Understanding Mechanisms of Food Effect and Developing Reliable PBPK Models Using a Middle-out Approach

Predicting gastric emptying of drug substances taken under postprandial conditions by combination of biorelevant dissolution and mechanistic in silico modeling

Physiologically based pharmacokinetic (PBPK) models can help to understand the effects of gastric emptying on pharmacokinetics and in particular also provide a platform for understanding mechanisms of food effects, as well as extrapolation between different postprandial conditions, whether standardized clinical or patient-oriented, non-clinical conditions. By integrating biorelevant dissolution data from the GastroDuo dissolution model into a previously described mechanistic model of fed-state gastric emptying, we simulated the effects of a high-calorie high-fat meal on the pharmacokinetics of sildenafil, febuxostat, acetylsalicylic acid, theobromine and caffeine. The model was able to simulate the variability in Cmax and tmax caused by the presence of the stomach road. The main influences investigated to affect the gastric emptying process were drug solubility (theobromine and caffeine), tablet dissolution rate (acetylsalicylic acid) and sensitivity to gastric motility (sildenafil and febuxostat). Finally, we showed how PBPK models can be used to extrapolate pharmacokinetics between different prandial states using theobromine as an example with results from a clinical study being presented.

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.

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.

Analysis of the interplay of physiological response to food intake and drug properties in food-drug interactions

The effect of food on oral drug absorption is determined by the complex interplay among gut physiological factors and drug properties. The currently used dissolution testing and classification systems (biopharmaceutics classification system, BCS or biopharmaceutics drug disposition classification system, BDDCS) do not account for dynamic changes in gastrointestinal physiology caused by food intake. This study aimed to identify key drug properties that influence food effect (FE) using supervised machine learning approaches. The analysis showed that drugs with high logP, dose number, and extraction ratio have a higher probability of positive FE, while drugs with low permeability and high efflux saturation index have a greater likelihood of negative FE. Weakly acidic drugs also showed a greater probability of positive FE, particularly at pKa >4.3. The importance of drug properties in predicting FE was ranked as logP, dose number, extraction ratio, pKa, and permeability. The accuracy of FE prediction using the models was compared with BCS and extended clearance classification system (ECCS). Overall, the likelihood or magnitude of FE depends on physiological changes to food intake such as altered bile acid secretion rate, intestinal metabolism, transport kinetics, and gastric emptying time, which should be considered along with drug properties (e.g., solubility, logP, and ionization) in predicting FE of orally administered drugs.

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.

Usefulness of the Beagle Model in the Evaluation of Paracetamol and Ibuprofen Exposure after Oral Administration to Pediatric Populations: An Exploratory Study

The present study aimed to explore the usefulness of beagle dogs in combination with physiologically based pharmacokinetic (PBPK) modeling in the evaluation of drug exposure after oral administration to pediatric populations at an early stage of pharmaceutical product development. An exploratory, single-dose, crossover bioavailability study in six beagles was performed. A paracetamol suspension and an ibuprofen suspension were coadministered in the fasted-state conditions, under reference-meal fed-state conditions, and under infant-formula fed-state conditions. PBPK models developed with GastroPlus v9.7 were used to inform the extrapolation of beagle data to human infants and children. Beagle-based simulation outcomes were compared with published human-adult-based simulations. For paracetamol, fasted-state conditions and reference-meal fed-state conditions in beagles appeared to provide adequate information for the applied scaling approach. Fasted-state and/or reference-meal fed-state conditions in beagles appeared suitable to simulate the performance of ibuprofen suspension in pediatric populations. Contrary to human-adult-based translations, extrapolations based on beagle data collected under infant-formula fed-state conditions appeared less useful for informing simulations of plasma levels in pediatric populations. Beagle data collected under fasted and/or reference-meal fed-state conditions appeared to be useful in the investigation of pediatric product performance of the two investigated highly permeable and highly soluble drugs in the upper small intestine. The suitability of the beagle as a preclinical model to understand pediatric drug product performance under different dosing conditions deserves further evaluation with a broader spectrum of drugs and drug products and comparisons with pediatric in vivo data.

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.

Acalabrutinib Maleate Tablets: The Physiologically Based Biopharmaceutics Model behind the Drug Product Dissolution Specification

Acalabrutinib maleate tablets correspond to an improved formulation compared to acalabrutinib capsules as they can be dosed with and without acid reducing agents and therefore benefit more cancer patients. The dissolution specification for the drug product was determined using all the information available on the drug safety, efficacy, and in vitro performance. In addition, a physiologically based biopharmaceutics model was developed for acalabrutinib maleate tablets on the back of a previously published model for acalabrutinib capsules to establish that the proposed drug product dissolution specification would ensure safe and effective products for all patients including those under acid reducing agent treatment. The model was built, validated, and used to predict the exposure of virtual batches where the dissolution was slower than that of the clinical target. A combination of exposure prediction and the use of a PK-PD model allowed it to be demonstrated that the proposed drug product dissolution specification was acceptable. This combination of models enabled a larger safe space than would have been granted by consideration of bioequivalence only.

