Quality Risk Management Competency Model-Case for the Need for QRM Competencies.

The Pharmaceutical Regulatory Science Team (PRST), a research team based at the Dublin Technological University (TU Dublin) in Ireland, recently conducted a Quality Risk Management (QRM) survey and a face-to-face focus group workshop to assess the level of formality of QRM roles in the biopharmaceutical sector. This was carried out as part of a research study, which identified the need for the development of QRM role-based competencies as fundamental to realizing QRM's benefits. The research study followed a hybrid Delphi research methodology composed of: (1) Survey 1, (2) focus group workshop, (3) Survey 2, and (4) competency model development. This paper presents the results of Survey 1 and the focus group workshop. Survey 1 explored the need for QRM role-based competencies and the subsequent face-to-face focus group workshop built on this to propose initial standard QRM roles, with a view to confirming these and developing associated competencies. This paper presents the findings from Survey 1 and the focus group workshop. The results of the follow-up research activities will be presented in a subsequent paper.LAY ABSTRACT: The publication of the ICH Q9 Quality Risk Management (QRM) guideline in 2005 has greatly impacted the biopharmaceutical sector. Fourteen years after Q9, the benefits of QRM are yet to be realized. The biopharmaceutical sector still struggles with the implementation of Q9 principles to effectively assess and manage product quality risks as a surrogate for patient safety.This paper looks at the need for standard QRM roles and the associated competencies for those roles.

The Discriminatory Power of the BCS-Based Biowaiver: A Retrospective With Focus on Essential Medicines.

This article summarizes historic developments, recent expert opinions, and (currently) unresolved challenges concerning the Biopharmaceutics Classification System (BCS)-based Biowaiver. An overview of approval statistics and application potential, case examples addressing the discriminatory power of the procedure, as well as an outlook on possible refinements in the future are provided and critically discussed. Over the last decade, regulatory guidance documents have been harmonized, for example, following scientific consent on allowing biowaivers for BCS class III drugs, making over 50% of orally administered drugs on the World Health Organization Essential Medicines List eligible for an abbreviated approval. Biowaiver monographs that present a complete risk-benefit evaluation for individual drugs have been issued by the International Pharmaceutical Federation for more than 25% of those drugs with the long-range aim of covering all essential drugs. Unresolved issues that have emerged from reported examples of false-negative and false-positive outcomes in the literature demand further adjustments to the regulatory requirements. Possible solutions for resolving these issues are the use of modeling and simulation and refined biorelevant in vitro tests that are better able to discriminate between dosage forms with unequal performance in vivo, potentially allowing biowaivers for selected BCS II drugs.

What Does It Really Look Like to Properly Address a "Human Error Problem" in Biopharma? The Human Performance Blue-Sky Description That Will Help Improve Industry Performance.

A clear picture of what Human Performance success looks like is now available from BioPhorum, where members of the Human Performance workstream have defined a blue-sky for the industry. This blue-sky document is both a guide and an assessment tool, which includes warning flags that help to identify significant obstacles in the way of effective human performance integration with operations that must be addressed. The effort to improve reliable operations within biopharma using elements of human performance borrowed from other industries have experienced uneven results and slow progress across the last seven years and has been bogged down for multiple significant reasons. These include a mental model that persists within the industry where workers are assumed to be the problem that needs fixing, the mistaken belief that Lean/Operational Excellence is a cure-all and nearly equivalent to human performance, neglecting the need to fundamentally rethink why and how investigations are performed, and truly underestimating the time, effort, strength of sponsor support, and strategy needed to change how work is designed, executed, and then later learned from.LAY ABSTRACT: Human Performance is an integrated risk management approach to improving systems, that includes human factors and systems safety, that leads to higher reliability and enhanced operational resilience. A clear picture of what Human Performance looks like in biopharma is available from the BioPhorum, where members of the Human Performance workstream have defined a blue-sky for the industry. This blue-sky document is both a guide and an assessment tool that will help to identify the steps to effective human performance integration with operations. The effort to improve reliable operations within biopharma using elements of human performance borrowed from other industries has experienced uneven results and slow progress across the last seven years and has been bogged down for multiple significant reasons. These include a mental model that persists within the industry where workers are assumed to be the problem that needs fixing, the mistaken belief that Lean practices (intended to improve productivity & efficiency) is a cure-all and nearly equivalent to human performance, neglecting the need to fundamentally rethink why and how investigations are performed, and truly underestimating the time, effort, strength of sponsor support needed to change how work is designed, executed, and then later learned from.

