Parameterization of Physiologically Based Biopharmaceutics Models: Workshop Summary Report.

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.

New Horizons of Model Informed Drug Development in Rare Diseases Drug Development.

Model-informed approaches provide a quantitative framework to integrate all available nonclinical and clinical data, thus furnishing a totality of evidence approach to drug development and regulatory evaluation. Maximizing the use of all available data and information about the drug enables a more robust characterization of the risk-benefit profile and reduces uncertainty in both technical and regulatory success. This offers the potential to transform rare diseases drug development, where conducting large well-controlled clinical trials is impractical and/or unethical due to a small patient population, a significant portion of which could be children. Additionally, the totality of evidence generated by model-informed approaches can provide confirmatory evidence for regulatory approval without the need for additional clinical data. In the article, applications of novel quantitative approaches such as quantitative systems pharmacology, disease progression modeling, artificial intelligence, machine learning, modeling of real-world data using model-based meta-analysis and strategies such as external control and patient-reported outcomes as well as clinical trial simulations to optimize trials and sample collection are discussed. Specific case studies of these modeling approaches in rare diseases are provided to showcase applications in drug development and regulatory review. Finally, perspectives are shared on the future state of these modeling approaches in rare diseases drug development along with challenges and opportunities for incorporating such tools in the rational development of drug products.

Tipifarnib physiologically-based pharmacokinetic modeling to assess drug-drug interaction, organ impairment, and biopharmaceutics in healthy subjects and cancer patients.

A physiologically-based pharmacokinetic (PBPK) model for tipifarnib, which included mechanistic absorption, was built and verified by integrating in vitro data and several clinical data in healthy subjects and cancer patients. The final PBPK model was able to recover the clinically observed single and multiple-dose plasma concentrations of tipifarnib in healthy subjects and cancer patients under several dosing conditions, such as co-administration with a strong CYP3A4 inhibitor and inducer, an acid-reducing agent (proton pump inhibitor and H2 receptor antagonist), and with a high-fat meal. In addition, the model was able to accurately predict the effect of mild or moderate hepatic impairment on tipifarnib exposure. The appropriately verified model was applied to prospectively simulate the liability of tipifarnib as a victim of CYP3A4 enzyme-based drug-drug interactions (DDIs) with a moderate inhibitor and inducer as well as tipifarnib as a perpetrator of DDIs with sensitive substrates of CYP3A4, CYP2B6, CYP2D6, CYP2C9, and CYP2C19 in healthy subjects and cancer patients. The effect of a high-fat meal, acid-reducing agent, and formulation change at the therapeutic dose was simulated. Finally, the model was used to predict the effect of mild, moderate, or severe hepatic, and renal impairment on tipifarnib PK. This multipronged approach of combining the available clinical data with PBPK modeling-guided dosing recommendations for tipifarnib under several conditions. This example showcases the totality of the data approach to gain a more thorough understanding of clinical pharmacology and biopharmaceutic properties of oncology drugs in development.

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.

Differential regulation of miRNAs involved in the susceptible and resistance responses of wheat cultivars to wheat streak mosaic virus and Triticum mosaic virus.

BACKGROUND: Wheat streak mosaic virus (WSMV) and Triticum mosaic virus (TriMV) are components of the wheat streak mosaic virus disease complex in the Great Plains region of the U.S.A. and elsewhere. Co-infection of wheat with WSMV and TriMV causes synergistic interaction with more severe disease symptoms compared to single infections. Plants are equipped with multiple antiviral mechanisms, of which regulation of microRNAs (miRNAs) is a potentially effective constituent. In this investigation, we have analyzed the total and relative expression of miRNA transcriptome in two wheat cultivars, Arapahoe (susceptible) and Mace (temperature-sensitive-resistant), that were mock-inoculated or inoculated with WSMV, TriMV, or both at 18 °C and 27 °C. RESULTS: Our results showed that the most abundant miRNA family among all the treatments was miRNA166, followed by 159a and 168a, although the order of the latter two changed depending on the infections. When comparing infected and control groups, twenty miRNAs showed significant upregulation, while eight miRNAs were significantly downregulated. Among them, miRNAs 9670-3p, 397-5p, and 5384-3p exhibited the most significant upregulation, whereas miRNAs 319, 9773, and 9774 were the most downregulated. The comparison of infection versus the control group for the cultivar Mace showed temperature-dependent regulation of these miRNAs. The principal component analysis confirmed that less abundant miRNAs among differentially expressed miRNAs were strongly correlated with the inoculated symptomatic wheat cultivars. Notably, miRNAs 397-5p, 398, and 9670-3p were upregulated in response to WSMV and TriMV infections, an observation not yet reported in this context. The significant upregulation of these three miRNAs was further confirmed with RT-qPCR analysis; in general, the RT-qPCR results were in agreement with our computational analysis. Target prediction analysis showed that the miRNAs standing out in our analysis targeted genes involved in defense response and regulation of transcription. CONCLUSION: Investigation into the roles of these miRNAs and their corresponding targets holds promise for advancing our understanding of the mechanisms of virus infection and possible manipulation of these factors for developing durable virus resistance in crop plants.