Bridging the Gap between Food Effects under Clinical Trial Conditions and Real Life: Modeling Delayed Gastric Emptying of Drug Substances and Gastric Content Volume Based on Meal Characteristics

Delayed gastric emptying is known to have a major impact on drug absorption. While the test meal recommended by the FDA and EMA to study food effects represents a worst-case scenario, it does not reflect the reality of the patients. Physiologically based pharmacokinetic (PBPK) models could bridge the gap between clinical settings of food effect studies and the diverse nonclinical situations by simulating the effect of meals with different compositions and volumes. A mathematical equation based on a stretched exponential function was reparameterized to describe the gastric emptying process of mixed solid meals. The model was fitted to literature data including the gastric emptying data of 23 meals from 15 studies. Using a multiple linear regression model, we were able to predict the two function parameters from the meal characteristics caloric content and the percentage of calories derived from fat. After implementation into the PBPK software PK-Sim, the model, together with a separate compartment for liquid gastric contents, was compared to commercially available software. The model is able to simulate the gastric emptying of mixed solid meals containing drugs based on specific meal characteristics. A second compartment allows for distribution between liquid and solid components and rapid gastric emptying along the Magenstrasse.

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.

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.

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.

Translational pharmacokinetics of a novel bispecific antibody against Ebola virus (MBS77E) from animal to human by PBPK modeling & simulation

The goal of this study was to construct a PBPK model to accelerate the translation of MBS77E, a humanized bispecific antibody against the Ebola virus. In-depth nonclinical pharmacokinetic studies in rats, monkeys, wild-type mice and transgenic mice were conducted. The pH-dependent affinities (K_D) of MBS77E to recombinant FcRn of different species were determined by surface plasmon resonance analysis. A mechanistic whole-body PBPK model of MBS77E was developed and validated in the assessment of PK profiles and tissue distributions in preclinical models. This PBPK model was finally used to predict human PK behaviors of MBS77E. Simulations from the PBPK model with measured and fitted parameters were able to yield good predictions of the serum and tissue pharmacokinetic parameters of MBS77E within 2-fold errors. The predicted serum concentration in humans was able to maintain a sufficiently high level for more than 14 days after 50 mg/kg i.v. administrating. This achievement unlocks that PBPK modeling is a powerful tool to gain insights into the properties of antibody drugs. It guided experimental efforts to obtain necessary information before entry into humans.

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.

A PBPK Model of Ternary Cyclodextrin Complex of ST-246 Was Built to Achieve a Reasonable IV Infusion Regimen for the Treatment of Human Severe Smallpox

ST-246 is an oral drug against pathogenic orthopoxvirus infections. An intravenous formulation is required for some critical patients. A ternary complex of ST-246/meglumine/hydroxypropyl-β-cyclodextrin with well-improved solubility was successfully developed in our institute. The aim of this study was to achieve a reasonable intravenous infusion regimen of this novel formulation by a robust PBPK model based on preclinical pharmacokinetic studies. The pharmacokinetics of ST-246 after intravenous injection at different doses in rats, dogs, and monkeys were conducted to obtain clearances. The clearance of humans was generated by using the allometric scaling approach. Tissue distribution of ST-246 was conducted in rats to obtain tissue partition coefficients (K_p). The PBPK model of the rat was first built using in vivo clearance and K_p combined with in vitro physicochemical properties, unbound fraction, and cyclodextrin effect parameters of ST-246. Then the PBPK model was transferred to a dog and monkey and validated simultaneously. Finally, pharmacokinetic profiles after IV infusion at different dosages utilizing the human PBPK model were compared to the observed oral PK profile of ST-246 at therapeutic dosage (600 mg). The mechanistic PBPK model described the animal PK behaviors of ST-246 via intravenous injection and infusion with fold errors within 1.2. It appeared that 6h-IV infusion at 5 mg/kg BID produced similar C_max and AUC as oral administration at 600 mg. A PBPK model of ST-246 was built to achieve a reasonable regimen of IV infusion for the treatment of severe smallpox, which will facilitate the clinical translation of this novel formulation.