Enabling adoption of 2D-NMR for the higher order structure assessment of monoclonal antibody therapeutics.

The increased interest in using monoclonal antibodies (mAbs) as a platform for biopharmaceuticals has led to the need for new analytical techniques that can precisely assess physicochemical properties of these large and very complex drugs for the purpose of correctly identifying quality attributes (QA). One QA, higher order structure (HOS), is unique to biopharmaceuticals and essential for establishing consistency in biopharmaceutical manufacturing, detecting process-related variations from manufacturing changes and establishing comparability between biologic products. To address this measurement challenge, two-dimensional nuclear magnetic resonance spectroscopy (2D-NMR) methods were introduced that allow for the precise atomic-level comparison of the HOS between two proteins, including mAbs. Here, an inter-laboratory comparison involving 26 industrial, government and academic laboratories worldwide was performed as a benchmark using the NISTmAb, from the National Institute of Standards and Technology (NIST), to facilitate the translation of the 2D-NMR method into routine use for biopharmaceutical product development. Two-dimensional 1H,15N and 1H,13C NMR spectra were acquired with harmonized experimental protocols on the unlabeled Fab domain and a uniformly enriched-15N, 20%-13C-enriched system suitability sample derived from the NISTmAb. Chemometric analyses from over 400 spectral maps acquired on 39 different NMR spectrometers ranging from 500 MHz to 900 MHz demonstrate spectral fingerprints that are fit-for-purpose for the assessment of HOS. The 2D-NMR method is shown to provide the measurement reliability needed to move the technique from an emerging technology to a harmonized, routine measurement that can be generally applied with great confidence to high precision assessments of the HOS of mAb-based biotherapeutics.

Recommendations for Comparison of Productivity Between Fed-Batch and Perfusion Processes.

Due to the growing interest in integrated continuous processing in the biopharmaceutical industry, productivity comparison of batch-based and continuous processes is considered a challenge. Integrated continuous manufacturing of biopharmaceuticals requires scientists and engineers to collaborate effectively. Differing definitions, for example, of volumetric productivity, may cause confusion in this interdisciplinary field. Therefore, the aim of this communication is to reiterate the standard definitions and their underlying assumptions. Applying them to an exemplary model scenario allows to demonstrate the differences and to develop recommendations for the comparison of productivity of different upstream processes.

Impact of the US FDA "Biopharmaceutics Classification System" (BCS) Guidance on Global Drug Development.

The FDA guidance on application of the biopharmaceutics classification system (BCS) for waiver of in vivo bioequivalence (BE) studies was issued in August 2000. Since then, this guidance has created worldwide interest among biopharmaceutical scientists in regulatory agencies, academia, and industry toward its implementation and further expansion. This article describes how the review implementation of this guidance was undertaken at the FDA and results of these efforts over last dozen years or so across the new, and the generic, drug domains are provided. Results show that greater than 160 applications were approved, or tentatively approved, based on the BCS approach across multiple therapeutic areas; an additional significant finding was that at least 50% of these approvals were in the central nervous system (CNS) area. These findings indicate a robust utilization of the BCS approach toward reducing unnecessary in vivo BE studies and speeding up availability of high quality pharmaceutical products. The article concludes with a look at the adoption of this framework by regulatory and health policy organizations across the globe, and FDA's current thinking on areas of improvement of this guidance.

Recent Topics of Research in the Characterization and Quality Control of Biopharmaceuticals in Japan.

