Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report.

Physiologically based biopharmaceutics modeling (PBBM) is used to elevate drug product quality by providing a more accurate and holistic understanding of how drugs interact with the human body. These models are based on the integration of physiological, pharmacological, and pharmaceutical data to simulate and predict drug behavior in vivo. Effective utilization of PBBM requires a consistent approach to model development, verification, validation, and application. Currently, only one country has a draft guidance document for PBBM, whereas other major regulatory authorities have had limited experience with the review of PBBM. To address this gap, industry submitted confidential PBBM case studies to be reviewed by the regulatory agencies; software companies committed to training. PBBM cases were independently and collaboratively discussed by regulators, and academic colleagues participated in some of the discussions. Successful bioequivalence "safe space" industry case examples are also presented. Overall, six regulatory agencies were involved in the case study exercises, including ANVISA, FDA, Health Canada, MHRA, PMDA, and EMA (experts from Belgium, Germany, Norway, Portugal, Spain, and Sweden), and we believe this is the first time such a collaboration has taken place. The outcomes were presented at this workshop, together with a participant survey on the utility and experience with PBBM submissions, to discuss the best scientific practices for developing, validating, and applying PBBMs. The PBBM case studies enabled industry to receive constructive feedback from global regulators and highlighted clear direction for future PBBM submissions for regulatory consideration.

Biopharmaceutics Risk Assessment-Connecting Critical Bioavailability Attributes with In Vitro, In Vivo Properties and Physiologically Based Biopharmaceutics Modeling to Enable Generic Regulatory Submissions.

Quality risk assessment following ICH Q9 principles is an important activity to ensure optimal clinical efficacy and safety of a drug product. Typically, risk assessment is focused on product performance wherein critical material attributes, formulation variables, and process parameters are evaluated from a manufacturing perspective. Extending ICH Q9 principles to biopharmaceutics risk assessment to identify factors that can impact in vivo performance is an upcoming area. This is evident by recent regulatory trends wherein a new term critical bioavailability attributes (CBA) has been coined to identify such factors. Although significant work has been performed for biopharmaceutics risk assessment for new molecules, there is a need for harmonized biopharmaceutics risk assessment workflow for generic submissions. In this manuscript, we attempted to provide a framework for performing biopharmaceutics risk assessment for generic regulatory submissions. A detailed workflow for performing biopharmaceutics risk assessment includes identification of initial CBA (iCBA), their confirmatory evaluation followed by definition of the control strategy. Tools for biopharmaceutics risk assessment, i.e., bio-discriminatory dissolution method and physiologically based biopharmaceutics modeling (PBBM) were discussed from a practical perspective. Furthermore, a case study for CBA evaluation using PBBM modeling for an extended-release product for regulatory submission has been described using the proposed workflow. Finally, future directions of integrating CBA evaluation, biopharmaceutics risk assessment to the FDA Knowledge Aided Structured Assessment (KASA) initiative, the necessity of risk assessment templates, and knowledge sharing between industry and academia are discussed. Overall, the work described in this manuscript can facilitate and provide guidance for biopharmaceutics risk assessment for generic submissions.

Current State and Challenges of Physiologically Based Biopharmaceutics Modeling (PBBM) in Oral Drug Product Development.

Physiologically based biopharmaceutics modeling (PBBM) emphasizes the integration of physicochemical properties of drug substance and formulation characteristics with system physiological parameters to predict the absorption and pharmacokinetics (PK) of a drug product. PBBM has been successfully utilized in drug development from discovery to postapproval stages and covers a variety of applications. The use of PBBM facilitates drug development and can reduce the number of preclinical and clinical studies. In this review, we summarized the major applications of PBBM, which are classified into six categories: formulation selection and development, biopredictive dissolution method development, biopharmaceutics risk assessment, clinically relevant specification settings, food effect evaluation and pH-dependent drug-drug-interaction risk assessment. The current state of PBBM applications is illustrated with examples from published studies for each category of application. Despite the variety of PBBM applications, there are still many hurdles limiting the use of PBBM in drug development, that are associated with the complexity of gastrointestinal and human physiology, the knowledge gap between the in vitro and the in vivo behavior of drug products, the limitations of model interfaces, and the lack of agreed model validation criteria, among other issues. The challenges and essential considerations related to the use of PBBM are discussed in a question-based format along with the scientific thinking on future research directions. We hope this review can foster open discussions between the pharmaceutical industry and regulatory agencies and encourage collaborative research to fill the gaps, with the ultimate goal to maximize the applications of PBBM in oral drug product development.

