Relative Performance of Volume of Distribution Prediction Methods for Lipophilic Drugs with Uncertainty in LogP Value.

PURPOSE: The goal was to assess, for lipophilic drugs, the impact of logP on human volume of distribution at steady-state (VDss) predictions, including intermediate fut and Kp values, from six methods: Oie-Tozer, Rodgers-Rowland (tissue-specific Kp and only muscle Kp), GastroPlus, Korzekwa-Nagar, and TCM-New. METHOD: A sensitivity analysis with focus on logP was conducted by keeping pKa and fup constant for each of four drugs, while varying logP. VDss was also calculated for the specific literature logP values. Error prediction analysis was conducted by analyzing prediction errors by source of logP values, drug, and overall values. RESULTS: The Rodgers-Rowland methods were highly sensitive to logP values, followed by GastroPlus and Korzekwa-Nagar. The Oie-Tozer and TCM-New methods were only modestly sensitive to logP. Hence, the relative performance of these methods depended upon the source of logP value. As logP values increased, TCM-New and Oie-Tozer were the most accurate methods. TCM-New was the only method that was accurate regardless of logP value source. Oie-Tozer provided accurate predictions for griseofulvin, posaconazole, and isavuconazole; GastroPlus for itraconazole and isavuconazole; Korzekwa-Nagar for posaconazole; and TCM-New for griseofulvin, posaconazole, and isavuconazole. Both Rodgers-Rowland methods provided inaccurate predictions due to the overprediction of VDss. CONCLUSIONS: TCM-New was the most accurate prediction of human VDss across four drugs and three logP sources, followed by Oie-Tozer. TCM-New showed to be the best method for VDss prediction of highly lipophilic drugs, suggesting BPR as a favorable surrogate for drug partitioning in the tissues, and which avoids the use of fup.

In Vitro Lipolysis Model to Predict Food Effect of Poorly Water-Soluble Drugs Itraconazole, Rivaroxaban, and Ritonavir.

It is desirable to predict positive food effect of oral formulations due to food mediated dissolution enhancement of lipophilic drugs. The objective was to assess the ability of in vitro lipolysis to anticipate a positive food effect. Tested formulations included rivaroxaban and itraconazole, where some formulations, but not all, exhibit a positive food effect in vivo in humans. Amorphous solid dispersion formulations of ritonavir, which exhibit a negative food effect in vivo in humans, were also studied. Fe-lipolysis and Fa-lipolysis media representing fed and fasted intestinal conditions were used. Results show frequent agreement between in vitro lipolysis predictions and in vivo human outcomes. For rivaroxaban, food effect of unformulated active pharmaceutical ingredient (API) and products were correctly predicted where 2.5 mg and 10 mg strengths did not show any food effect; however, 20 mg did show a positive food effect. For itraconazole, all four products were correctly predicted, with Sporanox, Sempera, and generic capsules having a food effect, but Tolsura not having a positive food effect. For ritonavir, lipolysis predicted a positive food effect for API and Norvir tablet and powder, but Norvir products have negative food effect in vivo in humans. Overall, the lipolysis model showed favorable predictability and merits additional evaluation.

Comparative Study of Basement-membrane Matrices for Human Stem Cell Maintenance and Intestinal Organoid Generation.

Extracellular matrix (ECM) plays a critical role in cell behavior and development. Organoids generated from human induced pluripotent stem cells (hiPSCs) are in the spotlight of many research areas. However, the lack of physiological cues in classical cell culture materials hinders efficient iPSC differentiation. Incorporating commercially available ECM into stem cell culture provides physical and chemical cues beneficial for cell maintenance. Animal-derived commercially available basement membrane products are composed of ECM proteins and growth factors that support cell maintenance. Since the ECM holds tissue-specific properties that can modulate cell fate, xeno-free matrices are used to stream up translation to clinical studies. While commercially available matrices are widely used in hiPSC and organoid work, the equivalency of these matrices has not been evaluated yet. Here, a comparative study of hiPSC maintenance and human intestinal organoids (hIO) generation in four different matrices: Matrigel (Matrix 1-AB), Geltrex (Matrix 2-AB), Cultrex (Matrix 3-AB), and VitroGel (Matrix 4-XF) was conducted. Although the colonies lacked a perfectly round shape, there was minimal spontaneous differentiation, with over 85% of the cells expressing the stem cell marker SSEA-4. Matrix 4-XF led to the formation of 3D round clumps. Also, increasing the concentration of supplement and growth factors in the media used to make the Matrix 4-XF hydrogel solution improved hiPSC expression of SSEA-4 by 1.3-fold. Differentiation of Matrix 2-AB -maintained hiPSC led to fewer spheroid releases during the mid-/hindgut stage compared to the other animal-derived basement membranes. Compared to others, the xeno-free organoid matrix (Matrix 4-O3) leads to larger and more mature hIO, suggesting that the physical properties of xeno-free hydrogels can be harnessed to optimize organoid generation. Altogether, the results suggest that variations in the composition of different matrices affect stages of IO differentiation. This study raises awareness about the differences in commercially available matrices and provides a guide for matrix optimization during iPSC and IO work.

