Biopharmaceutical Modeling of Food Effect─Exploring the Role of Dietary Fat.

In preclinical drug discovery, simple fraction absorbed calculators are exceptionally valuable tools to better understand the potential limitations to drug absorption and how different formulation approaches may address them. These tools often struggle to accurately capture the impact of food on drug absorption. One possible reason for this is that these models overlook the potential role of dietary fat in altering drug absorption. Herein, we present a novel approach to incorporate the fat content from diet within an absorption model as an additional set of particles that can accumulate in the mucus and act to reduce the effective thickness of the unstirred water layer. Using this approach, we demonstrate improved model prediction on the extent of food effect for a range of marketed compounds comparing two historical absorption models and the new model developed in this work using published food effect data for 21 marketed compounds. We extended this work to investigate each model's ability to predict the reported food effect across a range of dose levels for Venetoclax. Finally, we investigate the new model's capability to predict food effect in both low-fat and high-fat fed states and compare these predictions to the two historical models using three model compounds: Albendazole, Pazopanib, and Venetoclax.

Prediction of Liquid-Liquid Phase Separation at the Dissolving Drug Salt Particle Surface.

During the dissolution of drug salt particles, liquid-liquid phase separation (LLPS) of a free form can occur within the unstirred water layer (UWL) of the particles (UWL-LLPS). Theoretically, UWL-LLPS occurs when the free form concentration at the salt particle surface (C0) exceeds the intrinsic LLPS concentration (S0LLPS) of the free form. In the present study, we attempted to predict UWL-LLPS based on the intrinsic physicochemical properties of drugs. Cyproheptadine hydrochloride (CPH-HCl), diclofenac sodium (DCF-Na), papaverine hydrochloride (PAP-HCl), and propafenone hydrochloride (PRF-HCl) were selected as model drug salts. The pH0 and C0 values at pHs 4.0-9.5 (citric acid, phosphoric acid, and boric acid, buffer capacity = ca. 4 mM/ΔpH) were calculated using the pKa, solubility product (Ksp), and diffusion coefficient (D) of a drug. S0LLPS was measured using the pH-shift method. UWL-LLPS was predicted to occur when C0 ≥ S0LLPS. The prediction result was then compared with UWL-LLPS observed at each pH by polarized light microscopy (PLM). The pH-LLPS concentration (SpHLLPS) profile of each drug was also measured. UWL-LLPS was approximately correctly predicted for CPH-HCl, DCF-Na, and PRF-HCl. However, UWL-LLPS was not observable when C0 was close to S0LLPS. Furthermore, UWL-LLPS was not accurately predicted in the case of PAP-HCl. The pH-SpHLLPS profile of PAP did not follow the Henderson-Hasselbalch equation, probably because of the formation of cationic aggregates. In conclusion, UWL-LLPS was approximately predictable for drug salts using their intrinsic physicochemical properties (Ksp, pKa, D, and S0LLPS), except for PAP-HCl.

Lilly Absorption Modeling Platform: A Tool for Early Absorption Assessment.

Oral drug absorption modeling has developed at a rapid pace in the 40 years or so since the first ideas for mathematical approaches to oral absorption were introduced. The success of compartmental approaches accelerated the uptake of absorption modeling, and over the last 20 years, work on absorption modeling has shifted almost exclusively to the compartmental framework. This report describes a new noncompartmental absorption modeling framework, the Lilly Absorption Modeling Platform (LAMP). LAMP connects a well-mixed stomach to a continuous tube model of the small intestine with plug flow. Within the continuous tube framework, the model includes intestinal mixing and a novel highly tunable precipitation model that can describe a combination of rapid nucleation and slow growth. The framework is designed to balance speed, consistency, and ease of use with a minimum of model complexity to capture the essential features of gastrointestinal (GI) physiology and critical elements of the oral absorption process. The model was validated based on predictions of the fraction absorbed and the maximum absorbable dose for a set of Eli Lilly and Company clinical compounds.

Development, validation and application of physiologically based biopharmaceutics model to justify the change in dissolution specifications for DRL ABC extended release tablets.

