Endeavours made by trade associations, pharmaceutical companies and regulators in the replacement, reduction and refinement of animal experimentation in safety testing of pharmaceuticals.

Following the European Commission decision to develop a roadmap to phase out animal testing and the signing of the US Modernisation Act, there is additional pressure on regulators and the pharmaceutical industry to abandon animal experimentation in safety testing. Often, endeavours already made by governments, regulators, trade associations, and industry to replace, reduce and refine animal experimentation (3Rs) are unnoticed. Herein, we review such endeavours to promote wider application and acceptance of 3Rs. ICH guidelines have stated 3Rs objectives and have enjoyed many successes driven by global consensus. Initiatives driven by US and European regulators such as the removal of the Abnormal Toxicity Test are neutralised by reticent regional regulators. Stream-lined testing requirements have been proposed for new modalities, oncology, impurity management and animal pharmacokinetics/metabolism. Use of virtual controls, value of the second toxicity species, information sharing and expectations for life-threatening diseases, human specific or well-characterised targets are currently being scrutinised. Despite much effort, progress falls short of the ambitious intent of decisionmakers. From a clinical safety and litigation perspective pharmaceutical companies and regulators are reluctant to step away from current paradigms unless replacement approaches are validated and globally accepted. Such consensus has historically been best achieved through ICH initiatives.

Reusable vs Single Use: what Are the Device Trade-Offs in Improving Sustainability.

As autoinjector requirements become increasingly diverse and pharma companies look for quicker routes to market, with lower costs and improved sustainability, there is an increasing trend towards devices with a reusable element. The flexibility in reusable elements can be beneficial for pharma companies with access to these platforms, allowing a relatively rapid transition between different drug combinations. However, it can also lead to devices designed to cover a wide range of requirements which are over designed for their actual more limited end use. The challenge of creating both a cost and sustainability optimised platform device is significantly harder than if developing a single use device with a specific purpose in mind. This paper looks at the range of reusable products on the market, examining some of the assertions around the cost and sustainability benefits of these devices as well as where there are trade-offs relative to current single use format devices.

An Insight Into Risk Assessment and Reformulation of Drug Products Manufactured Using Benzene Grade Carbomer: A Regulatory Perspective.

Cancer has been an enormous pain point for patients and regulatory bodies across the globe. In Dec. 2023, the US FDA released guidance on benzene-grade carbomer formulations, which triggered pharmaceutical manufacturers to assess risk, test finished products, and reformulate drug products with benzene-grade carbomer. The immediate implementation of the stoppage of finished products with benzene-grade carbomers has threatened pharmaceutical excipients and finished product manufacturers. The gravity of this situation prompted the US Pharmacopeia to extend the deadline for discontinuation from August 1, 2025, to August 1, 2026, allowing manufacturers ample time for reformulation and regulatory compliance.There is an immediate need to understand the guidance and to learn how manufacturers should do the risk assessment and approach reformulation. This review provides an in-depth analysis of the risk assessment and reformulation processes involved in various dosage forms utilizing benzene-grade carbomer, supported by specific case studies.This review offers insights into navigating the USFDA guidelines to ensure formulation safety and compliance, thus enabling pharmaceutical practitioners to uphold the highest standards of patient care and tackle life cycle management challenges.The decision of the USFDA to restrict the usage of high benzene content of carbomer in the formulation is a welcome move. This article has shown a way for researchers to see opportunities in the path and provide best-in-class medicines to patients with a better formulation safety profile.

Statistical Signal Detection Algorithm in Safety Data: A Proprietary Method Compared to Industry Standard Methods.