Mechanistic Modeling of In Vitro Biopharmaceutic Data for a Weak Acid Drug: A Pathway Towards Deriving Fundamental Parameters for Physiologically Based Biopharmaceutic Modeling.

Mechanistic modeling of in vitro experiments using metabolic enzyme systems enables the extrapolation of metabolic clearance for in vitro-in vivo predictions. This is particularly important for successful clearance predictions using physiologically based pharmacokinetic (PBPK) modeling. The concept of mechanistic modeling can also be extended to biopharmaceutics, where in vitro data is used to predict the in vivo pharmacokinetic profile of the drug. This approach further allows for the identification of parameters that are critical for oral drug absorption in vivo. However, the routine use of this analysis approach has been hindered by the lack of an integrated analysis workflow. The objective of this tutorial is to (1) review processes and parameters contributing to oral drug absorption in increasing levels of complexity, (2) outline a general physiologically based biopharmaceutic modeling workflow for weak acids, and (3) illustrate the outlined concepts via an ibuprofen (i.e., a weak, poorly soluble acid) case example in order to provide practical guidance on how to integrate biopharmaceutic and physiological data to better understand oral drug absorption. In the future, we plan to explore the usefulness of this tutorial/roadmap to inform the development of PBPK models for BCS 2 weak bases, by expanding the stepwise modeling approach to accommodate more intricate scenarios, including the presence of diprotic basic compounds and acidifying agents within the formulation.

Exploring the impact of CYP2D6 and UGT2B7 gene-drug interactions, and CYP-mediated DDI on oxycodone and oxymorphone pharmacokinetics using physiologically-based pharmacokinetic modeling and simulation.

Oxycodone is one of the most commonly used opioids to treat moderate to severe pain. It is metabolized mainly by CYP3A4 and CYP2D6, while only a small fraction of the dose is excreted unchanged into the urine. Oxymorphone, the metabolite primarily formed by CYP2D6, has a 40- to 60-fold higher mu-opioid receptor affinity than the parent compound. While CYP2D6-mediated gene-drug-interactions (GDIs) and drug-drug interactions (DDIs) are well-studied, they only account for a portion of the variability in oxycodone and oxymorphone exposure. The combined impact of CYP2D6-mediated GDIs and DDIs, CYP3A4-mediated DDIs, and UGT2B7 GDIs is not fully understood yet and hard to study in head-to-head clinical trials given the relatively large number of scenarios. Instead, we propose the use of a physiologically-based pharmacokinetic model that integrates available information on oxycodone's metabolism to characterize and predict the impact of DDIs and GDIs on the exposure of oxycodone and its major, pharmacologically-active metabolite oxymorphone. To this end, we first developed and verified a PBPK model for oxycodone and its metabolites using published clinical data. The verified model was then applied to determine the dose-exposure relationship of oxycodone and oxymorphone stratified by CYP2D6 and UGT2B7 phenotypes respectively, and administered perpetrators of CYP-based drug interactions. Our simulations demonstrate that the combination of CYP2D6 UM and a UGT2B7Y (268) mutation may lead to a 2.3-fold increase in oxymorphone exposure compared to individuals who are phenotyped as CYP2D6 NM / UGT2B7 NM. The extent of oxymorphone exposure increases up to 3.2-fold in individuals concurrently taking CYP3A4 inhibitors, such as ketoconazole. Inhibition of the CYP3A4 pathway results in a relative increase in the partial metabolic clearance of oxycodone to oxymorphone. Oxymorphone is impacted to a higher extent by GDIs and DDIs than oxycodone. We predict oxymorphone exposure to be highest in CYP2D6 UMs/UGT2B7 PMs in the presence of ketoconazole (strong CYP3A4 index inhibitor) and lowest in CYP2D6 PMs/UGT2B7 NMs in the presence of rifampicin (strong CYP3A4 index inducer) covering a 55-fold exposure range.

