Physiologically Based Biopharmaceutics Modeling to Demonstrate Virtual Bioequivalence and Bioequivalence Safe-space for Ribociclib which has Permeation Rate-controlled Absorption

Conventional vs Mechanistic IVIVC: A Comparative Study in Establishing Dissolution Safe Space for Extended Release Formulations

The use of in vitro-in vivo correlation (IVIVC) for extended release oral dosage forms is an important technique that can avoid potential clinical studies. IVIVC has been a topic of discussion over the past two decades since the inception of USFDA guidance. It has been routinely used for biowaivers, establishment of dissolution safe space and clinically relevant dissolution specifications, for supporting site transfers, scale-up and post approval changes. Although conventional or mathematical IVIVC is routinely used, other approach such as mechanistic IVIVC can be of attractive choice as it integrates all the physiological aspects. In the present study, we have performed comparative evaluation of mechanistic and conventional IVIVC for establishment of dissolution safe space using divalproex sodium and tofacitinib extended release formulations as case examples. Conventional IVIVC was established using Phoenix and mechanistic IVIVC was set up using Gastroplus physiologically based biopharmaceutics model (PBBM). Virtual dissolution profiles with varying release rates were constructed around target dissolution profile using Weibull function. After internal and external validation, the virtual dissolution profiles were integrated into mechanistic and conventional IVIVC and safe space was established by absolute error and T/R ratio's methods. The results suggest that mechanistic IVIVC yielded wider safe space as compared to conventional IVIVC. The results suggest that a mechanistic approach of establishing IVIVC may be a flexible approach as it integrates physiological aspects. These findings suggest that mechanistic IVIVC has wider potential as compared to conventional IVIVC to gain wider dissolution safe space and thus can avoid potential clinical studies.

Can 3D Printed Tablets Be Bioequivalent and How to Test It: A PBPK Model Based Virtual Bioequivalence Study for Ropinirole Modified Release Tablets

As the field of personalized dosing develops, the pharmaceutical manufacturing industry needs to offer flexibility in terms of tailoring the drug release and strength to the individual patient's needs. One of the promising tools which have such capacity is 3D printing technology. However, manufacturing small batches of drugs for each patient might lead to huge test burden, including the need to conduct bioequivalence trials of formulations to support the change of equipment or strength. In this paper we demonstrate how to use 3D printing in conjunction with virtual bioequivalence trials based on physiologically based pharmacokinetic (PBPK) modeling. For this purpose, we developed 3D printed ropinirole formulations and tested their bioequivalence with the reference product Polpix. The Simcyp simulator and previously developed ropinirole PBPK model were used for the clinical trial simulations. The Weibull-fitted dissolution profiles of test and reference formulations were used as inputs for the model. The virtual bioequivalence trials were run using parallel design. The study power of 80% was reached using 125 individuals. The study demonstrated how to use PBPK modeling in conjunction with 3D printing to test the virtual bioequivalence of newly developed formulations. This virtual experiment demonstrated the bioequivalence of one of the newly developed formulations with a reference product available on a market.

Use of Pharmacokinetic and Pharmacodynamic Data to Develop the CDK4/6 Inhibitor Ribociclib for Patients with Advanced Breast Cancer

Ribociclib is an orally bioavailable, selective cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor. CDK4/6 inhibition by ribociclib leads to retinoblastoma tumor suppressor protein (Rb) reactivation, thereby restoring Rb-mediated cell cycle arrest. Ribociclib is approved for the treatment of patients with hormone receptor-positive/human epidermal growth factor receptor-2-negative (HR+/HER2-) advanced breast cancer (ABC), at the dose of 600 mg once daily (QD) during cycles of 21 days on/7 days off, with optional dose reduction to 400 mg and 200 mg. Ribociclib is rapidly absorbed with a median time to reach maximum plasma concentration of 2.4 h, mean half-life of 32.0 h and oral bioavailability of 65.8% at 600 mg. It is eliminated mainly by hepatic metabolism (~ 84% of total elimination), mostly by cytochrome P450 (CYP) 3A4. Age, body weight, race, baseline Eastern Cooperative Oncology Group status, food, mild hepatic impairment, mild-to-moderate renal impairment, proton pump inhibitors, and combination partners (non-steroidal aromatase inhibitors or fulvestrant) have no clinically relevant impact on ribociclib exposure. Ribociclib inhibits CYP3A at 600 mg leading to increased exposure of CYP3A substrates. Strong CYP3A inhibitors or inducers increase or decrease, respectively, ribociclib exposure. Exposure-safety and exposure-efficacy analyses support the clinical benefit of the 600 mg QD starting dose, with potential individualized dose reductions to 400 mg and 200 mg for effective management of the adverse events neutropenia and QTcF interval prolongation, while maintaining efficacy, in patients with HR+/HER2- ABC. Overall, these clinical pharmacology data informed ribociclib dose justification and clinical development, as well as its prescribing information for clinical use in advanced breast cancer patients.

