Predicting Surface pH in Unbuffered Conditions for Acids, Bases, and Their Salts - A Review of Modeling Approaches and Their Performance.

Dissolution of ionizable drugs and their salts is a function of drug surface solubility driven by the surface pH, i.e., the microenvironmental pH at the solid/liquid interface, which will deviate from bulk pH when there is an acid-base reaction occurring at the solid/liquid interface. In this work, we first present a brief overview of the modeling approaches available in the literature, classified according to the rate-determining step assumed in the dissolution process. In the second part, we present and evaluate the prediction performance of two different modeling approaches for surface pH. The first method relies only on thermodynamic equilibria, while the second method accounts for transport phenomena of charged compounds through the diffusional boundary layer using the Nernst - Planck equation. Model outcomes are compared with experimental data taken from the literature and obtained during this work. In terms of surface pH predictions, the models provide identical values for weak acids or weak bases. The models' outcomes for bases are in good agreement with experimental data in acidic conditions (bulk pH 1-4), while overpredictions are observed in the 5-7 bulk pH range in a system-dependent manner. Deviations can be related to the effect of surface dissolution (also referred to as surface reaction), which may become a controlling mechanism and slow the replenishment of the unionized drug at the surface of the crystal. Surface pH predictions for acids are generally in good agreement with experiments, with a slight underestimation for some drug examples, which could be related to errors in intrinsic solubility determination or to the assumption of thermodynamic equilibrium at the surface of the drug. A good agreement is also observed for salts with the thermodynamic model except for mesylate salts, suggesting that other phenomena, not currently included in the thermodynamic equilibrium model, may determine the surface pH.

Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report.

Physiologically based biopharmaceutics modeling (PBBM) is used to elevate drug product quality by providing a more accurate and holistic understanding of how drugs interact with the human body. These models are based on the integration of physiological, pharmacological, and pharmaceutical data to simulate and predict drug behavior in vivo. Effective utilization of PBBM requires a consistent approach to model development, verification, validation, and application. Currently, only one country has a draft guidance document for PBBM, whereas other major regulatory authorities have had limited experience with the review of PBBM. To address this gap, industry submitted confidential PBBM case studies to be reviewed by the regulatory agencies; software companies committed to training. PBBM cases were independently and collaboratively discussed by regulators, and academic colleagues participated in some of the discussions. Successful bioequivalence "safe space" industry case examples are also presented. Overall, six regulatory agencies were involved in the case study exercises, including ANVISA, FDA, Health Canada, MHRA, PMDA, and EMA (experts from Belgium, Germany, Norway, Portugal, Spain, and Sweden), and we believe this is the first time such a collaboration has taken place. The outcomes were presented at this workshop, together with a participant survey on the utility and experience with PBBM submissions, to discuss the best scientific practices for developing, validating, and applying PBBMs. The PBBM case studies enabled industry to receive constructive feedback from global regulators and highlighted clear direction for future PBBM submissions for regulatory consideration.

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.

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.

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

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

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.

Bioavailability of acalabrutinib suspension delivered via nasogastric tube in the presence or absence of a proton pump inhibitor in healthy subjects.

AIMS: Acalabrutinib, a selective Bruton tyrosine kinase inhibitor, is approved for the treatment of mantle cell lymphoma and chronic lymphocytic leukaemia. Many critically ill patients are unable to swallow and need oral medications to be delivered via a nasogastric (NG) tube. Furthermore, critically ill patients are typically administered proton-pump inhibitors (PPIs) to prevent stress ulcers. Concomitant administration with PPIs reduces acalabrutinib exposure and is not currently recommended. To evaluate acalabrutinib in subjects co-administered with PPIs who require NG delivery, a phase 1, open-label, randomized, crossover, single-dose study was conducted in healthy subjects. METHODS: The study assessed the relative bioavailability of an acalabrutinib suspension-in regular, degassed Coca-Cola-administered via NG tube (Acala-NG) versus the pharmacokinetics (PK) of an acalabrutinib capsule administered orally with water. In addition, the PPI effect was evaluated by comparing the PK following Acala-NG in the presence or absence of rabeprazole. RESULTS: Exposure of acalabrutinib and its active metabolite (ACP-5862) were comparable following administration of Acala-NG versus the oral capsule (Geo mean ratio, % ref [90% confidence interval, CI]: acalabrutinib AUCinf : 103 [93-113]; Cmax : 144 [120-173]). In addition, exposure was similar following administration of Acala-NG with and without a PPI (Geo mean ratio, % ref [90% CI]: acalabrutinib AUCinf : 105 [79-138]; Cmax : 95 [66-137]). No safety or tolerability concerns were observed, and all adverse events were mild and resolved without treatment. CONCLUSIONS: Acala-NG with or without a PPI is safe and well-tolerated without impeding bioavailability.

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.

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.

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.

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.

Mechanistic Models for USP2 Dissolution Apparatus, Including Fluid Hydrodynamics and Sedimentation.

