth or heavy cleaning to make sure that active components from Product A do not affect the quality of Product B, as well as ensuring that the non-active components (any cleaning agents used, and microbial residues remaining on the surface) are within acceptable levels. Similar to traditional batch processing, possible pharmacological and toxicity effects of Product A, as well as residue impacting the stability of Product B, need to be considered.

In establishing residue limits, safe concentration of the target residue in the subsequent product (i.e., Product B), referred to as Limit 1 (L1), needs to be understood. The safe dose (L0) or a scientifically derived health-based limit (i.e., an acceptable daily exposure [ADE] or permitted daily exposure [PDE]) of the residue (i.e., of Product A) is calculated using Equation 1, and L1 is calculated using Equation 2 (26–27).

[Eq. 1] L0 = Toxicity Assessment x Body Weight x Minimum Daily Dose of Product A

[Eq. 2] L1 = L0 / Maximum Daily Dose of Next Product

The L1 value calculated in Equation 2, multiplied by the batch size of the subsequent product (which, as previously discussed, must be defined in continuous manufacturing by the manufacturer), provides a maximum allowable carry-over value (MAC or MACO value, also known as L2).

From the L2 or MAC value, the limit per surface area can be calculated by dividing by the shared surface area of the equipment train.

This calculation assumes a uniform distribution of the residue and is considered a conservative approach to setting limits per surface area. Most cleaning validation swab sampling plans would include sampling the hardest-to-clean locations based on a risk assessment.

Stratified and non-uniform residue limits

The concept of uniform distribution is an ideal scenario and is not always true (28). This assumption, therefore, may lead to failing results on select equipment or sampling locations.

Stratified residue distribution on equipment splits the calculated L2 or MAC residue among the different pieces of equipment within the manufacturing process based on a risk assessment. It is important to document the risk assessment used to determine the stratification because it will be reviewed by auditors. The stratification scheme can also vary based on the target residue. For example, microbial limits may be set lower for the wet granulation and coating steps because there is a greater risk for microbial proliferation during these steps.

Non-uniform residue contamination in the product means that the residue on the surface of the equipment concentrates into the first units of production and is then reduced in subsequent units. In a tablet press, for example, the residue from the previous product will be transferred to the first tablets (or round of tablets) pressed at a higher concentration than the second and third tablets pressed. In a filling line, as another example, the residue from the previous product will be transferred to the first vials (or series of vials) filled at a higher concentration than the second and third vials filled.

Equation 3 shows a calculation for setting limits in a non-uniform contamination example. The limit (L0) of Residue A in Product B has been calculated (or defaulted) to be 10 ppm or approximately 10 μg/mL. The total surface area of the filling equipment and piping is 10,000 cm², and the limit per surface area of Residue A has been predetermined to be 1 μg/cm². Product B is filled in 10 mL vials. If the contamination of 1 μg/cm² of the total shared surface area of 10,000 cm² were concentrated into the first vial filled of 10 mL, then the residue level would be 1000 μg/mL or 1000 ppm, which is well above the 10 ppm limit. The first 10 or 100 vials should be discarded because the residue in the vials would be less than 100 or 10 ppm, respectfully.

[Eq. 3] (1 μg/cm²)(10,000 cm²)/10 mL = 1000 μg/mL or 1000 ppm

The understanding of non-uniform and stratified sampling is important for setting residue limits within a continuous manufacturing process because a small quantity of product may migrate through a manufacturing process, concentrating residue from one piece of equipment to another and defaulting to a traditional uniform residue limit, which can adversely impact the quality of the product and potentially impact the health of the patient.

Cleaning performance qualification

In the lifecycle approach to cleaning validation, Stage 2, the performance qualification stage, is a readiness check to ensure the cleaning process is able to be validated. This stage will involve checking that suppliers have been approved, analytical methods have been validated, personnel performing the cleaning have been trained, standard operating procedures and validation documents are ready to be performed or executed, and process equipment and utilities have been successfully qualified and ready for use (29).

If the critical process parameters and critical quality attributes were well characterized during the cleaning design stage, then the performance qualification (Stage 2) should be performed using normal operating parameters.