Simple and rapid quantification of ribociclib in rat plasma by protein precipitation and LC-MS/MS: An application to pharmacokinetics of ribociclib nanoparticles in rats

Ribociclib is a cyclin-dependent kinase (CDK4/6) inhibitor and is a standard of care for treating metastatic breast cancer. The drug has moderate oral bioavailability and exhibits permeability-controlled absorption. Novel formulations to enhance ribociclib pharmacokinetics are being developed and tested in rats. This requires developing analytical assays for quantifying ribociclib monitoring in rat plasma. We present a fully validated, sensitive, and simple LC-MS/MS method for measuring ribociclib in rat plasma. Ribociclib-D6 was utilized as an internal standard, and a simple protein precipitation procedure with acetonitrile was used in sample preparation. Excellent assay linearity was observed over a standard curve concentration of 1.008-1027.624 ng/mL. Acceptable intra- and inter-day accuracy and reproductivity were demonstrated for ribociclib quality controls (bias and CV% within ±15%). Complete extraction recovery of ribociclib was achieved, and a negligible matrix effect of analyte to internal standard ratio was observed. Ribociclib was stable at various conditions, including bench-top, freeze-thaw, and short-term stability. Overall, the presented method is simple, sensitive, accurate, and precise and was successfully applied to quantify ribociclib in plasma samples from a pharmacokinetic study of ribociclib suspension and nanoparticle formulation in rats.

Applications of Modeling and Simulation Approaches in Support of Drug Product Development of Oral Dosage Forms and Locally Acting Drug Products: a Symposium Summary

The number of modeling and simulation applications, including physiologically based pharmacokinetic (PBPK) models, physiologically based biopharmaceutics modeling (PBBM), and empirical models, has been constantly increasing along with the regulatory acceptance of these methodologies. While aiming at minimizing unnecessary human testing, these methodologies are used today to support the development and approval of novel drug products and generics. Modeling approaches are leveraged today for assessing drug-drug interaction, informing dose adjustments in renally or hepatically impaired patients, perform dose selection in pediatrics and pregnant women and diseased populations, and conduct biopharmaceutics-related assessments such as establish clinically relevant specifications for drug products and achieve quality assurance throughout the product life cycle. In the generics space, PBPK analyses are utilized toward virtual bioequivalence assessments within the scope of alternative bioequivalence approaches, product-specific guidance development, and food effect assessments among others. Case studies highlighting the evolving and expanding role of modeling and simulation approaches within the biopharmaceutics space were presented at the symposium titled "Model Informed Drug Development (MIDD): Role in Dose Selection, Vulnerable Populations, and Biowaivers - Chemical Entities" and Prologue "PBPK/PBBM to inform the Bioequivalence Safe Space, Food Effects, and pH-mediated DDIs" at the American Association of Pharmaceutical Scientists (AAPS) PharmSci 360 Annual Meeting in Boston, MA, on October 16-19, 2022, and are summarized here.

Application of physiologically based pharmacokinetics modeling in the research of small-molecule targeted anti-cancer drugs

INTRODUCTION

Physiologically based pharmacokinetics (PBPK) models are increasingly used in the drug research and development, especially in anti-cancer drugs. Between 2001 and 2020, a total of 89 small-molecule targeted antitumor drugs were approved in China and the United States, some of which already included PBPK modeling in their application or approval packages. This article intended to review the prevalence and application of PBPK model in these drugs.

METHOD

Article search was performed in the PubMed to collect English research articles on small-molecule targeted anti-cancer drugs using PBPK modeling. The selected articles were classified into nine categorizes according to the application areas and further analyzed.

RESULT

From 2001 to 2020, more than 60% of small-molecule targeted anti-cancer drugs (54/89) were studied using PBPK model with a wide range of application. Ninety research articles were included, of which 48 involved enzyme-mediated drug-drug interaction (DDI). Of these retrieved articles, Simcyp, GastroPlus, and PK-Sim were the most widely model building platforms, which account for 63.8%, 15.2%, and 8.6%, respectively.

