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

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.

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.

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.

Best Practices for Integration of Dissolution Data into Physiologically Based Biopharmaceutics Models (PBBM): A Biopharmaceutics Modeling Scientist Perspective

Dissolution is considered as a critical input into physiologically based biopharmaceutics models (PBBM) as it governs in vivo exposure. Despite many workshops, initiatives by academia, industry, and regulatory, wider practices are followed for dissolution data input into PBBM models. Due to variety of options available for dissolution data input into PBBM models, it is important to understand pros, cons, and best practices while using specific dissolution model. This present article attempts to summarize current understanding of various dissolution models and data inputs in PBBM software's and aims to discuss practical challenges and ways to overcome such scenarios. Different approaches to incorporate dissolution data for immediate, modified, and delayed release formulations are discussed in detail. Common challenges faced during fitting of z-factor are discussed along with novel approach of dissolution data incorporation using P-PSD model. Ways to incorporate dissolution data for MR formulations using Weibull and IVIVR approaches were portrayed with examples. Strategies to incorporate dissolution data for DR formulations was depicted along with practical aspects. Approaches to generate virtual dissolution profiles, using Weibull function, DDDPlus, and time scaling for defining dissolution safe space, and strategies to generate virtual dissolution profiles for justifying single and multiple dissolution specifications were discussed. Finally, novel ways to integrate dissolution data for complex products such as liposomes, data from complex dissolution systems, importance of precipitation, and bio-predictive ability of QC media for evaluation of CBA's impact were discussed. Overall, this article aims to provide an easy guide for biopharmaceutics modeling scientist to integrate dissolution data effectively into PBBM models.

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.

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 Pharmacokinetics Modeling in Biopharmaceutics: Case Studies for Establishing the Bioequivalence Safe Space for Innovator and Generic Drugs

For successful oral drug development, defining a bioequivalence (BE) safe space is critical for the identification of newer bioequivalent formulations or for setting of clinically relevant in vitro specifications to ensure drug product quality. By definition, the safe space delineates the dissolution profile boundaries or other drug product quality attributes, within which the drug product variants are anticipated to be bioequivalent. Defining a BE safe space with physiologically based biopharmaceutics model (PBBM) allows the establishment of mechanistic in vitro and in vivo relationships (IVIVR) to better understand absorption mechanism and critical bioavailability attributes (CBA). Detailed case studies on how to use PBBM to establish a BE safe space for both innovator and generic drugs are described. New case studies and literature examples demonstrate BE safe space applications such as how to set in vitro dissolution/particle size distribution (PSD) specifications, widen dissolution specification to supersede f2 tests, or application toward a scale-up and post-approval changes (SUPAC) biowaiver. A workflow for detailed PBBM set-up and common clinical study data requirements to establish the safe space and knowledge space are discussed. Approaches to model in vitro dissolution profiles i.e. the diffusion layer model (DLM), Takano and Johnson models or the fitted PSD and Weibull function are described with a decision tree. The conduct of parameter sensitivity analyses on kinetic dissolution parameters for safe space and virtual bioequivalence (VBE) modeling for innovator and generic drugs are shared. The necessity for biopredictive dissolution method development and challenges with PBBM development and acceptance criteria are described.

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 (AUC_inf 567.8 ng h/mL [36.9] vs 572.2 ng h/mL [38.2], C_max 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 C_max for acalabrutinib was lower when AT was administered in the fed versus the fasted state (C_max 255.6 ng/mL [%CV, 46.5] vs 504.9 ng/mL [49.9]); AUCs were similar. For AT + PPI, geometric mean C_max was lower (371.9 ng/mL [%CV, 81.4] vs 504.9 ng/mL [49.9]) and AUC_inf was higher (AUC_inf 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.

Physiologically based pharmacokinetic combined BTK occupancy modeling for optimal dosing regimen prediction of acalabrutinib in patients alone, with different CYP3A4 variants, co-administered with CYP3A4 modulators and with hepatic impairment

PURPOSE

To develop a mathematical model combined between physiologically based pharmacokinetic and BTK occupancy (PBPK-BO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of acalabrutinib (ACA) and active metabolite ACP-5862 in healthy humans as well as PD in patients. Next, to use the PBPK-BO to determine the optimal dosing regimens in patients alone, with different CYP3A4 variants, when co-administration with four CYP3A4 modulators and in patients with hepatic impairment, respectively.

METHODS

The PBPK-BO model was built using physicochemical and biochemical properties of ACA and ACP-5862 and then verified by observed PK and PD data from healthy humans and patients. Finally, the model was applied to determine optimal dosing regimens in various clinical situations.

