Use of Physiologically Based Pharmacokinetic Modeling for Predicting Drug-Food Interactions: Recommendations for Improving Predictive Performance of Low Confidence Food Effect Models

A physiologically based biopharmaceutics modeling (PBBM) framework for characterizing formulation-dependent food effects: Paving the road towards fed state virtual BE studies for itraconazole amorphous solid dispersions

This study leverages physiologically based biopharmaceutics modeling (PBBM) to predict the clinical performance of two itraconazole (ITRA) amorphous solid dispersions (ASDs), Sempera® and Tolsura®, under fasted and fed state conditions, exploring the potential of PBBM in predicting formulation-specific food interactions. The ITRA formulations were subjected to extensive in vitro biopharmaceutical testing, including solubility studies and dissolution tests under fasted and fed state conditions, revealing significant differences in dissolution behaviors between Sempera® and Tolsura®. The impact of food and hypochlorhydria on drug absorption was evaluated using a stepwise mechanistic deconvolution-reconvolution PBBM approach, integrating fundamental parameters based on the in vitro data into the final model. Our model not only successfully predicted the effects of acid reducing agents (ARA) and food on the oral absorption of ITRA, but also captured the between-subject variability, demonstrating the utility of this approach in understanding the complex interplay between drug, formulation, and gastrointestinal environment. Most importantly, the PBBM was able to accurately predict the positive impact of food on the absorption of Sempera® and the negative food effect of Tolsura®. The findings highlight the importance of considering formulation characteristics and gastrointestinal physiology, underscoring the potential of PBBM in bioequivalence (BE) assessment of generic formulations under varying physiological conditions, including in the fed state and in hypochlorhydric patients. The successful application of this stepwise and mechanistic PBBM approach suggests a potential pathway for streamlining drug development and may contribute to more informed decision-making for BE assessment.

Development of a Physiologically Based Biopharmaceutics Model Report Template: Considerations for Improved Quality in View of Regulatory Submissions

Pharmaceutical innovators and generic companies use Physiologically Based Biopharmaceutics Models (PBBMs) to guide drug product development and potentially waive clinical pharmacokinetic studies for both pre- and postapproval changes. This modeling approach can assist with biopharmaceutics risk assessment and the establishment of patient centric, clinically relevant drug product specifications. However, the variability of possible model strategies and the existence of gaps in scientific knowledge associated with the lack of standardized regulatory expectations for model parametrization, data requirements for model development, and criteria for fit-for-purpose model validation leads to varied acceptance rates and frequent requests for additional information and deficiencies in PBBM submissions across regulatory agencies. During the 2023 Maryland Center of Excellence in Regulatory Science and Innovation (M-CERSI) PBBM Best Practices for Drug Product Quality: Regulatory and Industry Perspectives workshop, it was identified that a PBBM report template summarizing model considerations and proposing a structure for presenting question(s) of interest, model context, input data, a modeling plan, and validation would be beneficial for both industry and regulatory agencies. The present work is not a regulatory guideline but rather a summary of current best practices and considerations for PBBM submissions. The associated template can be downloaded directly from the Supporting Information to guide one in the preparation of PBBM reports. The current paper discusses the critical elements of the PBBM report template, which were identified during the industry-regulator scientific collaboration and interactions.

Simulation of Antral Conditions for Estimating Drug Apparent Equilibrium Solubility after a High-Calorie, High-Fat Meal