CONCLUSION

PBPK modeling is commonly and widely used to research small-molecule targeted anti-cancer drugs.

Progressive tools and critical strategies for development of best fit PBPK model aiming better in vitro-in vivo correlation

Nowadays, conducting discriminative dissolution experiments employing physiologically based pharmacokinetic modeling (PBPK) or physiologically based biopharmaceutical modeling (PBBM) is gaining significant importance in quantitatively predicting oral absorption of drugs. Mechanistic understanding of each process involved in drug absorption and its impact on the performance greatly facilitates designing a formulation with high confidence. Unfortunately, the biggest challenge scientists are facing in current days is the lack of standardized protocol for integrating dissolution experiment data during PBPK modeling. However, in vitro-in vivo drug release interrelation can be improved with the consideration and development of appropriate biorelevant dissolution media that closely mimic physiological conditions. Multiple reported dissolution models have described nature and functionality of different regions of the gastrointestinal tract (GI) to more accurately design discriminative dissolution media. Dissolution experiment data can be integrated either mechanistically or without a mechanism depending primarily on the formulation type, biopharmaceutics classification system (BCS) class and particle size of the drug substance. All such parameters are required to be considered for selecting the appropriate functions during PBPK modeling to produce a best fit model. The primary focus of this review is to critically discuss various progressive dissolution models and tools, existing challenges and approaches for establishing best fit PBPK model aiming better in vitro-in vivo correlation (IVIVC). Strategies for proper selection of dissolution models as an input function in PBPK/PBBM modeling have also been critically discussed. Logical and scientific pathway for selection of different type of functions and integration events in the commercially available in silico software has been described through case studies.

Integration of artificial neural network and physiologically based biopharmaceutic models in the development of sustained-release formulations

Model-informed drug development is an important area recognized by regulatory authorities and is gaining increasing interest from the generic drug industry. Physiologically based biopharmaceutics modeling (PBBM) is a valuable tool to support drug development and bioequivalence assessments. This study aimed to utilize an artificial neural network (ANN) with a multilayer perceptron (MLP) model to develop a sustained-release matrix tablet of metformin HCl 500 mg, and to test the likelihood of the prototype formulation being bioequivalent to Glucophage® XR, using PBBM modeling and virtual bioequivalence (vBE). The ANN with MLP model was used to simultaneously optimize 735 formulations to determine the optimal formulation for Glucophage® XR release. The optimized formulation was evaluated and compared to Glucophage® XR using PBBM modeling and vBE. The optimized formulation consisted of 228 mg of hydroxypropyl methylcellulose (HPMC) and 151 mg of PVP, and exhibited an observed release rate of 42% at 1 h, 47% at 2 h, 55% at 4 h, and 58% at 8 h. The PBBM modeling was effective in assessing the bioequivalence of two formulations of metformin, and the vBE evaluation demonstrated the utility and relevance of translational modeling for bioequivalence assessments. The study demonstrated the effectiveness of using PBBM modeling and model-informed drug development methodologies, such as ANN and MLP, to optimize drug formulations and evaluate bioequivalence. These tools can be utilized by the generic drug industry to support drug development and biopharmaceutics assessments.

Dissolution Profile Similarity Assessment-Best Practices, Decision Trees and Global Harmonization

During the write-up of the meeting summary reports from the 2019 dissolution similarity workshop held at the University of Maryland's Center of Excellence in Regulatory Science and Innovation (M-CERSI), several coauthors continued their discussions to develop a "best-practice" document defining the steps required to assess dissolution profiles in support of certain biowaivers and postapproval changes. In previous reports, current challenges related to dissolution profile studies were discussed such that the steps outlined in the two flow charts ("decision trees") presented here can be applied. These decision trees include both recommendations for the use of equivalence procedures between reference and test products as well as application of the dissolution safe space concept. Common approaches towards establishing dissolution safe spaces are described. This paper encourages the preparation of protocols clearly describing why and how testing is performed along with the expected pass/fail criteria prior to generating data on the materials to be evaluated. The target audience of this manuscript includes CMC regulatory scientists, laboratory analysts, as well as statisticians from industry and regulatory health agencies involved in the assessment of product quality via in vitro dissolution testing. Building upon previous publications, this manuscript provides a solution to the current ambiguity related to dissolution profile comparison. The principles outlined in this and previous manuscripts provide a basis for global regulatory alignment in the application of dissolution profile assessment to support manufacturing changes and biowaiver requests.

