For over 15 years, US and EU regulations ensure that medicines developed for children are explicitly authorised for such use with age-appropriate forms and formulations, implying dedicated research. To shed light on how these regulations have been adopted by pharmaceutical companies and how various aspects of paediatric oral drug formulation development are currently handled, an exploratory survey was conducted. Topics included: general company policy, regulatory aspects, dosage form selection, in-vitro, in-silico and (non-)clinical in-vivo methods, and food effects assessment. The survey results clearly underline the positive impact of the paediatric regulations and their overall uptake across the pharmaceutical industry. Even though significant improvements have been made in paediatric product development, major challenges remain. In this respect, dosage form selection faces a discrepancy between the youngest age groups (liquid products preference) and older sub-populations (adult formulation preference). Additionally, concerted research is needed in the development and validation of in-vitro tools and physiology based pharmacokinetic models tailored to the paediatric population, and in estimating the effect of non-standard and paediatric relevant foods. The current momentum in paediatric drug development and research should allow for an evolution in standardised methodology and guidance to develop paediatric formulations, which would benefit pharmaceutical industry and regulators.

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

In vivo studies have shown cyclic bile salt (BS) outputs during fasting whereas higher amounts have been observed in fed states. This leads to fluctuations of intestinal BS concentrations ([BS]) that can affect the rate and extent of absorption of lipophilic drugs in particular. However, most PBPK models use fixed values of [BS] in fasted and fed states albeit with different values in different regions of the GI tract. During fasting, there is a relationship between gallbladder volume (GBV) and the phase of the Interdigestive Migrating Motor Complex cycle (IMMCc), showing cyclic GBV changes with periodic filling and emptying. This relationship is also affected by the origin of the IMMCc (antral or duodenal). In fed states, meta-analysis indicated that GB residual volume (% of fasting maximum) was 46.4 ± 27%CV and 30.7 ± 48%CV for low- and high-fat meals, respectively. The corresponding values for the duration of the emptying phase were for low fat meals 0.72h ± 1%CV and for high fat meals 1.17h ± 37%CV. The model, the Advanced Dynamic Bile Salt Model (ADBSM), was built bottom-up and its parameters were not fitted against in vivo measurements of [BS]. It involved update of the dynamic luminal fluid volumes model based on meta-analysis of available imaging data. The ADBSM is incorporated into the Simcyp (v18r2) PBPK simulator. The model predictivity was good (within 1.25-fold error for 11/20 of the clinical studies) and was assessed against clinical studies of luminal [BS] that provide only the type of meal (i.e., low- or high-fat), the timing of the meal and/or water intake events, and the number and age range of the study participants. The model is also an important component of models capturing enterohepatic recirculation of drug and metabolite. Further work is required to validate the current model and compare to simpler models with respect to drug absorption, especially of the lipophilic compounds.

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 (R) Simulator (ver.15.0.86.0), and GastroPlus (TM) (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.

The physiological relevance of single-phase (aqueous only) and 2-phase (aqueous and organic phase) in vitro dissolution experiments was compared by mechanistic modeling. For orally dosed dipyridamole, stepwise, sequential estimation/confirmation of biopharmaceutical parameters from in vitro solubility-dissolution data was followed, before applying them within a physiologically based pharmacokinetic (PBPK) model. The PBPK model predicted clinical dipyridamole luminal and plasma concentration profiles reasonably well for a range of doses only where the precipitation rate constant was derived from the 2-phase experiment. The population model predicted a distribution of maximal precipitated fractions from 0% to 45% of the 90 mg dose (mean 7.6%). Such population information cannot be obtained directly from a few in vitro experiments; however well they may represent an “average” and several extreme subjects (those with low-high luminal fluid volumes, pH, etc.) because there is no indication of outcome likelihood. For this purpose, direct input of in vitro dissolution/precipitation profiles to a PBPK model is insufficient—mechanistic modeling is required. Biopharmaceutical in vitro-in vivo extrapolation tools can also simulate the effect of key experimental parameters (dissolution volumes, pH, paddle speed, etc.) on dissolution/precipitation behavior, thereby helping to identify critical variables, which may impact the number or design of in vitro experiments.

