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This report summarizes the proceedings for Day 3 of the workshop titled " Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives ". This day focused on the current and future drug product quality applications of PBBM from the innovator and generic industries as well as the regulatory agencies perspectives. The presentations, which included several case studies, covered the applications of PBBM in generic drug product development, applications of virtual bioequivalence trials to support formulation bridging and the utility of absorption modeling in clinical pharmacology assessments. In addition, recent progress in the prediction of colon absorption and in vivo performance of extended-release drug products was shared. The morning session was concluded by representatives from FDA, ANVISA, MHRA, Health Canada, EMA, and PMDA giving their perspectives on the application of PBBM in regulatory submissions. The afternoon breakout sessions focused on four parallel topics: 1) PBBM in generic drug product development; 2) virtual bioequivalence trials applications; 3) safe space and extrapolation; and 4) regional absorption and modified release PBBM applications. This allowed the participants to engage in in-depth discussions of best practices as well to identify key points of consideration to allow further progress on the applications of PBBM.

The proceedings from the 30th August 2023 (Day 2) of the workshop "Physiologically Based Biopharmaceutics Models (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives" are provided herein. Day 2 covered PBBM case studies from six regulatory authorities which provided considerations for model verification, validation, and application based on the context of use (COU) of the model. PBBM case studies to define critical material attribute (CMA) specification settings, such as active pharmaceutical ingredient (API) particle size distributions (PSDs) were shared. PBBM case studies to define critical quality attributes (CQAs) such as the dissolution specification setting or to define the bioequivalence safe space were also discussed. Examples of PBBM using the credibility assessment framework, COU and model risk assessment, as well as scientific learnings from PBBM case studies are provided. Breakout session discussions highlighted current trends and barriers to application of PBBMs including: (a) PBBM credibility assessment framework and level of validation, (b) use of disposition parameters in PBBM and points to consider when iv data are not available, (c) conducting virtual bioequivalence trials and dealing with variability, (d) model acceptance criteria, and (e) application of PBBMs for establishing safe space and failure edges.

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.

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.

The rate and extent of colon absorption are important determinants of the in vivo performance of extended-release (ER) drug products. The ability to appropriately predict this at different stages of development using mechanistic physiologically based biopharmaceutic modeling (PBBM) is highly desirable. This investigation aimed to evaluate the prediction performance of three different approaches to account for colon absorption in predictions of the in vivo performance of ER drug product variants with different in vitro release profiles. This was done by mechanistic predictions of the absorption and plasma exposure of the ER drug products using GastroPlus and GI-Sim for five drugs with different degrees of colon absorption limitations in humans. Colon absorption was accounted for in the predictions using three different approaches: (1) by an a priori approach using the default colon models, (2) by fitting the colon absorption scaling factors to the observed plasma concentration-time profiles after direct administration to the colon in humans, or (3) from the ER drug product variant with the slowest in vitro release profile. The prediction performance was evaluated based on the percentage prediction error and the average absolute prediction error (AAPE). Two levels of acceptance criteria corresponding to highly accurate (AAPE ≤ 20%) and accurate (AAPE 20-50%) predictions were defined prior to the evaluation. For the a priori approach, the relative bioavailability ( F rel ), AUC 0-t , and C max of the ER drug product variants for the low to medium colon absorption limitation risk drugs was accurately predicted with an AAPE range of 11-53 and 8-59% for GastroPlus and GI-Sim, respectively. However, the prediction performance was poor for the high colon absorption limitation risk drugs. Moreover, accounting for the human regional colon absorption data in the models did not improve the prediction performance. In contrast, using the colon absorption scaling factors derived from the slowest ER variant significantly improved the prediction performance regardless of colon absorption limitation, with a majority of the predictions meeting the high accuracy criteria. For the slowest ER approach, the AAPE ranges were 5-24 and 5-32% for GastroPlus and GI-Sim, respectively, excluding the low permeability drug. In conclusion, the a priori PBBM can be used during candidate selection and early product design to predict the in vivo performance of ER drug products for low to medium colon absorption limitation risk drugs with sufficient accuracy. The results also indicate a limited value in performing human regional absorption studies in which the drug is administered to the colon as a bolus to support PBBM development for ER drug products. Instead, by performing an early streamlined relative bioavailability study with the slowest relevant ER in vitro release profile, a highly accurate PBBM suitable for ER predictions for commercial and regulatory applications can be developed, except for permeability-limited drugs.