Rare oncology therapeutics: review of clinical pharmacology package of drug approvals (2019-2023) by US FDA, best practices and recommendations.

There are many challenges with rare diseases drug development and rare oncology indications are not different. To understand the regulatory landscape as it relates to application of clinical pharmacology principles in rare oncology product development, we reviewed publicly available information of 39 approvals by US FDA between January 2019 and March 2023. The objective was to understand the expected clinical pharmacology studies and knowledge base in such approvals. Model informed drug development (MIDD) applications were also reviewed, as such approaches are expected to play a critical role in filling clinical pharmacology gaps in rare oncology, where number of clinical trials and size of these trials will perhaps continue to be small. The findings highlighted how clinical pharmacology contributed to the evidence of effectiveness, dose optimization and elucidation of intrinsic and extrinsic factors affecting drug's behavior. Clinical pharmacology studies were often integrated with modeling in many of the NDAs/BLAs. Of the post marketing requirements (PMR) received, 18% were for dose optimization, 49% for DDI, 8% for QTc, 49% for specific population, and 5% for food effect. Two post marketing commitments (PMC) were issued for immunogenicity of the 11 biologics submissions. 15% (6 of 39) of the submissions used maximum tolerated dose (MTD) to advance their molecule into Phase 2 studies. Of them 3 approvals received PMR for dose optimization. 3 + 3 was the most prevalent Phase 1 design with use in 74% of the New Drug Applications (NDA)/Biologic License Applications (BLA) reviewed. Rest used innovative approaches such as BLRM, BOIN or mTPi, with BLRM being the most common. Seamless clinical pharmacology and MIDD approaches are paramount for rare oncology drug development.

Model-Informed Approaches and Innovative Clinical Trial Design for Adeno-Associated Viral Vector-Based Gene Therapy Product Development: A White Paper.

The promise of viral vector-based gene therapy (GT) as a transformative paradigm for treating severely debilitating and life-threatening diseases is slowly coming to fruition with the recent approval of several drug products. However, they have a unique mechanism of action often necessitating a tortuous clinical development plan. Expertise in such complex therapeutic modality is still fairly limited in this emerging class of adeno-associated virus (AAV) vector-based gene therapies. Because of the irreversible mode of action and incomplete understanding of genotype-phenotype relationship and disease progression in rare diseases careful considerations should be given to GT product's benefit-risk profile. In particular, special attention needs to be paid to safe dose selection, reliable dose exposure response (including clinically relevant endpoints), or creative approaches in study design targeting small patient populations during clinical development. We believe that quantitative tools encompassed within model-informed drug development (MIDD) framework fits quite well in the development of such novel therapies, as they enable us to benefit from the totality of data approach in order to support dose selection as well as optimize clinical trial designs, end point selection, and patient enrichment. In this thought leadership paper, we provide our collective experiences, identify challenges, and suggest areas of improvement in applications of modeling and innovative trial design in development of AAV-based GT products and reflect on the challenges and opportunities for incorporating MIDD tools and more in rational development of these products.

Regulatory utility of physiologically-based pharmacokinetic modeling to support alternative bioequivalence approaches and risk assessment: A workshop summary report.

This report summarizes the proceedings for day 2 sessions 1 and 3 of the 2-day public workshop entitled "Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches," a jointly sponsored workshop by the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics (CRCG). The aims of this workshop were: (1) to discuss how mechanistic modeling, including physiologically-based pharmacokinetic (PBPK) modeling and simulation, can support product development, and regulatory submissions; (2) to share the current state of mechanistic modeling for bioequivalence (BE) assessment through case studies; (3) to establish a consensus on best practices for using PBPK modeling for BE assessment to help drive further investment by the generic drug industry into mechanistic modeling and simulation; and (4) to introduce the concept of a Model Master File to improve model-sharing. The theme of day 2 covered PBPK absorption model for oral products as an alternative BE approach and a tool for supporting risk assessment and biowaiver (session 1), oral PBPK for evaluating the impact of food on BE (session 2), successful cases, and challenges for oral PBPK (session 3). This report summarizes the topics of the presentations of day 2 sessions 1 and session 3 from FDA, academia, and pharmaceutical industry, including the current status of oral PBPK, case examples as well as the challenges and opportunities in this area. In addition, panel discussions on the utility of oral PBPK in both new drugs and generic drugs from regulatory and industry perspective are also summarized.