The aim of this study was to derive region-specific transporter expression data suitable for in vitro-to-in vivo extrapolation (IVIVE) within a physiologically based pharmacokinetic (PBPK) modeling framework. A meta-analysis was performed whereby literary sources reporting region-specific transporter expression obtained via absolute and relative quantification approaches were considered in healthy adult Caucasian individuals. Furthermore, intestinal total membrane protein yield was calculated to enable mechanistic IVIVE via absolute transporter abundances. Where required, authors were contacted for additional information. A refined database was constructed where samples were excluded based on quantification in, non-Caucasian subjects, disease tissue, subjects <18 years old, duplicated samples, non-total membrane matrix, pooled matrices, or cDNA. Demographic data were collected where available. The weighted and geometric mean, coefficient of variation, and between-study homogeneity was calculated in each of eight gut segments (duodenum, two jejunum, four ileum, and colon) for 16 transporters. Expression data were normalized to that in the proximal jejunum. From a total of 47 articles, the final database consisted of 2238 measurements for 16 transporters. The solute carrier peptide transporter 1 (PepT1) showed the highest jejunal abundance, while multidrug resistance-associated protein (MRP) 2 was the highest abundance ATP-binding cassette transporter. Transporters displaying significant region-specific expression included the ileal bile acid transporter, which showed 18-fold greater terminal ileum expression compared with the proximal jejunum, while MRP3, organic cation transporter type 1 (OCTN1), and OCT1 showed >2-fold higher expression in other regions compared with the proximal jejunum. This is the first systematic analysis incorporating absolute quantification methodology to determine region-specific intestinal transporter expression. It is expected to be beneficial for mechanistic transporter IVIVE in healthy adult Caucasians. SIGNIFICANCE STATEMENT Given the burgeoning reports of absolute transporter abundances in the human intestine, the incorporation of such information into mechanistic IVIVE-PBPK models could offer a distinct advantage in facilitating the robust assessment of the impact of gut transporters on drug disposition. The systematic and formal assessment via a literature meta-analysis described herein, enables assignment of the regional-specific expression, absolute transporter abundances, interindividual variability, and other associated scaling factors to healthy Caucasian populations within PBPK models. The resulting values are available to incorporate into PBPK models, and offer a verifiable account describing intestinal transporter expression within PBPK models for persons wishing to utilize them. Furthermore, these data facilitate the development of appropriate IVIVE scaling strategies using absolute transporter abundances.

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.

Mechanistic modeling of in vitro data generated from metabolic enzyme systems (viz., liver microsomes, hepatocytes, rCYP enzymes, etc.) facilitates in vitro-in vivo extrapolation (IVIV_E) of metabolic clearance which plays a key role in the successful prediction of clearance in vivo within physiologically-based pharmacokinetic (PBPK) modeling. A similar concept can be applied to solubility and dissolution experiments whereby mechanistic modeling can be used to estimate intrinsic parameters required for mechanistic oral absorption simulation in vivo. However, this approach has not widely been applied within an integrated workflow. We present a stepwise modeling approach where relevant biopharmaceutics parameters for ketoconazole (KTZ) are determined and/or confirmed from the modeling of in vitro experiments before being directly used within a PBPK model. Modeling was applied to various in vitro experiments, namely: (a) aqueous solubility profiles to determine intrinsic solubility, salt limiting solubility factors and to verify pKa; (b) biorelevant solubility measurements to estimate bile-micelle partition coefficients; (c) fasted state simulated gastric fluid (FaSSGF) dissolution for formulation disintegration profiling; and (d) transfer experiments to estimate supersaturation and precipitation parameters. These parameters were then used within a PBPK model to predict the dissolved and total (i.e., including the precipitated fraction) concentrations of KTZ in the duodenum of a virtual population and compared against observed clinical data. The developed model well characterized the intraluminal dissolution, supersaturation, and precipitation behavior of KTZ. The mean simulated AUC0-t of the total and dissolved concentrations of KTZ were comparable to (within 2-fold of) the corresponding observed profile. Moreover, the developed PBPK model of KTZ successfully described the impact of supersaturation and precipitation on the systemic plasma concentration profiles of KTZ for 200, 300, and 400 mg doses. These results demonstrate that IVIV_E applied to biopharmaceutical experiments can be used to understand and build confidence in the quality of the input parameters and mechanistic models used for mechanistic oral absorption simulations in vivo, thereby improving the prediction performance of PBPK models. Moreover, this approach can inform the selection and design of in vitro experiments, potentially eliminating redundant experiments and thus helping to reduce the cost and time of drug product development.