INTRODUCTION: Several quantitative methods have been established, in pharmacovigilance, to detect signals of disproportionate reporting (SDRs) from databases containing reports of adverse drug reactions (ADRs). The signal detection algorithms (SDAs) and the source of the reporting per product vary, but it is unclear whether any algorithm can provide satisfactory performance using data with such large variance factors. OBJECTIVE: Determine the appropriate SDA for Biogen's internal Global Safety Database (GSD) given the characteristics of the database including frequencies of events, data skewness, outliers, and missing information. Compare performance of standard approaches (EBGM, EB05, PRR, and ROR), well accepted by industry, to a Biogen-developed Machine Learning (ML) Regression Decision Tree (RDT) model, across several Biogen products, to determine a champion SDA. METHODS: All data associated with seven marketed Biogen products were chosen and a historical subset of reported ADRs were considered. Six SDAs (five common industry disproportionality methods) and RDT were evaluated. The SDRs were calculated on training and test data composed of quarterly reporting intervals from 2004-2019. The performance measures used were sensitivity, precision, time to detect new events, and frequency of detected cases for each algorithm for each product. Outcomes in the test data are known a priori and easily compared to predicted outcomes. Validation was performed via rates of misclassification. This work solely represents Biogen's internal information, intentionally chosen to serve the performance review of its signal detection systems, and results will not necessarily be generalizable to other external sources. RESULTS: Several algorithms performed differently among products, but no one method dominated any other. Performance was dependent on the thresholds used to define a signal according to different criteria. However, those different statistics subtly influenced the achievable performance. The relative performance of RDT and Medicines and Healthcare products Regulatory Agency (MHRA) algorithms were superior and paired across products. A reduction in precision for all methods spanning the products was present. Hence, companies evaluating signal detection approaches, search for innovative methods to minimize this effect. CONCLUSIONS: In designing signal detection systems, careful consideration should be given to the criteria that are used to define SDRs. The choice of disproportionality statistics does not affect the achievable range of signal detection performance. These choices should consider mainly ease of implementation and interpretation. The implementation of a method is specific to its accuracy. The RDT attempted to take advantage of known methods and compare results on a per-product basis. Many factors influencing ADRs may improve RDT in future efforts. In this experiment, RDT demonstrated superiority in terms of quickest time to detect and capturing of the highest number of ADRs. Next steps include expansion of data for products representing other indications and testing models in external databases to investigate generalizability of estimates when comparing SDAs.

Recommendations for Development and Validation of a Fit-For-Purpose Biomarker Assays Using Western Blotting; An-AAPS Sponsored Initiative to Harmonize Industry Practices.

Western blot (WB) assays are routinely used for detection and quantification of biomarkers. Although assay validation to measure biomarkers in complex matrices has become a mainstay process for ligand binding assays (LBA) and mass spectrometry (MS), no guidelines exist yet validate biomarker methods using WB techniques. In this cross-industry white paper, we outlined in detail the key steps for development and for validation of WB assays for protein biomarkers under different contexts of use (COU). In addition, we described how to determine the level of assay validation needed for biomarker assays using Western blotting. For simplicity, we described two paths of WB assay validation. The first path (Path 1) is for biomarkers being analyzed for exploratory research or for internal go- or no/go- decision making. The second path (Path 2) is for clinical decision making such as dose determination or drug response that need to be run in a regulated environment. This work is supported through AAPS Biomarkers and Precision Medicine subteam and represents AAPS members opinion.

Industry perspective on regulatory authority (RA) quality reviews of biosimilar applications - an evaluation of RA guidance and expectations for chemical, manufacturing, and controls information through in-depth query analysis.