The research and development of next-generation innovative medicines is a prominent interest of both the government and industries in Japan. On June 29, 2017, a kickoff meeting of a new research group focused on the quality issues of biopharmaceuticals was held in Tokyo with Prof. John Carpenter as an invited guest. The group's research focuses mainly on the evaluation and control of protein aggregates/subvisible particles in drug products, but the research topics also include glycan analysis, host-cell protein evaluation, bioassay validation, and analytical quality by design. The purpose of the group's activities is to resolve the critical and fundamental quality issues important to pharmaceutical companies through the collaboration of industries, academia, and regulatory agencies. In this commentary, our current plan to address these issues and the discussion at the kickoff meeting are described.

Opportunities and challenges of real-time release testing in biopharmaceutical manufacturing.

Real-time release testing (RTRT) is defined as "the ability to evaluate and ensure the quality of in-process and/or final drug product based on process data, which typically includes a valid combination of measured material attributes and process controls" (ICH Q8[R2]). This article discusses sensors (process analytical technology, PAT) and control strategies that enable RTRT for the spectrum of critical quality attributes (CQAs) in biopharmaceutical manufacturing. Case studies from the small-molecule and biologic pharmaceutical industry are described to demonstrate how RTRT can be facilitated by integrated manufacturing and multivariable control strategies to ensure the quality of products. RTRT can enable increased assurance of product safety, efficacy, and quality-with improved productivity including faster release and potentially decreased costs-all of which improve the value to patients. To implement a complete RTRT solution, biologic drug manufacturers need to consider the special attributes of their industry, particularly sterility and the measurement of viral and microbial contamination. Continued advances in on-line and in-line sensor technologies are key for the biopharmaceutical manufacturing industry to achieve the potential of RTRT. Related article: http://onlinelibrary.wiley.com/doi/10.1002/bit.26378/full.

Throughput Optimization of Continuous Biopharmaceutical Manufacturing Facilities.

In order to operate profitably under different product demand scenarios, biopharmaceutical companies must design their facilities with mass output flexibility in mind. Traditional biologics manufacturing technologies pose operational challenges in this regard due to their high costs and slow equipment turnaround times, restricting the types of products and mass quantities that can be processed. Modern plant design, however, has facilitated the development of lean and efficient bioprocessing facilities through footprint reduction and adoption of disposable and continuous manufacturing technologies. These development efforts have proven to be crucial in seeking to drastically reduce the high costs typically associated with the manufacturing of recombinant proteins. In this work, mathematical modeling is used to optimize annual production schedules for a single-product commercial facility operating with a continuous upstream and discrete batch downstream platform. Utilizing cell culture duration and volumetric productivity as process variables in the model, and annual plant throughput as the optimization objective, 3-D surface plots are created to understand the effect of process and facility design on expected mass output. The model shows that once a plant has been fully debottlenecked it is capable of processing well over a metric ton of product per year. Moreover, the analysis helped to uncover a major limiting constraint on plant performance, the stability of the neutralized viral inactivated pool, which may indicate that this should be a focus of attention during future process development efforts.LAY ABSTRACT: Biopharmaceutical process modeling can be used to design and optimize manufacturing facilities and help companies achieve a predetermined set of goals. One way to perform optimization is by making the most efficient use of process equipment in order to minimize the expenditure of capital, labor and plant resources. To that end, this paper introduces a novel mathematical algorithm used to determine the most optimal equipment scheduling configuration that maximizes the mass output for a facility producing a single product. The paper also illustrates how different scheduling arrangements can have a profound impact on the availability of plant resources, and identifies limiting constraints on the plant design. In addition, simulation data is presented using visualization techniques that aid in the interpretation of the scientific concepts discussed.

Assessment Methodology for Process Validation Lifecycle Stage 3A.

