A special panel session at the 2024 NCS Conference in Wiesbaden, Germany, brought together experts to explore the evolving landscape of patient-centric drug product development and specifications. Traditional specifications often rely on manufacturing variability and phase 3 clinical trial data. However, patient-centric specifications shift the focus toward direct clinical relevance, establishing customer-driven acceptance criteria. Discussions covered innovative approaches to defining patient-centric specifications, leveraging prior knowledge, biopharmaceutics, formulation science, regulatory input, and statistical methodologies. The session also highlighted efficient QbD studies, enabling the linkage of Critical Process Parameters (CPPs) and Critical Material Attributes (CMAs) to Chemistry, Manufacturing and Controls (CMC) Critical Quality Attributes (CQAs). While these approaches hold great promise, challenges remain such as cross-disciplinary collaboration, data integration, and the development of robust databases to inform future drug and biologicals development. As industry experience grows, these efforts will pave the way for continuous improvement in nonclinical-clinical linkage designs, enhancing patient outcomes.

The regulatory framework for Biopharmaceutics Classification System (BCS) class III drug products provides a pathway for streamlined biowaivers in drug development, eliminating the need for expensive and time-consuming bioavailability and bioequivalence studies while maintaining quality standards. To qualify, the Test must align with the excipients of the Reference product, while variations in flavor, color, and preservatives are allowed. Quantities of excipients, including changes in grade and percentage, must remain comparable, with cumulative differences not exceeding 10%. However, excipient modifications may affect drug release, potentially necessitating further evaluation for equivalence. Additionally, in cases where very rapid dissolution is not met, it limits the use of a BCS class III-based biowaiver for demonstrating bioequivalence. This article examines the regulatory landscape across regulatory agencies surrounding the application of physiologically based biopharmaceutics modeling (PBBM) to support BCS class III biowaivers, providing insights into the current level of acceptance and expectations. Additionally, it addresses the scientific and regulatory challenges associated with implementing PBBM, highlighting knowledge gaps and obstacles that could hinder adoption in regulatory decision-making. The article also presents case studies demonstrating practical approaches to leveraging PBBM and risk assessment for BCS class III biowaivers, offering valuable insights into successful applications and potential future directions.

Objectives: Omaveloxolone is a nuclear factor (erythroid-derived 2)-like 2 activator approved in the US and EU for the treatment of Friedreich ataxia in patients aged ≥16 years. It is approved at a dosage of 150 mg administered orally once daily on an empty stomach. Food-drug interactions can potentially alter the pharmacokinetic (PK) parameters of an oral drug, which may affect its efficacy and/or safety profile. Physiologically based biopharmaceutics modeling (PBBM) enables prediction of the PK profiles of oral drugs by integrating drug physicochemical properties and formulation factors with system physiological parameters. A PBBM was developed to predict and explain the effect of the US Food and Drug Administration high-fat meal on the PK of omaveloxolone. Methods: The PBBM was developed using physicochemical, dissolution, bile salt solubilization, precipitation, permeability, and in vitro and in vivo metabolism data. It was then validated across 9 distinct clinical scenarios that evaluated the impact of food, dose proportionality, and drug-drug interactions. Sensitivity analyses were performed to identify the parameters that could impact the absorption and metabolism of omaveloxolone in the fasted state. Results: The model’s predictive ability was evaluated based on the model’s performance indicators of maximum plasma concentration (Cmax) and area under the plasma concentration versus time curve (AUC), which met predefined acceptance criteria across all analyzed clinical scenarios. Key parameters influencing the PK of omaveloxolone included bile salt solubilization, maximum rate of reaction of CYP3A4, particle size distribution, and permeability. The PBBM predicted a 350% increase in Cmax, with only a 15% increase in the AUC; this is consistent with clinical study findings. The effect of a high-fat meal on the PK of omaveloxolone is unique, as it differs from the linear correlation between Cmax and AUC ratios reported for other compounds from 323 food effect studies.[1-6] The PBBM showed that in vivo omaveloxolone absorption is solubility and dissolution rate limited. In the fed state, bile salt solubilization resulted in more rapid dissolution, leading to enhanced drug absorption in the upper gastrointestinal tract compared with the fasted state. Consequently, there was an increase in first-pass gut extraction, which explains a large transient elevation in Cmax without a corresponding increase in AUC. Conclusions: By mechanically integrating solubility and dissolution into PBBM, the unique impact of a high-fat meal on the PK profile of omaveloxolone was accurately anticipated. These findings reinforce the drug label recommendations on administration of omaveloxolone on an empty stomach. PBBM has the potential to predict the impact of food on drug PK and possibly eliminates the need for a clinical study.Citations: [1] Singh BN, Malhotra BK. Clin Pharmacokinet. 2004;43(15):1127-1156.[2] Qin H, et al. Basic Clin Pharmacol Toxicol. 2022;130(2):268-276.[3] Riedmaier AE, et al. AAPS J. 2020;22(6):123.[4] Omachi F, et al. J Pharm Health Care Sci. 2019;5:26.[5] Kesisoglou F, et al. AAPS J. 2023;25(4):60.[6] Li M, et al. CPT Pharmacometrics Syst Pharmacol. 2018;7(2):82-89.

