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

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 Currently, only one country has a draft guidance document for PBBM, whereas other major regulatory authorities have had limited experience with the review of PBBM.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

Approaches to Account for Colon Absorption in Physiologically Based Biopharmaceutics Modeling of Extended-Release Drug Products.

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 (Frel), AUC0-t, and Cmax 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.

Physiologically based biopharmaceutics modeling of regional and colon absorption in humans.

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.

Physiologically Based Biopharmaceutics Modeling of Regional and Colon Absorption in Dogs.

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, AUC0-t, and the relative bioavailability in the colon (Frel,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 AUC0-t and Frel,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 AUC0-t and Frel,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 AUC0-t and Frel,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 AUC0-t and Frel,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.

In Vitro Biopredictive Methods: A Workshop Summary Report.

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

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 4: Prediction accuracy and software comparisons with improved data and modelling strategies.

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 (AUC0-tlast), Maximal concentration (Cmax), half-life (t1/2)) 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 AUC0-tlast and around 90% of the simulations were within 10-fold error for AUC0-tlast. Oral bioavailability (Foral) 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 AUC0-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, AUC0-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.

Nanofibrous Scaffolds Support a 3D in vitro Permeability Model of the Human Intestinal Epithelium.

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 BioGIT System: a Valuable In Vitro Tool to Assess the Impact of Dose and Formulation on Early Exposure to Low Solubility Drugs After Oral Administration.

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). AUC0-0.75h values were calculated from the apparent concentration versus time data in the duodenal compartment of the BioGIT system. Differences in AUC0-0.75h values were evaluated versus differences in AUC0-1h and in AUC0-2h values calculated from previously collected plasma data in healthy adults. Ratios of mean AUC0-0.75h, mean AUC0-1h, and mean AUC0-2h values were estimated using the lowest dose or the formulation with the lower AUC0-0.75h 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 AUC0-0.75h ratios correlated significantly with log-transformed mean plasma AUC0-1h ratios. Based on this correlation, BioGIT AUC0-0.75h ratios between 0.3 and 10 directly reflect corresponding plasma AUC0-1h ratios. BioGIT system is a valuable tool for the assessment of the impact of dose and formulation on early exposure to low solubility drugs.

Regional Intestinal Permeability in Rats: A Comparison of Methods.

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 (Peff) and apparent (Papp) permeability in all three regions and at both pH levels. Metoprolol had high Peff in all regions and at both pHs and high Papp at both pHs and in all regions except the jejunum, where Papp was low. Atenolol had low Peff in all regions and at both pHs, but had high Papp at pH 6.5 and low Papp at pH 7.4. There were good correlations between these rat in situ Peff (SPIP) and human in vivo Peff 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.

In Vivo Mechanisms of Intestinal Drug Absorption from Aprepitant Nanoformulations.

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 (Jdisapp) 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 (Japp) and, subsequently, the effective diffusion constant (Deff) were calculated using the plasma concentrations. Japp was, like Jdisapp, 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.

Preclinical Effect of Absorption Modifying Excipients on Rat Intestinal Transport of Model Compounds and the Mucosal Barrier Marker 51Cr-EDTA.

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, 51Cr-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 51Cr-EDTA, independent of the AME. Thus, 51Cr-EDTA could be used as a general, sensitive, and validated marker molecule for absorption enhancement when developing novel formulations.

The Ussing Chamber Assay to Study Drug Metabolism and Transport in the Human Intestine.

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.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2: An introduction to the simulation exercise and overview of results.

Orally administered drugs are subject to a number of barriers impacting bioavailability (Foral), 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, Foral and relative AUC (Frel) 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.

Reply to "Comment on 'In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models'".

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.

IMI - oral biopharmaceutics tools project - evaluation of bottom-up PBPK prediction success part 1: Characterisation of the OrBiTo database of compounds.

Predicting oral bioavailability (Foral) 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 Foral 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.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 3: Identifying gaps in system parameters by analysing In Silico performance across different compound classes.

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 (Foral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foral 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. Foral 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.

Biopharmaceutic Profiling of Salts to Improve Absorption of Poorly Soluble Basic Drugs.

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.

Regional Intestinal Permeability of Three Model Drugs in Human.

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.

Regional Intestinal Permeability in Dogs: Biopharmaceutical Aspects for Development of Oral Modified-Release Dosage Forms.

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.

In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models.

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.