Pharmacokinetic and Pharmacodynamic Modeling of siRNA Therapeutics - a Minireview.

The approval of four small interfering RNA (siRNA) products in the past few years has demonstrated unequivocally the therapeutic potential of this novel modality. Three such products (givosiran, lumasiran and inclisiran) are liver-targeted, using tris N-acetylgalactosamine (GalNAc)3 as the targeting ligand. Upon subcutaneous administration, GalNAc-conjugated siRNAs rapidly distribute into the liver via asialoglycoprotein receptor (ASGPR) mediated uptake in the hepatocytes, resulting in fast elimination from the systemic circulation. Patisiran, on the other hand, has been formulated in a lipid nanoparticle for optimal delivery to the liver. While several publications have described preclinical and clinical pharmacokinetic (PK) and pharmacodynamic (PD) results, including absorption, distribution, metabolism, and elimination (ADME) profiles in selected species as well as limited modeling efforts for siRNA therapeutics, there is no systematic review of the PK and PD models developed for these agents or work summarizing the utility and application(s) of such models in drug development and regulatory review. Here, we provide a mini-review of the current state of modeling efforts for siRNA therapeutics within the early preclinical, translational, and clinical stages of siRNA development. Diverse modeling methods including simple compartmental, mechanistic and systems PK/PD, physiologically-based PK (PBPK), population PK/PD, and dose-response-time models are introduced and reviewed. The utility of such models in development and regulatory review for siRNA therapeutics is also discussed with examples. Finally, the current knowledge gaps in mechanism of action of siRNA and resulting challenges in model development are summarized. The goal of this minireview is to trigger cross-functional discussion amongst all key stakeholders to generate key experimental datasets and align on current assumptions, model structures, and approaches to facilitate development and application of robust PK/PD models for siRNA therapeutics.

PBPK Modeling as a Tool for Predicting and Understanding Intestinal Metabolism of Uridine 5'-Diphospho-glucuronosyltransferase Substrates.

Uridine 5'-diphospho-glucuronosyltransferases (UGTs) are expressed in the small intestines, but prediction of first-pass extraction from the related metabolism is not well studied. This work assesses physiologically based pharmacokinetic (PBPK) modeling as a tool for predicting intestinal metabolism due to UGTs in the human gastrointestinal tract. Available data for intestinal UGT expression levels and in vitro approaches that can be used to predict intestinal metabolism of UGT substrates are reviewed. Human PBPK models for UGT substrates with varying extents of UGT-mediated intestinal metabolism (lorazepam, oxazepam, naloxone, zidovudine, cabotegravir, raltegravir, and dolutegravir) have demonstrated utility for predicting the extent of intestinal metabolism. Drug-drug interactions (DDIs) of UGT1A1 substrates dolutegravir and raltegravir with UGT1A1 inhibitor atazanavir have been simulated, and the role of intestinal metabolism in these clinical DDIs examined. Utility of an in silico tool for predicting substrate specificity for UGTs is discussed. Improved in vitro tools to study metabolism for UGT compounds, such as coculture models for low clearance compounds and better understanding of optimal conditions for in vitro studies, may provide an opportunity for improved in vitro-in vivo extrapolation (IVIVE) and prospective predictions. PBPK modeling shows promise as a useful tool for predicting intestinal metabolism for UGT substrates.

Establishing the Bioequivalence Safe Space for Immediate-Release Oral Dosage Forms using Physiologically Based Biopharmaceutics Modeling (PBBM): Case Studies.

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.

Impact of gastrointestinal tract variability on oral drug absorption and pharmacokinetics: An UNGAP review.