The simulation of antral conditions for estimating drug apparent equilibrium solubility after a high-calorie, high-fat meal is challenging. In this study, (1) we measured the apparent equilibrium solubility of two model lipophilic drugs, ketoconazole and danazol, in antral aspirates collected at various time points after a minced high-calorie, high-fat meal and a glass of water 30 min after initiation of meal administration, and we designated one point estimate for ketoconazole and one point estimate for danazol; (2) we evaluated the usefulness of FeSSGF-V2 and FEDGAS pH = 3 in reproducing the two point estimates; (3) we evaluated potential compositions of FeSSGF-V3 that simulate the pH, the buffer capacity toward both less acidic and more acidic values, and the antral lipid and protein contents with easily accessible, commercially available products, and (4) we identified the most useful composition of FeSSGF-V3 for reproducing the two point estimates. For both model drugs, apparent solubility in FeSSGF-V2 and in FEDGAS pH 3 deviated substantially from the corresponding point estimate. For FeSSGF-V3, hydrochloric acid, acetates, and FEDGASbuffer pH 3 were evaluated for regulating the pH and buffer capacity, FEDGASgel was used for simulating the lipid content, and Régilait skimmed milk powder was used for simulating the protein content. Level III FeSSGF-V3 prepared with hydrochloric acid, 6.1% (w/v) Régilait, and 2.83% (w/v) FEDGASgel, i.e., one-sixth of FEDGASgel concentration in FEDGAS pH 3, was comparatively the most useful medium for point estimating ketoconazole and danazol apparent solubility in antral contents after water administration in the fed state, induced as requested by regulatory authorities in oral drug bioavailability studies. Level III FeSSGF-V3 prepared by using hydrochloric acid as the principal pH controlling species could be useful in the evaluation of food effects on drug absorption with in silico physiologically based biopharmaceutics modeling approaches and, also, with biorelevant in vitro methodologies.

Key Factors for Improving Predictive Accuracy and Avoiding Overparameterization of the PBPK Absorption Model in Food Effect Studies of Weakly Basic Water-Insoluble Compounds in Immediate Release Formulations

Background/Objectives: Physiologically based pharmacokinetic (PBPK) absorption models are instrumental for assessing drug absorption prior to clinical food effect studies, though discrepancies in predictive and actual outcomes are observed. This study focused on immediate release formulations of weakly basic water-insoluble compounds, namely rivaroxaban, ticagrelor, and PB-201, to investigate factors that could improve the predictive accuracy of PBPK models regarding food effects. Methods: Comprehensive in vitro experimental results provided the basis for the development of mechanistic absorption models, which were then combined with mechanistic disposition models to predict the systemic exposure of the model drugs in both fasted and fed states. Results: The developed PBPK models showed moderate to high predictive accuracy for food effects in Caucasian populations. For the Chinese population, the ticagrelor model's initial overestimation of fed-state absorption was addressed by updating the permeability parameters from Caco-2 cell assays to those derived from parallel artificial membrane permeability assays in FaSSIF and FeSSIF media. This refinement was also applied to the rivaroxaban and ticagrelor models, leading to a more accurate representation of absorption in Caucasians. Conclusions: This study highlights the importance of apparent permeability in enhancing the predictive accuracy of PBPK absorption models for weakly basic water-insoluble compounds. Furthermore, the precipitation of PB-201 in the two-stage transfer experiments suggests that precipitation may not be a universal phenomenon for such compounds in vivo. Consequently, the precipitation rate constant, a theoretically essential parameter, should be determined based on experimental evidence to avoid overparameterization and ensure robust predictive accuracy of PBPK models.

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.

On the processes limiting oral drug absorption when amorphous solid dispersions are administered after a high-calorie, high-fat meal: Sporanox® pellets

OBJECTIVES

1) Identify processes limiting the arrival of itraconazole at the intestinal epithelium when Sporanox® amorphous solid dispersion (ASD) pellets are transferred from the stomach through the upper small intestine, after a high-calorie, high-fat meal. 2) Evaluate whether itraconazole concentrations in the colloidal phase of aqueous contents of the upper small intestine are useful for the assessment of dose effects in the fed state and food effects on plasma levels.

METHODS

Itraconazole concentrations, apparent viscosity, and solubilization capacity were measured in aspirates from the upper gastrointestinal lumen collected during a recently performed clinical study in healthy adults. Published itraconazole concentrations in plasma, after a high-calorie high-fat meal and Sporanox® ASD pellets, and in contents of the upper small intestine of healthy adults, after administration of Sporanox® ASD pellets in the fasted state, were used to achieve the second objective.