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.

This report summarizes the proceedings for Day 3 of the workshop titled “Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives”. This day focused on the current and future drug product quality applications of PBBM from the innovator and generic industries as well as the regulatory agencies perspectives. The presentations, which included several case studies, covered the applications of PBBM in generic drug product development, applications of virtual bioequivalence trials to support formulation bridging and the utility of absorption modeling in clinical pharmacology assessments. In addition, recent progress in the prediction of colon absorption and in vivo performance of extended-release drug products was shared. The morning session was concluded by representatives from FDA, ANVISA, MHRA, Health Canada, EMA, and PMDA giving their perspectives on the application of PBBM in regulatory submissions. The afternoon breakout sessions focused on four parallel topics: 1) PBBM in generic drug product development; 2) virtual bioequivalence trials applications; 3) safe space and extrapolation; and 4) regional absorption and modified release PBBM applications. This allowed the participants to engage in in-depth discussions of best practices as well to identify key points of consideration to allow further progress on the applications of PBBM.

This work shows the utilization of a physiologically based biopharmaceutics model (PBBM) to mechanistically explain the impact of diverse food types on the pharmacokinetics (PK) of isoniazid (INH) and acetyl-isoniazid (Ac-INH). The model was established and validated using published PK profiles for INH along with a combination of measured and predicted values for the physico-chemical and biopharmaceutical propertied of INH and Ac-INH. A dedicated ontogeny model was developed for N-acetyltransferase 2 (NAT2) in human integrating Michaelis Menten parameters for this enzyme in the physiologically based pharmacokinetic (PBPK) model tissues and in the gut, to explain the pre-systemic and systemic metabolism of INH across different acetylator types. Additionally, a novel equation was proposed to calculate the luminal drug degradation related to the presence of reducing sugars, using individual sugar molar concentrations in the meal. By incorporating luminal degradation into the model, adjusting bile salt concentrations and gastric emptying according to food type and quantity, the PBBM was able to accurately predict the negative effect of carbohydrate-rich diets on the PK of INH.

AbstractOmaveloxolone is a nuclear factor (erythroid‐derived 2)‐like 2 activator approved in the United States and the European Union for the treatment of patients with Friedreich ataxia aged ≥16 years, with a recommended dosage of 150 mg orally once daily on an empty stomach. The effect of the US Food and Drug Administration (FDA) high‐fat breakfast on the pharmacokinetic profile of omaveloxolone observed in study 408‐C‐1703 (NCT03664453) deviated from the usual linear correlation between fed/fasted maximum plasma concentration (Cmax) and area under the concentration–time curve (AUC) ratios reported for various oral drugs across 323 food effect studies. Here, physiologically based biopharmaceutics modeling (PBBM) was implemented to predict and explain the effect of the FDA high‐fat breakfast on a 150‐mg dose of omaveloxolone. The model was developed and validated based on dissolution and pharmacokinetic data available across dose‐ranging, food effect, and drug–drug interaction clinical studies. PBBM predictions support clinical observations of the unique effect of a high‐fat meal on omaveloxolone pharmacokinetic profile, in which the Cmax increased by 350% with only a 15% increase in the AUC. Key parameters influencing omaveloxolone pharmacokinetics in the fasted state based on a parameter sensitivity analysis included bile salt solubilization, CYP3A4 activity, drug substance particle size distribution, and permeability. Mechanistically, in vivo omaveloxolone absorption was solubility and dissolution rate limited. However, in the fed state, higher bile salt solubilization led to more rapid dissolution with predominant absorption in the upper gastrointestinal tract, resulting in increased susceptibility to first‐pass gut extraction; this accounts for the lack of correlation between Cmax and AUC for omaveloxolone.