The aim of this study was to evaluate gastrointestinal (GI) dissolution, supersaturation, and precipitation of posaconazole, formulated as an acidified (pH 1.6) and neutral (pH 7.1) suspension. A physiologically based pharmacokinetic (PBPK) modeling and simulation tool was applied to simulate GI and systemic concentration-time profiles of posaconazole, which were directly compared with intraluminal and systemic data measured in humans. The Advanced Dissolution Absorption and Metabolism (ADAM) model of the Simcyp Simulator correctly simulated incomplete gastric dissolution and saturated duodenal concentrations of posaconazole in the duodenal fluids following administration of the neutral suspension. In contrast, gastric dissolution was approximately 2-fold higher after administration of the acidified suspension, which resulted in supersaturated concentrations of posaconazole upon transfer to the upper small intestine. The precipitation kinetics of posaconazole were described by two precipitation rate constants, extracted by semimechanistic modeling of a two-stage medium change in vitro dissolution test. The 2-fold difference in exposure in the duodenal compartment for the two formulations corresponded with a 2-fold difference in systemic exposure. This study demonstrated for the first time predictive in silico simulations of GI dissolution, supersaturation, and precipitation for a weakly basic compound in part informed by modeling of in vitro dissolution experiments and validated via clinical measurements in both GI fluids and plasma. Sensitivity analysis with the PBPK model indicated that the critical supersaturation ratio (CSR) and second precipitation rate constant (sPRC) are important parameters of the model. Due to the limitations of the two-stage medium change experiment the CSR was extracted directly from the clinical data. However, in vitro experiments with the BioGIT transfer system performed after completion of the in silico modeling provided an almost identical CSR to the clinical study value; this had no significant impact on the PBPK model predictions.

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.

medium was changed (pH 1.0, pH 5.5, pH 6.8) during the experiment; b) A small scale two-phase dissolution set up that contained an aqueous phase medium (with the same pH changes during the experiment as above) with an octanol phase as a separate layer1 (Fig 1.).  These two in vitro experiments were modelled mechanistically to estimate supersaturation and precipitation parameters for dipyridamole using Simcyp’s standalone in vitro modelling toolkit SIVA (Simcyp, UK).

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 16.9 L/h (interquartile range: 11.6-43.6 L/h; n = 23), volume of distribution was 80.8 L (54.5-239 L; 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. (C) 2016 Elsevier B.V. All rights reserved.