RESULTS

When Sporanox® ASD pellets (up to 200 mg) are transferred from the stomach through the upper small intestine, after a high-calorie, high-fat meal, itraconazole concentrations in the colloidal phase or the micellar phase of aqueous contents of the upper small intestine are unsaturated, in most cases. During the first 3 h post-dosing after a high-calorie, high-fat meal, the impact of dose (200 mg vs. 100 mg) on itraconazole concentrations in the colloidal phase of aqueous contents of the upper small intestine seems to underestimate the impact of dose on plasma levels. When Sporanox® ASD pellets are administered after a high-calorie, high-fat meal at the 200 mg dose level, itraconazole concentrations in the colloidal phase of aqueous contents of the upper small intestine are, on average, lower than those achieved in fasted state.

CONCLUSIONS

When Sporanox® ASD pellets are transferred from the stomach to the upper small intestine after a high-calorie, high-fat meal, itraconazole's arrival at the intestinal epithelium seems to be limited by its arrival at the colloidal phase of aqueous contents of the upper small intestine. The impact of dose (100 mg vs. 200 mg) on plasma levels after a high-calorie, high-fat meal and during the gastrointestinal transfer of Sporanox® pellets requires consideration of pre-systemic itraconazole metabolism. At the 200 mg dose level, after taking into consideration differences in the volume of the contents of the upper small intestine between the fasted and the fed state during the gastrointestinal transfer of Sporanox® ASD pellets, itraconazole concentrations in the colloidal phase of aqueous contents of the upper small intestine suggest a mild negative food effect on average plasma levels; published clinical data are inconclusive.

Physiologically-based pharmacokinetic models versus allometric scaling for prediction of tyrosine-kinase inhibitor exposure from adults to children

PURPOSE

Model-based methods can predict pediatric exposure and support initial dose selection. The aim of this study was to evaluate the performance of allometric scaling of population pharmacokinetic (popPK) versus physiologically based pharmacokinetic (PBPK) models in predicting the exposure of tyrosine kinase inhibitors (TKIs) for pediatric patients (≥ 2 years), based on adult data. The drugs imatinib, sunitinib and pazopanib were selected as case studies due to their complex PK profiles including high inter-patient variability, active metabolites, time-varying clearances and non-linear absorption.

METHODS

Pediatric concentration measurements and adult popPK models were derived from the literature. Adult PBPK models were generated in PK-Sim® using available physicochemical properties, calibrated to adult data when needed. PBPK and popPK models for the pediatric populations were translated from the models for adults and were used to simulate concentration-time profiles that were compared to the observed values.

RESULTS

Ten pediatric datasets were collected from the literature. While both types of models captured the concentration-time profiles of imatinib, its active metabolite, sunitinib and pazopanib, the PBPK models underestimated sunitinib metabolite concentrations. In contrast, allometrically scaled popPK simulations accurately predicted all concentration-time profiles. Trough concentration (Ctrough) predictions from the popPK model fell within a 2-fold range for all compounds, while 3 out of 5 PBPK predictions exceeded this range for the imatinib and sunitinib metabolite concentrations.

CONCLUSION

Based on the identified case studies it appears that allometric scaling of popPK models is better suited to predict exposure of TKIs in pediatric patients ≥ 2 years. This advantage may be attributed to the stable enzyme expression patterns from 2 years old onwards, which can be easily related to adult levels through allometric scaling. In some instances, both methods performed comparably. Understanding where discrepancies between the model methods arise, can further inform model development and ultimately support pediatric dose selection.

Evaluating Utilization of Tiny-TIM to Assess the Effect of Food on the Absorptions of Oral Drugs and Its Application on Biopharmaceutical Modeling

Safety and efficacy are the most critical factors for the development of modern medications. For oral drugs, evaluating drug exposure under various conditions is one of the most important outcomes for clinical trials. These data will help to better understand the safety and efficacy of new drugs. Studies involving potential drug-drug interactions, proton pump inhibitors, and intake of food are often conducted to assess the above. Among the above, the influence of food on exposure to the drug is one of the key data sets for regulatory submission. Since food may have either a positive or negative effect on drug exposure, it is important to obtain an early assessment of the food effect. To better forecast and plan for clinical studies, substantial efforts have been made in the industry to develop modeling and in-vitro and in-vivo assays. Despite the efforts, predicting the effect of food on exposure without integrating the dynamic of the gastrointestinal tract in the assessment remains challenging. In this study, we evaluated the utilization of the dynamic Gastro-Intestinal Model (Tiny-TIM) for the food effect of over 20 drugs/formulations in development or on the market that covers all BCS classes. In general, the Tiny-TIM predicted food effects were in good agreement with the reported data in humans. This suggests that Tiny-TIM can successfully capture the impact of physicochemical properties on absorption under the influence of food.