Background/Objectives: The combination of isoniazid (INH) and rifampicin (RIF) is indicated for the treatment maintenance phase of tuberculosis (TB) in adults and children. In Brazil, there is no current reference listed drug for this indication in children. Farmanguinhos has undertaken the development of an age-appropriate dispersible tablet to be taken with water for all age groups from birth to adolescence. The primary objective of this work was to develop and validate a physiologically-based biopharmaceutics model (PBBM) in GastroPlusTM, to link the product’s in vitro performance to the observed pharmacokinetic (PK) data in adults and children. Methods: The PBBM was developed based on measured or predicted physico-chemical and biopharmaceutical properties of INH and RIF. The metabolic clearance was specified mechanistically in the gut and liver for both parent drugs and acetyl-isoniazid. The model incorporated formulation related measurements such as dosage form disintegration and dissolution as inputs and was validated using extensive literature as well as in house clinical data. Results: The model was used to predict the exposure in children across the targeted dosing regimen for each age group using the new age-appropriate formulation. Probabilistic models of efficacy and safety versus exposure, combined with real world data on children, were utilized to assess drug efficacy and safety in the target populations. Conclusions: The model predictions (systemic exposure) along with clinical data from the literature linking systemic exposure to clinical outcomes confirmed that the proposed dispersible pediatric tablet and dosing regimen are anticipated to be as safe and as effective as adult formulations at similar doses.

This Article shares the proceedings from the August 29th, 2023 (day 1) workshop "Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives". The focus of the day was on model parametrization; regulatory authorities from Canada, the USA, Sweden, Belgium, and Norway presented their views on PBBM case studies submitted by industry members of the IQ consortium. The presentations shared key questions raised by regulators during the mock exercise, regarding the PBBM input parameters and their justification. These presentations also shed light on the regulatory assessment processes, content, and format requirements for future PBBM regulatory submissions. In addition, the day 1 breakout presentations and discussions gave the opportunity to share best practices around key questions faced by scientists when parametrizing PBBMs. Key questions included measurement and integration of drug substance solubility for crystalline vs amorphous drugs; impact of excipients on apparent drug solubility/supersaturation; modeling of acid-base reactions at the surface of the dissolving drug; choice of dissolution methods according to the formulation and drug properties with a view to predict the in vivo performance; mechanistic modeling of in vitro product dissolution data to predict in vivo dissolution for various patient populations/species; best practices for characterization of drug precipitation from simple or complex formulations and integration of the data in PBBM; incorporation of drug permeability into PBBM for various routes of uptake and prediction of permeability along the GI tract.

Pexidartinib is a systemic treatment for patients with tenosynovial giant cell tumor not amenable to surgery. Oral absorption of pexidartinib is affected by food; administration with a high-fat meal (HFM) or low-fat meal (LFM) increases absorption by approximately 100% and approximately 60%, respectively, compared with the fasted state. Pexidartinib is currently dosed 250 mg orally twice daily with an LFM (approximately 11-14 g of total fat). We developed a physiologically based pharmacokinetic model to determine the impact on drug exposure of dose timing with respect to meals, meal type, and caloric content. A 15%-16% increase in plasma exposure was predicted when consuming an HFM 1 hour after dosing with an LFM, but almost no effect on pharmacokinetics was predicted when an HFM was consumed 3 hours or more before or after pexidartinib dosing with an LFM. Exposure was not significantly affected when pexidartinib was taken with a 500-kcal LFM over the range of fat (approximately 11-14 g of total fat; 20%-25% calories from fat) for an LFM. These findings on timing of pexidartinib dose with respect to meals should be considered by patients and physicians to reduce the potential for side effects.