The paper introduces evaluation methodologies and associated statistical approaches for process validation lifecycle Stage 3A. The assessment tools proposed can be applied to newly developed and launched small molecule as well as bio-pharma products, where substantial process and product knowledge has been gathered. The following elements may be included in Stage 3A: number of 3A batch determination; evaluation of critical material attributes, critical process parameters, critical quality attributes; in vivo in vitro correlation; estimation of inherent process variability (IPV) and PaCS index; process capability and quality dashboard (PCQd); and enhanced control strategy. US FDA guidance on Process Validation: General Principles and Practices, January 2011 encourages applying previous credible experience with suitably similar products and processes. A complete Stage 3A evaluation is a valuable resource for product development and future risk mitigation of similar products and processes. Elements of 3A assessment were developed to address industry and regulatory guidance requirements. The conclusions made provide sufficient information to make a scientific and risk-based decision on product robustness.

Optimizing Clinical Drug Product Performance: Applying Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid.

The aim of Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid is to facilitate optimization of clinical performance of drug products. BioRAM strategy relies on therapy-driven drug delivery and follows an integrated systems approach for formulating and addressing critical questions and decision-making (J Pharm Sci. 2014,103(11): 3777-97). In BioRAM, risk is defined as not achieving the intended in vivo drug product performance, and success is assessed by time to decision-making and action. Emphasis on time to decision-making and time to action highlights the value of well-formulated critical questions and well-designed and conducted integrated studies. This commentary describes and illustrates application of the BioRAM Scoring Grid, a companion to the BioRAM strategy, which guides implementation of such an integrated strategy encompassing 12 critical areas and 6 assessment stages. Application of the BioRAM Scoring Grid is illustrated using published literature. Organizational considerations for implementing BioRAM strategy, including the interactions, function, and skillsets of the BioRAM group members, are also reviewed. As a creative and innovative systems approach, we believe that BioRAM is going to have a broad-reaching impact, influencing drug development and leading to unique collaborations influencing how we learn, and leverage and share knowledge.

A Roadmap for the Implementation of Continued Process Verification.

In 2014, the members of the BioPhorum Operations Group (BPOG) produced a 100-page continued process verification case study, entitled "Continued Process Verification: An Industry Position Paper with Example Protocol". This case study captures the thought processes involved in creating a continued process verification plan for a new product in response to the U.S. Food and Drug Administration's guidance on the subject introduced in 2011. In so doing, it provided the specific example of a plan developed for a new molecular antibody product based on the "A MAb Case Study" that preceded it in 2009.This document provides a roadmap that draws on the content of the continued process verification case study to provide a step-by-step guide in a more accessible form, with reference to a process map of the product life cycle. It could be used as a basis for continued process verification implementation in a number of different scenarios: For a single product and process;For a single site;To assist in the sharing of data monitoring responsibilities among sites;To assist in establishing data monitoring agreements between a customer company and a contract manufacturing organization. LAY ABSTRACT: The U.S. Food and Drug Administration issued guidance on the management of manufacturing processes designed to improve quality and control of drug products. This involved increased focus on regular monitoring of manufacturing processes, reporting of the results, and the taking of opportunities to improve. The guidance and practice associated with it is known as continued process verification This paper summarizes good practice in responding to continued process verification guidance, gathered from subject matter experts in the biopharmaceutical industry.

Manufacturing of Plasma-Derived Medicinal Products: Qualification Process of Plasma Suppliers.

Manufacturers of human plasma-derived products ensure, through their qualification departments, the quality and safety of human plasma-the biological starting material of the industrial fractionation process. The qualification department has established written procedures to approve the plasma supplier (i.e., initial qualification) according to current regulations and to the manufacturer's plasma specifications. Once the plasma supplier is approved, a periodical assessment is necessary (i.e., continuous qualification) to guarantee the level of compliance. In addition, a signed quality agreement between the plasma supplier and the manufacturer defines the duties and the responsibilities of both parties. The qualification department implements the following requirements to ensure the quality of plasma from suppliers: (i) a regular audit program to confirm the satisfactory initiation of the quality arrangements and (ii) monitoring of the quality and safety of plasma including critical quality parameters. For several years, the Grifols Qualification Department has worked with several plasma suppliers of the European Union (EU) and has performed a detailed, continuous assessment of the audits, deviations, operational incidences, epidemiological data, and quality controls. In this article, we will report data from this Grifols assessment from 2010 through 2013 on plasma suppliers from four EU countries. In the future, additional data will be collected and studied to confirm and verify the conclusions and trends observed in this study.