Drug product dissolution is a key input to Physiologically Based Biopharmaceutics Models (PBBM) to be able to predict in vivo dissolution. The integration of product dissolution in PBBMs for immediate release drug products should be mechanistic, i.e. allow to capture the main determinants of the in vitro dissolution experiment, and extract product batch specific parameter(s). This work focussed on the Product Particle Size Distribution (P-PSD), which was previously shown to integrate the effect of dose, volume, solubility (pH), size and concentration of micelles in the calculation of a batch specific input to PBBMs, and proposed new hydrodynamic (HD) models, which integrate the effect of USP2 apparatus paddle rotation speed and medium viscosity on dissolution. In addition, new models are also proposed to estimate the quantitative impact of formulation and drug sedimentation or "coning" on dissolution. Model "HDC-1" predicts coning in the presence of formulation insoluble excipients and "HDC-2" predicts the sedimentation of the drug substance only. These models were parameterized and validated on 166 dissolution experiments and 18 different drugs. The validation showed that the HD model average fold errors (AFE) for dissolution rate prediction of immediate release formulations, is comprised between 0.85 and 1.15, and the absolute average fold errors (AAFE) are comprised between 1.08 and 1.28, which shows satisfactory predictive power. For experiments where coning was suspected, the HDC-1 model improved the precision of the prediction (defined as ratio of "AAFE-1"values) by 2.46 fold compared to HD model. The calculation of a P-PSD integrating the impact of USP2 paddle rotation, medium viscosity and coning, will improve the PBBM predictions, since these parameters could have an influence on in vitro dissolution, and could open the way to better prediction of the effect of prandial state on human exposure, by developing new in silico tools which could integrate variation of velocity profiles due to the chyme viscosity.

Application of In Vivo Imaging Techniques and Diagnostic Tools in Oral Drug Delivery Research.

Drug absorption following oral administration is determined by complex and dynamic interactions between gastrointestinal (GI) physiology, the drug, and its formulation. Since many of these interactions are not fully understood, the COST action on "Understanding Gastrointestinal Absorption-related Processes (UNGAP)" was initiated in 2017, with the aim to improve the current comprehension of intestinal drug absorption and foster future developments in this field. In this regard, in vivo techniques used for the characterization of human GI physiology and the intraluminal behavior of orally administered dosage forms in the GI tract are fundamental to gaining deeper mechanistic understanding of the interplay between human GI physiology and drug product performance. In this review, the potential applications, advantages, and limitations of the most important in vivo techniques relevant to oral biopharmaceutics are presented from the perspectives of different research fields.

Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series.

A webinar series that was organised by the Academy of Pharmaceutical Sciences Biopharmaceutics focus group in 2021 focused on the challenges of developing clinically relevant dissolution specifications (CRDSs) for oral drug products. Industrial scientists, together with regulatory and academic scientists, came together through a series of six webinars, to discuss progress in the field, emerging trends, and areas for continued collaboration and harmonisation. Each webinar also hosted a Q&A session where participants could discuss the shared topic and information. Although it was clear from the presentations and Q&A sessions that we continue to make progress in the field of CRDSs and the utility/success of PBBM, there is also a need to continue the momentum and dialogue between the industry and regulators. Five key areas were identified which require further discussion and harmonisation.

Bioequivalence and Relative Bioavailability Studies to Assess a New Acalabrutinib Formulation That Enables Coadministration With Proton-Pump Inhibitors.

Acalabrutinib is a Bruton tyrosine kinase (BTK) inhibitor approved to treat adults with chronic lymphocytic leukemia, small lymphocytic lymphoma, or previously treated mantle cell lymphoma. As the bioavailability of the acalabrutinib capsule (AC) depends on gastric pH for solubility and is impaired by acid-suppressing therapies, coadministration with proton-pump inhibitors (PPIs) is not recommended. Three studies in healthy subjects (N = 30, N = 66, N = 20) evaluated the pharmacokinetics (PKs), pharmacodynamics (PDs), safety, and tolerability of acalabrutinib maleate tablet (AT) formulated with pH-independent release. Subjects were administered AT or AC (orally, fasted state), AT in a fed state, or AT in the presence of a PPI, and AT or AC via nasogastric (NG) route. Acalabrutinib exposures (geometric mean [% coefficient of variation, CV]) were comparable for AT versus AC (AUCinf 567.8 ng h/mL [36.9] vs 572.2 ng h/mL [38.2], Cmax 537.2 ng/mL [42.6] vs 535.7 ng/mL [58.4], respectively); similar results were observed for acalabrutinib's active metabolite (ACP-5862) and for AT-NG versus AC-NG. The geometric mean Cmax for acalabrutinib was lower when AT was administered in the fed versus the fasted state (Cmax 255.6 ng/mL [%CV, 46.5] vs 504.9 ng/mL [49.9]); AUCs were similar. For AT + PPI, geometric mean Cmax was lower (371.9 ng/mL [%CV, 81.4] vs 504.9 ng/mL [49.9]) and AUCinf was higher (AUCinf 694.1 ng h/mL [39.7] vs 559.5 ng h/mL [34.6]) than AT alone. AT and AC were similar in BTK occupancy. Most adverse events were mild with no new safety concerns. Acalabrutinib formulations were comparable and AT could be coadministered with PPIs, food, or via NG tube without affecting the PKs or PDs.

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.

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.

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.