Colon absorption is a key determinant for successful development of extended release and colon targeted drug products. This is the first systematic evaluation of the ability to predict in vivo regional differences in absorption and the extent of colon absorption in humans using mechanistic physiologically based biopharmaceutics modeling (PBBM). A new dataset, consisting of 19 drugs with a wide range of biopharmaceutics properties and extent of colon absorption in humans, was established. Mechanistic predictions of the extent of absorption and plasma exposure after oral, or jejunal and direct colon administration were performed in GastroPlus and GI-Sim using an a priori approach. Two new colon models developed in GI-Sim, were also evaluated to assess if the prediction performance could be improved. Both GastroPlus and GI-Sim met the pre-defined criteria for accurate predictions of regional and colon absorption for high permeability drugs irrespective of formulation type, while the prediction performance was poor for low permeability drugs. For solutions, the two new GI-Sim colon models improved the colon absorption prediction performance for the low permeability drugs while maintaining the accurate prediction performance for the high permeability drugs. In contrast, the prediction performance decreased for non-solutions using the two new colon models. In conclusion, PBBM can be used with sufficient accuracy to predict regional and colon absorption in humans for high permeability drugs in candidate selection as well as early design and development of extended release or colon targeted drug products. The prediction performance of the current models needs to be improved to allow high accuracy predictions for commercial drug product applications including highly accurate predictions of the entire plasma concentration-time profiles as well as for low permeability drugs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Colon absorption is a key determinant for the successful development of modified-release (MR) formulations, and the risk that colon absorption may limit the in vivo performance of an MR product can be assessed early by various in vitro tests or by preclinical in vivo regional absorption studies in dogs. Mechanistic physiologically based biopharmaceutics modeling (PBBM) is becoming increasingly accepted to predict in vivo performance and guide formulation development; however, no evaluation of the ability to predict colon absorption has been performed. The purpose of this study was to investigate if regional and colon absorption of drugs in dogs could be predicted with sufficient accuracy using PBBM to enable the replacement of in vivo dog studies in the early assessment of colon absorption limitation risks. This was done by predicting the regional and colon absorption and plasma exposure of 14 drugs after administration to the dog colon according to an a priori approach using the in silico absorption models GI-Sim and GastroPlus. Predictive performance was primarily assessed by comparing observed and predicted plasma concentration-time profiles, AUC 0- t , and the relative bioavailability in the colon ( F rel,colon ) as compared to an oral/duodenal reference. Trends in dependency of prediction performance on predicted fraction absorbed, permeability, and solubility/dissolution rate were also investigated. For GI-Sim, the absolute average fold error (AAFE) values for AUC 0- t and F rel,colon were within a 2-fold prediction error for both solutions (1.88 and 1.51, respectively) and suspensions (1.58 and 1.99, respectively). For GastroPlus, the AAFE values for AUC 0- t and F rel,colon were outside the set 2-fold prediction error limit for accurate predictions for both solutions (3.63 and 2.98, respectively) and suspensions (2.94 and 2.09, respectively). No trends for over- or underprediction were observed for GI-Sim, whereas GastroPlus showed a slight trend for underprediction of both AUC 0- t and F rel,colon for compounds with low permeability. In addition, regional differences in the plasma profiles were qualitatively predicted in the majority of cases for both software. Despite the differences in prediction performance, both models can be considered to predict regional differences in absorption as well as AUC 0- t and F rel,colon with acceptable accuracy in an early development setting. The results of this study indicate that it is acceptable to replace in vivo regional absorption studies in dogs with the evaluated models as a method for the early assessment of the risk for colon absorption limitation of MR drug product candidates.

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., (Copyright © 2020 American Pharmacists Association®. All rights reserved.)