Evaluation and prediction of oral drug absorption and bioequivalence with food-drug interaction

This article reviews the impacts on the in vivo prediction of oral bioavailability (BA) and bioequivalence (BE) based on Biopharmaceutical classification systems (BCS) by the food-drug interaction (food effect) and the gastrointestinal (GI) environmental change. Various in vitro and in silico predictive methodologies have been used to expect the BA and BE of the test oral formulation. Food intake changes the GI physiology and environment, which affect oral drug absorption and its BE evaluation. Even though the pHs and bile acids in the GI tract would have significant influence on drug dissolution and, hence, oral drug absorption, those impacts largely depend on the physicochemical properties of oral medicine, active pharmaceutical ingredients (APIs). BCS class I and III drugs are high soluble drugs in the physiological pH range, food-drug interaction may not affect their BA. On the other hand, BCS class II and IV drugs have pH-dependent solubility, and the more bile acid secretion and the pH changes by food intake might affect their BA. In this report, the GI physiological changes between the fasted and fed states are described and the prediction on the oral drug absorption by food-drug interaction have been introduced.

Justifying Ribociclib Dose in Patients with Advanced Breast Cancer with Renal Impairment Based on PK, Safety, and Efficacy Data: An Innovative Approach Integrating Data from a Dedicated Renal Impairment Study and Oncology Clinical Trials

BACKGROUND AND OBJECTIVE

Renal impairment is common in patients with cancer and can alter the PK and thus the safety and efficacy of drugs. We assessed the impact of renal impairment during treatment with ribociclib, a cyclin-dependent kinase 4/6 inhibitor, and determined dose recommendations for patients with advanced breast cancer with renal impairment.

METHODS

A comprehensive assessment integrating pharmacokinetic, safety, and efficacy data from a phase I dedicated renal impairment study in non-cancer subjects and six phase I-III trials in patients with cancer was performed.

RESULTS

Ribociclib showed higher pharmacokinetic exposure in subjects with renal impairment than those with normal renal function following a single 400-mg dose in the dedicated renal impairment study. However, in patient trials, both single-dose and steady‑state ribociclib exposure was comparable between patients with cancer with mild/moderate renal impairment and those with normal renal function following the recommended starting dose of 600 mg. Model-predicted steady‑state exposure in patients with advanced breast cancer was also similar across the renal function groups. Progression-free survival was similar and safety profiles were generally consistent across the renal cohorts (normal/mild/moderate) in patients with advanced breast cancer, with low-grade and manageable adverse events, demonstrating a positive benefit-risk profile.

CONCLUSIONS

From the collective evidence and considering a real-world clinical setting, no dose adjustment is recommended for patients with mild/moderate renal impairment, whereas a reduced dose is recommended for patients with severe renal impairment. This report presented a holistic and innovative strategy to determine dose in patients with renal impairment and demonstrated the effectiveness of integrating the data of both a clinical pharmacology study and patient trials to justify doses in patients with renal impairment.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov identifiers: NCT02431481, NCT01958021, NCT02422615, NCT02278120, NCT01237236, NCT01898845, NCT01872260.

Establishing the Safe Space via Physiologically Based Biopharmaceutics Modeling. Case Study: Fevipiprant/QAW039

Physiologically based pharmacokinetic and absorption modeling has increasingly been implemented for biopharmaceutics applications to define the safe space for drug product quality attributes such as dissolution. For fevipiprant/QAW039, simulations were performed to assess the impact of in vitro dissolution on the in vivo performance of immediate-release film-coated tablets during development and scaling up to commercial scale. A fevipiprant dissolution safe space was established using observed clinical intravenous and oral PK data from bioequivalent and non-bioequivalent formulations. Quality control dissolution profiles with tablets were used as GastroPlus™ model inputs to estimate the in vivo dissolution in the gastrointestinal tract and to simulate human exposure. The model was used to evaluate the intraluminal performance of the dosage forms and to predict the absorption rate limits for the 450 mg dose. The predictive model performance was demonstrated for various oral dosage forms (150‒500 mg), including the non-bioequivalent batches in fasted healthy adults. To define the safe space at 450 mg, simulations were performed using theoretical dissolution profiles. A specification of Q = 80% dissolved in 60 min or less for an immediate-release oral solid dosage form reflected the boundaries of the safe space. The dissolution profile of the 450 mg commercial scale batch was within a dissolution region where bioequivalence is anticipated, not near an edge of failure for dissolution, providing additional confidence to the proposed acceptance criteria. Thus, the safe space allowed for a wider than 10% dissolution difference for bioequivalent batches, superseding f₂ similarity analyses.