In Vitro-In Silico Tools for Streamlined Development of Acalabrutinib Amorphous Solid Dispersion Tablets

Amorphous solid dispersion (ASD) dosage forms can improve the oral bioavailability of poorly water-soluble drugs, enabling the commercialization of new chemical entities and improving the efficacy and patient compliance of existing drugs. However, the development of robust, high-performing ASD dosage forms can be challenging, often requiring multiple formulation iterations, long timelines, and high cost. In a previous study, acalabrutinib/hydroxypropyl methylcellulose acetate succinate (HPMCAS)-H grade ASD tablets were shown to overcome the pH effect of commercially marketed Calquence in beagle dogs. This study describes the streamlined in vitro and in silico approach used to develop those ASD tablets. HPMCAS-H and -M grade polymers provided the longest acalabrutinib supersaturation sustainment in an initial screening study, and HPMCAS-H grade ASDs provided the highest in vitro area under the curve (AUC) in gastric to intestinal transfer dissolution tests at elevated gastric pH. In silico simulations of the HPMCAS-H ASD tablet and Calquence capsule provided good in vivo study prediction accuracy using a bottom–up approach (absolute average fold error of AUC_0-inf < 2). This streamlined approach combined an understanding of key drug, polymer, and gastrointestinal properties with in vitro and in silico tools to overcome the acalabrutinib pH effect without the need for reformulation or multiple studies, showing promise for reducing time and costs to develop ASD drug products.

The Impact of Diet and Exercise on Drug Responses

It is well known that lifestyle changes can alter several physiological functions in the human body. For exercise and diet, these effects are used sensibly in basic therapies, as in cardiovascular diseases. However, the physiological changes induced by exercise and a modified diet also have the capacity to influence the efficacy and toxicity of several drugs, mainly by affecting different pharmacokinetic mechanisms. This pharmacological plasticity is not clinically relevant in all cases but might play an important role in altering the effects of very common drugs, particularly drugs with a narrow therapeutic window. Therefore, with this review, we provide insights into possible food–drug and exercise–drug interactions to sharpen awareness of the potential occurrence of such effects.

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

Food can alter drug absorption and impact safety and efficacy. Besides conducting clinical studies, in vitro approaches such as biorelevant solubility and dissolution testing and in vivo dog studies are typical approaches to estimate a drug's food effect. The use of physiologically based pharmacokinetic models has gained importance and is nowadays a standard tool for food effect predictions at preclinical and clinical stages in the pharmaceutical industry. This manuscript is part of a broader publication from the IQ Consortium's food effect physiologically based pharmacokinetic model (PBPK) modeling working group and complements previous publications by focusing on cases where the food effect was predicted with low confidence. Pazopanib-HCl, trospium-Cl, and ziprasidone-HCl served as model compounds to provide insights into why several food effect predictions failed in the first instance. Furthermore, the manuscript depicts approaches whereby PBPK-based food effect predictions may be improved. These improvements should focus on the PBPK model functionality, especially better reflecting fasted- and fed-state gastric solubility, gastric re-acidification, and complex mechanisms related to gastric emptying of drugs. For improvement of in vitro methodologies, the focus should be on the development of more predictive solubility, supersaturation, and precipitation assays. With regards to the general PBPK modeling methodology, modelers should account for the full solubility profile when modeling ionizable compounds, including common ion effects, and apply a straightforward strategy to account for drug precipitation.

On Absorption Modeling and Food Effect Prediction of Rivaroxaban, a BCS II Drug Orally Administered as an Immediate-Release Tablet

The present work evaluates the food effect on the absorption of rivaroxaban (Riva), a BCS II drug, from the orally administered commercial immediate-release tablet (Xarelto IR) using physiologically based pharmacokinetic (PBPK) and conventional in vitro-in vivo correlation (IVIVC) models. The bioavailability of Riva upon oral administration of Xarelto IR tablet is reported to exhibit a positive food effect. The PBPK model for Riva was developed and verified using the previously reported in vivo data for oral solution (5 and 10 mg) and Xarelto IR tablet (5 and 10 mg dose strength). Once the PBPK model was established, the in vivo performance of the tablet formulation with the higher dose strength (Xarelto IR tablet 20 mg in fasted and fed state) was predicted using the experimentally obtained data of in vitro permeability, biorelevant solubility and in vitro dynamic dissolution data using United States Pharmacopeia (USP) IV flow-through cell apparatus. In addition, the mathematical IVIVC model was developed using the in vitro dissolution and in vivo profile of 20 mg strength Xarelto IR tablet in fasted condition. Using the developed IVIVC model, the pharmacokinetic (PK) profile of the Xarelto IR tablet in fed condition was predicted and compared with the PK parameters obtained via the PBPK model. A virtual in vivo PK study was designed using a single-dose, 3-treatment cross-over trial in 50 subjects to predict the PK profile of the Xarelto® IR tablet in the fed state. Overall, the results obtained from the IVIVC model were found to be comparable with those from the PBPK model. The outcome from both models pointed to the positive food effect on the in vivo profile of the Riva. The developed models thus can be effectively extended to establish bioequivalence for the marketed and novel complex formulations of Riva such as amorphous solid dispersions.