Oral drug absorption is a complex process depending on many factors, including the physicochemical properties of the drug, formulation characteristics and their interplay with gastrointestinal physiology and biology. Physiological-based pharmacokinetic (PBPK) models integrate all available information on gastro-intestinal system with drug and formulation data to predict oral drug absorption. The latter together with in vitro-in vivo extrapolation and other preclinical data on drug disposition can be used to predict plasma concentration-time profiles in silico. Despite recent successes of PBPK in many areas of drug development, an improvement in their utility for evaluating oral absorption is much needed. Current status of predictive performance, within the confinement of commonly available in vitro data on drugs and formulations alongside systems information, were tested using 3 PBPK software packages (GI-Sim (ver.4.1), Simcyp® Simulator (ver.15.0.86.0), and GastroPlus™ (ver.9.0.00xx)). This was part of the Innovative Medicines Initiative (IMI) Oral Biopharmaceutics Tools (OrBiTo) project. Fifty eight active pharmaceutical ingredients (APIs) were qualified from the OrBiTo database to be part of the investigation based on a priori set criteria on availability of minimum necessary information to allow modelling exercise. The set entailed over 200 human clinical studies with over 700 study arms. These were simulated using input parameters which had been harmonised by a panel of experts across different software packages prior to conduct of any simulation. Overall prediction performance and software packages comparison were evaluated based on performance indicators (Fold error (FE), Average fold error (AFE) and absolute average fold error (AAFE)) of pharmacokinetic (PK) parameters. On average, PK parameters (Area Under the Concentration-time curve (AUC 0-tlast ), Maximal concentration (C max ), half-life (t 1/2 )) were predicted with AFE values between 1.11 and 1.97. Variability in FEs of these PK parameters was relatively high with AAFE values ranging from 2.08 to 2.74. Around half of the simulations were within the 2-fold error for AUC 0-tlast and around 90% of the simulations were within 10-fold error for AUC 0-tlast . Oral bioavailability (F oral ) predictions, which were limited to 19 APIs having intravenous (i.v.) human data, showed AFE and AAFE of values 1.37 and 1.75 respectively. Across different APIs, AFE of AUC 0-tlast predictions were between 0.22 and 22.76 with 70% of the APIs showing an AFE > 1. When compared across different formulations and routes of administration, AUC 0-tlast for oral controlled release and i.v. administration were better predicted than that for oral immediate release formulations. Average predictive performance did not clearly differ between software packages but some APIs showed a high level of variability in predictive performance across different software packages. This variability could be related to several factors such as compound specific properties, the quality and availability of information, and errors in scaling from in vitro and preclinical in vivo data to human in vivo behaviour which will be explored further. Results were compared with previous similar exercise when the input data selection was carried by the modeller rather than a panel of experts on each in vitro test. Overall, average predictive performance was increased as reflected in smaller AAFE value of 2.8 as compared to AAFE value of 3.8 in case of previous exercise., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Advances in drug research not only depend on high throughput screening to evaluate large numbers of lead compounds but also on the development of in vitro models which can simulate human tissues in terms of drug permeability and functions. Potential failures, such as poor permeability or interaction with efflux drug transporters, can be identified in epithelial Caco-2 monolayer models and can impact a drug candidate's progression onto the next stages of the drug development process. Whilst monolayer models demonstrate reasonably good prediction of in vivo permeability for some compounds, more developed in vitro tools are needed to assess new entities that enable closer in vivo in vitro correlation. In this study, an in vitro model of the human intestinal epithelium was developed by utilizing nanofibers, fabricated using electrospinning, to mimic the structure of the basement membrane. We assessed Caco-2 cell response to these materials and investigated the physiological properties of these cells cultured on the fibrous supports, focusing on barrier integrity and drug-permeability properties. The obtained data illustrate that 2D Caco-2 Transwell ® cultures exhibit artificially high trans-epithelial electrical resistance (TEER) compared to cells cultured on the 3D nanofibrous scaffolds which show TEER values similar to ex vivo porcine tissue (also measured in this study). Furthermore, our results demonstrate that the 3D nanofibrous scaffolds influence the barrier integrity of the Caco-2 monolayer to confer drug-absorption properties that more closely mimic native gut tissue particularly for studying passive epithelial transport. We propose that this 3D model is a suitable in vitro model for investigating drug absorption and intestinal metabolism.

The purpose of this study was to evaluate the usefulness of the in vitro biorelevant gastrointestinal transfer (BioGIT) system in assessing the impact of dose and formulation on early exposure by comparing in vitro data with previously collected human plasma data of low solubility active pharmaceutical ingredients. Eight model active pharmaceutical ingredients were tested; Lu 35-138C (salt of weak base in a HP-beta-CD solution, three doses), fenofibrate (solid dispersion, tablet, two doses), AZD2207 EQ (salt of weak base, capsule, three doses), posaconazole (Noxafil® suspension, two doses), SB705498 (weak base, tablets vs. capsules), cyclosporine A (Sandimmun® vs. Sandimmun® Neoral), nifedipine (Adalat® capsule vs. Macorel® tablet), and itraconazole (Sporanox® capsule vs. Sporanox® solution). AUC 0-0.75h values were calculated from the apparent concentration versus time data in the duodenal compartment of the BioGIT system. Differences in AUC 0-0.75h values were evaluated versus differences in AUC 0-1h and in AUC 0-2h values calculated from previously collected plasma data in healthy adults. Ratios of mean AUC 0-0.75h , mean AUC 0-1h , and mean AUC 0-2h values were estimated using the lowest dose or the formulation with the lower AUC 0-0.75h value as denominator. The BioGIT system qualitatively identified the impact of dose and of formulation on early exposure in all cases. Log-transformed mean BioGIT AUC 0-0.75h ratios correlated significantly with log-transformed mean plasma AUC 0-1h ratios. Based on this correlation, BioGIT AUC 0-0.75h ratios between 0.3 and 10 directly reflect corresponding plasma AUC 0-1h ratios. BioGIT system is a valuable tool for the assessment of the impact of dose and formulation on early exposure to low solubility drugs.

There is a renewed interest from the pharmaceutical field to develop oral formulations of compounds, such as peptides, oligonucleotides, and polar drugs. However, these often suffer from insufficient absorption across the intestinal mucosal barrier. One approach to circumvent this problem is the use of absorption modifying excipient(s) (AME). This study determined the absorption enhancing effect of four AMEs (sodium dodecyl sulfate, caprate, chitosan, N-acetylcysteine) on five model compounds in a rat jejunal perfusion model. The aim was to correlate the model compound absorption to the blood-to-lumen clearance of the mucosal marker for barrier integrity, 51 Cr-EDTA. Sodium dodecyl sulfate and chitosan increased the absorption of the low permeation compounds but had no effect on the high permeation compound, ketoprofen. Caprate and N-acetylcysteine did not affect the absorption of any of the model compounds. The increase in absorption of the model compounds was highly correlated to an increased blood-to-lumen clearance of 51 Cr-EDTA, independent of the AME. Thus, 51 Cr-EDTA could be used as a general, sensitive, and validated marker molecule for absorption enhancement when developing novel formulations.