A science based approach to topical drug classification system (TCS).

The Biopharmaceutics Classification System (BCS) for oral immediate release solid drug products has been very successful; its implementation in drug industry and regulatory approval has shown significant progress. This has been the case primarily because BCS was developed using sound scientific judgment. Following the success of BCS, we have considered the topical drug products for similar classification system based on sound scientific principles. In USA, most of the generic topical drug products have qualitatively (Q1) and quantitatively (Q2) same excipients as the reference listed drug (RLD). The applications of in vitro release (IVR) and in vitro characterization are considered for a range of dosage forms (suspensions, creams, ointments and gels) of differing strengths. We advance a Topical Drug Classification System (TCS) based on a consideration of Q1, Q2 as well as the arrangement of matter and microstructure of topical formulations (Q3). Four distinct classes are presented for the various scenarios that may arise and depending on whether biowaiver can be granted or not.

Biopharmaceutics classification system-based biowaivers for generic oncology drug products: case studies.

Establishing bioequivalence (BE) of drugs indicated to treat cancer poses special challenges. For ethical reasons, often, the studies need to be conducted in cancer patients rather than in healthy volunteers, especially when the drug is cytotoxic. The Biopharmaceutics Classification System (BCS) introduced by Amidon (1) and adopted by the FDA, presents opportunities to avoid conducting the bioequivalence studies in humans. This paper analyzes the application of the BCS approach by the generic pharmaceutical industry and the FDA to oncology drug products. To date, the FDA has granted BCS-based biowaivers for several drug products involving at least four different drug substances, used to treat cancer. Compared to in vivo BE studies, development of data to justify BCS waivers is considered somewhat easier, faster, and more cost effective. However, the FDA experience shows that the approval times for applications containing in vitro studies to support the BCS-based biowaivers are often as long as the applications containing in vivo BE studies, primarily because of inadequate information in the submissions. This paper deliberates some common causes for the delays in the approval of applications requesting BCS-based biowaivers for oncology drug products. Scientific considerations of conducting a non-BCS-based in vivo BE study for generic oncology drug products are also discussed. It is hoped that the information provided in our study would help the applicants to improve the quality of ANDA submissions in the future.

Using tolerance intervals for assessment of pharmaceutical quality.

In quality control of drug products, tolerance intervals are commonly used methods to assure a certain proportion of the products covered within a pre-specified acceptance interval. Depending on the nature of the quality attributes, the corresponding acceptance interval could be one-sided or two-sided. Thus, the tolerance intervals can also be one-sided or two-sided. To better utilize tolerance intervals for quality assurance, we reviewed the computation method and studied their statistical properties in terms of batch acceptance probability in this article. We also illustrate the application of one-sided and two-sided tolerance, as well as two one-sided tests through the examples of dose content uniformity test, delivered dose uniformity test, and dissolution test.

Statistical evaluation of several methods for cut-point determination of immunogenicity screening assay.

The cut point of the immunogenicity screening assay is the level of response of the immunogenicity screening assay at or above which a sample is defined to be positive and below which it is defined to be negative. The Food and Drug Administration Guidance for Industry on Assay Development for Immunogenicity Testing of Therapeutic recommends the cut point to be an upper 95 percentile of the negative control patients. In this article, we assume that the assay data are a random sample from a normal distribution. The sample normal percentile is a point estimate with a variability that decreases with the increase of sample size. Therefore, the sample percentile does not assure at least 5% false-positive rate (FPR) with a high confidence level (e.g., 90%) when the sample size is not sufficiently enough. With this concern, we propose to use a lower confidence limit for a percentile as the cut point instead. We have conducted an extensive literature review on the estimation of the statistical cut point and compare several selected methods for the immunogenicity screening assay cut-point determination in terms of bias, the coverage probability, and FPR. The selected methods evaluated for the immunogenicity screening assay cut-point determination are sample normal percentile, the exact lower confidence limit of a normal percentile (Chakraborti and Li, 2007) and the approximate lower confidence limit of a normal percentile. It is shown that the actual coverage probability for the lower confidence limit of a normal percentile using approximate normal method is much larger than the required confidence level with a small number of assays conducted in practice. We recommend using the exact lower confidence limit of a normal percentile for cut-point determination.