Effect of Food Composition on the PK of Isoniazid Quantitatively Explained Using Physiologically Based Biopharmaceutics Modeling

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

Preliminary Investigation of a Rapid and Feasible Therapeutic Drug Monitoring Method for the Real-Time Estimation of Blood Pazopanib Concentrations

Pazopanib is a multi-kinase inhibitor used to treat advanced/metastatic renal cell carcinoma and advanced soft tissue tumors; however, side effects such as diarrhea and hypertension have been reported, and dosage adjustment based on drug concentration in the blood is necessary. However, measuring pazopanib concentrations in blood using the existing methods is time-consuming; and current dosage adjustments are made using the results of blood samples taken at the patient's previous hospital visit (approximately a month prior). If the concentration of pazopanib could be measured during the waiting period for a doctor's examination at the hospital (in approximately 30 min), the dosage could be adjusted according to the patient's condition on that day. Therefore, we aimed to develop a method for rapidly measuring blood pazopanib concentrations (in approximately 25 min) using common analytical devices (a tabletop centrifuge and a spectrometer). This method allowed for pazopanib quantification in the therapeutic concentration range (25-50 μg/mL). Additionally, eight popular concomitant medications taken simultaneously with pazopanib did not interfere with the measurements. We used the developed method to measure blood concentration in two patients and obtained similar results to those measured using the previously reported HPLC method. By integrating it with the point of care and sample collection by finger pick, this method can be used for measurements in pharmacies and patients' homes. This method can maximize the therapeutic effects of pazopanib by dose adjustment to control adverse events.

Role of Physiologically Based Biopharmaceutics Modeling (PBBM) in Fed Bioequivalence Study Waivers: Regulatory Outlook, Case Studies and Future Perspectives

Over the past few decades, physiologically based biopharmaceutics modeling (PBBM) has demonstrated its utility in both new drug and generic product development. Applications of PBBM for fed bioequivalence study waivers is an upcoming area. Recently Innovation & Quality (IQ) consortium demonstrated utility of PBBM to avoid repeat food effect studies for new drugs. In the similar lines, the current manuscript aims to discuss role of PBBM in generic fed bioequivalence study waivers. Generic industry practices related to PBBM model development to predict fed bioequivalence was portrayed with special emphasis on fed bio-predictive media. Media that can simulate fed bioequivalence study outcome were discussed from practical perspective. In-depth analysis, collating the data from 36 products was performed to understand predictability of PBBM for fed bioequivalence. Cases where PBBM was successful to predict fed bioequivalence was correlated with BCS class, formulation category and type of food effect. Further, two case studies were presented wherein fed bioequivalence study waiver obtained with PBBM approach. Lastly, future direction in terms of fed bioequivalence study waivers, regulatory perspectives and best practices for PBBM were portrayed. Overall, this article paves a way to utilize PBBM for generic fed bioequivalence study waivers.

Using Mechanistic Modeling Approaches to Support Bioequivalence Assessments for Oral Products

This report summarizes the proceedings for Day 1 Session 3 of the 2-day public workshop entitled "Best Practices for Utilizing Modeling Approaches to Support Generic Product Development," a jointly sponsored workshop by the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics (CRCG) in the year 2022. The aims of this workshop were to discuss how to modernize approaches for efficiently demonstrating bioequivalence (BE), to establish their role in modern paradigms of generic drug development, and to explore and develop best practices for the use of modeling and simulation approaches in regulatory submissions and approval. The theme of this session is mechanistic modeling approaches supporting BE assessments for oral drug products. As a summary, with more successful cases of PBPK absorption modeling being developed and shared, the general strategies/frameworks on using PBPK for oral products are being formed; this will help further evolvement of this area. In addition, the early communications between the industry and the agency through appropriate pathways (e.g., pre-abbreviated new drug applications (pre-ANDA) meetings) are encouraged, and this will speed up the successful development and utility of PBPK modeling for oral products.