Currently, the screening of new drug candidates for intestinal permeation is typically based on in vitro models which give no information regarding regional differences along the gut. When evaluation of intestinal permeability by region is undertaken, two preclinical rat models are commonly used, the Ussing chamber method and single-pass intestinal perfusion (SPIP). To investigate the robustness of in vivo predictions of human intestinal permeability, a set of four model compounds was systematically investigated in both these models, using tissue specimens and segments from the jejunum, ileum, and colon of rats from the same genetic strain. The influence of luminal pH was also determined at two pH levels. Ketoprofen had high and enalaprilat had low effective (P eff ) and apparent (P app ) permeability in all three regions and at both pH levels. Metoprolol had high P eff in all regions and at both pHs and high P app at both pHs and in all regions except the jejunum, where P app was low. Atenolol had low P eff in all regions and at both pHs, but had high P app at pH 6.5 and low P app at pH 7.4. There were good correlations between these rat in situ P eff (SPIP) and human in vivo P eff determined previously for the same compounds by both intestinal perfusion of the jejunum and regional intestinal dosing. The results of this study indicate that both investigated models are suitable for determining the regional permeability of the intestine; however, the SPIP model seems to be the more robust and accurate regional permeability model.

Over recent decades there has been an increase in the proportion of BCS class II and IV drug candidates in industrial drug development. To overcome the biopharmaceutical challenges associated with the less favorable properties of solubility and/or intestinal permeation of these substances, the development of formulations containing nanosuspensions of the drugs has been suggested. The intestinal absorption of aprepitant from two nanosuspensions (20 μM and 200 μM total concentrations) in phosphate buffer, one nanosuspension (200 μM) in fasted-state simulated intestinal fluid (FaSSIF), and one solution (20 μM) in FaSSIF was investigated in the rat single-pass intestinal perfusion model. The disappearance flux from the lumen (J disapp ) was faster for formulations containing a total concentration of aprepitant of 200 μM than for those containing 20 μM, but was unaffected by the presence of vesicles. The flux into the systemic circulation (J app ) and, subsequently, the effective diffusion constant (D eff ) were calculated using the plasma concentrations. J app was, like J disapp , faster for the formulations containing higher total concentrations of aprepitant, but was also faster for those containing vesicles (ratios of 2 and 1.5). This suggests that aprepitant is retained in the lumen when presented as nanoparticles in the absence of vesicles. In conclusion, increased numbers of nanoparticles and the presence of vesicles increased the rate of transport and availability of aprepitant in plasma. This effect can be attributed to an increased rate of mass transport through the aqueous boundary layer (ABL) adjacent to the gut wall.

The Ussing chamber is an old but still powerful technique originally designed to study the vectorial transport of ions through frog skin. This technique is also used to investigate the transport of chemical agents through the intestinal barrier as well as drug metabolism in enterocytes, both of which are key determinants for the bioavailability of orally administered drugs. More contemporary model systems, such as Caco-2 cell monolayers or stably transfected cells, are more limited in their use compared to the Ussing chamber because of differences in expression rates of transporter proteins and/or metabolizing enzymes. While there are limitations to the Ussing chamber assay, the use of human intestinal tissue remains the best laboratory test for characterizing the transport and metabolism of compounds following oral administration. Detailed in this unit is a step-by-step protocol for preparing human intestinal tissue, for designing Ussing chamber experiments, and for analyzing and interpreting the findings. © 2017 by John Wiley & Sons, Inc., (Copyright © 2017 John Wiley & Sons, Inc.)

This is a reply to the comment on "In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models" by Turner and other Simcyp associates. In the reply we address the major concerns raised by Turner et al. regarding the methodology to compare the predictive performance of the different absorption models and at the same time ensure that the systemic pharmacokinetic input was exactly the same for the different models; the selection of the human effective permeability value of fexofenadine; the adoption of model default values and settings; and how supersaturation/precipitation was handled. In addition, we also further discuss aspects related to differences in in silico models and the potential implications of such differences. Our original report should be viewed as the starting point in a thorough and transparent review of absorption prediction models with the overall aim of improving their application as validated tools for bridging studies of active pharmaceutical ingredients from various sources and origins in a regulatory context. With this reply we encourage other independent investigators to perform further model evaluations of commercial as well as other existing or recently implemented models. This will boost the overall progression of physiologically based biopharmaceutical models for predicting and simulating intestinal drug absorption both in research and development and in a regulatory context.