RESULTS

The simulations demonstrated that 100 mg ACA twice daily (BID) was the optimal dosing regimen in patients alone. Additionally, dosage regimens might be reduced to 50 mg BID in patients with five CYP3A4 variants. Moreover, the dosing regimen should be modified to 100 mg (even to 50 mg) once daily (QD) when co-administration with erythromycin or clarithromycin, and be increased to 200 mg BID with rifampicin, and but be avoided co-administration with itraconazole. Furthermore, dosage regimen simulations showed that optimal dosing might be decreased to 50 mg BID in patients with mild and moderate hepatic impairment, and be avoided taking ACA in severely hepatically impaired patients.

CONCLUSION

This PBPK-BO model can predict PK and PD in healthy humans and patients and also predict the optimal dosing regimens in various clinical situations.

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.

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.

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 leukemia. 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% CI]: acalabrutinib AUC_inf : 103 [93-113]; C_max : 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 AUC_inf : 105 [79-138]; C_max : 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.

Predicting Solubility of Newly-Approved Drugs (2016–2020) with a Simple ABSOLV and GSE(Flexible-Acceptor) Consensus Model Outperforming Random Forest Regression

This study applies the ‘Flexible-Acceptor’ variant of the General Solubility Equation, GSE(Φ,B), to the prediction of the aqueous intrinsic solubility, log₁₀S₀, of FDA recently-approved (2016–2020) ‘small-molecule’ new molecular entities (NMEs). The novel equation had been shown to predict the solubility of drugs beyond Lipinski’s ‘Rule of 5’ chemical space (bRo5) to a precision nearly matching that of the Random Forest Regression (RFR) machine learning method. Since then, it was found that the GSE(Φ,B) appears to work well not only for bRo5 NMEs, but also for Ro5 drugs. To put context to GSE(Φ,B), Yalkowsky’s GSE(classic), Abraham’s ABSOLV, and Breiman’s RFR models were also applied to predict log₁₀ S₀ of 72 newly-approve NMEs, for which useable reported solubility values could be accessed (nearly 60% from FDA New Drug Application published reports). Except for GSE (classic), the prediction models were retrained with an enlarged version of the Wiki-pS₀ database (nearly 400 added log₁₀ S₀ entries since our recent previous study). Thus, these four models were further validated by the additional independent solubility measurements which the newly-approved drugs introduced. The prediction methods ranked RFR ~ GSE (Φ,B) > ABSOLV > GSE (classic) in performance. It was further demonstrated that the biases generated in the four separate models could be nearly eliminated in a consensus model based on the average of just two of the methods: GSE (Φ,B) and ABSOLV. The resulting consensus prediction equation is simple in form and can be easily incorporated into spreadsheet calculations. Even more significant, it slightly outperformed the RFR method.

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.

Establishing the Bioequivalence Safe Space for Immediate-Release Oral Dosage Forms using Physiologically Based Biopharmaceutics Modeling (PBBM): Case Studies

For oral drug products, in vitro dissolution is the most used surrogate of in vivo dissolution and absorption. In the context of drug product quality, safe space is defined as the boundaries of in vitro dissolution, and relevant quality attributes, within which drug product variants are expected to be bioequivalent to each other. It would be highly desirable if the safe space could be established via a direct link between available in vitro data and in vivo pharmacokinetics. In response to the challenges with establishing in vitro-in vivo correlations (IVIVC) with traditional modeling approaches, physiologically based biopharmaceutics modeling (PBBM) has been gaining increased attention. In this manuscript we report five case studies on using PBBM to establish a safe space for BCS Class 2 and 4 across different companies, including applications in an industrial setting for both internal decision making or regulatory applications. The case studies provide an opportunity to reflect on practical vs. ideal datasets for safe space development, the methodologies for incorporating dissolution data in the model and the criteria used for model validation and application. PBBM and safe space, still represent an evolving field and more examples are needed to drive development of best practices.

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.