The Global Bioequivalence Harmonisation Initiative (GBHI): Report of the fifth international EUFEPS/AAPS conference

The series of conferences of the Global Bioequivalence Harmonisation Initiative (GBHI) was started in 2015 by the European Federation for Pharmaceutical Sciences (EUFEPS). All GBHI meetings so far were co-organised together with the American Association of Pharmaceutical Scientists (AAPS). Beginning with the 3rd workshop US-FDA joined as co-sponsor - to support global harmonisation of regulatory recommendations for bioequivalence (BE) assessment. At the 5th GBHI conference, the following BE topics were intensively discussed, and the following main conclusions were drawn: (1) Statistical considerations for BE assessment in specific situations covering scaling approaches for highly variable drug (HVD) products, two-stage adaptive design and opportunities of modelling and simulation to support BE: even though special BE study concepts like adaptive designs are not often used in practise so far, a majority of the workshop participants were in favour of a more frequent application of such approaches. The regulatory conditions relevant in this context need further concretisation and harmonisation between the regions. Moreover, modelling and simulation were considered as a promising and evolving approach, also for BE development programmes. (2) Fed versus fasting conditions in BE trials: Findings that BE between generic products could be confirmed only after fasted administration but failed under fed conditions seem more an exception than the rule. Obviously, BCS class IV compounds are most problematic in this context. Differences in critical excipients such as surfactants or pH-modifiers may be relevant reasons for different sensitivity for interactions in fasted versus fed conditions. Consequently, such deviations in composition of generic preparations should be avoided. Moreover, confirmation of BE may be generally difficult comparing different dosage forms, such like capsules versus tablets, especially in fed state. (3) BE assessment of locally acting drug products applied topically to the skin: Appropriateness and potential benefit of in-vitro tests as alternatives to clinical efficacy studies have been comprehensively discussed. In addition to the already well-established in-vitro release and permeation tests, other techniques were suggested, e.g., Raman spectroscopy or dermal open flow microperfusion. Validation of those methods is challenging and, despite significant progress already achieved during previous years, more research is needed before they may be fully accepted for regulatory purposes. (4) BE evaluation of narrow therapeutic index (NTI) drugs: The discrepancies amongst regulatory agencies in necessity of tighter BE acceptance ranges, the recommendations for inclusion of peak and total drug exposure into BE assessment with more restrictive criteria and the importance of comparison of the product-related within-subject variability for NTI drugs were debated. Arguments in favour and against the different approaches were presented and discussed but need further consideration before harmonisation can be achieved. The highly interactive meeting and extensive exchange between regulators and scientists from industry and academia resulted in useful progress in open BE issues and supported the goal of science-driven harmonisation.

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.

Solubility-Permeability Interplay in Facilitating the Prediction of Drug Disposition Routes, Extent of Absorption, Food Effects, Brain Penetration and Drug Induced Liver Injury Potential

Here I detail the use of measures of permeability rate and solubility in predicting drug disposition characteristics through the utilization of the Biopharmaceutics Drug Disposition Classification System (BDDCS) and the Extended Clearance Classification System (ECCS) as well as the accuracy of the systems in predicting the major route of elimination and the extent of oral absorption of a new small molecule therapeutics. I compare the BDDCS and ECCS with the FDA Biopharmaceutics Classification System (BCS). I also detail the use of the BCS in predicting food effects and the BDDCS in predicting brain disposition of small molecule therapeutics and in validating DILI predictive metrics. This review provides an update of the current status of these classification systems and their uses in the drug development process.

Exploring the Use of a Kinetic pH Calculation to Correct the ACAT Model with a Single Stomach Compartment Setting: Impact of Stomach Setting on Food Effect Prediction for Basic Compounds

Advanced compartmental absorption and transit (ACAT) based computational models have become increasingly popular in the industry for predicting oral drug product performance. However, due to its complexity, some compromises have been made in practice, and the stomach is often assigned as a single compartment. Although this assignment worked generally, it may not be sufficient to reflect the complexity of the gastric environment under certain conditions. For example, this setting was found to be less accurate in estimating stomach pH and solubilization of certain drugs under food intake, which leads to a misprediction of the food effect. To overcome the above, we explored the use of a kinetic pH calculation (KpH) for the single-compartment stomach setting. Several drugs have been tested with the KpH approach and compared with the default setting of Gastroplus. In general, the Gastroplus prediction of food effect is greatly improved, suggesting this approach is effective in improving the estimation of physicochemical properties related to food effect for several basic drugs by Gastroplus.