Development of a Novel Gastric Process Simulation Model: The Successful Assessment of Bioequivalence and Bioinequivalence of a Biopharmaceutics Classification System Class II Weak Acid Drug.

Bioequivalence has been assessed using in vitro dissolution testing, such as in vivo predictive dissolution methodology. However, the assessment of bioequivalence should be performed carefully, considering the effect of the in vivo environment and according to the properties of the drug. The gastric emptying process is a key factor for the assessment of biopharmaceutics classification system class II (BCS class IIa) drugs with acidic properties since they cannot dissolve in the acidic stomach, but do dissolve in the small intestine (SI). The disintegration of a tablet in the stomach affects the distribution/dissolution in the SI due to the difference in the gastric emptying step, which in turn is a result of the varying formulation of the drugs. In this study, we used the reported dynamic pH change method and a novel gastric process simulation (GPS) model, which can compare the gastric emptying of particular-sized drug particles. The in vitro results were compared to clinical data using bioequivalent and bioinequivalent products of candesartan cilexetil. It was revealed that the dynamic pH change method was inappropriate, whereas the amount of filtered drug in GPS studies with 20 and 50 µm pore size filters could reflect the clinical results of all products. The evaluation of the gastric emptying process of drug particles less than 50 µm enabled us to assess the bioequivalence because they probably caused the difference in the distribution in the SI. This study demonstrated the utility of the GPS model for the assessment of bioequivalence of BCS class IIa drugs.

Denaturing and Native Mass Spectrometric Analytics for Biotherapeutic Drug Discovery Research: Historical, Current, and Future Personal Perspectives.

Mass spectrometry (MS) plays a key role throughout all stages of drug development and is now as ubiquitous as other analytical techniques such as surface plasmon resonance, nuclear magnetic resonance, and supercritical fluid chromatography, among others. Herein, we aim to discuss the history of MS, both electrospray and matrix-assisted laser desorption ionization, specifically for the analysis of antibodies, evolving through to denaturing and native-MS analysis of newer biologic moieties such as antibody-drug conjugates, multispecific antibodies, and interfering nucleic acid-based therapies. We discuss challenging therapeutic target characterization such as membrane protein receptors. Importantly, we compare and contrast the MS and hyphenated analytical chromatographic methods used to characterize these therapeutic modalities and targets within biopharmaceutical research and highlight the importance of appropriate MS deconvolution software and its essential contribution to project progression. Finally, we describe emerging applications and MS technologies that are still predominantly within either a development or academic stage of use but are poised to have significant impact on future drug development within the biopharmaceutic industry once matured. The views reflected herein are personal and are not meant to be an exhaustive list of all relevant MS performed within biopharmaceutical research but are what we feel have been historically, are currently, and will be in the future the most impactful for the drug development process.

CART manufacturing process and reasons for academy-pharma collaboration.

The success of genetically engineered T-cells modified with a chimeric antigen receptor as an adoptive cell immunotherapy and the subsequent last regulatory approvals of products based on this therapy are leading to a crescent number of both academic and pharmaceutical industry clinical trials testing new approaches of this "living drugs". The aim of this review is to outline the latest developments and regulatory considerations in this field, with a particular emphasis to differences and similarities between academic and industry approaches and the role they should play to coexist and move forward together. To do that, the main considerations for the manufacturing process are firstly discussed, from the chimeric antigen receptor design to final production steps, passing through ex vivo T-cell handling, gene delivery methods, patient´s final product infusion observations or possible associated side effects of this treatment.

A Comparison Between Emerging and Current Biophysical Methods for the Assessment of Higher-Order Structure of Biopharmaceuticals.