Best Practices for Integration of Dissolution Data into Physiologically Based Biopharmaceutics Models (PBBM): A Biopharmaceutics Modeling Scientist Perspective

Dissolution is considered as a critical input into physiologically based biopharmaceutics models (PBBM) as it governs in vivo exposure. Despite many workshops, initiatives by academia, industry, and regulatory, wider practices are followed for dissolution data input into PBBM models. Due to variety of options available for dissolution data input into PBBM models, it is important to understand pros, cons, and best practices while using specific dissolution model. This present article attempts to summarize current understanding of various dissolution models and data inputs in PBBM software's and aims to discuss practical challenges and ways to overcome such scenarios. Different approaches to incorporate dissolution data for immediate, modified, and delayed release formulations are discussed in detail. Common challenges faced during fitting of z-factor are discussed along with novel approach of dissolution data incorporation using P-PSD model. Ways to incorporate dissolution data for MR formulations using Weibull and IVIVR approaches were portrayed with examples. Strategies to incorporate dissolution data for DR formulations was depicted along with practical aspects. Approaches to generate virtual dissolution profiles, using Weibull function, DDDPlus, and time scaling for defining dissolution safe space, and strategies to generate virtual dissolution profiles for justifying single and multiple dissolution specifications were discussed. Finally, novel ways to integrate dissolution data for complex products such as liposomes, data from complex dissolution systems, importance of precipitation, and bio-predictive ability of QC media for evaluation of CBA's impact were discussed. Overall, this article aims to provide an easy guide for biopharmaceutics modeling scientist to integrate dissolution data effectively into PBBM models.

Physiologically Based Absorption Modelling to Explore the Formulation and Gastric pH Changes on the Pharmacokinetics of Acalabrutinib

Acalabrutinib, a selective Bruton's tyrosine kinase inhibitor, is a biopharmaceutics classification system class II drug. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to mechanistically describe absorption of immediate release capsule formulation of acalabrutinib in humans. Integration of in vitro biorelevant measurements, dissolution studies and in silico modelling provided clinically relevant inputs for the mechanistic absorption PBPK model. The batch specific dissolution data were integrated in two ways, by fitting a diffusion layer model scalar to the drug product dissolution with integration of drug substance laser diffraction particle size data, or by fitting a product particle size distribution to the dissolution data. The latter method proved more robust and biopredictive. In both cases, the drug surface solubility was well predicted by the Simcyp simulator. The model using the product particle size distribution (P-PSD) for each clinical batch adequately captured the PK profiles of acalabrutinib and its active metabolite. Average fold errors were 0.89 for both Cmax and AUC, suggesting good agreement between predicted and observed PK values. The model also accurately predicted pH-dependent drug-drug interactions between omeprazole and acalabrutinib, which was similar across all clinical formulations. The model predicted acalabrutinib geometric mean AUC ratios (with omeprazole vs acalabrutinib alone) were 0.51 and 0.68 for 2 batches of formulations, which are close to observed values of 0.43 and 0.51~0.63, respectively. The mechanistic absorption PBPK model could be potentially used for future applications such as optimizing formulations or predicting the PK for different batches of the drug product.

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.

Physiologically Based Biopharmaceutics Model for Selumetinib Food Effect Investigation and Capsule Dissolution Safe Space - Part I: Adults

OBJECTIVE

A physiologically based biopharmaceutics model (PBBM) was developed to mechanistically investigate the effect of formulation and food on selumetinib pharmacokinetics.

METHODS

Selumetinib is presented as a hydrogen sulfate salt, and in vitro and in vivo data were used to verify the precipitation rate to apply to simulations. Dissolution profiles observed for capsules and granules were used to derive product-particle size distributions for model input. The PBBM incorporated gut efflux and first-pass gut metabolism, based on intravenous and oral pharmacokinetic data, alongside in vitro data for the main enzyme isoform and P-glycoprotein efflux. The PBBM was validated across eight clinical scenarios.

RESULTS

The quality-control dissolution method for selumetinib capsules was found to be clinically relevant through PBBM validation. A safe space for capsule dissolution was established using a virtual batch. The effect of food (low fat vs high fat) on capsules and granules was elucidated by the PBBM. For capsules, a lower amount was dissolved in the fed state due to a pH increase in the stomach followed by higher precipitation in the small intestine. First-pass gut extraction is higher for capsules in the fed state due to drug dilution in the stomach chyme and reduced concentration in the lumen. The enteric-coated granules dissolve more slowly than capsules after stomach emptying, attenuating the difference in first-pass gut extraction between prandial states.