OBJECTIVE: The generic drug product DRL ABC is an Extended Release (ER) Tablet manufactured by Dr. Reddy's Laboratories Limited and have multi point dissolution as part of release specification. A proposal is being made to revise the dissolution specification and the aim of present work was to evaluate if this would still provide bioequivalent product. METHODS: PBBM was developed for DRL ABC using literature reported pharmacokinetic (PK) data. The intravenous PK data and in vitro metabolic rate constants were utilized for developing PBPK model first, followed by that in conjugation with mechanistic ACATTM model, a PBBM is developed for per-oral immediate release formulations. The validated model was applied to predict clinical bioequivalence (BE) study data for the Reference (Innovator ER Tablet) and Test product. For Reference and Test product, in vivo dissolution profiles were mechanistically deconvoluted from plasma concentration (Cp)-time profiles. Further, mechanistic in vitro-in vivo relationship (IVIVR) applied to in vitro release profiles of two hypothetical Test product batches (one with single point low dissolution profile (SPLP) and other with overall low dissolution profile (LP)) in order to calculate their in vivo releases and population simulation was performed with 40 virtual subjects. RESULTS: Results from the cross-over virtual trials showed BE between the Reference and various Test product batches (SPLP and LP), with maximum Cp (Cmax) and area under the Cp-time curve (AUC0-inf) well within 80-125% range. CONCLUSION: PBBM in conjugation with IVIVR and virtual BE was successfully applied for justifying changes in dissolution specification of DRL ABC.

In vitro-In vivo Relationship and Bioequivalence Prediction for Modified-Release Capsules Based on a PBPK Absorption Model.

A physiologically based pharmacokinetic (PBPK) absorption model was developed in GastroPlus™ based on data on intravenous, immediate-release (IR), and modified-release (MR) drug products. The predictability of the model was evaluated by comparing predicted and observed plasma concentration profiles; average prediction errors (PE) were below 10%. IVIVR was developed using mechanistic deconvolution for a MR drug product to evaluate the in vivo effect of a proposed change in dissolution specification. The predictability of the IVIVR was evaluated and PE were below 10%; however, external validation was not possible due to the lack of data. The developed PBPK absorption model and IVIVR were used to predict plasma concentration profiles and pharmacokinetic (PK) parameters for a hypothetical formulation with 0% of drug dissolved in 2 h in in vitro dissolution test. Both methods predicted the insignificant effect of a change in in vitro dissolution profile on in vivo product performance. The bioequivalence of a hypothetical formulation to the test product was evaluated using virtual clinical trial. The performed analysis supported the proposed change in dissolution specification. A validated PBPK absorption model was proposed as an adequate alternative to IVIVC, when IVIVC could not have been developed according to the guidelines.

Radiation induced in-situ cationic polymerization of polystyrene organogel for selective absorption of cholorophenols from petrochemical wastewater.

A new in-situ cationic polymerization was performed to synthesize a cross-linked (91%) polystyrene (PS) organogel through tetrachloroethylene radiolysis assisted by 60Co gamma rays. Hoernschemeyer diagram and swelling capacity test show a better selectivity of PS organogel to chlorinated molecules compared to ester, hydrocarbons and alcohols organic molecules by 80-184 folds. Response surface modeling (RSM) of CPs (2,4,6-trichlorophenol) sorption from artificial wastewater confirm superiority of PS organogel to absorb 1746 µmol CPs/g (∼345 mg CPs/g) at broad pH (4-10) and temperature (25-45 °C). Based on ANOVA statistic, simulated CPs absorption model onto PS organogel was successfully developed, with accuracy of prediction of R2≈ RAdj2 of 0.991-0.995 and lower coefficient of variation of 2.73% with Fmodel of 611.4 at p < .0001. Particularly, the usage of PS organogel for petroleum wastewater reclamation exhibited higher absorption affinities for all the organic contaminants especially for CPs (>99%) by non-covalent and/or dispersive interaction mechanisms with a well-term reusability and good stability up to 5 cycles.

Physiologically Based Absorption Modeling of Salts of Weak Bases Based on Data in Hypochlorhydric and Achlorhydric Biorelevant Media.

