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.

SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters.

PURPOSE: To construct a detailed mechanistic and physiologically based biopharmaceutics model capable of predicting 1) device-formulation-tissue interaction during the injection process and 2) binding, degradation, local distribution, diffusion, and drug absorption, following subcutaneous injection. This paper is part of a series and focusses on the first aspect. METHODS: A mathematical model, SubQ-Sim, was developed incorporating the details of the various substructures within the subcutaneous environment together with the calculation of dynamic drug disposition towards the lymph ducts and venous capillaries. Literature was searched to derive key model parameters in healthy and diseased subjects. External factors such as body temperature, exercise, body position, food or stress provide a means to calculate the impact of "life events" on the pharmacokinetics of subcutaneously administered drugs. RESULTS: The model predicts the tissue backpressure time profile during the injection as a function of injection rate, volume injected, solution viscosity, and interstitial fluid viscosity. The shape of the depot and the concentrations of the formulation and proteins in the depot are described. The model enables prediction of formulation backflow following premature needle removal and the resulting formulation losses. Finally, the effect of disease (type 2 diabetes) or the presence of recombinant human hyaluronidase in the formulation on the injection pressure, are explored. CONCLUSIONS: This novel model can successfully predict tissue back pressure, depot dimensions, drug and protein concentration and formulation losses due to incorrect injection, which are all important starting conditions for predicting drug absorption from a subcutaneous dose. The next article will describe the absorption model and validation against clinical data.

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.

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.

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.

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

Over the last 10 years, 40% of approved oral drugs exhibited a significant effect of food on their pharmacokinetics (PK) and currently the only method to characterize the effect of food on drug absorption, which is recognized by the authorities, is to conduct a clinical evaluation. Within the pharmaceutical industry, there is a significant effort to predict the mechanism and clinical relevance of a food effect. Physiologically based pharmacokinetic (PBPK) models combining both drug-specific and physiology-specific data have been used to predict the effect of food on absorption and to reveal the underlying mechanisms. This manuscript provides detailed descriptions of how a middle-out modeling approach, combining bottom-up in vitro-based predictions with limited top-down fitting of key model parameters for clinical data, can be successfully used to predict the magnitude and direction of food effect when it is predicted poorly by a bottom-up approach. For nefazodone, a mechanistic clearance for the gut and liver was added, for furosemide, an absorption window was introduced, and for aprepitant, the biorelevant solubility was refined using multiple solubility measurements. In all cases, these adjustments were supported by literature data and showcased a rational approach to assess the factors limiting absorption and exposure.

In Vitro Biopredictive Methods: A Workshop Summary Report.

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

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

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

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

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

Bridging in vitro dissolution and in vivo exposure for acalabrutinib. Part II. A mechanistic PBPK model for IR formulation comparison, proton pump inhibitor drug interactions, and administration with acidic juices.

Acalabrutinib (Calquence®) 100 mg (bid) has received accelerated approval by FDA for the treatment of adult patients with mantle cell lymphoma (MCL) who have received at least one prior therapy. Acalabrutinib is a substrate of PgP and CYP3A4, with a significant fraction of drug metabolized by first pass gut extraction and 25% absolute bioavailability. The absorption of acalabrutinib is affected by stomach pH, with lower pharmacokinetic exposure observed following co-administration with proton pump inhibitors. During dissolution at pH values below its highest basic pKa, the two basic moieties of acalabrutinib react with protons from the aqueous solution, leading to a higher pH at the drug surface than in the bulk solution. A batch-specific product particle size distribution (P-PSD), was derived from dissolution data using a mechanistic model that was based on the understanding of surface pH and the contribution of micelles to the dissolution rate. P-PSD values obtained for various batches of acalabrutinib products in simple buffers, or in complex fluids such as fruit juices, were successfully integrated into a physiologically based pharmacokinetic (PBPK) model developed using GastroPlus v9.0™. The integrated model allowed the prediction of clinical pharmacokinetics under normal physiological stomach pH conditions as well as following treatment with proton pump inhibitors. The model also accounted for lower pharmacokinetic exposure that was observed when acalabrutinib was co-administered with the acidic beverages, grapefruit juice, (which contains CYP3A inhibitors), and orange drink (which does not contain CYP3A inhibitors), relative to administration with water. The integration of dissolution data in the PBPK model enables mechanistic understanding and the establishment of more robust in vitro-in vivo correlations (IVIVC) under a variety of conditions. The model can then distinguish the interplay between dissolution and first pass extraction and how in vivo stomach pH, saturation of gut PgP, and saturation or inhibition of gut CYP3A4, will impact the pharmacokinetics of acalabrutinib.

Bridging in vitro dissolution and in vivo exposure for acalabrutinib. Part I. Mechanistic modelling of drug product dissolution to derive a P-PSD for PBPK model input.

Drug product dissolution for four batches of acalabrutinib 100 mg capsules were analyzed with in vitro dissolution in various pH conditions and in media containing synthetic surfactant micelles or biorelevant micelles. Non-sink conditions, where the drug is unionized, were used to derive a batch specific drug product particle size distribution (P-PSD). The purpose of this P-PSD is to serve as an input in physiological based pharmacokinetic (PBPK) models to calculate in vivo dissolution in various administration conditions. The P-PSD was used to predict dissolution in all other conditions tested, introducing a different Unstirred Water Layer (UWL) thickness for free- and micelle-bound drug and the calculation of surface solubility using a theoretical model. With the proposed P-PSD approach and proposed model inputs, percent dissolved at all time points and for all conditions and batches were adequately anticipated with an 11% overprediction. In contrast, the use of drug substance laser diffraction particle size data with equivalent inputs to the models led to an underprediction of observed percent dissolved by 31% overall. Finally, the use of bulk solubility instead of surface solubility led to an overall 48% overprediction of the dissolution data. Batch specific P-PSD were used to predict in vivo dissolution of acalabrutinib drug products with PBPK models. The current limitations of PBPK models for integration of in vitro dissolution are also discussed and improvements are suggested to improve future predictions.

Justification of Drug Product Dissolution Rate and Drug Substance Particle Size Specifications Based on Absorption PBPK Modeling for Lesinurad Immediate Release Tablets.

In silico absorption modeling has been performed, to assess the impact of in vitro dissolution on in vivo performance for ZURAMPIC (lesinurad) tablets. The dissolution profiles of lesinurad tablets generated using the quality control method were used as an input to a GastroPlus model to estimate in vivo dissolution in the various parts of the GI tract and predict human exposure. A model was set up, which accounts for differences of dosage form transit, dissolution, local pH in the GI tract, and fluid volumes available for dissolution. The predictive ability of the model was demonstrated by confirming that it can reproduce the Cmax observed for independent clinical trial. The model also indicated that drug product batches that pass the proposed dissolution specification of Q = 80% in 30 min are anticipated to be bioequivalent to the clinical reference batch. To further explore the dissolution space, additional simulations were performed using a theoretical dissolution profile below the proposed specification. The GastroPlus modeling indicates that such a batch will also be bioequivalent to standard clinical batches despite having a dissolution profile, which would fail the proposed dissolution specification of Q = 80% in 30 min. This demonstrates that the proposed dissolution specification sits comfortably within a region of dissolution performance where bioequivalence is anticipated and is not near an edge of failure for dissolution, providing additional confidence to the proposed specifications. Finally, simulations were performed using a virtual drug substance batch with a particle size distribution at the limit of the proposed specification for particle size. Based on these simulations, such a batch is also anticipated to be bioequivalent to clinical reference, demonstrating that the proposed specification limits for particle size distribution would give products bioequivalent to the pivotal clinical batches.