Application of PBPK modeling to predict human intestinal metabolism of CYP3A substrates – An evaluation and case study using GastroPlus™

PBPK modeling: What is the role of CYP3A4 expression in the gastrointestinal tract to accurately predict first-pass metabolism?

Gastrointestinal first-pass metabolism plays an important role in bioavailability and in drug-drug interactions. Physiologically-based pharmacokinetic (PBPK) modeling is a powerful tool to integrate these processes mechanistically. However, a correct bottom-up prediction of GI first-pass metabolism is challenging and depends on various model parameters like the level of enzyme expression and the basolateral intestinal mucosa permeability (Pmucosa). This work aimed to investigate if cytochrome P450 (CYP) 3A4 expression could help predict the first-pass effect using PBPK modeling or whether additional factors like Pmucosa do play additional roles using PBPK modeling. To this end, a systematic review of the absolute CYP3A expression in the human gastrointestinal tract and liver was conducted. The resulting CYP3A4 expression profile and two previously published profiles were applied to PBPK models of seven CYP3A4 substrates (alfentanil, alprazolam, felodipine, midazolam, sildenafil, triazolam, and verapamil) built-in PK-Sim®. For each compound, it was assessed whether first-pass metabolism could be adequately predicted based on the integrated CYP3A4 expression profile alone or whether an optimization of Pmucosa was required. Evaluation criteria were the precision of the predicted interstudy bioavailabilities and area under the concentration-time curves. It was found that none of the expression profiles provided upfront an adequate description of the extent of GI metabolism and that optimization of Pmucosa as a compound-specific parameter improved the prediction of most models. Our findings indicate that a pure bottom-up prediction of gastrointestinal first-pass metabolism is currently not possible and that compound-specific features like Pmucosa must be considered as well.

Physiologically based in vitro - in vivo correlation of modified release oral formulations with non-linear intestinal absorption: A case study using mirabegron

Establishing an in vitro - in vivo correlation (IVIVC) for oral modified release (MR) formulations would make it possible to substitute an in vitro dissolution test for human bioequivalence (BE) studies when changing the formulation or manufacturing methods. However, the number of IVIVC applications and approvals are reportedly low. One of the main reasons for failure to obtain IVIVCs using conventional methodologies may be the lack of consideration of the dissolution and absorption mechanisms of drugs in the physiological environment. In particular, it is difficult to obtain IVIVC using conventional methodologies for drugs with non-linear absorption processes. Therefore, the aim of the present study was to develop a physiologically based biopharmaceutics model (PBBM) that enables Level A IVIVCs for mirabegron MR formulations with non-linear absorption characteristics. Using human pharmacokinetic (PK) data for immediate-release formulations of mirabegron, the luminal drug concentration-dependent membrane permeation coefficient was calculated through curve fitting. The membrane permeation coefficient data were then applied to the human PK data of the MR formulations to estimate the in vivo dissolution rate by curve fitting. It was assumed that in vivo dissolution could be described using a zero-order rate equation. Furthermore, a Levy plot was generated using the estimated in vivo dissolution rate and the in vitro dissolution rate obtained from the literature. Finally, the dissolution rate of the MR formulations from the Levy plot was applied to the PBBM to predict the oral PK of the mirabegron MR formulations. This PB-IVIVC approach successfully generated linear Levy plots with slopes of almost 1.0 for MR formulations with different dose strengths and dissolution rates. The Cmax values of the MR formulations were accurately predicted using this approach, whereas the prediction errors for AUC exceeded the Level A IVIVC criteria. This can be attributed to the incomplete description of colonic absorption in the current PBBM.

Quantitatively Predicting Effects of Exercise on Pharmacokinetics of Drugs Using a Physiologically Based Pharmacokinetic Model

Exercise significantly alters human physiological functions, such as increasing cardiac output and muscle blood flow and decreasing glomerular filtration rate (GFR) and liver blood flow, thereby altering the absorption, distribution, metabolism, and excretion of drugs. In this study, we aimed to establish a database of human physiological parameters during exercise and to construct equations for the relationship between changes in each physiological parameter and exercise intensity, including cardiac output, organ blood flow (e.g., muscle blood flow and kidney blood flow), oxygen uptake, plasma pH and GFR, etc. The polynomial equation P = ΣaiHRi was used for illustrating the relationship between the physiological parameters (P) and heart rate (HR), which served as an index of exercise intensity. The pharmacokinetics of midazolam, quinidine, digoxin, and lidocaine during exercise were predicted by a whole-body physiologically based pharmacokinetic (WB-PBPK) model and the developed database of physiological parameters following administration to 100 virtual subjects. The WB-PBPK model simulation results showed that most of the observed plasma drug concentrations fell within the 5th-95th percentiles of the simulations, and the estimated peak concentrations (Cmax) and area under the curve (AUC) of drugs were also within 0.5-2.0 folds of observations. Sensitivity analysis showed that exercise intensity, exercise duration, medication time, and alterations in physiological parameters significantly affected drug pharmacokinetics and the net effect depending on drug characteristics and exercise conditions. In conclusion, the pharmacokinetics of drugs during exercise could be quantitatively predicted using the developed WB-PBPK model and database of physiological parameters. SIGNIFICANCE STATEMENT: This study simulated real-time changes of human physiological parameters during exercise in the WB-PBPK model and comprehensively investigated pharmacokinetic changes during exercise following oral and intravenous administration. Furthermore, the factors affecting pharmacokinetics during exercise were also revealed.