The absorption of oral drugs is frequently plagued by significant variability with potentially serious therapeutic consequences. The source of variability can be traced back to interindividual variability in physiology, differences in special populations (age- and disease-dependent), drug and formulation properties, or food-drug interactions. Clinical evidence for the impact of some of these factors on drug pharmacokinetic variability is mounting: e.g. gastric pH and emptying time, small intestinal fluid properties, differences in pediatrics and the elderly, and surgical changes in gastrointestinal anatomy. However, the link of colonic factors variability (transit time, fluid composition, microbiome), sex differences (male vs. female) and gut-related diseases (chronic constipation, anorexia and cachexia) to drug absorption variability has not been firmly established yet. At the same time, a way to decrease oral drug pharmacokinetic variability is provided by the pharmaceutical industry: clinical evidence suggests that formulation approaches employed during drug development can decrease the variability in oral exposure. This review outlines the main drivers of oral drug exposure variability and potential approaches to overcome them, while highlighting existing knowledge gaps and guiding future studies in this area.

In Vitro Biopredictive Methods: A Workshop Summary Report.

This workshop report summarizes the proceedings of Day 1 of a three-day workshop on "Current State and Future Expectations of Translational Modeling Strategies to Support Drug Product Development, Manufacturing Changes and Controls". Physiologically based biopharmaceutics models (PBBM) are tools which enable the drug product quality attributes to be linked to the in vivo performance. These tools rely on key quality inputs in order to provide reliable predictions. After introducing the objectives of the workshop and the expectations from the breakout sessions, Day 1 of the workshop focused on the best practices and challenges in measuring in vitro inputs needed for modeling, such as the drug solubility, the dissolution rate of the drug product, potential precipitation of the drug and drug permeability. This paper reports the podium presentations and summarizes breakout session discussions related to A) the best strategies for determining solubility, supersaturation and critical supersaturation; B) the best strategies for the development of biopredictive (clinically relevant) dissolution methods; C) the challenges associated with describing gastro-intestinal systems parameters such as mucus, liquid volume and motility; and D) the challenges with translating biopharmaceutical measures of drug permeability along the gastrointestinal tract to a meaningful model parameter.

Current State and Future Expectations of Translational Modeling Strategies to Support Drug Product Development, Manufacturing Changes and Controls: A Workshop Summary Report.

The implementation of clinically relevant drug product specifications (CRDPS) depends on establishing a link between in vitro performance and in vivo exposure. The scientific community, including regulatory agencies, relies on biopharmaceutics tools on the in vitro performance side, while to enable the link to in vivo exposure, physiologically based pharmacokinetic (PBPK) modeling offers much promise. However, when it comes to PBPK applications in support of CRDPS, otherwise called physiologically based biopharmaceutics models (PBBM), the tools are not yet at the desired level. Currently, it is not possible to integrate detailed variations in chemistry, manufacturing and controls (CMC) attributes and parameters into these models in a way that can consistently predict their effect on local and systemic drug exposure. Specifically, to achieve the desired level, there is a need to advance the science and policy of PBBM. This manuscript summarizes the proceedings of a three-day workshop where the following themes were discussed: 1) Challenges in the development and implementation of in vitro biopredictive tools needed for successful mechanistic modeling; 2) Best practices in model development, verification and validation; and 3) Appropriate terminology (e.g., PBBM vs. PBPK models for biopharmaceutics applications) and applications of PBBM in support of drug product quality.

Applications of Physiologically Based Biopharmaceutics Modeling (PBBM) to Support Drug Product Quality: A Workshop Summary Report.

This report summarizes the proceedings for Day 3 of the workshop titled "Current State and Future Expectations of Translational Modeling Strategies toSupportDrug Product Development, Manufacturing Changes and Controls". From a drug product quality perspective, patient-centric product development necessitates the development of clinically relevant drug product specifications (CRDPS). In this regard, Physiologically Based Biopharmaceutics modeling (PBBM) is a viable tool to establish links between in-vitro to in-vivo data, and support with establishing CRDPS. The theme of day 3 was practical applications of PBBM to support drug product quality. In this manuscript, case studies from US FDA, EMA and pharmaceutical industry on applications of PBBM in drug product quality are summarized which include 1) regulatory agency's perspectives on establishing the safe space and achieving study waivers, 2) model-informed risk assessment on the effects of acid reducing agents, bridging of dissolution methods, food effect, and formulation selection, and 3) understanding clinical formulation performance. Breakout session discussions focused on four topics - 1) terminologies related to physiologically based modeling in support of drug product quality, 2) regulatory harmonization on evidentiary standards, 3) CRDPS approaches and 4) bridging between biorelevant and quality control (QC) dissolution methods.