Orally administered drugs are subject to a number of barriers impacting bioavailability (F oral ), causing challenges during drug and formulation development. Physiologically-based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI-Sim, Simcyp®, and GastroPlus™) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm-institution-software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two-fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, F oral and relative AUC (F rel ) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large-scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7-fold differences in AFE between SimCYP and GI-Sim, however average performance was relatively consistent across the three software platforms., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp® Simulator, and GastroPlus™) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded "bottom-up" anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (F oral ) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. F oral was also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. F oral was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water-soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug-specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data "as is" in this blinded bottom-up prediction approach., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Predicting oral bioavailability (F oral ) is of importance for estimating systemic exposure of orally administered drugs. Physiologically-based pharmacokinetic (PBPK) modelling and simulation have been applied extensively in biopharmaceutics recently. The Oral Biopharmaceutical Tools (OrBiTo) project (Innovative Medicines Initiative) aims to develop and improve upon biopharmaceutical tools, including PBPK absorption models. A large-scale evaluation of PBPK models may be considered the first step. Here we characterise the OrBiTo active pharmaceutical ingredient (API) database for use in a large-scale simulation study. The OrBiTo database comprised 83 APIs and 1475 study arms. The database displayed a median logP of 3.60 (2.40-4.58), human blood-to-plasma ratio of 0.62 (0.57-0.71), and fraction unbound in plasma of 0.05 (0.01-0.17). The database mainly consisted of basic compounds (48.19%) and Biopharmaceutics Classification System class II compounds (55.81%). Median human intravenous clearance was 16.9L/h (interquartile range: 11.6-43.6L/h; n=23), volume of distribution was 80.8L (54.5-239L; n=23). The majority of oral formulations were immediate release (IR: 87.6%). Human F oral displayed a median of 0.415 (0.203-0.724; n=22) for IR formulations. The OrBiTo database was found to be largely representative of previously published datasets. 43 of the APIs were found to satisfy the minimum inclusion criteria for the simulation exercise, and many of these have significant gaps of other key parameters, which could potentially impact the interpretability of the simulation outcome. However, the OrBiTo simulation exercise represents a unique opportunity to perform a large-scale evaluation of the PBPK approach to predicting oral biopharmaceutics., (Copyright © 2016 Elsevier B.V. All rights reserved.)

AZD1175 and AZD2207 are 2 highly lipophilic compounds with a significant risk of not achieving therapeutic plasma concentrations due to solubility-limited absorption. The compounds have the same molecular weight and minimal structural differences. The aim of the present work was to investigate whether salts could be applied to improve the intestinal absorption, and the subsequent in vivo exposure. Drug solubilities, dissolution rates, and degree of supersaturation and precipitation were determined in biorelevant media. Dog studies were performed, in the absence and presence of a precipitation inhibitor (hydroxypropyl methylcellulose). Finally, a human phase I study was performed. For AZD1175, there was a good agreement between dissolution rates, in vivo exposure in dog, and the obtained exposure in human with the selected hemi-1,5-naphthalenedisulfonate of the compound. For AZD2207, the picture was more complex. The same counter ion was selected for the study in man. In addition, the chloride salt of AZD2207 showed promising data in the presence of a precipitation inhibitor in vitro and in dog that, however, could not be repeated in man. The differences in observations between the 2 compounds could be attributed to the difference in solubility and to the degree of supersaturation in the gastric environment rather than in the intestine., (Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.)

The development of oral modified-release (MR) dosage forms requires an active pharmaceutical ingredient (API) with a sufficiently high absorption rate in both the small and large intestine. Dogs are commonly used in preclinical evaluation of regional intestinal absorption and in the development of novel MR dosage forms. This study determined regional intestinal effective permeability (Peff) in dogs with the aim to improve regional Peff prediction in humans. Four model drugs, atenolol, enalaprilat, metoprolol, and ketoprofen, were intravenously and regionally dosed twice as a solution into the proximal small intestine (P-SI) and large intestine (LI) of three dogs with intestinal stomas. Based on plasma data from two separate study occasions for each dog, regional Peff values were calculated using a validated intestinal deconvolution method. The determined mean Peff values were 0.62, 0.14, 1.06, and 3.66 × 10(-4) cm/s in the P-SI, and 0.13, 0.02, 1.03, and 2.20 × 10(-4) cm/s in the LI, for atenolol, enalaprilat, metoprolol, and ketoprofen, respectively. The determined P-SI Peff values in dog were highly correlated (R(2) = 0.98) to the historically directly determined human jejunal Peff after a single-pass perfusion. The determined dog P-SI Peff values were also successfully implemented in GI-Sim to predict the risk for overestimation of LI absorption of low permeability drugs. We conclude that the dog intestinal stoma model is a useful preclinical tool for determination of regional intestinal permeability. Still, further studies are recommended to evaluate additional APIs, sources of variability, and formulation types, for more accurate determination of the dog model in the drug development process.