Physiologically based absorption modeling has been attracting increased attention to study the interactions of weakly basic drug compounds with acid-reducing agents like proton-pump inhibitors and H2 blockers. Recently, standardized gastric and intestinal biorelevant media to simulate the achlorhydric and hypochlorhydric stomach were proposed and solubility and dissolution data for two model compounds were generated. In the current manuscript, for the first time, we report the utility of these recently proposed biorelevant media as input into physiologically based absorption modeling. Where needed, data collected with the biorelevant gastrointestinal transfer (BioGIT) system were used for informing the simulations in regard to the precipitation kinetics. Using two model compounds, a HCl salt and a semi-fumarate co-crystal which as expected dissolve to a greater extent in these media (and in gastric and intestinal human aspirates) compared to what the pH-solubility profile of the free form would suggest, we demonstrate successful description of the plasma concentration profiles and correctly predicted the lack of significant interaction after administration with pantoprazole or famotidine, respectively. Thus, the data reported in this manuscript represent an initial step towards defining biorelevant input for such simulations on interactions with acid-reducing agents.

Physiologically Based Absorption Modeling for Amorphous Solid Dispersion Formulations.

Amorphous solid dispersion (ASD) formulations are routinely used to enable the delivery of poorly soluble compounds. This type of formulations can enhance bioavailability due to higher kinetic solubility of the drug substance and increased dissolution rate of the formulation, by the virtue of the fact that the drug molecule exists in the formulation in a high energy amorphous state. In this article we report the application of physiologically based absorption models to mechanistically understand the clinical pharmacokinetics of solid dispersion formulations. Three case studies are shown here to cover a wide range of ASD bioperformance in human and modeling to retrospectively understand their in vivo behavior. Case study 1 is an example of fairly linear PK observed with dose escalation and the use of amorphous solubility to predict bioperformance. Case study 2 demonstrates the development of a model that was able to accurately predict the decrease in fraction absorbed (%Fa) with dose escalation thus demonstrating that such model can be used to predict the clinical bioperformance in the scenario where saturation of absorption is observed. Finally, case study 3 shows the development of an absorption model with the intent to describe the observed incomplete and low absorption in clinic with dose escalation. These case studies highlight the utility of physiologically based absorption modeling in gaining a thorough understanding of ASD performance and the critical factors impacting performance to drive design of a robust drug product that would deliver the optimal benefit to the patients.

High-throughput micro-scale cultivations and chromatography modeling: Powerful tools for integrated process development.

Upstream processes are rather complex to design and the productivity of cells under suitable cultivation conditions is hard to predict. The method of choice for examining the design space is to execute high-throughput cultivation screenings in micro-scale format. Various predictive in silico models have been developed for many downstream processes, leading to a reduction of time and material costs. This paper presents a combined optimization approach based on high-throughput micro-scale cultivation experiments and chromatography modeling. The overall optimized system must not necessarily be the one with highest product titers, but the one resulting in an overall superior process performance in up- and downstream. The methodology is presented in a case study for the Cherry-tagged enzyme Glutathione-S-Transferase from Escherichia coli SE1. The Cherry-Tag™ (Delphi Genetics, Belgium) which can be fused to any target protein allows for direct product analytics by simple VIS absorption measurements. High-throughput cultivations were carried out in a 48-well format in a BioLector micro-scale cultivation system (m2p-Labs, Germany). The downstream process optimization for a set of randomly picked upstream conditions producing high yields was performed in silico using a chromatography modeling software developed in-house (ChromX). The suggested in silico-optimized operational modes for product capturing were validated subsequently. The overall best system was chosen based on a combination of excellent up- and downstream performance.

Food-Drug Effects and Pediatric Drug Development Studies Submitted to the US Food and Drug Administration, 2012-2022.

Food effect (FE) studies characterize food-drug interactions that may alter the efficacy or safety of a drug, but these studies are not conducted in pediatric patients. Pediatric patients have substantial physiologic, anatomic, and dietary differences from adults, which may result in differences in their FE considerations. Therefore, the objective of this study was to identify oral drug products approved for use in pediatric patients aged <6 years with an FE observed in adults. Additional objectives were to summarize the therapeutic areas, pharmacokinetic effects, and labeling instructions that resulted from these studies. Publicly available data were searched for products studied in pediatric patients and approved for use by the United States Food and Drug Administration (FDA) from 2012 to 2022. Of the 102 oral drug products approved for use in patients aged <6 years, 43 recommended the consideration of food intake in the drug labeling. These included drug products recommended to be taken with food (n = 21, 49%) or without food (n = 14, 33%). Each of the 14 drug products recommended to be taken without food are approved for use in pediatric patients aged <2 years. The products approved for use in pediatric patients aged <2 years comprised the highest proportion with area under the plasma concentration-time curve extrapolated to infinity (AUCinf, n = 35, 75%) and maximum serum concentration (Cmax, n = 45, 80%) affected by food. Close monitoring is warranted during the postapproval period for products identified as having a significant FE in adults and that are approved for use in pediatric patients aged <6 years. Promising tools for predicting pediatric FE may include physiologically based pharmacokinetic absorption modeling.