Biowaiver Monograph for Immediate-Release Solid Oral Dosage Forms: Isavuconazonium Sulfate.

A Biopharmaceutics Classification System (BCS)-based biowaiver monograph is presented for isavuconazonium sulfate. A BCS-based biowaiver is a regulatory option to substitute appropriate in vitro data for in vivo bioequivalence studies. Isavuconazonium sulfate is the prodrug of isavuconazole, a broad-spectrum azole antifungal indicated for invasive fungal infections. While the prodrug can be classified as a BCS Class III drug with high solubility but low permeability, the parent drug can be classified as a BCS Class II drug with low solubility but high permeability. Interestingly, the in vivo behavior of both is additive and leads isavuconazonium sulfate to act like a BCS class I drug substance after oral administration. In this work, experimental solubility and dissolution data were evaluated and compared with available literature data to investigate whether it is feasible to approve immediate release solid oral dosage forms containing isavuconazonium sulfate according to official guidance from the FDA, EMA and/or ICH. The risks associated with waiving a prodrug according to the BCS-based biowaiver guidelines are reviewed and discussed, noting that current regulations are quite restrictive on this point. Further, results show high solubility but instability of isavuconazonium sulfate in aqueous media. Although experiments on the dissolution of the capsule contents confirmed 'very rapid' dissolution of the active pharmaceutical ingredient (API) isavuconazonium sulfate, its release from the commercial marketed capsule formulation Cresemba is limited by the choice of capsule shell material, providing an additional impediment to approval of generic versions via the BCS-Biowaiver approach.

Adult and pediatric physiologically-based biopharmaceutics modeling to explain lamotrigine immediate release absorption process.

Physiologically-based biopharmaceutics modeling (PBBM) has potential to accelerate the development of new drug and formulations. An important application of PBBM is for special populations such as pediatrics that have pharmacokinetics dependent on the maturation process. Lamotrigine (LTG) is a Biopharmaceutics Classification System (BCS) II drug and is widely prescribed. Therefore, the goal of this study was to assess the biopharmaceutics risk of the low-soluble drug LTG when the ontogeny on gastrointestinal tract (GIT) physiological parameters are considered. An oral physiologically-based pharmacokinetic model and a PBBM were developed and verified using GastroPlus™ software for both adults and children (2-12 years old, 12-52 kg). The biopharmaceutics properties and GIT physiological parameters were evaluated by sensitivity analysis. High doses were simulated assuming a worst case scenario, that is, the dose of 200 mg for adults and 5 mg/kg (up to the maximum of 200 mg) for 2-year-old children. Although several authors have suggested that ontogeny may have an effect on gastrointestinal fluid volume, our study found no evidence of interference between fluid and dose volumes with in vivo dissolution of LTG. The most impactful parameter was found to be the gastric transit time. Therefore, the hypothesis is developed to examine whether LTG exhibits characteristics of a BCS II classification in vitro while showing BCS I-like behavior in vivo. This hypothesis could act as a base for conducting novel studies on model-informed precision dosing, tailored to specific populations and clinical conditions. In addition, it could be instrumental in assessing the influence of various release profiles on in vivo performance for both adult and pediatric populations.

Challenges in Permeability Assessment for Oral Drug Product Development.