CONCLUSIONS

The PBBM was instrumental in understanding and explaining the different behaviors of the selumetinib formulations. The model can be used to predict the impact of food in humans.

Physiologically Based Pharmacokinetics Modeling in Biopharmaceutics: Case Studies for Establishing the Bioequivalence Safe Space for Innovator and Generic Drugs

For successful oral drug development, defining a bioequivalence (BE) safe space is critical for the identification of newer bioequivalent formulations or for setting of clinically relevant in vitro specifications to ensure drug product quality. By definition, the safe space delineates the dissolution profile boundaries or other drug product quality attributes, within which the drug product variants are anticipated to be bioequivalent. Defining a BE safe space with physiologically based biopharmaceutics model (PBBM) allows the establishment of mechanistic in vitro and in vivo relationships (IVIVR) to better understand absorption mechanism and critical bioavailability attributes (CBA). Detailed case studies on how to use PBBM to establish a BE safe space for both innovator and generic drugs are described. New case studies and literature examples demonstrate BE safe space applications such as how to set in vitro dissolution/particle size distribution (PSD) specifications, widen dissolution specification to supersede f2 tests, or application toward a scale-up and post-approval changes (SUPAC) biowaiver. A workflow for detailed PBBM set-up and common clinical study data requirements to establish the safe space and knowledge space are discussed. Approaches to model in vitro dissolution profiles i.e. the diffusion layer model (DLM), Takano and Johnson models or the fitted PSD and Weibull function are described with a decision tree. The conduct of parameter sensitivity analyses on kinetic dissolution parameters for safe space and virtual bioequivalence (VBE) modeling for innovator and generic drugs are shared. The necessity for biopredictive dissolution method development and challenges with PBBM development and acceptance criteria are described.

Utility of Physiologically Based Biopharmaceutics Modeling (PBBM) in Regulatory Perspective: Application to Supersede f2, Enabling Biowaivers & Creation of Dissolution Safe Space

Product DRL is a generic IR tablet formulation with BCS Class-III API, available in two strengths: 50mg & 100mg. The reference and test formulations have salt-A & salt-B of API but both products were bioequivalent based on the in vivo bioequivalence study conducted for higher strength 100mg. While leveraging the generic product to different market, the reference product from other market showed slower release than generic formulation resulting in f2<50 in pH 6.8 for both 50mg and 100mg, because of which waiver for BE study couldn't be granted. To support f2 mismatch at 100mg, 50mg and to facilitate biowaiver of 50mg, a Gastroplus® PBBM model was developed & validated. Virtual bioequivalence trials were performed using the slower dissolution profile of other market reference. It was demonstrated that despite slower dissolution, bioequivalence was achieved for test product against other market reference for 50mg & 100mg strengths. Additionally, dissolution safe space was created using virtual dissolution profiles, which indicated that when >85% released up to 60 min there is no impact on bioequivalence. Overall, for molecules with permeability controlled absorption (i.e. BCS-III), very rapid dissolution criteria can be relaxed by defining dissolution safe space thereby enabling more waivers in future.

The Use of Physiologically Based Pharmacokinetic Analyses-in Biopharmaceutics Applications -Regulatory and Industry Perspectives

The use of physiologically based pharmacokinetic (PBPK) modeling to support the drug product quality attributes, also known as physiologically based biopharmaceutics modeling (PBBM) is an evolving field and the interest in using PBBM is increasing. The US-FDA has emphasized on the use of patient centric quality standards and clinically relevant drug product specifications over the years. Establishing an in vitro in vivo link is an important step towards achieving the goal of patient centric quality standard. Such a link can aid in constructing a bioequivalence safe space and establishing clinically relevant drug product specifications. PBBM is an important tool to construct a safe space which can be used during the drug product development and lifecycle management. There are several advantages of using the PBBM approach, though there are also a few challenges, both with in vitro methods and in vivo understanding of drug absorption and disposition, that preclude using this approach and therefore further improvements are needed. In this review we have provided an overview of experience gained so far and the current perspective from regulatory and industry point of view. Collaboration between scientists from regulatory, industry and academic fields can further help to advance this field and deliver on promises that PBBM can offer towards establishing patient centric quality standards.