Streamlining Food Effect Assessment - Are Repeated Food Effect Studies Needed? An IQ Analysis

Current regulatory guidelines on drug-food interactions recommend an early assessment of food effect to inform clinical dosing instructions, as well as a pivotal food effect study on the to-be-marketed formulation if different from that used in earlier trials. Study waivers are currently only granted for BCS class 1 drugs. Thus, repeated food effect studies are prevalent in clinical development, with the initial evaluation conducted as early as the first-in-human studies. Information on repeated food effect studies is not common in the public domain. The goal of the work presented in this manuscript from the Food Effect PBPK IQ Working Group was to compile a dataset on these studies across pharmaceutical companies and provide recommendations on their conduct. Based on 54 studies collected, we report that most of the repeat food effect studies do not result in meaningful differences in the assessment of the food effect. Seldom changes observed were more than twofold. There was no clear relationship between the change in food effect and the formulation change, indicating that in most cases, once a compound is formulated appropriately within a specific formulation technology, the food effect is primarily driven by inherent compound properties. Representative examples of PBPK models demonstrate that following appropriate validation of the model with the initial food effect study, the models can be applied to future formulations. We recommend that repeat food effect studies should be approached on a case-by-case basis taking into account the totality of the evidence including the use of PBPK modeling.

Assessment of food effects during clinical development

Food-drug interactions frequently hamper oral drug development due to various physicochemical, physiological and formulation-dependent mechanisms. This has stimulated the development of a range of promising biopharmaceutical assessment tools which, however, lack standardized settings and protocols. Hence, this manuscript aims to provide an overview of the general approach and the methodology used in food effect assessment and prediction. For in vitro dissolution-based predictions, the expected food effect mechanism should be carefully considered when selecting the level of complexity of the model, together with its drawbacks and advantages. Typically, in vitro dissolution profiles are then incorporated into physiologically based pharmacokinetic models, which can estimate the impact of food-drug interactions on bioavailability within 2-fold prediction error, at least. Positive food effects related to drug solubilization in the GI tract are easier to predict than negative food effects. Preclinical animal models also provide a good level of food effect prediction, with beagle dogs remaining the gold standard. When solubility-related food-drug interactions have large clinical impact, advanced formulation approaches can be used to improve fasted state pharmacokinetics, hence decreasing the fasted/fed difference in oral bioavailability. Finally, the knowledge from all studies should be combined to secure regulatory approval of the labelling instructions.

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.

Integrating In Vitro Biopharmaceutics into Physiologically Based Biopharmaceutic Model (PBBM) to Predict Food Effect of BCS IV Zwitterionic Drug (GSK3640254)

A strategy followed to integrate in vitro solubility and permeability data into a PBBM model to predict the food effect of a BCS IV zwitterionic drug (GSK3640254) observed in clinical studies is described. The PBBM model was developed, qualified and verified using clinical data of an immediate release (IR)-tablet (10-320 mg) obtained in healthy volunteers under fasted and fed conditions. The solubility of GSK3640254 was a function of its ionization state, the media composition and pH, whereas its permeability determined using MDCK cell lines was enhanced by the presence of mixed micelles. In vitro data alongside PBBM modelling suggested that the positive food effect observed in the clinical studies was attributed to micelle-mediated enhanced solubility and permeability. The biorelevant media containing oleic acid and cholesterol in fasted and fed levels enabled the model to appropriately capture the magnitude of the food effect. Thus, by using Simcyp^® v20 software, the PBBM model accurately predicted the results of the food effect and predicted data were within a two-fold error with 70% being within 1.25-fold. The developed model strategy can be effectively adopted to increase the confidence of using PBBM models to predict the food effect of BCS class IV drugs.