Amorphous Solid Dispersion Tablets Overcome Acalabrutinib pH Effect in Dogs

Calquence^® (crystalline acalabrutinib), a commercially marketed tyrosine kinase inhibitor (TKI), exhibits significantly reduced oral exposure when taken with acid-reducing agents (ARAs) due to the low solubility of the weakly basic drug at elevated gastric pH. These drug-drug interactions (DDIs) negatively impact patient treatment and quality of life due to the strict dosing regimens required. In this study, reduced plasma drug exposure at high gastric pH was overcome using a spray-dried amorphous solid dispersion (ASD) comprising 50% acalabrutinib and 50% hydroxypropyl methylcellulose acetate succinate (HPMCAS, H grade) formulated as an immediate-release (IR) tablet. ASD tablets achieved similar area under the plasma drug concentration-time curve (AUC) at low and high gastric pH and outperformed Calquence capsules 2.4-fold at high gastric pH in beagle dogs. In vitro multicompartment dissolution testing conducted a priori to the in vivo study successfully predicted the improved formulation performance. In addition, ASD tablets were 60% smaller than Calquence capsules and demonstrated good laboratory-scale manufacturability, physical stability, and chemical stability. ASD dosage forms are attractive for improving patient compliance and the efficacy of acalabrutinib and other weakly basic drugs that have pH-dependent absorption.

Current challenges and future perspectives in oral absorption research: An opinion of the UNGAP network

Although oral drug delivery is the preferred administration route and has been used for centuries, modern drug discovery and development pipelines challenge conventional formulation approaches and highlight the insufficient mechanistic understanding of processes critical to oral drug absorption. This review presents the opinion of UNGAP scientists on four key themes across the oral absorption landscape: (1) specific patient populations, (2) regional differences in the gastrointestinal tract, (3) advanced formulations and (4) food-drug interactions. The differences of oral absorption in pediatric and geriatric populations, the specific issues in colonic absorption, the formulation approaches for poorly water-soluble (small molecules) and poorly permeable (peptides, RNA etc.) drugs, as well as the vast realm of food effects, are some of the topics discussed in detail. The identified controversies and gaps in the current understanding of gastrointestinal absorption-related processes are used to create a roadmap for the future of oral drug absorption research.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been extensively applied to quantitatively translate in vitro data, predict the in vivo performance, and ultimately support waivers of in vivo clinical studies. In the area of biopharmaceutics and within the context of model-informed drug discovery and development (MID3), there is a rapidly growing interest in applying verified and validated mechanistic PBPK models to waive in vivo clinical studies. However, the regulatory acceptance of PBPK analyses for biopharmaceutics and oral drug absorption applications, which is also referred to variously as "PBPK absorption modeling" [Zhang et al. CPT: Pharmacometrics Syst. Pharmacol. 2017, 6, 492], "physiologically based absorption modeling", or "physiologically based biopharmaceutics modeling" (PBBM), remains rather low [Kesisoglou et al. J. Pharm. Sci. 2016, 105, 2723] [Heimbach et al. AAPS J. 2019, 21, 29]. Despite considerable progress in the understanding of gastrointestinal (GI) physiology, in vitro biopharmaceutic and in silico tools, PBPK models for oral absorption often suffer from an incomplete understanding of the physiology, overparameterization, and insufficient model validation and/or platform verification, all of which can represent limitations to their translatability and predictive performance. The complex interactions of drug substances and (bioenabling) formulations with the highly dynamic and heterogeneous environment of the GI tract in different age, ethnic, and genetic groups as well as disease states have not been yet fully elucidated, and they deserve further research. Along with advancements in the understanding of GI physiology and refinement of current or development of fully mechanistic in silico tools, we strongly believe that harmonization, interdisciplinary interaction, and enhancement of the translational link between in vitro, in silico, and in vivo will determine the future of PBBM. This Perspective provides an overview of the current status of PBBM, reflects on challenges and knowledge gaps, and discusses future opportunities around PBPK/PD models for oral absorption of small and large molecules to waive in vivo clinical studies.

Best Practices in the Development and Validation of Physiologically Based Biopharmaceutics Modeling. A Workshop Summary Report

This workshop report summarizes the proceedings of Day 2 of a three-day workshop on "Current State and Future Expectations of Translational Modeling Strategies toSupportDrug Product Development, Manufacturing Changes and Controls". From a drug product quality perspective, physiologically based biopharmaceutics modeling (PBBM) is a tool to link variations in the drug product quality attributes to in vivo outcomes enabling the establishment of clinically relevant drug product specifications (CRDPS). Day 2 of the workshop focused on best practices in developing, verifying and validating PBBM. This manuscript gives an overview of podium presentations and summarizes breakout (BO) session discussions related to (1) challenges and opportunities for using PBBM to assess the clinical impact of formulation and manufacturing changes on the in vivo performance of a drug product, (2) best practices to account for parameter uncertainty and variability during model development, (3) best practices in the development, verification and validation of PBBM and (4) opportunities and knowledge gaps related to leveraging PBBM for virtual bioequivalence simulations.