The higher-order structure (HOS) of protein therapeutics is a critical quality attribute directly related to their function. Traditionally, the HOS of protein therapeutics has been characterized by methods with low to medium structural resolution such as Fourier-transform infrared (FTIR), circular dichroism (CD), and intrinsic fluorescence spectroscopy, and differential scanning calorimetry (DSC). Recently, high-resolution nuclear magnetic resonance (NMR) methods have emerged as powerful tools for HOS characterization. NMR is a multi-attribute method with unique capabilities to provide information about all the structural levels of proteins in solution. We have in this study compared 1 D 1H Profile NMR with the established biophysical methods for HOS assessments using a set of blended samples of the monoclonal antibodies belonging to the subclasses IgG1 and IgG2. The study shows that Profile NMR can distinguish between most sample combinations (93%), DSC can differentiate 61% of the sample combinations, and near-ultraviolet CD spectroscopy can differentiate 52% of the sample combinations, whereas no significant distinction could be made between any samples using FTIR or intrinsic fluorescence. Our data therefore show that NMR has superior ability to address differences in HOS, a feature that could be directly applicable in comparability and similarity assessments.

In vivo models and decision trees for formulation development in early drug development: A review of current practices and recommendations for biopharmaceutical development.

The ability to predict new chemical entity performance using in vivo animal models has been under investigation for more than two decades. Pharmaceutical companies use their own strategies to make decisions on the most appropriate formulation starting early in development. In this paper the biopharmaceutical decision trees available in four EFPIA partners (Bayer, Boehringer Ingelheim, Bristol Meyers Squibb and Janssen) were discussed by 7 companies of which 4 had no decision tree currently defined. The strengths, weaknesses and opportunities for improvement are discussed for each decision tree. Both pharmacokineticists and preformulation scientists at the drug discovery & development interface responsible for lead optimization and candidate selection contributed to an overall picture of how formulation decisions are progressed. A small data set containing compound information from the database designed for the IMI funded OrBiTo project is examined for interrelationships between measured physicochemical, dissolution and relative bioavailability parameters. In vivo behavior of the drug substance and its formulation in First in human (FIH) studies cannot always be well predicted from in vitro and/or in silico tools alone at the time of selection of a new chemical entity (NCE). Early identification of the risks, challenges and strategies to prepare for formulations that provide sufficient preclinical exposure in animal toxicology studies and in FIH clinical trials is needed and represents an essential part of the IMI funded OrBiTo project. This article offers a perspective on the use of in vivo models and biopharmaceutical decision trees in the development of new oral drug products.

A fast and reliable test for parallelism in bioassay.

Parallelism in bioassay is a synonym of similarity between two concentration-response curves. Before the determination of relative potency in bioassays, it is necessary to test for and claim parallelism between the pair of concentration-response curves of reference standard and test sample. Methods for parallelism testing include p-value-based significance tests and interval-based equivalence tests. Most of the latter approaches make statistical inference about the equivalence of parameters of the concentration-response curve models. An apparent drawback of such methods is that equivalence in model parameters does not guarantee similarity between the reference and test sample. In contrast, a Bayesian method was recently proposed that directly tests the parallelism hypothesis that the concentration-response curve of the test sample is a horizontal shift of that of the reference. In other words, the testing sample is a dilution or concentration of the reference standard. The Bayesian approach is shown to protect against type I error and provides sufficient statistical power for parallelism testing. In practice, however, it is challenging to implement the method as it requires both specialized Bayesian software and a relatively long run time. In this paper, we propose a frequentist version of the test with split-second run time. The empirical properties of the frequentist parallelism test method are evaluated and compared with the original Bayesian method. It is demonstrated that the frequentist method is both fast and reliable for parallelism testing for a variety of concentration-response models.

Implementation of Fully Integrated Continuous Antibody Processing: Effects on Productivity and COGm.

The changing landscape of the biopharmaceutical market is driving a paradigm shift toward continuous manufacturing. To date, integrated continuous bioprocessing has not been realized as enabling technologies are nascent. In this work, a fully integrated continuous process is successfully demonstrated from pilot scale bioreactor to drug substance. Comparable product quality is observed between the continuous process and a 500 L fed-batch conventional process. The continuous process generated material at a rate of 1 kg of purified mAb every 4 days, achieving a 4.6-fold increase in productivity compared to the fed-batch process A plant throughput analysis using BioSolve software shows that a fed-batch facility with 4 × 12 500 L stainless steel bioreactors and purification train of the corresponding scale can be replaced by a continuous facility consisting of 5 × 2000 L single use bioreactors and smaller purification train, with a cost reduction of 15%.

Fifty-Eight Years and Counting: High-Impact Publishing in Computational Pharmaceutical Sciences and Mechanism-Based Modeling.