Best Practices in the Development and Validation of Physiologically Based Biopharmaceutics Modeling. A Workshop Summary Report.

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.

Soybean Nodule-Associated Non-Rhizobial Bacteria Inhibit Plant Pathogens and Induce Growth Promotion in Tomato.

The root nodules are a unique environment formed on legume roots through a highly specific symbiotic relationship between leguminous plants and nodule-inducing bacteria. Previously, Rhizobia were presumed to be the only group of bacteria residing within nodules. However, recent studies discovered diverse groups of bacteria within the legume nodules. In this report soybean nodule-associated bacteria were studied in an effort to identify beneficial bacteria for plant disease control and growth promotion. Analysis of surface-sterilized single nodules showed bacterial diversity of the nodule microbiome. Five hundred non-rhizobial colonies from 10 nodules, 50 colonies per nodule, were tested individually against the tomato wilt causing bacterial pathogen Clavibacter michiganensis subsp. michiganensis (Cmm) for inhibition of pathogen growth. From the initial screening, 54 isolates were selected based on significant growth inhibition of Cmm. These isolates were further tested in vitro on another bacterial pathogen Pseudomonas syringae pv. tomato (Pst) and two fungal pathogens Rhizoctonia solani and Sclerotinia sclerotiorum. Bacterial metabolites were extracted from 15 selected isolates with ethanol and tested against pathogen Cmm and Pst. These isolates were identified by using MALDI-TOF mass spectrometry and 16S rRNA gene sequencing. Pseudomonas spp. were the dominant soybean nodule-associated non-rhizobial bacterial group. Several isolates imparted significant protection against pathogens and/or plant growth promotion on tomato seedlings. The most promising nodule-associated bacterial isolate that suppressed both Cmm and Pst in vitro and Pst in tomato seedlings was identified as a Proteus species. Isolation and identification of beneficial nodule-associated bacteria established the foundation for further exploration of potential nodule-associated bacteria for plant protection and growth promotion.

Prediction of fasted and fed bioequivalence for immediate release drug products using physiologically based biopharmaceutics modeling (PBBM).

Bioequivalence studies are an integral part of clinical pharmacology strategy for drug development. Physiologically based biopharmaceutics modeling (PBBM) can be a helpful tool to assess potential bioequivalence risks and predict the outcome of bioequivalence studies. In this study, GastroPlus™ was used for virtual bioequivalence (VBE) assessment of 6 case studies which includes four BCS 2, and one each of BCS 1 and 3 molecules. The purpose was to investigate if bioequivalence in fed state can be accurately predicted based on model developed on data from bioequivalence study in fasted state and known food effect from clinical studies. Our results show that we were able to successfully predict passing (5 cases) and failed (1 case) bioequivalence studies. Ultimately, if there is confidence in such models, a case can be made to waive fed bioequivalence study, on a case-by-case basis (e.g. for BCS class 1 and 2 molecules with known food effect mechanism, reliable estimate of human pharmacokinetic parameters, and available in vivo data in fasted state for model verification). This has the potential to reduce clinical burden in drug development, increase confidence in pivotal BE studies and support regulatory applications such as justify waiving of BE study for Scale-Up and Post Approval Changes (SUPAC). Hence VBE can significantly reduce time and cost of drug development, as well as minimize drug exposure to healthy volunteers.

Using Physiologically Based Pharmacokinetic Modeling to Assess the Risks of Failing Bioequivalence Criteria: a Tale of Two Ibuprofen Products.

The aims of the proposed study were to develop and verify a quantitative model-based framework to anticipate the in vivo bioequivalence of ibuprofen immediate release formulations. This stepwise approach integrated virtual bioequivalence trials to simulate the test to reference (T/R) ratio for positive (i.e., bioequivalent) and negative (i.e., non-bioequivalent) control formulations containing ibuprofen, approximated distribution of interoccasion variability (IOV) on ibuprofen peak (Cmax) and extent of exposure (AUC) by bootstrapping resampling methods, post hoc incorporation of IOV to simulated T/R ratios, and power curve analysis. After post hoc incorporation of the bootstrapped IOV to the simulated Cmax T/R geometric mean ratios, the resulting 90% confidence intervals overlapped with the in vivo observations for both pairwise comparisons. On the other hand, simulated and observed AUC TNBE/R geometric mean ratios differed, likely due to the lack of propagating clearance-related IOV to the simulations. This approach is in line with modern regulatory initiatives that advocate leveraging quantitative methods and modeling to modernize generic drug development and review. Graphical abstract.