Dissolution curve comparisons through the F(2) parameter, a Bayesian extension of the f(2) statistic.

Dissolution (or in vitro release) studies constitute an important aspect of pharmaceutical drug development. One important use of such studies is for justifying a biowaiver for post-approval changes which requires establishing equivalence between the new and old product. We propose a statistically rigorous modeling approach for this purpose based on the estimation of what we refer to as the F2 parameter, an extension of the commonly used f2 statistic. A Bayesian test procedure is proposed in relation to a set of composite hypotheses that capture the similarity requirement on the absolute mean differences between test and reference dissolution profiles. Several examples are provided to illustrate the application. Results of our simulation study comparing the performance of f2 and the proposed method show that our Bayesian approach is comparable to or in many cases superior to the f2 statistic as a decision rule. Further useful extensions of the method, such as the use of continuous-time dissolution modeling, are considered.

Statistical considerations in setting product specifications.

According to ICH Q6A (1999), a specification is defined as a list of tests, references to analytical procedures, and appropriate acceptance criteria, which are numerical limits, ranges, or other criteria for the tests described. For drug products, specifications usually consist of test methods and acceptance criteria for assay, impurities, pH, dissolution, moisture, and microbial limits, depending on the dosage forms. They are usually proposed by the manufacturers and subject to the regulatory approval for use. When the acceptance criteria in product specifications cannot be pre-defined based on prior knowledge, the conventional approach is to use data from a limited number of clinical batches during the clinical development phases. Often in time, such acceptance criterion is set as an interval bounded by the sample mean plus and minus two to four standard deviations. This interval may be revised with the accumulated data collected from released batches after drug approval. In this article, we describe and discuss the statistical issues of commonly used approaches in setting or revising specifications (usually tighten the limits), including reference interval, (Min, Max) method, tolerance interval, and confidence limit of percentiles. We also compare their performance in terms of the interval width and the intended coverage. Based on our study results and review experiences, we make some recommendations on how to select the appropriate statistical methods in setting product specifications to better ensure the product quality.

A practical discussion of risk management for manufacturing of pharmaceutical products.

Quality risk management (QRM) is now a regulatory expectation, and it makes good business sense. The goal of the risk assessment is to increase process understanding and deliver safe and effective product to the patients. Risk analysis and management is an acceptable and effective way to minimize patient risk and determine the appropriate level of controls in manufacturing. While understanding the elements of QRM is important, knowing how to apply them in the manufacturing environment is essential for effective process performance and control. This article will preview application of QRM in pharmaceutical and biopharmaceutical manufacturing to illustrate how QRM can help the reader achieve that objective. There are several areas of risk that a drug company may encounter in pharmaceutical manufacturing, specifically addressing oral solid and liquid formulations. QRM tools can be used effectively to identify the risks and develop strategy to minimize or control them. Risks are associated throughout the biopharmaceutical manufacturing process-from raw material supply through manufacturing and filling operations to final distribution via a controlled cold chain process. Assessing relevant attributes and risks for biotechnology-derived products is more complicated and challenging for complex pharmaceuticals. This paper discusses key risk factors in biopharmaceutical manufacturing. LAY ABSTRACT: Successful development and commercialization of pharmaceutical products is all about managing risks. If a company was to take zero risk, most likely the path to commercialization would not be commercially viable. On the other hand, if the risk taken was too much, the product is likely to have a suboptimal safety and efficacy profile and thus is unlikely to be a successful product. This article addresses the topic of quality risk management with the key objective of minimizing patient risk while creating an optimal process and product. Various tools are presented to aid implementation of these concepts.