Preclinical modeling of intravitreal suspensions.

There are a number of obstacles that complicate the development of intravitreal delivered small molecules therapies. One serious complication is the potential need for complex polymer depot formulations early in the drug discovery process. The development of such formulations often requires substantial investment of time and material which may not be readily available in preclinical development. Herein I present a diffusion limited pseudo-steady state model to provide prediction of drug release from an intravitreally administered suspension formulation. By using such a model, a preclinical formulator may be able to more confidently determine if development of a complex formulation is required or if a simple suspension may work to support a study design. In this report, the model is used to predict the intravitreal preformance of two different molecules (triamcinolone acetonide and GNE-947) at multiple dose levels in rabbit eyes as well as provide a prediction for the performance of a marketed formulation of Trimacinolone Acetonide in humans.

Developing a Formulation Strategy Coupled with PBPK Modeling and Simulation for the Weakly Basic Drug Albendazole.

Albendazole (ABZ) is a weakly basic drug that undergoes extensive presystemic metabolism after oral administration and converts to its active form albendazole sulfoxide (ABZ_SO). The absorption of albendazole is limited by poor aqueous solubility, and dissolution is the rate-limiting step in the overall exposure of ABZ_SO. In this study, PBPK modeling was used to identify formulation-specific parameters that impact the oral bioavailability of ABZ_SO. In vitro experiments were carried out to determine pH solubility, precipitation kinetics, particle size distribution, and biorelevant solubility. A transfer experiment was conducted to determine the precipitation kinetics. A PBPK model for ABZ and ABZ_SO was developed using the Simcyp™ Simulator based on parameter estimates from in vitro experiments. Sensitivity analyses were performed to assess the impact of physiological parameters and formulation-related parameters on the systemic exposure of ABZ_SO. Model simulations predicted that increased gastric pH significantly reduced ABZ absorption and, subsequently, ABZ_SO systemic exposure. Reducing the particle size below 50 µm did not improve the bioavailability of ABZ. Modeling results illustrated that systemic exposure of ABZ_SO was enhanced by increasing solubility or supersaturation and decreasing the drug precipitation of ABZ at the intestinal pH level. These results were used to identify potential formulation strategies to enhance the oral bioavailability of ABZ_SO.

Application of physiologically based absorption and pharmacokinetic modeling in the development process of oral modified release generic products.

Physiologically based pharmacokinetic (PBPK) modeling for biopharmaceutics applications holds great promise as modelling and simulation tool in the field of modern oral modified release (MR) products. Understanding of gastro-intestinal absorption related processes is crucial to ensure the successful development of complex oral drug generic products. In the recent years, PBPK approach has been gradually influencing decision making ability of pharmaceutical industry as well as regulatory agencies. However, there is a gap in understanding its contribution in the field of oral modified release products. In this review, we have collected different recent research articles illustrating the significant contribution of PBPK to the research and development process of oral MR products, with special emphasis on generic drug products. Concretely, literature examples on the utility of PBPK formulation development, for in vitro- in vivo correlations (IVIVC) and prediction of oral bioavailability, and for in-silico food effect predictions were included in the review.

Percutaneous absorption of steroids from finite doses: Predicting urinary excretion from in vitro skin permeation testing.

Pharmacokinetic (PK) models are widely used to describe drug permeation across the epidermal membrane barrier, the stratum corneum (SC). Here, we extend our previously reported diffusion and compartment-in-series models to describe plasma concentrations, urinary excretion-time profiles and exposure estimates after topically applied finite doses of solvent deposited solids. In vivo models were derived by convolution of a skin absorption input function for finite dosing with that for in vivo disposition PK. In vitro skin permeation test (IVPT) and in vivo urinary excretion data for cortisone, desoxycorticosterone, and testosterone were extracted from literature for model validation and establishment of in vitro - in vivo relationships (IVIVR). Both SC diffusion and SC 3-compartment-in-series PK models adequately described experimental in vitro and in vivo permeation data, with similar model parameter estimates for SC diffusion time and bioavailability. A satisfactory IVIVR was generated for cortisone, whereas testosterone and desoxycorticosterone showed higher bioavailability in vitro compared to in vivo. In recognising that future prospective studies need to both have an adequate sampling schedule and be harmonized for robust IVIVRs, we developed expressions for predicting extent of absorption and time for peak absorption for both in vitro and in vivo studies. Other study parameters, such as application site, applied dose, and application techniques, can also affect drug permeability through skin during dosage form metamorphosis after finite dose application, and a lack of correlation may result if these are poorly matched.