Drug permeation across the intestinal epithelium is a prerequisite for successful oral drug delivery. The increased interest in oral administration of peptides, as well as poorly soluble and poorly permeable compounds such as drugs for targeted protein degradation, have made permeability a key parameter in oral drug product development. This review describes the various in vitro, in silico and in vivo methodologies that are applied to determine drug permeability in the human gastrointestinal tract and identifies how they are applied in the different stages of drug development. The various methods used to predict, estimate or measure permeability values, ranging from in silico and in vitro methods all the way to studies in animals and humans, are discussed with regard to their advantages, limitations and applications. A special focus is put on novel techniques such as computational approaches, gut-on-chip models and human tissue-based models, where significant progress has been made in the last few years. In addition, the impact of permeability estimations on PK predictions in PBPK modeling, the degree to which excipients can affect drug permeability in clinical studies and the requirements for colonic drug absorption are addressed.

Comprehensive Physiologically Based Pharmacokinetic Model to Assess Drug-Drug Interactions of Phenytoin.

Regulatory agencies worldwide expect that clinical pharmacokinetic drug-drug interactions (DDIs) between an investigational new drug and other drugs should be conducted during drug development as part of an adequate assessment of the drug's safety and efficacy. However, it is neither time nor cost efficient to test all possible DDI scenarios clinically. Phenytoin is classified by the Food and Drug Administration as a strong clinical index inducer of CYP3A4, and a moderate sensitive substrate of CYP2C9. A physiologically based pharmacokinetic (PBPK) platform model was developed using GastroPlus® to assess DDIs with phenytoin acting as the victim (CYP2C9, CYP2C19) or perpetrator (CYP3A4). Pharmacokinetic data were obtained from 15 different studies in healthy subjects. The PBPK model of phenytoin explains the contribution of CYP2C9 and CYP2C19 to the formation of 5-(4'-hydroxyphenyl)-5-phenylhydantoin. Furthermore, it accurately recapitulated phenytoin exposure after single and multiple intravenous and oral doses/formulations ranging from 248 to 900 mg, the dose-dependent nonlinearity and the magnitude of the effect of food on phenytoin pharmacokinetics. Once developed and verified, the model was used to characterize and predict phenytoin DDIs with fluconazole, omeprazole and itraconazole, i.e., simulated/observed DDI AUC ratio ranging from 0.89 to 1.25. This study supports the utility of the PBPK approach in informing drug development.

A robust, viable, and resource sparing HPLC-based logP method applied to common drugs.

Reliable, experimentally determined partition coefficient P (logP) for most drugs are often unavailable in the literature. Many values are from in silico predictions and may not accurately reflect drug lipophilicity. In this study, a robust, viable, and resource sparing method to measure logP was developed using reverse phase high performance liquid chromatography (RP-HPLC). The logP of twelve common drugs was measured using calibration curves at pH 6 and 9 that were created using reference standards with well-established logP. The HPLC method reported here can be used for high throughput estimation of logP of commonly used drugs. LogP values here showed general agreement with the other few HPLC-based literature logP values available. Additionally, the HPLC-based logP values found here agreed partially with literature logP values found using other methodologies (±10%). However, there was no strong agreement since there are few experimentally determined literature logP values. This paper shows a facile method to estimate logP without using octanol or computational approaches. This method has excellent promise to provide reliable logP values of commonly used drugs available in literature. A larger pool of reliable logP values of commonly drugs has promise to improve quality of medicinal chemistry and pharmacokinetic (PK) models.

Model-Based Analysis of In Vivo Release Data of Levonorgestrel Implants: Projecting Long-Term Systemic Exposure.

Levonorgestrel (LNG) is a progestin used in many contraceptive formulations, including subcutaneous implants. There is an unmet need for developing long-acting formulations for LNG. To develop long-acting formulations, release functions need to be investigated for LNG implant. Therefore, a release model was developed and integrated into an LNG physiologically-based pharmacokinetic (PBPK) model. Utilizing a previously developed LNG PBPK model, subcutaneous administration of 150 mg LNG was implemented into the modeling framework. To mimic LNG release, ten functions incorporating formulation-specific mechanisms were explored. Release kinetic parameters and bioavailability were optimized using Jadelle® clinical trial data (n = 321) and verified using two additional clinical trials (n = 216). The First-order release and Biexponential release models showed the best fit with observed data, the adjusted R-squared (R2) value is 0.9170. The maximum released amount is approximately 50% of the loaded dose and the release rate is 0.0009 per day. The Biexponential model also showed good agreement with the data (adjusted R2 = 0.9113). Both models could recapitulate observed plasma concentrations after integration into the PBPK simulations. First-order and Biexponential release functionality may be useful in modeling subcutaneous LNG implants. The developed model captures central tendency of the observed data as well as variability of release kinetics. Future work focuses on incorporating various clinical scenarios into model simulations, including drug-drug interactions and a range of BMIs.