www.dissolutiontech.com 100 INTRODUCTION The virtual workshop, “A Quest for Biowaiver, Including Next Generation Dissolution Characterization and Modelling,” was held on November 16–17th, 2022, via the MS Teams platform. The conference was co-sponsored by Jagiellonian University Medical College (JUMC) in Cracow, Poland and the American Association of Pharmaceutical Scientists (AAPS). The workshop was chaired by Vivian Gray (AAPS) and Prof Aleksander Mendyk (JUMC), with the support of the co-chairs Prof Nikoletta Fotaki (AAPS), Prof Jie Shen (AAPS), and Dr Jakub Szlęk (JUMC).

This report summarizes podium presentations and breakout sessions from the second day of the 2019 M-CERSI workshop on In Vitro Dissolution Similarity Assessment in Support of Drug Product Quality: What, How, and When? Presenters from the U.S. Food and Drug Administration (FDA), Health Canada (HC), European Medicines Agency (EMA), Brazilian Health Surveillance Agency (ANVISA), and the pharmaceutical industry shared experiences/concerns with dissolution profile similarity assessment supporting minor/moderate Chemistry, Manufacturing and Control (CMC) changes. Members from regulatory agencies explained that dissolution profile similarity testing is only part of the overall assessment of the acceptability of the proposed changes; decisions are usually made based on aggregate weight of evidence. Scientific shortcomings of f2 were highlighted but no proposal on how to replace it was made. Controlling dissolution timepoint variability and application of pairwise batch-to-batch comparisons (PBC) of dissolution profiles caused considerable debate. Several industry participants suggested increased sample sizes to raise confidence in decision-making and to avoid PBC. They proposed identification of a single mathematical method with predefined acceptance criteria and suggested that dissolution timepoint selection should follow EMA and HC guidance. A majority of meeting attendees favored applying clinically relevant dissolution specifications (CRDS) and dissolution safe space to determine the impact of minor/moderate CMC changes as opposed to dissolution profile similarity assessment via statistical methods. Day 2 of the workshop highlighted the need and opportunities for global harmonization including variability, timepoint selection, role of CRDS, and statistical methods to address the ambiguity globally operating pharmaceutical companies are currently facing.

The pharmaceutical industry and regulatory agencies rely on dissolution similarity testing to make critical product decisions as part of drug product life cycle management. Accordingly, the application of mathematical approaches to evaluate dissolution profile similarity is described in regulatory guidance with the emphasis given to the similarity factor f2 with little discussion of alternative methods. In an effort to highlight current practices to assess dissolution profile similarity and to strive toward global harmonization, a workshop entitled “In Vitro Dissolution Similarity Assessment in Support of Drug Product Quality: What, How, When” was held on May 21–22, 2019 at the University of Maryland, Baltimore. This manuscript provides in-depth discussion of the mathematical principles of the model-independent statistical methods for dissolution profile similarity analyses presented in the workshop. Deeper understanding of the testing objective and statistical properties of the available statistical methods is essential to identify methods which are appropriate for application in practice. A decision tree is provided to aid in the selection of an appropriate statistical method based on the underlying characteristics of the drug product. Finally, the design of dissolution profile studies is addressed regarding analytical and statistical recommendations to sufficiently power the study. This includes a detailed discussion on evaluation of dissolution profile data for which several batches per reference and/or test product are available.

To date, few examples of dissolution models for real-time release testing (RTRT) have been approved for commercial drug products or published in literature. Thus, a structured approach has not been established by which a novice to the field could design, develop, validate, and implement an RTRT dissolution model. Moreover, with scant examples available, there has not been a body of work by which to learn of general regulatory expectations for such models. To address these gaps and to encourage conversation between regulatory and industrial experts on these topics, a virtual (web-based) workshop entitled "Predictive Dissolution Models for Real-Time Release Testing: Development and Implementation" was held November 11-12, 2021. This article summarizes key points from the podium presentations, panel discussions, and breakout sessions focusing on (1) the current best practices to establish predictive model specifications; (2) designing models to predict the "safe space" of a release test and creating models utilizing process analytical technology (PAT); and (3) exploring the strategy of compliant regulatory submissions, including model validation and post-approval lifecycle management. Industrial case studies were presented showcasing attempted approaches to and successful implementations of RTRT of dissolution for drug product manufacturing.