PBPK Modeling as a Tool for Predicting and Understanding Intestinal Metabolism of Uridine 5'-Diphospho-glucuronosyltransferase Substrates.

Uridine 5'-diphospho-glucuronosyltransferases (UGTs) are expressed in the small intestines, but prediction of first-pass extraction from the related metabolism is not well studied. This work assesses physiologically based pharmacokinetic (PBPK) modeling as a tool for predicting intestinal metabolism due to UGTs in the human gastrointestinal tract. Available data for intestinal UGT expression levels and in vitro approaches that can be used to predict intestinal metabolism of UGT substrates are reviewed. Human PBPK models for UGT substrates with varying extents of UGT-mediated intestinal metabolism (lorazepam, oxazepam, naloxone, zidovudine, cabotegravir, raltegravir, and dolutegravir) have demonstrated utility for predicting the extent of intestinal metabolism. Drug-drug interactions (DDIs) of UGT1A1 substrates dolutegravir and raltegravir with UGT1A1 inhibitor atazanavir have been simulated, and the role of intestinal metabolism in these clinical DDIs examined. Utility of an in silico tool for predicting substrate specificity for UGTs is discussed. Improved in vitro tools to study metabolism for UGT compounds, such as coculture models for low clearance compounds and better understanding of optimal conditions for in vitro studies, may provide an opportunity for improved in vitro-in vivo extrapolation (IVIVE) and prospective predictions. PBPK modeling shows promise as a useful tool for predicting intestinal metabolism for UGT substrates.

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 AUC0-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.

Integrated computer-aided formulation design: A case study of andrographolide/ cyclodextrin ternary formulation.

Current formulation development strongly relies on trial-and-error experiments in the laboratory by pharmaceutical scientists, which is time-consuming, high cost and waste materials. This research aims to integrate various computational tools, including machine learning, molecular dynamic simulation and physiologically based absorption modeling (PBAM), to enhance andrographolide (AG) /cyclodextrins (CDs) formulation design. The lightGBM prediction model we built before was utilized to predict AG/CDs inclusion's binding free energy. AG/γ-CD inclusion complexes showed the strongest binding affinity, which was experimentally validated by the phase solubility study. The molecular dynamic simulation was used to investigate the inclusion mechanism between AG and γ-CD, which was experimentally characterized by DSC, FTIR and NMR techniques. PBAM was applied to simulate the in vivo behavior of the formulations, which were validated by cell and animal experiments. Cell experiments revealed that the presence of D-α-Tocopherol polyethylene glycol succinate (TPGS) significantly increased the intracellular uptake of AG in MDCK-MDR1 cells and the absorptive transport of AG in MDCK-MDR1 monolayers. The relative bioavailability of the AG-CD-TPGS ternary system in rats was increased to 2.6-fold and 1.59-fold compared with crude AG and commercial dropping pills, respectively. In conclusion, this is the first time to integrate various computational tools to develop a new AG-CD-TPGS ternary formulation with significant improvement of aqueous solubility, dissolution rate and bioavailability. The integrated computational tool is a novel and robust methodology to facilitate pharmaceutical formulation design.

Biorelevant dissolution testing and physiologically based absorption modeling to predict in vivo performance of supersaturating drug delivery systems.