Currently there are only a limited number of determinations of human Peff in the distal small intestine and none in the large intestine. This has hindered the validation of preclinical models with regard to absorption in the distal parts of the intestinal tract, which can be substantial for BCS class II-IV drugs, and drugs formulated into modified-release (MR) dosage forms. To meet this demand, three model drugs (atenolol, metoprolol, and ketoprofen) were dosed in solution intravenously, and into the jejunum, ileum, and colon of 14 healthy volunteers. The Peff of each model drug was then calculated using a validated deconvolution method. The median Peff of atenolol in the jejunum, ileum, and colon was 0.45, 0.15, and 0.013 × 10(-4) cm/s, respectively. The corresponding values for metoprolol were 1.72, 0.72, and 1.30 × 10(-4) cm/s, and for ketoprofen 8.85, 6.53, and 3.37 × 10(-4) cm/s, respectively. This is the first study where the human Peff of model drugs has been determined in all parts of the human intestinal tract in the same subjects. The jejunal values were similar to directly determined values using intestinal single-pass perfusion, indicating that the deconvolution method is a valid approach for determining regional Peff. The values from this study will be highly useful in the validation of preclinical regional absorption models and in silico tools.

Gastrointestinal (GI) drug absorption is a complex process determined by formulation, physicochemical and biopharmaceutical factors, and GI physiology. Physiologically based in silico absorption models have emerged as a widely used and promising supplement to traditional in vitro assays and preclinical in vivo studies. However, there remains a lack of comparative studies between different models. The aim of this study was to explore the strengths and limitations of the in silico absorption models Simcyp 13.1, GastroPlus 8.0, and GI-Sim 4.1, with respect to their performance in predicting human intestinal drug absorption. This was achieved by adopting an a priori modeling approach and using well-defined input data for 12 drugs associated with incomplete GI absorption and related challenges in predicting the extent of absorption. This approach better mimics the real situation during formulation development where predictive in silico models would be beneficial. Plasma concentration-time profiles for 44 oral drug administrations were calculated by convolution of model-predicted absorption-time profiles and reported pharmacokinetic parameters. Model performance was evaluated by comparing the predicted plasma concentration-time profiles, Cmax, tmax, and exposure (AUC) with observations from clinical studies. The overall prediction accuracies for AUC, given as the absolute average fold error (AAFE) values, were 2.2, 1.6, and 1.3 for Simcyp, GastroPlus, and GI-Sim, respectively. The corresponding AAFE values for Cmax were 2.2, 1.6, and 1.3, respectively, and those for tmax were 1.7, 1.5, and 1.4, respectively. Simcyp was associated with underprediction of AUC and Cmax; the accuracy decreased with decreasing predicted fabs. A tendency for underprediction was also observed for GastroPlus, but there was no correlation with predicted fabs. There were no obvious trends for over- or underprediction for GI-Sim. The models performed similarly in capturing dependencies on dose and particle size. In conclusion, it was shown that all three software packages are useful to guide formulation development. However, as a consequence of the high fraction of inaccurate predictions (prediction error >2-fold) and the clear trend toward decreased accuracy with decreased predicted fabs observed with Simcyp, the results indicate that GI-Sim and GastroPlus perform better than Simcyp in predicting the intestinal absorption of the incompletely absorbed drugs when a higher degree of accuracy is needed. In addition, this study suggests that modeling and simulation research groups should perform systematic model evaluations using their own input data to maximize confidence in model performance and output.

The objective of this study was to develop and evaluate an in vitro method to investigate bacterial-mediated luminal degradation of drugs in colon in humans. This would be a valuable tool for the assessment of drug candidates during early drug development, especially for compounds intended to be developed as oral extended release formulations. Freshly prepared faecal homogenate from healthy human volunteers (n=3-18), dog (n=6) and rat (colon and caecal content, n=3) was homogenised with 3.8 parts (w/w) physiological saline under anaerobical conditions. Four model compounds (almokalant, budesonide, ximelagatran and metoprolol) were then incubated (n=3-18) separately in the human faecal homogenate for up to 120min at 37°C. In addition, ximelagatran was also incubated in the faecal or colonic content from dog and rat. The mean (±SD) in vitro half-life for almokalant, budesonide and ximelagatran was 39±1, 68±21 and 26±12min, respectively, in the human faecal homogenate. Metoprolol was found to be stable in the in vitro model. The in vitro degradation data was then compared to literature data on fraction absorbed after direct colon administration in humans. The percentage of drug remaining after 60min of in vitro incubation correlated (R(2)=0.90) with the fraction absorbed from colon in humans. The mean in vitro half-life of ximelagatran was similar in human faeces (26±12min) and rat colon content (34±31min), but significantly (p<0.05) longer in rat caecum content (50±11min) and dog faeces (126±17min). The in vitro method is in vivo relevant both qualitatively as all the model drugs that undergoes colonic degradation in vivo was rapidly degraded in the faecal homogenates as well as quantitatively since a correlation was established between percentage degraded in vitro at 60min and fraction absorbed in the colon for the model drugs, which have no other absorption limiting properties. Also, the method is easy to use from a technical point of view, which suggests that the method is suitable for use in early assessment of colonic absorption of extended release formulation candidates. Further improvement of the confidence in the use of the method would either require an extension of the correlation, which most likely will require more human regional absorption studies, or by including colonic degradation rate as an input in a physiological mechanistic absorption model and evaluate if the prediction of the plasma exposure after colonic administration of the present model drugs is improved., (Copyright © 2013 Elsevier B.V. All rights reserved.)