PURPOSE: Evaluate the type and quantity of quality information (i.e. Chemistry, Manufacturing, and Control) requested by the US FDA and EMA in queries pertaining to biosimilar applications. METHODS: Numbers/types of queries received following regulatory submissions (FDA/EMA, n = 7/n = 5) for seven biosimilars (PF-filgrastim [Nivestym], PF-rituximab [Ruxience®], PF-trastuzumab [Trazimera®], PF-bevacizumab [Zirabev®], PF-pegfilgrastim [Nyvepria®], PF-adalimumab [Abrilada™/Amsparity®], PF-infliximab [Ixifi]) from a single product portfolio were analyzed considering published regulatory authority (RA) guidance and in relation to sections/subsections of Module 3: Quality from the Common Technical Document regulatory dossier and topics based on keyword assignment. RESULTS: Queries were most frequently assigned (FDA/EMA %, range) to Drug Substance Manufacture (subsection 3.2.S.2; 21-35%/13-50%), Control of Drug Substance (3.2.S.4; 3-11%/5-17%), Drug Product Pharmaceutical Development (3.2.P.2; 1-12%/1-15%) and Manufacture (3.2.P.3; 17-41%/2-13%), and Analytical Similarity (3.2.R; 4-21%/4-20%). The proportion of Drug Substance and Drug Product queries was significantly different between RAs (n1 = 952, n2 = 468, p-value <0.001; two-sample proportion z-test). Topic assignments included: Control (12-27%/12-28%), Manufacturing (56-72%/34-66%), Stability (1-12%/2-24%), Biosimilarity (5-16%/5-25%), and Container Closure (0-3%/0-9%). CONCLUSION: The focus of both RAs on topics related to manufacturing and controls is valuable in understanding expectations for scientific and technical content related to gaining biosimilar approval.

Leveraging AI and Machine Learning in Six-Sigma Documentation for Pharmaceutical Quality Assurance.

The pharmaceutical industry must maintain stringent quality assurance standards to ensure product safety and regulatory compliance. A key component of the well-known Six Sigma methodology for process improvement and quality control is precise and comprehensive documentation. However, there are a number of significant issues with traditional documentation procedures, including as slowness, human error, and difficulties with regulatory standards. This review research looks at innovative ways to employ machine learning (ML) and artificial intelligence (AI) to enhance Six Sigma documentation processes in the pharmaceutical sector. AI and ML provide cutting-edge technologies that have the potential to drastically alter documentation processes by automating data entry, collection, and analysis. Natural language processing (NLP) and computer vision technologies have the potential to significantly reduce human error rates and increase the efficacy of documentation processes. By applying machine learning algorithms to support real-time data analysis, predictive analytics, and proactive quality management, pharmaceutical organizations may be able to identify potential quality issues early on and take proactive efforts to address them. Combining AI and ML improves documentation accuracy and reliability while also strengthening compliance with stringent regulatory criteria. The primary barriers and limitations to the current state of Six Sigma documentation in the pharmaceutical industry are identified in this study. It examines the fundamentals of AI and ML with an emphasis on their specific applications in quality assurance and potential benefits for Six Sigma processes. The report includes extensive case studies that highlight notable developments and explain how AI/ML enhanced documentation is used in the real world.

[Application of process analysis technology in traditional Chinese medicine manufacturing industry].

In the traditional Chinese medicine(TCM) manufacturing industry, quality control determines the safety, effectiveness, and quality stability of the final product. The traditional quality control method generally carries out sampling off-line testing of drugs after the end of the batch production, which is incomprehensive, and it fails to find the problems in the production process in time. Process analysis technology(PAT) uses process testing, mathematical modeling, data analysis, and other technologies to collect, analyze, feedback, control, and continuously improve the critical quality attributes(CQA) in all aspects of the production of TCM preparations in real time. The application of PAT in the TCM manufacturing industry is one of the research hotspots in recent years, which has the advantages of real-time, systematic, non-destructive, green, and rapid detection for the production quality control of TCM preparations. It can effectively ensure the stability of the quality of TCM preparations, improve production efficiency, and play a key role in the study of the quantity and quality transfer law of TCM. Commonly used PAT includes near-infrared spectroscopy, Raman spectroscopy, online microwave, etc. In addition, the establishment of an online detection model by PAT is the key basic work to realize intelligent manufacturing in TCM production. Obtaining real-time online detection data through PAT and establishing a closed-loop control model on this basis are a key common technical difficulty in the industry. This paper adopted systematic literature analysis to summarize the relevant Chinese and foreign literature, policies and regulations, and production applications, and it introduced the development trend and practical application of PAT, so as to provide references for accelerating the application of PAT in the TCM manufacturing industry, the intelligent transformation and upgrading, and high-quality development of the TCM industry.