With this issue of the Journal of Pharmaceutical Sciences, we celebrate the nearly 6 decades of contributions to mechanistic-based modeling and computational pharmaceutical sciences. Along with its predecessor, The Journal of the American Pharmaceutical Association: Scientific Edition first published in 1911, JPharmSci has been a leader in the advancement of pharmaceutical sciences beginning with its inaugural edition in 1961. As one of the first scientific journals focusing on pharmaceutical sciences, JPharmSci has established a reputation for publishing high-quality research articles using computational methods and mechanism-based modeling. The journal's publication record is remarkable. With over 15,000 articles, 3000 notes, and more than 650 reviews from industry, academia, and regulatory agencies around the world, JPharmSci has truly been the leader in advancing pharmaceutical sciences.

Relative Bioavailability Risk Assessment: A Systematic Approach to Assessing In Vivo Risk Associated With CM&C-Related Changes.

Relative bioavailability (RBA) studies are often carried out to bridge changes made between drug products used for clinical studies. In this work, we describe the development of a risk assessment (RA) tool that comprehensively and objectively assesses the risk of noncomparable in vivo performance associated with Chemistry, Manufacturing, and Controls (CM&C)-related changes. The RA tool is based on a risk grid that provides a quantitative context to facilitate discussions to determine the need for an in vivo RBA study. Relevant regulatory guidances and the required in vitro and in silico absorption modeling data, on which the RA is based, are discussed. In addition, an analysis of previously executed RBA studies at Eli Lilly and Company over a period of several years is presented. The risk grid incorporates individual risk factors for a given study and provides a recommendation on the risk associated with bypassing an RBA study. The outcome of an RA results in 1 of 3 possible risk zones; lower tier risk, intermediate tier risk, and upper tier risk. In cases where the outcome from the RA falls into the intermediate tier risk zone, further in depth data analysis is required.

Introduction to the OrBiTo decision tree to select the most appropriate in vitro methodology for release testing of solid oral dosage forms during development.

The EU research initiative OrBiTo (oral biopharmaceutics tools) involving partners from academia, pharmaceutical industry, small medium enterprises and a regulatory agency was launched with the goal of improving tools to predict the absorption of drugs in humans and thereby accelerating the formulation development process. The OrBiTo project was divided into four work packages (WP), with WP2 focusing on characterization of drug formulations. The present work introduces the OrBiTo WP2 Decision Tree, which is designed to assist the investigator in choosing the most appropriate in vitro methods for optimizing the oral formulation design and development process. The WP2 Decision Tree consists of four stages to guide the investigator. At the first stage, the investigator is asked to choose the formulation type of interest. At the second stage, the investigator is asked to identify which type of equipment (compendial/modified/noncompendial) is preferred/available. At the third stage, characteristics of the active pharmaceutical ingredient (API) are evaluated and in the fourth stage of the decision tree, suitable experimental protocols are recommended. A link to the living Decision Tree document is provided, and we now invite the pharmaceutical sciences community to apply it to current research and development projects and offer suggestions for improvement and expansion.

Delivery Considerations of Highly Viscous Polymeric Fluids Mimicking Concentrated Biopharmaceuticals: Assessment of Injectability via Measurement of Total Work Done "WT".

An account is given of the recent development of the highly viscous complex biopharmaceuticals in relation to syringeability and injectability. The specific objective of this study is to establish a convenient method to examine problem of the injectability for the needle-syringe-formulation system when complex formulations with diverse viscosities are used. This work presents the inter-relationship between needle size, syringe volume, viscosity, and injectability of polymeric solutions having typical viscosities encountered in concentrated biologics, by applying a constant probe crosshead speed on the plunger-syringe needle assembly and continuously recording the force-distance profiles. A computerized texture analyzer was used to accurately capture, display, and store force, displacement, and time data. The force-distance curve and area under the curve are determined, and total work done for complete extrusion of the syringe content was calculated automatically by applying an established Matlab program. Various concentrations (i.e., 0.5-4% w/v of polymeric fluids/dispersions) of polyethylene oxide (PEO) and hydroxypropyl methylcellulose (HPMC) with viscosity ranges of 5-100 cP mimicking concentrated monoclonal antibody solutions and complex biopharmaceutical formulations are investigated. Results indicate that calculated values of total work done to completely extrude the syringe content are the most appropriate parameter that describes viscosity-injection force of dispersed formulations. Additionally, the rheological properties of HPMC and PEO fluids in the context of syringeability and injectability are discussed.