Objectives: Success of clinical trial simulations greatly depends on identifying and incorporating true anatomical and physiological covariates when generating virtual populations. Recently, the inter-correlations between CYP450 (and UGT) metabolising enzymes in human liver microsomes have been reported [1, 2]. These data enable population-based PBPK models to more realistically assign CYP/UGT abundances when generating virtual subjects using Correlated Monte Carlo sampling. This work aims at using reported data in [1, 2] to determine CYP450 enzymes covariance matrix of multivariate probability distribution function and compare the distributions against the currently generated data in Simcyp Simulator version 14. Methods: The marginal distributions of each CYP450 are assumed to be log-normal and are checked by obtaining normal plots for the log transformed abundance value. The correlation and covariance matrices for the whole dataset have been calculated using R Package (v 3.1.2). Eigenvalues of the covariance matrix have been tested for positivity and if negative eigenvalues occurred, then the nearest positive definite covariance matrix has been calculated. A new correlated sample has been obtained by calculating the Cholesky decomposition [3] of the nearest positive definite covariance matrix and this sample has been transformed into its original log-normal marginal distribution. A virtual population matching the real population demographics has been generated using the Simcyp Simulator v 14 and the results were compared with Monte Carlo sampling data. Results: Multivariate Cramer-Test shows dissimilarity between the empirical distributions of the correlated and uncorrelated samples with 95% CI critical T-statistic of 141.565 vs observed: 9269.496. Kernel density estimate visually showed the differences between the two distributions. Conclusions: Incorporation of the correlated CYP450 enzyme abundances when generating virtual subjects enables PBPK simulators to generate more realistic virtual population which can improve clinical study design and prediction of clinical outcome during drug development. Further research is needed to establish various transporters abundances inter-correlations which can have a significant impact on the drug concentration at the site of action and as a result on drug safety and efficacy. References: [1] Brahim Achour, Matthew R. Russel, Jill Barber, and Amin Rostami-Hodjegan, Simultaneous Quantification of the Abundance of Several Cytochrome P450 and Uridine 59-Diphospho-Glucuronosyltransferase Enzymes in Human Liver Microsomes Using Multiplexed Targeted Proteomics, Drug Metab Dispos 42:500?510 (2014) [2] Brahim Achour, Jill Barber, and Amin Rostami-Hodjegan, Expression of Hepatic Drug-Metabolizing Cytochrome P450 Enzymes and Their Intercorrelations: A Meta-Analysis, Drug Metab Dispos 42:1349?1356 (2014) [3] G�nther H�mmerlin, Karl-Heinz Hoffmann, Numerical Mathematics, Springer-Verlag New York Inc. (1991)

Bioequivalence testing of transdermal drug delivery systems (TDDS) has always been a subject of high concern for generic companies due to the formulation complexity and the fact that they are subtle to even minor manufacturing differences and hence should be clearly qualified in terms of quality, safety and efficacy. In recent times bioequivalence testing of transdermal patches has gained a global attention and many regulatory authorities worldwide have issued recommendations to set specific framework for demonstrating equivalence between two products. These current regulatory procedures demand a complete characterization of the generic formulation in terms of its physicochemical sameness, pharmacokinetics disposition, residual content and/or skin irritation/sensitization testing with respect to the reference formulation. This paper intends to highlight critical in vitro tests in assessing the therapeutic equivalence of products and also outlines their valuable applications in generic product success. Understanding these critical in vitro parameters can probably help to decode the complex bioequivalence outcomes, directing the generic companies to optimize the formulation design in reduced time intervals. It is difficult to summarize a common platform which covers all possible transdermal products; hence few case studies based on this approach has been presented in this review.

The topic of bioequivalence evaluation of nanoparticulate intravenous formulations is one that has been intensely debated in recent times since the release of the specific recommendations by many regulatory authorities worldwide. Product specific bioequivalence guidelines for many of the nanoparticulate systems where therapeutic molecules are directly coupled (human albumin bound paclitaxel nanosuspension), functionalized (iron- carbohydrate preparations) or entrapped/coated to a carrier (doxorubicin liposomal formulations), have been approved by the drug regulatory agencies. These current regulatory procedures include complete characterization of the generic formulation in terms of its physicochemical characteristics, pharmacokinetics disposition and/or non clinical testing with respect to the reference formulation. The concept of in vitro equivalency is emerging as a valuable tool in these guidances as generic product differing in in vitro parameters can result in a different biopharmaceutical profile with respect to pharmacokinetics and biodistribution. Furthermore, in case of systems with entrapped drug, classical pharmacokinetic parameters alone may only ensure the equivalent clearance of test and reference product from systemic circulation but may fail to detect the extent to which the nanoparticles are taken up by different target organs and, consequently, the safety and efficacy effects. Hence, additional tissue distribution study in preclinical study models has reflected in recent guidances. Understanding and interpretation of these regulatory requirements thus presents most critical component of a generic product development cycle. This article reviews these current regulatory procedures with special emphasis on in vitro population bioequivalence (POP BE) and preclinical testing of generic formulations.