Comparison of permitted daily exposure (PDE) values for active pharmaceutical ingredients (APIs) - Evidence of a robust approach.

Permitted Daily Exposure Limits (PDEs) are set for Active Pharmaceutical Ingredients (APIs) to control cross-contamination when manufacturing medicinal products in shared facilities. With the lack of official PDE lists for pharmaceuticals, PDEs have to be set by each company separately. Although general rules and guidelines for the setting of PDEs exist, inter-company variations in the setting of PDEs occur and are considered acceptable within a certain range. To evaluate the robustness of the PDE approach between different pharmaceutical companies, data on PDE setting of five marketed APIs (amlodipine, hydrochlorothiazide, metformin, morphine, and omeprazole) were collected and compared. Findings show that the variability between PDE values is within acceptable ranges (below 10-fold) for all compounds, with the highest difference for morphine due to different Point of Departures (PODs) and Adjustment Factors (AFs). Factors of PDE variability identified and further discussed are: (1) availability of data, (2) selection of POD, (3) assignment of AFs, (4) route-to-route extrapolation, and (5) expert judgement and differences in company policies. We conclude that the investigated PDE methods and calculations are robust and scientifically defensible. Additionally, we provide further recommendations to harmonize PDE calculation approaches across the pharmaceutical industry.

Growing value of data standardization: Allotrope Foundation Connect Workshop Proceedings.

Recent Allotrope Foundation (AF) Connect Workshops (2021-2023) showcased some of the latest advancements in data standardization for analytical data in the pharmaceutical industry. These workshops demonstrated the adaption of two key technologies, the Allotrope Data Format (ADF) and the Allotrope Simple Model (ASM), which streamline instrument data representation and terminology to enhance interoperability across systems. Notably, ASM has facilitated broader adoption of the standard. The increasing significance of data-driven decision-making in the life sciences is underscored by the evolving landscape of open-source solutions and commercial implementations, as demonstrated by industry leaders adopting these standards. Here, we highlight selected examples that illustrate the collective efforts of the community in advancing data standards and data management in the life sciences.

A retrospective regulatory analysis of FDA recalls carried out by pharmaceutical companies from 2012 to 2023.

To introduce products in the US market, pharmaceutical companies must first obtain FDA clearance. Manufacturers might recall a product if it poses a risk of damage or violates FDA regulations. This study investigates the types, causes and consequences of recalls, as well as FDA participation and suitable recall strategies. We relied on the FDA website to gather recall data sets from 2012 to 2023, collecting information on the date of issuance, company and type of violation. The most frequent causes for recalls were sterility issues and inadequate compliance with current good manufacturing practices (cGMP). An examination of sterility recalls revealed two primary causes: a lack of assurance in sterility (accounting for 48% of recalls) and instances of non-sterility (making up 45% of recalls). A thorough examination of cGMP recalls revealed five primary types of violations: process control issues, inadequate storage practices, manufacturing problems, the presence of nitroso-amine impurities and concerns regarding stability. The findings demonstrate that sterility and cGMP compliance are FDA priorities. Pharmaceutical companies must, therefore, enhance quality compliance and create effective quality management systems that oversee the manufacturing process, quality control, personnel training and documentation to avoid these recalls. Companies should establish an internal compliance checklist and be prepared for the rectification process.

In-lab synthesized turn-off fluorescence sensor for estimation of Gemigliptin and Rosuvastatin polypill appraised by Spider diagram, AGREE and whiteness metrics.