Supersaturating drug delivery systems (SDDS) enhance the oral absorption of poorly water-soluble drugs by achieving a supersaturated state in the gastrointestinal tract. The maintenance of a supersaturated state is decided by the complex interplay among inherent properties of drug, excipients and physiological conditions of gastrointestinal tract. The biopharmaceutical advantage through SDDS can be mechanistically investigated by coupling biopredictive dissolution testing with physiologically based absorption modeling (PBAM). However, the development of biopredictive dissolution methods possess challenges due to concurrent dissolution, supersaturation, precipitation, and possible redissolution of precipitates during gastrointestinal transit of SDDS. In this comprehensive review, our effort is to critically assess the current state-of-knowledge and provide future directions for PBAM of SDDS. The review outlines various methods used to retrieve physiologically relevant values for input parameters like solubility, dissolution, precipitation, lipid-digestion and permeability of SDDS. SDDS-specific parameterization includes solubility values corresponding to apparent physical form, dissolution in physiologically relevant volumes with biorelevant media, and transfer experiments to incorporate precipitation kinetics. Interestingly, the lack of experimental permeability values and modification of absorption flux through SDDS possess the additional challenge for its PBAM. Supersaturation triggered permeability modifications are reported to fit the observed plasma concentration-time profile. Hence, the experimental insights on good fitting with modified permeability can be potential area of future research for the development of in vitro methods to reliably predict oral absorption of SDDS.

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Predict the Impact of CYP2C9 Genetic Polymorphisms, Co-Medication and Formulation on the Pharmacokinetics and Pharmacodynamics of Flurbiprofen.

Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models can serve as a powerful framework for predicting the influence as well as the interaction of formulation, genetic polymorphism and co-medication on the pharmacokinetics and pharmacodynamics of drug substances. In this study, flurbiprofen, a potent non-steroid anti-inflammatory drug, was chosen as a model drug. Flurbiprofen has absolute bioavailability of ~95% and linear pharmacokinetics in the dose range of 50-300 mg. Its absorption is considered variable and complex, often associated with double peak phenomena, and its pharmacokinetics are characterized by high inter-subject variability, mainly due to its metabolism by the polymorphic CYP2C9 (fmCYP2C9 ≥ 0.71). In this study, by leveraging in vitro, in silico and in vivo data, an integrated PBPK/PD model with mechanistic absorption was developed and evaluated against clinical data from PK, PD, drug-drug and gene-drug interaction studies. The PBPK model successfully predicted (within 2-fold) 36 out of 38 observed concentration-time profiles of flurbiprofen as well as the CYP2C9 genetic effects after administration of different intravenous and oral dosage forms over a dose range of 40-300 mg in both Caucasian and Chinese healthy volunteers. All model predictions for Cmax, AUCinf and CL/F were within two-fold of their respective mean or geometric mean values, while 90% of the predictions of Cmax, 81% of the predictions of AUCinf and 74% of the predictions of Cl/F were within 1.25 fold. In addition, the drug-drug and drug-gene interactions were predicted within 1.5-fold of the observed interaction ratios (AUC, Cmax ratios). The validated PBPK model was further expanded by linking it to an inhibitory Emax model describing the analgesic efficacy of flurbiprofen and applying it to explore the effect of formulation and genetic polymorphisms on the onset and duration of pain relief. This comprehensive PBPK/PD analysis, along with a detailed translational biopharmaceutic framework including appropriately designed biorelevant in vitro experiments and in vitro-in vivo extrapolation, provided mechanistic insight on the impact of formulation and genetic variations, two major determinants of the population variability, on the PK/PD of flurbiprofen. Clinically relevant specifications and potential dose adjustments were also proposed. Overall, the present work highlights the value of a translational PBPK/PD approach, tailored to target populations and genotypes, as an approach towards achieving personalized medicine.

PBPK Absorption Modeling: Establishing the In Vitro-In Vivo Link-Industry Perspective.

The establishment of an in vitro-in vivo correlation (IVIVC) is considered the gold standard to establish in vivo relevance of a dissolution method and to utilize dissolution data in the context of regulatory bioequivalence questions, including the development of dissolution specifications. However, several recent publications, including industry surveys and reviews from regulatory agencies, have indicated a low success rate for IVIVCs, especially for immediate-release formulations. In recent years, the use of physiologically based pharmacokinetics (PBPK) and absorption modeling, as a tool to facilitate formulation development, has been attracting increased attention. This manuscript provides an industry perspective on the current challenges with establishing IVIVCs and the potential PBPK and absorption modeling offer to increase their impact. Case studies across both immediate-release and extended-release formulations from five pharmaceutical companies are utilized to demonstrate how physiologically based IVIVC (PB-IVIVC) may facilitate drug product understanding and to inform bioequivalence assessment and clinically relevant specifications. Finally, PB-IVIVC best practices and a strategy for model development and application are proposed.