Exploring in vitro solubility of lamotrigine in physiologically mimetic conditions to prospect the in vivo dissolution in pediatric population.

Pediatric drugs knowledge still leaves several gaps to be filled, all the while many biopharmaceutic properties applied to adults do not work in pediatrics. The solubility in many cases is extrapolated to pediatrics; however, sometimes it may not represent the real scenario. In this context, the aim of this study was to assess the possibility of the extrapolation of the solubility data assumed for adults to children aged 2-12 years using lamotrigine (LTG) as a model. LTG showed that its solubility is dependent on the pH of the medium, no precipitate formation was seen, and biomimetic media showed a greater capacity to solubilize it. Based on the dose number (D0 ) in adults, the LTG was soluble in acidic pH media and poorly soluble in neutral to basic. Similar behavior was found in conditions which mimic children aged 10-12 years at a dose of 5 and 15 mg/kg. The D0 for 5-year-old children at a dose of 15 mg/kg showed different behaviors between biorelevant and pharmacopeial buffers media. For children aged 2-3 years, LTG appeared to be poorly soluble under both gastric and intestinal conditions. Solubility was dependent on the volume of fluid calculated for each age group, and this may impact the development of better pharmaceutical formulations for this population, better pharmacokinetic predictions in tools as PBPK, and physiologically-based biopharmaceutics modeling, greater accuracy in the justifications for biowaiver, and many other possibilities.

Leveraging Physiologically Based Modelling to Provide Insights on the Absorption of Paliperidone Extended-Release Formulation under Fed and Fasting Conditions.

Paliperidone was approved by the US FDA in 2006 as an extended-release (ER) tablet (Invega®) for the once-daily treatment of schizophrenia. This osmotic-controlled release oral delivery system (OROS) offers advantages, such as the prevention of plasma concentration fluctuation and reduced dosing frequency. The administration of the ER after a high-fat/high-calorie meal leads to increased maximum plasma concentration and area under the curve values by 60% and 54%, respectively. Food has various effects on gastrointestinal (GI) physiology, including changed transit times, changed volumes, altered pH in different GI compartments, secretion of bile salts, and increased hepatic blood flow. This may affect solubility, the dissolution rate, absorption, and the pharmacokinetics. The aim of this study was to apply physiologically based absorption modeling (PBAM) to provide insights on paliperidone ER absorption under fed and fasting conditions. The PBAM adequately predicted absorption from the OROS formulation under both conditions. Absorption primarily occurs in the ascending colon and caecum. After a high-fat/high-calorie meal, absorption is increased through the jejunum, ileum, and colon due to either increased solubilization or the better efficiency of the OROS technology. PBAM-guided approaches can improve the understanding of branded drugs and thereby aid in guiding the development of generic formulations or formulation alternatives.

Effect of Roux-En-Y Gastric Bypass in the Pharmacokinetics of (R)-Carvedilol and (S)-Carvedilol.

Roux-en-Y gastric bypass is one of the most common surgical treatments for obesity due to the effective long-term weight loss and remission of associated comorbidities. Carvedilol, a third-generation ß-blocker, is prescribed to treat cardiovascular diseases. This drug is a weak base with low and pH-dependent solubility and dissolution and high permeability. As the changes in the gastrointestinal tract anatomy and physiology after roux-en-Y gastric bypass can potentially affect drug pharmacokinetics, this study aimed to assess the effect of roux-en-Y gastric bypass on the pharmacokinetics of carvedilol enantiomers. Nonobese (n = 15, body mass index < 25 kg/m2 ), obese (n = 19, body mass index ≥ 30), and post-roux-en-Y gastric bypass subjects submitted to surgery for at least 6 months (n = 19) were investigated. All subjects were administered a single oral dose of 25-mg racemic carvedilol, and blood was sampled for up to 24 hours. Plasma concentrations of (R)- and (S)-carvedilol were determined by liquid chromatography-tandem mass spectrometry. The maximum plasma concentration (Cmax ) and the area under the plasma concentration-time curve (AUC) of (R)-carvedilol were 2- to 3-fold higher than (S)-carvedilol in all groups. Obese subjects have shown reduced Cmax of (R)- and (S)-carvedilol without changing the AUC. Post-roux-en-Y gastric bypass subjects presented a 3.5-fold reduction in the Cmax of the active (S)-carvedilol and a 1.9 reduction in the AUC from time 0 to infinity compared to nonobese subjects. The time to reach Cmax of (S)-carvedilol increased 2.5-fold in post-roux-en-Y gastric bypass subjects compared to obese or nonobese. Although the ß-blockade response was not assessed, the reduced exposure to carvedilol in subjects post-roux-en-Y gastric bypass may be clinically relevant and require dose adjustment.