Gemigliptin-Rosuvastatin single-pill combination is a promising therapeutic tool in the effective control of hyperglycemia and hypercholesterolemia. Organic sensors with high quantum yields have profoundly significant applications in the pharmaceutical industry, such as routine quality control of marketed formulations. Herein, the fluorescence sensor, 2-Morpholino-4,6-dimethyl nicotinonitrile 3, (λex; 226 nm, λem; 406 nm), was synthesized with a fluorescence quantum yield of 56.86% and fully characterized in our laboratory. This sensor showed high efficiency for the determination of Gemigliptin (GEM) and Rosuvastatin (RSV) traces through their stoichiometric interactions and simultaneously fractionated by selective solvation. The interaction between the stated analytes and sensor 3 was a quenching effect. Various experimental parameters and the turn-off mechanism were addressed. The adopted approach fulfilled the ICH validation criteria and showed linear satisfactory ranges, 0.2-2 and 0.1-1 µg/mL for GEM and RSV, respectively with nano-limits of detection less than 30 ng/mL for both analytes. The synthesized sensor has been successfully applied for GEM and RSV co-assessment in their synthetic polypill with excellent % recoveries of 98.83 ± 0.86 and 100.19 ± 0.64, respectively. No statistically significant difference between the results of the proposed and reported spectrophotometric methods in terms of the F- and t-tests. Ecological and whiteness appraisals of the proposed study were conducted via three novel approaches: the Greenness Index via Spider Diagram, the Analytical Greenness Metric, and the Red-Green-Blue 12 model. The aforementioned metrics proved the superiority of the adopted approach over the previously published one regarding eco-friendliness and sustainability. Our devised fluorimetric turn-off sensing method showed high sensitivity, selectivity, feasibility, and rapidity with minimal cost and environmental burden over other sophisticated techniques, making it reliable in quality control labs.

[Problems and thoughts in clinical safety evaluation of traditional Chinese medicine].

Amid the modernization and internationalization of traditional Chinese medicine(TCM), the safety of TCM has attracted much attention. At the moment, the government, scientific research teams, and pharmaceutical enterprises have made great efforts to explore methods and techniques for clinical safety evaluation of TCM. Although considerable achievements have been made, there are still many problems, such as the non-standard terms of adverse reactions of TCM, unclear evaluation indicators, unreasonable judgment methods, lack of evaluation models, out-of-date evaluation standards, and unsound reporting systems. Therefore, it is urgent to further deepen the research mode and method of clinical safety evaluation of TCM. Based on the current national requirements for the life-cycle management of drugs, this study focused on the problems in the five dimensions of clinical safety evaluation of TCM, including normative terms, evaluation modes, judgment methods, evaluation standards, and reporting systems, and proposed suggestions on the development of a life-cycle clinical safety evaluation method that conformed to the characteristics of TCM, hoping to provide a reference for future research.

Data integrity issues in pharmaceutical industry: Common observations, challenges and mitigations strategies.

Data integrity (DI) reaffirms the pharmaceutical industry's commitment to manufacture drugs that are safe, effective and fulfil quality standards. At the same time, DI is a crucial tool for regulatory authorities to use in protecting public health. Recent FDA Form-483 observations and warning letters indicate that DI is the main issue the pharmaceutical industry is currently dealing with. Failure to comply with DI requirements may result in a high number of un-validated results, which may cause post-marketing issues and frequent product recalls. To address the underlying causes of DI problems, a comprehensive approach is necessary. The majority of DI issues are caused by poor quality culture, organizational or individual behaviour, leadership, processes, or technology. DI should be effectively integrated into the quality management system, and it should apply to both paper and electronic records. Employees should be trained on 21 CFR Part 11. Consistent review and audit are required to ensure that procedures are followed and audit trails are generated. Electronic systems, in addition to being an efficient solution (system integration, data verification at both input and output, security), offer advantages over traditional paper-based systems in terms of improved compliance with DI regulatory requirements. For example, many electronic system platforms provide enhanced security features and audit trail capabilities. Finally, management support for data governance is essential for successful implementation of DI. This article reviews commonly observed deviations by FDA pertaining to DI and discusses measures to be undertaken to avoid them.

The default of 1998 and pharmaceutical market. Report I. The chronicle of disaster.

The researchers, in series of articles, analyze significance of the default of 1998 for both pharmaceutical industry and participants of pharmaceutical market. The Report I presents results of investigation of corresponding economic and social aspects of issue. The article presents contradictions in tax and financial policies of then ruling authorities; regulatory drawbacks created by inefficient awareness of economic situation and social specificity of pharmaceutics; means for pharmaceutical companies to survive in these conditions.