Perfluoropolyether-Based Gut-Liver-on-a-Chip for the Evaluation of First-Pass Metabolism and Oral Bioavailability of Drugs

In the evolving field of drug discovery and development, multiorgans-on-a-chip and microphysiological systems are gaining popularity owing to their ability to emulate in vivo biological environments. Among the various gut-liver-on-a-chip systems for studying oral drug absorption, the chip developed in this study stands out with two distinct features: incorporation of perfluoropolyether (PFPE) to effectively mitigate drug sorption and a unique enterohepatic single-passage system, which simplifies the analysis of first-pass metabolism and oral bioavailability. By introducing a bolus drug injection into the liver compartment, hepatic extraction alone could be evaluated, further enhancing our estimation of intestinal availability. In a study on midazolam (MDZ), PFPE-based chips showed more than 20-times the appearance of intact MDZ in the liver compartment effluent compared to PDMS-based counterparts. Notably, saturation of hepatic metabolism at higher concentrations was confirmed by observations when the dose was reduced from 200 μM to 10 μM. This result was further emphasized when the metabolism was significantly inhibited by the coadministration of ketoconazole. Our chip, which is designed to minimize the dead volume between the gut and liver compartments, is adept at sensitively observing the saturation of metabolism and the effect of inhibitors. Using genome-edited CYP3A4/UGT1A1-expressing Caco-2 cells, the estimates for intestinal and hepatic availabilities were 0.96 and 0.82, respectively; these values are higher than the known human in vivo values. Although the metabolic activity in each compartment can be further improved, this gut-liver-on-a-chip can not only be used to evaluate oral bioavailability but also to carry out individual assessment of both intestinal and hepatic availability.

Ex vivo gut-hepato-biliary organ perfusion model to characterize oral absorption, gut-wall metabolism, pre-systemic hepatic metabolism and biliary excretion; application to midazolam

To date, characterization of the first-pass effect of orally administered drugs consisting of local intestinal absorption and metabolism, portal vein transport and hepatobiliary processes remains challenging. Aim of this study was to explore the applicability of a porcine ex-vivo perfusion model to study oral absorption, gut-hepatobiliary metabolism and biliary excretion of midazolam. Slaughterhouse procured porcine en bloc organs (n = 4), were perfused via the aorta and portal vein. After 120 min of perfusion, midazolam, atenolol, antipyrine and FD4 were dosed via the duodenum and samples were taken from the systemic- and portal vein perfusate, intestinal faecal effluent and bile to determine drug and metabolite concentrations. Stable arterial and portal vein flow was obtained and viability of the perfused organs was confirmed. After intraduodenal administration, midazolam was rapidly detected in the portal vein together with 1-OH midazolam (EG-pv of 0.16±0.1) resulting from gut wall metabolism through oxidation. In the intestinal faecal effluent, 1-OH midazolam and 1-OH midazolam glucuronide (EG-intestine 0.051±0.03) was observed resulting from local gut glucuronidation. Biliary elimination of midazolam (0.04±0.01 %) and its glucuronide (0.01±0.01 %) only minimally contributed to the enterohepatic circulation. More extensive hepatic metabolism (FH 0.35±0.07) over intestinal metabolism (FG 0.78±0.11) was shown, resulting in oral bioavailability of 0.27±0.05. Ex vivo perfusion demonstrated to be a novel approach to characterize pre-systemic extraction of midazolam by measuring intestinal as well as hepatic extraction. The model can generate valuable insights into the absorption and metabolism of new drugs.

Alternatives of Animal Models for Biomedical Research: a Comprehensive Review of Modern Approaches

Biomedical research has long relied on animal models to unravel the intricacies of human physiology and pathology. However, concerns surrounding ethics, expenses, and inherent species differences have catalyzed the exploration of alternative avenues. The contemporary alternatives to traditional animal models in biomedical research delve into three main categories of alternative approaches: in vitro models, in vertebrate models, and in silico models. This unique approach to artificial intelligence and machine learning has been a keen interest to be used in different biomedical research. The main goal of this review is to serve as a guide to researchers seeking novel avenues for their investigations and underscores the importance of considering alternative models in the pursuit of scientific knowledge and medical breakthroughs, including showcasing the broad spectrum of modern approaches that are revolutionizing biomedical research and leading the way toward a more ethical, efficient, and innovative future. Models can insight into cellular processes, developmental biology, drug interaction, assessing toxicology, and understanding molecular mechanisms.