This review summarizes the current knowledge on anatomy and physiology of the human gastrointestinal tract in comparison with that of common laboratory animals (dog, pig, rat and mouse) with emphasis on in vivo methods for testing and prediction of oral dosage form performance. A wide range of factors and methods are considered in addition, such as imaging methods, perfusion models, models for predicting segmental/regional absorption, in vitro in vivo correlations as well as models to investigate the effects of excipients and the role of food on drug absorption. One goal of the authors was to clearly identify the gaps in today's knowledge in order to stimulate further work on refining the existing in vivo models and demonstrate their usefulness in drug formulation and product performance testing., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Drug absorption from the gastrointestinal (GI) tract is a highly complex process dependent upon numerous factors including the physicochemical properties of the drug, characteristics of the formulation and interplay with the underlying physiological properties of the GI tract. The ability to accurately predict oral drug absorption during drug product development is becoming more relevant given the current challenges facing the pharmaceutical industry. Physiologically-based pharmacokinetic (PBPK) modeling provides an approach that enables the plasma concentration-time profiles to be predicted from preclinical in vitro and in vivo data and can thus provide a valuable resource to support decisions at various stages of the drug development process. Whilst there have been quite a few successes with PBPK models identifying key issues in the development of new drugs in vivo, there are still many aspects that need to be addressed in order to maximize the utility of the PBPK models to predict drug absorption, including improving our understanding of conditions in the lower small intestine and colon, taking the influence of disease on GI physiology into account and further exploring the reasons behind population variability. Importantly, there is also a need to create more appropriate in vitro models for testing dosage form performance and to streamline data input from these into the PBPK models. As part of the Oral Biopharmaceutical Tools (OrBiTo) project, this review provides a summary of the current status of PBPK models available. The current challenges in PBPK set-ups for oral drug absorption including the composition of GI luminal contents, transit and hydrodynamics, permeability and intestinal wall metabolism are discussed in detail. Further, the challenges regarding the appropriate integration of results from in vitro models, such as consideration of appropriate integration/estimation of solubility and the complexity of the in vitro release and precipitation data, are also highlighted as important steps to advancing the application of PBPK models in drug development. It is expected that the "innovative" integration of in vitro data from more appropriate in vitro models and the enhancement of the GI physiology component of PBPK models, arising from the OrBiTo project, will lead to a significant enhancement in the ability of PBPK models to successfully predict oral drug absorption and advance their role in preclinical and clinical development, as well as for regulatory applications., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Oral drug delivery is the predominant administration route for a major part of the pharmaceutical products used worldwide. Further understanding and improvement of gastrointestinal drug absorption predictions is currently a highly prioritized area of research within the pharmaceutical industry. The fraction absorbed (fabs) of an oral dose after administration of a solid dosage form is a key parameter in the estimation of the in vivo performance of an orally administrated drug formulation. This study discloses an evaluation of the predictive performance of the mechanistic physiologically based absorption model GI-Sim. GI-Sim deploys a compartmental gastrointestinal absorption and transit model as well as algorithms describing permeability, dissolution rate, salt effects, partitioning into micelles, particle and micelle drifting in the aqueous boundary layer, particle growth and amorphous or crystalline precipitation. Twelve APIs with reported or expected absorption limitations in humans, due to permeability, dissolution and/or solubility, were investigated. Predictions of the intestinal absorption for different doses and formulations were performed based on physicochemical and biopharmaceutical properties, such as solubility in buffer and simulated intestinal fluid, molecular weight, pK(a), diffusivity and molecule density, measured or estimated human effective permeability and particle size distribution. The performance of GI-Sim was evaluated by comparing predicted plasma concentration-time profiles along with oral pharmacokinetic parameters originating from clinical studies in healthy individuals. The capability of GI-Sim to correctly predict impact of dose and particle size as well as the in vivo performance of nanoformulations was also investigated. The overall predictive performance of GI-Sim was good as >95% of the predicted pharmacokinetic parameters (C(max) and AUC) were within a 2-fold deviation from the clinical observations and the predicted plasma AUC was within one standard deviation of the observed mean plasma AUC in 74% of the simulations. GI-Sim was also able to correctly capture the trends in dose- and particle size dependent absorption for the study drugs with solubility and dissolution limited absorption, respectively. In addition, GI-Sim was also shown to be able to predict the increase in absorption and plasma exposure achieved with nanoformulations. Based on the results, the performance of GI-Sim was shown to be suitable for early risk assessment as well as to guide decision making in pharmaceutical formulation development., (Copyright © 2013 Elsevier B.V. All rights reserved.)