Continued process verification

The third stage of the lifecycle model is continued process verification. Implementation of process controls such as change control, preventative maintenance, and corrective and preventative action systems ensure a validated state. The cleaning process continuously operates in a state of control. A periodic review of the cleaning program is also crucial to ensure that the cleaning process remains in control and is flexible to change when required. This periodic review of the cleaning validation program should be reviewed in a similar manner as the yearly product quality review. A review of product cleaning is generally part of the yearly product quality review, but it is generally not thorough enough and often doesn’t review similarities and difference between multiple products manufactured in the same equipment.

Table IV: Examples of impact changes.

Figure 2: Roadmap to the cleaning validation lifecycle approach.

Items that should be reviewed include change control data, monitoring data, deviations, corrective and preventive actions, maintenance, quality records, and retraining events.

If the review shows control and consistency, then summarize the findings and conclude that the cleaning program is operating in a state of control (i.e., a validated state). The review can also identify high-risk or high-waste areas that need to be improved. A corrective action plan or lean manufacturing event can be used to develop a plan to correct this deficiency.

Managing change

Depending on the type of change being proposed, it may be necessary to go back to the design stage to determine the impact of the change to the cleaning process. For this reason, validated cleaning procedures must be included in the change control management system. This ensures that any proposed changes are evaluated fully for their impact on the validated state of the procedure.

Table IV is not an all-inclusive list of possible changes but helps provide an idea of the type of changes and their potential impact (29). The impact of the change to the cleaning process may have already been assessed during the design stage; otherwise additional testing within the design stage may be warranted to mitigate risk prior to implementation of the change. This action is depicted in Figure 2 as arrows from Stage 3 to Stage 1 or 2 as a result of the change (29).

Managing change is an important process because the goal of the design stage and continuous monitoring stage of the cleaning validation lifecycle approach for continuous manufacturing production facilities is to operate within a state of control and to drive out waste to improve efficiency and maintain flexibility of the cleaning process.

Conclusion

Continuous manufacturing focuses on streamlining production while minimizing the process footprint and waste from non-value activities. To ensure cGMP compliance, cleaning is required on some frequency between batches of the same product and when switching between different products. Developing a cleaning validation program using the process lifecycle approach provides a firm understanding of the critical cleaning process parameters as well as the critical quality attributes that need to be monitored.

The equipment used for continuous manufacturing may vary based on the type of product manufactured as well as the method of cleaning. It is important to evaluate cleaning during the drafting of the user requirement specifications and functional requirement specifications of the production equipment. The development and proof of concept of a laboratory-scale cleaning model during the design phase of the cleaning process and equipment fabrication will aid in the validation of cleaning processes. This model will also help in the ability to conduct additional investigations to support process and cleaning changes to reduce waste. The use of health-based limits, such as an ADE or PDE value, for any route of administration, along with a rationalized use of non-uniform and stratified residue limits, allows for setting practical, achievable, and justified acceptance limits.

References

S.E. Kuehn, Pharm Manuf. 14 (8) 31-33 (2015).

G. Malhotra, Contract Pharma. 17 (5) 74- 79 (2015).

FDA, Code of Federal Regulations, Title 21, Part 211.67 "Equipment Cleaning and Maintenance" (Washington, DC).

FDA, Guide to Inspections Validation of Cleaning Processes. (Silver Spring, MD, 1993).

Pharmaceutical Inspection Convention/Pharmaceutical Inspection Co-Operation Scheme (PIC/S). Validation Master Plan Installation And Operational Qualification Non-Sterile Process Validation Cleaning Validation. (Geneva, Switzerland, Sept., 2009).

Health Canada, Cleaning Validation Guidelines (Guide-0028). (Ottawa, Ontario, January 2008).

C. Baccarelli, et al. BioPharm Int. 28 (8) 38-40 (2015).

S. Chatterjee, “FDA Perspective on Continuous Manufacturing,” Presentation at IFPAC Annual Meeting (Baltimore, MD, January 2012).

