The application of physiologically based pharmacokinetic (PBPK) modeling has developed rapidly within the pharmaceutical industry and is becoming an integral part of drug discovery and development. In this study, we provide a cross pharmaceutical industry position on "how PBPK modeling can be applied in industry" focusing on the strategies for application of PBPK at different stages, an associated perspective on the confidence and challenges, as well as guidance on interacting with regulatory agencies and internal best practices.

Based on the dataset evaluated in this study, PBPK gave reasonable predictions of human pharmacokinetics using preclinical data and is the recommended approach in the majority of cases. In addition, PBPK modelling is a useful tool to gain insights into the properties of a compound. Thus, PBPK can guide experimental efforts to obtain the relevant information necessary to understand the compound's properties before entry into human, ultimately resulting in a higher level of prediction accuracy.

ABSTRACT:With efforts to reduce cytochrome P450-mediated clearance (CL) during the early stages of drug discovery, transporter-mediated CL mechanisms are becoming more prevalent. However, the prediction of plasma concentration-time profiles for such compounds using physiologically based pharmacokinetic (PBPK) modeling is far less established in comparison with that for compounds with passively mediated pharmacokinetics (PK). In this study, we have assessed the predictability of human PK for seven organic aniontransporting polypeptide (OATP) substrates (pravastatin, cerivastatin, bosentan, fluvastatin, rosuvastatin, valsartan, and repaglinide) for which clinical intravenous data were available. In vitro data generated from the sandwich culture human hepatocyte system were simultaneously fit to estimate parameters describing both uptake and biliary efflux. Use of scaled active uptake, passive distribution, and biliary efflux parameters as inputs into a PBPK model resulted in the overprediction of exposure for all seven drugs investigated, with the exception of pravastatin. Therefore, fitting of in vivo data for each individual drug in the dataset was performed to establish empirical scaling factors to accurately capture their plasma concentration-time profiles. Overall, active uptake and biliary efflux were under-and overpredicted, leading to average empirical scaling factors of 58 and 0.061, respectively; passive diffusion required no scaling factor. This study illustrates the mechanistic and model-driven application of in vitro uptake and efflux data for human PK prediction for OATP substrates. A particular advantage is the ability to capture the multiphasic plasma concentration-time profiles for such compounds using only preclinical data. A prediction strategy for novel OATP substrates is discussed.

Quantitative prediction of human pharmacokinetics is critical in assessing the viability of drug candidates and in determining first-in-human dosing. Numerous prediction methodologies, incorporating both in vitro and preclinical in vivo data, have been developed in recent years, each with advantages and disadvantages. However, the lack of a comprehensive data set, both preclinical and clinical, has limited efforts to evaluate the optimal strategy (or strategies) that results in quantitative predictions of human pharmacokinetics. To address this issue, the authors conducted a retrospective analysis using 50 proprietary compounds for which in vitro, preclinical pharmacokinetic data and oral single-dose human pharmacokinetic data were available. Five predictive strategies, involving either allometry or use of unbound intrinsic clearance from microsomes or hepatocytes, were then compared for their ability to predict human oral clearance, half-life through predictions of systemic clearance, volume of distribution, and bioavailability. Use of a single-species scaling approach with rat, dog, or monkey was as accurate as or more accurate than using multiple-species allometry. For those compounds cleared almost exclusively by P450-mediated pathways, scaling from human liver microsomes was as predictive as single-species scaling of clearance based on data from rat, dog, or monkey. These data suggest that use of predictive methods involving either single-species in vivo data or in vitro human liver microsomes can quantitatively predict human in vivo pharmacokinetics and suggest the possibility of streamlining the predictive methodology through use of a single species or use only of human in vitro microsomal preparations.

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The posttranslational modification of chromatin through acetylation at selected histone lysine residues is governed by histone acetyltransferases (HATs) and histone deacetylases (HDACs). The significance of this subset of the epigenetic code is interrogated and interpreted by an acetyllysine-specific protein–protein interaction with bromodomain reader modules. Selective inhibition of the bromo and extra C-terminal domain (BET) family of bromodomains with a small molecule is feasible, and this may represent an opportunity for disease intervention through the recently disclosed antiproliferative and anti-inflammatory properties of such inhibitors. Herein, we describe the discovery and structure–activity relationship (SAR) of a novel, small-molecule chemical probe for BET family inhibition that was identified through the application of structure-based fragment assessment and optimization techniques. This has yielded a potent, selective compound with cell-based activity (PFI-1) that may further add to the understanding of BET family function within the bromodomains.

ABSTRACT:The substrate depletion method is a popular approach used for the measurement of in vitro intrinsic clearance (CL int ). However, the incubation conditions used in these studies can vary, the consequences of which have not been systematically explored. Initial substrate depletion incubations using rat microsomes and hepatocytes were performed for eight benzodiazepines: alprazolam, clobazam, clonazepam, chlordiazepoxide, diazepam, flunitrazepam, midazolam, and triazolam. Subsequent predictions of in vivo CL int (ranging from 3 to 200 ml/min) and hepatic clearance (CL H ) (ranging from 0.3 to 15 ml/min) demonstrated that the general predictive ability of this approach was similar to that of the traditional metabolite formation method. A more detailed study of the substrate depletion profiles and CL int estimates indicated that the concentration of enzyme used is of particular importance.The metabolism of triazolam, clonazepam, and diazepam was monoexponential at all cell densities using hepatocytes; however, with microsomes, biphasic depletion was apparent, particularly at higher microsomal protein concentrations (2-5 mg/ml). Enzyme activity studies indicated that enzyme loss was more pronounced in the microsomal system (ranged from 8 to 65% activity after a 1-h incubation) compared with the hepatocyte system (approximately 100% activity after a 1-h incubation). For clonazepam (a low clearance substrate), these biphasic profiles could be explained by loss of enzyme activity. To ensure accurate predictions of in vivo CL int and CL H when using the substrate depletion approach, based on the results obtained for this class of drugs, it is recommended that low enzyme concentrations and short incubation times are used whenever possible.The in vitro measurement of intrinsic clearance (CL int ) using hepatic microsomes and/or hepatocytes is frequently used in both academia and the pharmaceutical industry to estimate the in vivo metabolic stability of new drug entities in both rat and human (Houston, 1994;Iwatsubo et al., 1997;Obach, 1999;McGinnity and Riley, 2001). The results of these assays are scaled and modeled, as described in eq. 1 for the well stirred liver model, to estimate in vivo hepatic clearance (CL H ).where Q H is the hepatic blood flow, SF represents the milligrams of microsomal protein or million cells per gram of liver multiplied by the grams of liver weight; f u b is the unbound fraction of drug in the blood, and f u inc is the unbound fraction in the incubation matrix.Traditionally, the metabolite formation method has been used for measurement of in vitro CL int , where the initial rate of metabolite production using hepatic microsomes or hepatocytes is measured over a range of substrate concentrations under linear conditions with respect to protein concentration/cell density and time (Madan et al., 2002;Houston et al., 2003). In general, short incubation times and low enzyme (protein) concentrations are used in these studies, since compliance with the Michaelis-Menten equation assumes less t...