What NMR can do in the biopharmaceutical industry.

Nuclear magnetic resonance (NMR) spectroscopy has a unique capability to probe the primary and higher order molecular structure and the structural dynamics of biomolecules at an atomic resolution, and this capability has been greatly fortified over the last five decades by an astonishing NMR instrumental and methodological development. Because of these factors, NMR has become a primary tool for the structure investigation of biomolecules, spawning a whole scientific subfield dedicated to the subject. This role of NMR is by now well established and broadly appreciated, especially in the context of academic research dealing with proteins that are purified and isotope-labeled in order to facilitate the necessary sophisticated multidimensional NMR measurements. However, the more recent industrial development, manufacturing, and quality control of biopharmaceuticals provide a different framework for NMR. For example, protein drug substances are not isotope-labeled and are present in a medium of excipients, which make structural NMR measurements much more difficult. On the other hand, biotechnology involves many other analytical requirements that can be efficiently addressed by NMR. In this respect the scope and limitations of NMR are less well understood. Having the non-expert reader in mind, herein we wish to highlight the ways in which modern NMR can effectively support biotechnological developments. Our focus will be on biosimilar proteins, pointing out certain cases where its use is probably essential. Based partly on literature data, and partly on our own hands-on experience, this paper is intended to be a guide for choosing the proper NMR approach for analytical questions concerning the structural comparability of therapeutic proteins, monitoring technology-related impurities, protein quantification, analysis of spent media, identification of extractable and leachable components, etc. Also, we focus on critical considerations, particularly those coming from drug authority guidelines, which limit the use of the well-established NMR tools in everyday practice.

An Intercompany Perspective on Biopharmaceutical Drug Product Robustness Studies.

The Biophorum Development Group (BPDG) is an industry-wide consortium enabling networking and sharing of best practices for the development of biopharmaceuticals. To gain a better understanding of current industry approaches for establishing biopharmaceutical drug product (DP) robustness, the BPDG-Formulation Point Share group conducted an intercompany collaboration exercise, which included a bench-marking survey and extensive group discussions around the scope, design, and execution of robustness studies. The results of this industry collaboration revealed several key common themes: (1) overall DP robustness is defined by both the formulation and the manufacturing process robustness; (2) robustness integrates the principles of quality by design (QbD); (3) DP robustness is an important factor in setting critical quality attribute control strategies and commercial specifications; (4) most companies employ robustness studies, along with prior knowledge, risk assessments, and statistics, to develop the DP design space; (5) studies are tailored to commercial development needs and the practices of each company. Three case studies further illustrate how a robustness study design for a biopharmaceutical DP balances experimental complexity, statistical power, scientific understanding, and risk assessment to provide the desired product and process knowledge. The BPDG-Formulation Point Share discusses identified industry challenges with regard to biopharmaceutical DP robustness and presents some recommendations for best practices.

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.

Integrating biopharmaceutics risk assessment and in vivo absorption model in formulation development of BCS class I drug using the QbD approach.

OBJECTIVE: Clinically relevant critical quality attributes (CQA's) were identified for the development of generic drug products containing fluconazole and potential design spaces relevant to the clinical application of the drug candidate was explored. SIGNIFICANCE: A simplified scoring system for the biopharmaceutics risk assessment roadmap (BioRAM) is proposed to guide product development. METHODS: Factorial design of experiments was employed to study the effect of formulation and process variables on CQA's. The in vivo model was developed for predicting the fraction of drug absorbed and to identify the effect of formulation components on drug absorption. RESULTS: BioRAM yielded low scores for fluconazole absorption with respect to severity (risks of sub and supra-bioavailable drug products), probability of incidence of bioinequivalent results and capacity of detection. The results demonstrated that dissolution was highly influenced by the active pharmaceutical ingredient (API) polymorphism and the ratio of diluents. Process variables (mixing time, lubricant concentration, lubrication time and filling speed) did not impact the clinical outcome of the formulation with respect to dissolution and content uniformity. CONCLUSIONS: Understanding the clinical implications of the adopted formulation approach led to the construction of purposeful design space and control strategy.