The purpose of this study was to evaluate the use of human intestinal tissue in Ussing chamber to predict oral and colonic drug absorption and intestinal metabolism. Data on viability, correlation between apparent permeability coefficients (P(app)) and fraction absorbed (f(a)) after oral and colonic administration, regional permeability, active uptake and efflux of drugs as well as intestinal metabolism were compiled from experiments using 159 human donors. Permeability coefficients for up to 28 drugs were determined using one or several of four intestinal regions: duodenum, jejunum, ileum and colon and 10 drugs were studied bidirectionally. Viability was monitored simultaneously with transport experiments by recording potential difference (PD), short-circuit current (SCC) and the resistance (TER). Intestinal metabolism was studied using testosterone and midazolam as probe substrates. There was a steep sigmoidal correlation between P(app) in the Ussing chamber, using jejunal segments, and oral f(a) in humans, for a set of 25 drugs (R(2): 0.85, p<0.01). A clear sigmoidal relationship was also obtained between P(app) in colonic segments and f(a) after colonic administration in humans for a set of 10 drugs (R(2): 0.93, p<0.05). Regional permeability data showed a tendency for highly permeable compounds to have higher or similar P(app) in colon as in the small intestinal segments, while the colonic regions showed a lower P(app) for more polar compounds as well as for d-glucose and l-leucine. Bidirectional transport (mucosa to serosa and serosa to mucosa direction) in jejunum showed well functioning efflux- and uptake asymmetry. Intestinal metabolic extraction during transport across jejunum segments was found for both testosterone and midazolam. In conclusion, viable excised human intestine mounted in the Ussing chamber, is a powerful technique for predicting regional fraction absorbed (f(a)), transporter-mediated uptake or efflux as well as intestinal metabolism of drug candidates in man. Furthermore, a sigmoidal relationship of P(app) vs. f(a) was obtained when permeability data from the present study were merged with data from 2 other independent laboratories (R(2): 0.83, p<0.01). The correlation curve reported can be used by any laboratory for predictions of human permeability and f(a)(.) In addition, for the first time a correlation curve between colonic P(app) and human colonic f(a) is reported, which demonstrates the usefulness of this methodology in early assessment of the colonic absorption potential of extended release formulation candidates., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The purpose of this study was to increase the understanding of in vivo colonic drug absorption in humans by summarizing and evaluating all regional in vivo human absorption data with focus on the interpretation of the colonic absorption data in relation to intestinal permeability and solubility. In addition, the usefulness of the Biopharmaceutics Classification System (BCS) in early assessment of the in vivo colonic absorption potential of controlled release drug candidates was investigated. Clinical regional absorption data (Cmax, Tmax, and AUC) of 42 drugs were collected from journal articles, abstracts, and internal reports, and the relative bioavailability in the colon (Frel(colon)) was obtained directly or calculated. Bioavailability, fraction dose absorbed, and information if the compounds were substrates for P-glycoprotein (P-gp) or cytochrome P450 3A (CYP3A) were also obtained. The BCS I drugs were well absorbed in the colon (Frel(colon) > 70%), although some drugs had lower values due to bacterial degradation in the colon. The low permeability drugs (BCS III/IV) had a lower degree of absorption in the colon (Frel(colon) < 50%). There was a clear correlation between in vitro Caco-2 permeability and Frel(colon), and atenolol and metoprolol may function as permeability markers for low and high colonic absorption, respectively. No obvious effect of P-gp on the colonic absorption of the drugs in this study was detected. There was insufficient data available to fully assess the impact of low solubility and slow dissolution rate. The estimated in vivo fractions dissolved of the only two compounds administered to the colon as both a solution and as solid particles were 55% and 92%, respectively. In conclusion, permeability and solubility are important barriers to colonic absorption in humans, and in vitro testing of these properties is recommended in early assessment of colonic absorption potential.

Several transporter systems in the liver and intestine are known to change their expression and function during cholestatic disease states. The objective of the present in vivo study was to investigate the effect of biliary depletion, as a method to mimic cholestasis, on the bioavailability and disposition of digoxin in biliary and pancreatic duct cannulated pigs. The study was divided in two parts. In the first part, a solution of 10 microg/kg digoxin was administered intravenously to the cannulated pigs with intact enterohepatic circulation (Control) and during depletion of the bile and pancreatic juice. In the second part, the same dose of digoxin was administered intraduodenally with intact enterohepatic circulation (Control) and during depletion of either bile or pancreatic juice or both. Biliary depletion decreased the flow of bile and pancreas juice as well as the amount of digoxin appearing in the bile. Deprivation of both bile and pancreas juice significantly increased the bioavailability of digoxin, the plasma AUC after enteral administration increased from 17.6+/-4.2 nmol/lh (Control) to 29.6+/-8.3 nmol/lh (P<0.05). The biliary clearance decreased significantly, from 0.22+/-0.11 l/h/kg (Control) to 0.04+/-0.03 l/h/kg during pancreatic and biliary depletion (P<0.05). There was a significant decrease in elimination half-life (P<0.05) and volume of distribution (P<0.01) during the depletion experiments while the systemic clearance remained unchanged. The results clearly suggest that biliary depletion trigger a short-term downregulation, most likely posttranscriptionally mediated, of a sinusoidal uptake transporter in the liver, possibly a pig ortholog of OATP.