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 Biopharmaceutics Modeling of Food Effect for Basmisanil: A Retrospective Case Study of the Utility for Formulation Bridging

Basmisanil, is a lipophilic drug substance, exhibiting poor solubility and good permeability (BCS class 2). A validated physiologically based biopharmaceutics model (PBBM) has been previously described for tablets dosed in the fed state. The PBBM captured the less than proportional increases in exposure at higher doses well and indicated that absorption was dissolution rate-limited below 200 mg while solubility was limiting for higher doses. In this study, a model for dosing in the fasted state is described and is verified for simulation of the food effect where exposures were ~1.5 fold higher when a 660 mg tablet was given with food. The model is then applied to simulate the food effect for a granules formulation given at a lower dose (120 mg). The food effect at the lower dose was reasonably simulated with a ratio of simulated/observed food effect of 1.35 for Cmax and 0.83 for AUC. Sensitivity analysis was carried out for uncertain model parameters to confirm that the model could predict the magnitude of the positive food effect with moderate to high confidence. This study suggests that a verified PBBM can provide a useful alternative to a repeat food effect study when formulation changes are minor. However, there is need for further evaluation of the approach and a definition of what formulation changes are minor in this context. In addition, this work highlights some uncertainties in the handling of solubility in PBBM, in particular around temperature dependency of solubility and the parameterization of bile salt solubilization using measurements in biorelevant media.

Regulatory utility of physiologically based pharmacokinetic modeling for assessing food impact in bioequivalence studies: A workshop summary report

This workshop report summarizes the presentations and panel discussion related to the use of physiologically based pharmacokinetic (PBPK) modeling approaches for food effect assessment, collected from Session 2 of Day 2 of the workshop titled "Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches." The US Food and Drug Administration in collaboration with the Center for Research on Complex Generics organized this workshop where this particular session titled "Oral PBPK for Evaluating the Impact of Food on BE" presented successful cases of PBPK modeling approaches for food effect assessment. Recently, PBPK modeling has started to gain popularity among academia, industries, and regulatory agencies for its potential utility during bioavailability (BA) and/or bioequivalence (BE) studies of new and generic drug products to assess the impact of food on BA/BE. Considering the promises of PBPK modeling in generic drug development, the aim of this workshop session was to facilitate knowledge sharing among academia, industries, and regulatory agencies to understand the knowledge gap and guide the path forward. This report collects and summarizes the information presented and discussed during this session to disseminate the information into a broader audience for further advancement in this area.

Dynamic Changes in Gastrointestinal Fluid Characteristics after Food Ingestion Are Important for Quantitatively Predicting the In Vivo Performance of Oral Solid Dosage Forms in Humans in the Fed State

The aim of this study was to develop a simulation model to predict the in vivo performance of solid oral dosage forms in humans in the fed state. We focused on investigating the effect of dynamic changes in gastrointestinal (GI) fluid characteristics in the fed state on the in vivo performance of solid dosage forms. We used six solid dosage forms containing weak base drugs as model formulations, two with positive food effects in humans, two with negative food effects, and two which are not affected by food ingestion. These model drug formulations were used to perform biorelevant dissolution tests in the stomach and small intestine under both prandial states. The in vitro properties of the drug products obtained from these tests were then coupled with in silico models (fasted or fed) to predict food effects in humans. We successfully incorporated the dynamic changes in GI fluid characteristics and their effects on the in vivo dissolution of drugs into the prediction model for the fed state. This newly designed physiologically based biopharmaceutics modeling approach provided the precise and quantitative prediction of food effects (i.e., changes in C_max and AUC after food ingestion) in humans while considering the dynamic changes in fluid characteristics in the fed state.