FDA, Guidance for Industry, Q8 Pharmaceutical Development (Silver Spring, MD, May 2006).

FDA, Guidance for Industry, Q9 Quality Risk Management (Silver Spring, MD, June 2006).

FDA, Guidance for Industry, Q10 Quality Systems Approach to Pharmaceutical cGMP Regulations (Silver Spring, MD, Sept. 2006).

FDA, Process Validation: General Principles and Practices (Rockville, MD, November 2011).

G. Verghese and N. Kaiser, “Cleaning Agents and Cleaning Chemistry, Chapter 7” in Cleaning and Cleaning Validation Volume I, P. Pluta Ed. (Davis Healthcare International and Parenteral Drug Association, 2009) pp 103-121.

G. Verghese, “Selection of Cleaning Agents and Parameters for cGMP Processes,” Proceedings of the INTERPHEX Conference (Philadelphia, 1998) pp. 89-99.

IEC, 61025-1990, Fault Tree Analysis (Geneva, Switzerland, 1990).

IEC, 812-1985, Analysis techniques for system reliability – Procedure for failure mode and effect analysis (FMEA) (Geneva, Switzerland, 1985).

N. Rathore, et al., Biopharm Int. 22 (3) 32-44 (2009).

FDA, Guidance for Industry: PAT – A Framework for innovative pharmaceutical development, manufacturing, and quality assurance. (Rockville, MD, September, 2004).

G. Verghese and P. Lopolito, "Process Analytical Technology and Cleaning," Contamination Control, Fall 2007. pp 22-26.

K. Bader, et al., Pharm. Eng. 29 (1) 8-20 (2009).

M. Gietl, B. Meadows, and P. Lopolito, "Cleaning Agent Residue Detection with UHPLC,". Pharm. Manufacturing (April, 2013) www.pharmamanufacturing.com/articles/2013/1304_SolutionsTroubleshooting/, accessed Oct. 20, 2016.

E. Rivera, "Basic equipment-design concepts to enable cleaning in place: Part I," Pharm. Tech. Equipment and Processing Report, (June 15, 2011), www.pharmtech.com/basic-equipment-design-concepts-enable-cleaning-place-part-i, accessed Oct. 20, 2016.

E. Rivera, "Basic equipment-design concepts to enable cleaning in place: Part II," Pharm. Tech. Equipment and Processing Report, (July 20, 2011), www.pharmtech.com/basic-equipment-design-concepts-enable-cleaning-place-part-ii, accessed Oct. 20, 2016.

G. Verghese and P. Lopolito, "Cleaning Engineering and Equipment Design," in Cleaning and Cleaning Validation Volume I, P. Pluta Ed. (DHI Publishing and the Parenteral Drug Association, 2009) pp 123-150.

D. LeBlanc, "Cleaning Validation for Continuous Manufacture," Cleaning Validation Technologies Memos (April 2014), www.cleaningvalidation.com/files/98772132.pdf, accessed Oct. 20, 2016.

EMA, Guideline on setting health based exposure limits for use in risk identification in the manufacture of different medicinal products in shared facilities, EMA/CVMP/SWP169430/2012 (London, November 2014).

ISPE, Baseline Guide: Risk Based Manufacture of Pharmaceutical Products (Risk-MAPP) Chapter 5, pp 33-46 (Bethesda, MD, 2010).

G. Kleina, Pharma. Outsourcing 16 (4) 40-43 (2015).

P. Lopolito and E. Rivera, "Cleaning Validation: Process Lifecycle Approach," in Contamination Control in Healthcare Product Manufacturing, Vol 3. R. Madsen and J. Moldenhauer, Eds. (DHI Publishing, PDA Books, 2014).

About the Authors

Paul Lopolito and Elizabeth Rivera are technical services managers for the Life Sciences Division of STERIS Corporation in Mentor, Ohio.

Article Details

Pharmaceutical Technology
Vol. 40, No. 11
Pages: 34–42, 55

Citation

When referring to this article, please cite it as P. Lopolito and E. Rivera, "Cleaning Validation in Continuous Manufacturing," Pharmaceutical Technology 40 (11) 2016.

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