Interchangeability of biosimilars: A study of expert views and visions regarding the science and substitution.

Healthcare systems have reached a critical point regarding the question of whether biosimilar substitution should become common practice. To move the discussion forward, the study objective was to investigate the views of experts from medicines agencies and the pharmaceutical industry on the science underpinning interchangeability of biosimilars. We conducted an empirical qualitative study using semi-structured interviews informed by a cross-disciplinary approach encompassing regulatory science, law, and pharmaceutical policy. In total 25 individuals with experience within biologics participated during September 2018-August 2019. Eight participants were EU national medicines authority regulators, and 17 had pharmaceutical industry background: five from two originator-only companies, four from two companies with both biosimilar and originator products, and eight from seven biosimilar-only companies. Two analysts independently conducted inductive content analysis, resulting in data-driven themes capturing the meaning of the data. The participants reported that interchangeability was more than a scientific question of likeness between biosimilar and reference products: it also pertained to regulatory practices and trust. Participants were overall confident in the science behind exchanging biosimilar products for the reference products via switching, i.e., with physician involvement. However, their opinions differed regarding the scientific risk associated with biosimilar substitution, i.e., without physician involvement. Almost all participants saw no need for additional scientific data to support substitution. Moreover, the participants did not believe that switching studies, as required in the US, were appropriate for obtaining scientific certainty due to their small size. It is unclear why biosimilar switching is viewed as scientifically safer than substitution; therefore, we expect greater policy debate on biosimilar substitution in the near future. We urge European and UK policymakers and regulators to clarify their visions for biosimilar substitution; the positions of these two frontrunners are likely to influence other jurisdictions on the future of biosimilar use.

PDE concept for controlling cleaning agent residues in pharmaceuticals- A critical analysis.

Cleaning agents (CAs) are used in multipurpose facilities to control carryover contamination of active pharmaceutical ingredients (APIs) to scientifically justified limits. While this is often done with the PDE methodology used for API impurities, it is unclear if it is justifiable and necessary for cleaning agents, which generally represent a comparatively lower health risk. Comparing calculated oral PDE values for CA ingredients (CAIs) from four companies with PDEs of a selected number of small-molecule APIs showed that the toxicity of CAIs is several orders of magnitude lower. Furthermore, a critical review of the toxicity and everyday exposure to the general population of the main CAIs functional groups showed that the expected health risks are generally negligible. This is particularly true if the associated mode of actions cause local toxicity that is usually irrelevant at the concentration of potential residue carryover. This work points towards alternative approaches to the PDE concept to control CAIs' contamination and provides some guidance on grouping and identifying compounds with lower health risks based on exposure and mode of action reasoning. In addition, this work supports the concept that limit values should only be set for CAIs of toxicological concern.

Meeting report: an exploration into the scientific and regulatory aspects of pharmaceutical drug quality in the United States.

INTRODUCTION: The University of Florida College of Pharmacy, Department of Pharmaceutical Outcomes and Policy hosted a seminar 6-7 March 2021, on the quality of pharmaceutical products in the United States. This meeting report summarizes the topics presented at the seminar and highlights the expert opinions offered by the presenters. AREAS COVERED: The seminar, held virtually due to the COVID-19 pandemic, included slide presentations and faculty-moderated panel discussions from experts in the field. These experts from regulatory, academic, and private sectors discussed bioequivalence standards, existing and emerging efforts to promote quality in brand and generic manufacturing, as well as market-based solutions throughout the drug supply chain. EXPERT OPINION: The time spent understanding bioequivalence standards during the seminar felt especially important and relevant in our current pandemic environment, given the present need to have confidence in the science of drug development and to advocate for the safety of pharmaceuticals. Also an important point to emphasize from the seminar, was that every stakeholder along the drug supply chain has a responsibility to do their part to maintain its quality. And those in attendance, many of whom were students of healthcare sciences, were encouraged to be leaders in their fields and develop strategies to advance innovative improvements.