Preparation and Characterization of Pazopanib Hydrochloride-Loaded Four-Component Self-Nanoemulsifying Drug Delivery Systems Preconcentrate for Enhanced Solubility and Dissolution

The aim of this study was to develop a four-component self-nanoemulsifying drug delivery system (FCS) to enhance the solubility and dissolution of pazopanib hydrochloride (PZH). In the solubility test, PZH showed a highly pH-dependent solubility (pH 1.2 > water >> pH 4.0 and pH 6.8) and was solubilized at 70 °C in the order Kollisolv PG (5.38%, w/w) > Kolliphor RH40 (0.49%) > Capmul MCM C10 (0.21%) and Capmul MCM C8 (0.19%), selected as the solubilizer, the surfactant, and the oils, respectively. In the characterization of the three-component SNEDDS (TCS) containing Kolliphor RH40/Capmul MCM C10, the particle size of dispersion was very small (<50 nm) and the PZH loading was 0.5% at the weight ratio of 9/1. In the characterization of FCS containing additional Kollisolv PG to TCS, PZH loading was increased to 5.30% without any PZH precipitation, which was 10-fold higher compared to the TCS. The optimized FCS prepared with the selected formulation (Kolliphor RH40/Capmul MCM C10/Kollisolv PG) showed a consistently complete and high dissolution rate (>95% at 120 min) at four different pHs with 1% polysorbate 80, whereas the raw PZH and Kollisolv PG solution showed a pH-dependent poor dissolution rate (about 40% at 120 min), specifically at pH 6.8 with 1% polysorbate 80. In conclusion, PZH-loaded FCS in this work demonstrated enhanced solubility and a consistent dissolution rate regardless of medium pH.

Development of In Vitro Dissolution Testing Methods to Simulate Fed Conditions for Immediate Release Solid Oral Dosage Forms

In vitro dissolution testing is widely used to mimic and predict in vivo performance of oral drug products in the gastrointestinal (GI) tract. This literature review assesses the current in vitro dissolution methodologies being employed to simulate and predict in vivo drug dissolution under fasted and fed conditions, with emphasis on immediate release (IR) solid oral dosage forms. Notable human GI physiological conditions under fasted and fed states have been reviewed and summarized. Literature results showed that dissolution media, mechanical forces, and transit times are key dissolution test parameters for simulating specific postprandial conditions. A number of biorelevant systems, including the fed stomach model (FSM), GastroDuo device, dynamic gastric model (DGM), simulated gastrointestinal tract models (TIM), and the human gastric simulator (HGS), have been developed to mimic the postprandial state of the stomach. While these models have assisted in expanding physiological relevance of in vitro dissolution tests, in general, these models lack the ability to fully replicate physiological conditions/processes. Furthermore, the translatability of in vitro data to an in vivo system remains challenging. Additionally, physiologically based pharmacokinetic (PBPK) modeling has been employed to evaluate the effect of food on drug bioavailability and bioequivalence. Here, we assess the current status of in vitro dissolution methodologies and absorption PBPK modeling approaches to identify knowledge gaps and facilitate further development of in vitro dissolution methods that factor in fasted and fed states. Prediction of in vivo drug performance under fasted and fed conditions via in vitro dissolution testing and modeling may potentially help efforts in harmonizing global regulatory recommendations regarding in vivo fasted and fed bioequivalence studies for solid oral IR products.

State of the Art and Uses for the Biopharmaceutics Drug Disposition Classification System (BDDCS): New Additions, Revisions, and Citation References

The Biopharmaceutics Drug Disposition Classification system (BDDCS) is a four-class approach based on water solubility and extent of metabolism/permeability rate. Based on the BDDCS class to which a drug is assigned, it is possible to predict the role of metabolic enzymes and transporters on the drug disposition of a new molecular entity (NME) prior to its administration to animals or humans. Here, we report a total of 1475 drugs and active metabolites to which the BDDCS is applied. Of these, 379 are new entries, and 1096 are revisions of former classification studies with the addition of references for the approved maximum dose strength, extent of the systemically available drug excreted unchanged in the urine, and lowest solubility over the pH range 1.0–6.8 when such information is available in the literature. We detail revised class assignments of previously misclassified drugs and the literature analyses to classify new drugs. We review the process of solubility assessment for NMEs prior to drug dosing in humans and approved dose classification, as well as the comparison of Biopharmaceutics Classification System (BCS) versus BDDCS assignment. We detail the uses of BDDCS in predicting, prior to dosing animals or humans, disposition characteristics, potential brain penetration, food effect, and drug-induced liver injury (DILI) potential. This work provides an update on the current status of the BDDCS and its uses in the drug development process.