Physiologically Based Absorption Modelling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Entrectinib

Entrectinib is a potent and selective tyrosine kinase inhibitor (TKI) of TRKA/B/C, ROS1, and ALK with both systemic and CNS activities, which has recently received FDA approval for ROS1 fusion-positive non-small cell lung cancer and NTRK fusion-positive solid tumors. This paper describes the application of a physiologically based biophamaceutics modeling (PBBM) during clinical development to understand the impact of food and gastric pH changes on absorption of this lipophilic, basic, molecule with reasonable permeability but strongly pH-dependent solubility. GastroPlus™ was used to develop a physiologically based pharmacokinetics (PBPK) model integrating in vitro and in silico data and dissolution studies and in silico modelling in DDDPlus™ were used to understand the role of self-buffering and acidulant on formulation performance. Models were verified by comparison of simulated pharmacokinetics for acidulant and non-acidulant containing formulations to clinical data from a food effect study and relative bioavailability studies with and without the gastric acid-reducing agent lansoprazole. A negligible food effect and minor pH-dependent drug-drug interaction for the market formulation were predicted based on biorelevant in vitro measurements, dissolution studies, and in silico modelling and were confirmed in clinical studies. These outcomes were explained as due to the acidulant counteracting entrectinib self-buffering and greatly reducing the effect of gastric pH changes. Finally, sensitivity analyses with the verified model were applied to support drug product quality. PBBM has great potential to streamline late-stage drug development and may have impact on regulatory questions.

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.

Selection of In Vivo Predictive Dissolution Media Using Drug Substance and Physiological Properties

The rate and extent of drug dissolution in the gastrointestinal (GI) tract are highly dependent upon drug physicochemical properties and GI fluid properties. Biorelevant dissolution media (BDM), which aim to facilitate in vitro prediction of in vivo dissolution performance, have evolved with our understanding of GI physiology. However, BDM with a variety of properties and compositions are available, making the choice of dissolution medium challenging. In this tutorial, we describe a simple and quantitative methodology for selecting practical, yet physiologically relevant BDM representative of fasted humans for evaluating dissolution of immediate release formulations. Specifically, this methodology describes selection of pH, buffer species, and concentration and evaluates the importance of including bile salts and phospholipids in the BDM based upon drug substance log D, pK_a, and intrinsic solubility. The methodology is based upon a mechanistic understanding of how three main factors affect dissolution, including (1) drug ionization at gastrointestinal pH, (2) alteration of surface pH by charged drug species, and (3) drug solubilization in mixed lipidic aggregates comprising bile salts and phospholipids. Assessment of this methodology through testing and comparison with literature reports showed that the recommendations correctly identified when a biorelevant buffer capacity or the addition of bile salts and phospholipids to the medium would appreciably change the drug dissolution profile. This methodology can enable informed decisions about when a time, complexity, and/or cost-saving buffer is expected to lead to physiologically meaningful in vitro dissolution testing, versus when a more complex buffer would be required.

A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP

The application of in silico modeling to predict the in vivo outcome of an oral drug product is gaining a lot of interest. Fully relying on these models as a surrogate tool requires continuous optimization and validation. To do so, intraluminal and systemic data are desirable to judge the predicted outcomes. The aim of this study was to predict the systemic concentrations of ibuprofen after oral administration of an 800 mg immediate-release (IR) tablet to healthy subjects in fasted-state conditions. A mechanistic oral absorption model coupled with a two-compartmental pharmacokinetic (PK) model was built in Phoenix WinNonlinWinNonlin^® software and in the GastroPlus™ simulator. It should be noted that all simulations were performed in an ideal framework as we were in possession of a plethora of in vivo data (e.g., motility, pH, luminal and systemic concentrations) in order to evaluate and optimize these models. All this work refers to the fact that important, yet crucial, gastrointestinal (GI) variables should be integrated into biopredictive dissolution testing (low buffer capacity media, considering phosphate versus bicarbonate buffer, hydrodynamics) to account for a valuable input for physiologically-based pharmacokinetic (PBPK) platform programs. While simulations can be performed and mechanistic insights can be gained from such simulations from current software, we need to move from correlations to predictions (IVIVC → IVIVP) and, moreover, we need to further determine the dynamics of the GI variables controlling the dosage form transit, disintegration, dissolution, absorption and metabolism along the human GI tract. Establishing the link between biopredictive in vitro dissolution testing and mechanistic oral absorption modeling (i.e., physiologically-based biopharmaceutics modeling (PBBM)) creates an opportunity to potentially request biowaivers in the near future for orally administered drug products, regardless of its classification according to the Biopharmaceutics Classification System (BCS).