Integrating Forward and Reverse Translation in PBPK Modeling to Predict Food Effect on Oral Absorption of Weakly Basic Drugs.

INTRODUCTION: Ketoconazole and posaconazole are two weakly basic broad-spectrum antifungals classified as Biopharmaceutics Classification System class II drugs, indicating that they are highly permeable, but exhibit poor solubility. As a result, oral bioavailability and clinical efficacy can be impacted by the formulation performance in the gastrointestinal system. In this work, we have leveraged in vitro biopharmaceutics and clinical data available in the literature to build physiologically based pharmacokinetic (PBPK) models for ketoconazole and posaconazole, to determine the suitability of forward in vitro-in vivo translation for characterization of in vivo drug precipitation, and to predict food effect. METHODS: A stepwise modeling approach was utilized to derive key parameters related to absorption, such as drug solubility, dissolution, and precipitation kinetics from in vitro data. These parameters were then integrated into PBPK models for the simulation of ketoconazole and posaconazole plasma concentrations in the fasted and fed states. RESULTS: Forward in vitro-in vivo translation of intestinal precipitation kinetics for both model drugs resulted in poor predictions of PK profiles. Therefore, a reverse translation approach was applied, based on limited fitting of precipitation-related parameters to clinical data. Subsequent simulations for ketoconazole and posaconazole demonstrated that fasted and fed state PK profiles for both drugs were adequately recapitulated. CONCLUSION: The two examples presented in this paper show how middle-out modeling approaches can be used to predict the magnitude and direction of food effects provided the model is verified on fasted state PK data.

Real-world effect of a potential drug-drug interaction between topiramate and oral contraceptives on unintended pregnancy outcomes.

OBJECTIVE: To evaluate the association of concomitant topiramate and oral hormonal contraceptive use with unintended pregnancies. STUDY DESIGN: We conducted a retrospective cohort design in MarketScan Research Databases (2005-2018) on women aged 12-48 who had migraines or chronic headaches and concomitantly used topiramate and oral contraceptives. We used a cohort of patients with oral contraceptives and concomitant use of other migraine prevention therapies (propranolol, metoprolol, amitriptyline, venlafaxine, or verapamil) as a comparator. We followed patients for up to 1 year from cohort entry to assess the occurrence of unintended pregnancy (i.e., contraception failure). Pregnancy events were measured via an algorithm harnessing medical encounters information with live births, terminations, or prenatal visits. Statistical models accounted for multiple cohort entries and adjusted for measured confounders via a propensity score weighting method. RESULTS: We identified 63,649 episodes of oral contraceptives+topiramateand 59,012 episodes of oral contraceptives+other maintenance therapies. The mean age was 29.2±9.0 and 29.0±9.3 years in the study cohorts. In the adjusted analysis, the contraception failure rate (95% confidence interval) was 1.3 (1.1, 1.6) per 100 person-years in the oral contraceptives+topiramate cohort and 1.3 (1.1, 1.6) in the oral contraceptives+other maintenance therapies cohort. The adjusted rate ratio and rate difference measures were 1.00 (0.80, 1.26) and 0.00 (-0.3, 0.3). CONCLUSION: Concomitant use of low-dose topiramate and oral contraceptives among patients with migraines was not associated with a higher risk for unintended pregnancies. IMPLICATIONS: Our real-world findings confirm clinical pharmacology trials, suggesting that low-dose (≤200 mg/d) topiramate may not influence oral contraceptive effectiveness.

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.