On May 4, 2020, the US Food and Drug Administration (FDA) hosted an online public workshop titled “FY 2020 Generic Drug Regulatory Science Initiatives Public Workshop” to provide an overview of the status of the science and research priorities and to solicit input on the development of Generic Drug User Fee Amendments fiscal year 2021 priorities. This report summarizes the podium presentations and the outcome of discussions along with innovative ways to overcome challenges and significant opportunities related to model‐based approaches in bioequivalence assessment for breakout session 4 titled, “Data analysis and model‐based bioequivalence (BE).” This session focused on the application of model‐based approaches in the generic drug development, with a vision of accelerating regulatory decision making for abbreviated new drug application assessments. The session included both podium presentations and panel discussions with three topics of interest: (i) in vitro study evaluation methods and their clinical relevance, (ii) challenges in model‐based BE, (iii) emerging expertise and tools in implementing new BE approaches.

For oral drug products, in vitro dissolution is the most used surrogate of in vivo dissolution and absorption. In the context of drug product quality, safe space is defined as the boundaries of in vitro dissolution, and relevant quality attributes, within which drug product variants are expected to be bioequivalent to each other. It would be highly desirable if the safe space could be established via a direct link between available in vitro data and in vivo pharmacokinetics. In response to the challenges with establishing in vitro-in vivo correlations (IVIVC) with traditional modeling approaches, physiologically based biopharmaceutics modeling (PBBM) has been gaining increased attention. In this manuscript we report five case studies on using PBBM to establish a safe space for BCS Class 2 and 4 across different companies, including applications in an industrial setting for both internal decision making or regulatory applications. The case studies provide an opportunity to reflect on practical vs. ideal datasets for safe space development, the methodologies for incorporating dissolution data in the model and the criteria used for model validation and application. PBBM and safe space, still represent an evolving field and more examples are needed to drive development of best practices.

Highly variable disposition after oral ingestion of acyclovir has been reported, although little is known regarding the underlying mechanisms. Different studies using the same reference product (Zovirax ®) showed that Cmax and AUC were respectively 44 and 35% lower in Saudi Arabians than Europeans, consistent with higher frequencies of reduced-activity polymorphs of the organic cation transporter (OCT1) in Europeans. In this study, the contribution of physiology (i.e., OCT1 activity) to the oral disposition of acyclovir immediate release (IR) tablets was hypothesized to be greater than dissolution. The potential role of OCT1 was studied in a validated physiologically-based biopharmaceutics model (PBBM), while dissolution of two Chilean generics (with demonstrated bioequivalence) and the reference product was assessed in vitro. The PBBM suggested that OCT1 activity could partially explain population-related pharmacokinetic differences. Further, dissolution of generics was slower than the regulatory criterion for BCS III IR products. Remarkably, virtual bioequivalence (incorporating in vitro dissolution into the PBBM) correctly and robustly predicted the bioequivalence of these products, showcasing its value in support of failed BCS biowaivers. These findings suggest that very-rapid dissolution for acyclovir IR products may not be critical for BCS biowaiver. They also endorse the relevance of cross-over designs in bioequivalence trials.

This workshop report summarizes the proceedings of Day 2 of a three-day workshop on "Current State and Future Expectations of Translational Modeling Strategies toSupportDrug Product Development, Manufacturing Changes and Controls". From a drug product quality perspective, physiologically based biopharmaceutics modeling (PBBM) is a tool to link variations in the drug product quality attributes to in vivo outcomes enabling the establishment of clinically relevant drug product specifications (CRDPS). Day 2 of the workshop focused on best practices in developing, verifying and validating PBBM. This manuscript gives an overview of podium presentations and summarizes breakout (BO) session discussions related to (1) challenges and opportunities for using PBBM to assess the clinical impact of formulation and manufacturing changes on the in vivo performance of a drug product, (2) best practices to account for parameter uncertainty and variability during model development, (3) best practices in the development, verification and validation of PBBM and (4) opportunities and knowledge gaps related to leveraging PBBM for virtual bioequivalence simulations.