In-depth analysis of patterns in selection of different physiologically-based pharmacokinetic modeling tools: Part II - Assessment of model reusability and comparison between open and non-open source-code software

Whilst the reproducibility of models in the area of systems biology and quantitative systems pharmacology has been the focus of attention lately, the concept of 'reusability' is not addressed. With the advent of the 'Model Master File' dominating some regulatory discussions on pharmaceutical applications of physiologically-based pharmacokinetic (PBPK) models, reusability becomes a vital aspect of confidence in their use. Herein, we define 'reusability' specifically in the context of PBPK models and investigate the influence of open versus non-open source-code (NOSC) nature of the software on the extent of 'reusability'. Original articles (n = 145) that were associated with the development of novel PBPK models were identified as source models and citations to these reports, which involved further PBPK model development, were explored (n > 1800) for reuse cases of the source PBPK model whether in full or partial form. The nature of source-code was a major determinant of external reusability for PBPK models (>50% of the NOSC models as opposed <25% of open source-code [OSC]). Full reusability of the models was not common and mostly involved internal reuse of the OSC model (by the group who had previously developed the original model). The results were stratified by the software utilised (various), organisations involved (academia, industry, regulatory), and type of reusability (full vs. partial). The clear link between external reuse of models and NOSC PBPK software might stem from many elements related to quality and trust that require further investigation, and challenges the unfounded notion that OSC models are associated with higher uptake for reuse.

A Physiologically Based Pharmacokinetic and Pharmacodynamic Model of the CYP3A4 Substrate Felodipine for Drug-Drug Interaction Modeling

The antihypertensive felodipine is a calcium channel blocker of the dihydropyridine type, and its pharmacodynamic effect directly correlates with its plasma concentration. As a sensitive substrate of cytochrome P450 (CYP) 3A4 with high first-pass metabolism, felodipine shows low oral bioavailability and is susceptible to drug–drug interactions (DDIs) with CYP3A4 perpetrators. This study aimed to develop a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) parent–metabolite model of felodipine and its metabolite dehydrofelodipine for DDI predictions. The model was developed in PK-Sim^® and MoBi^® using 49 clinical studies (94 plasma concentration–time profiles in total) that investigated different doses (1–40 mg) of the intravenous and oral administration of felodipine. The final model describes the metabolism of felodipine to dehydrofelodipine by CYP3A4, sufficiently capturing the first-pass metabolism and the subsequent metabolism of dehydrofelodipine by CYP3A4. Diastolic blood pressure and heart rate PD models were included, using an E_max function to describe the felodipine concentration–effect relationship. The model was tested in DDI predictions with itraconazole, erythromycin, carbamazepine, and phenytoin as CYP3A4 perpetrators, with all predicted DDI AUC_last and C_max ratios within two-fold of the observed values. The model will be freely available in the Open Systems Pharmacology model repository and can be applied in DDI predictions as a CYP3A4 victim drug.

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

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

Administration in fed state but not controlled release in the colon increases oral bioavailability of DF030263, a promising drug candidate for chronic lymphocytic leukemia

For treatment of chronic cancers, the oral administration route is preferred as it provides numerous advantages over other delivery routes. However, these benefits of oral chemotherapy can be limited due to unfavorable pharmacokinetics. Accordingly, pharmacokinetic development of chemotherapeutic agents is crucial to the improvement of cancer treatment. In this study, assessment and optimization of biopharmaceutical properties of a promising drug candidate for cyclin-dependent kinase 9 (CDK9) inhibitor (DF030263) was performed to promote oral delivery. Oral bioavailability of DF030263 in fasted rats was 23.8%, and a distinct double-peak phenomenon was observed. A two-site absorption windows mechanism was proposed as a possible explanation to the phenomenon. The two-site absorption window hypothesis was supported by in vitro solubility assays in biorelevant fluids with different pH levels, as well as by in silico simulation by GastroPlus™. Controlled release to the colon was conducted in rats in order to exploit the colonic absorption window but did not improve the oral bioavailability. On the other hand, oral administration at postprandial conditions in rats (performed based on the high in vitro solubility in fed state simulated fluid and reduced pH-dependency) resulted in an almost 3-fold increase in bioavailability to 63.6%. In conclusion, this study demonstrates an efficient in vitro-in vivo-in silico drug development approach for improving the oral bioavailability of DF030263, a promising candidate for the treatment of chronic lymphocytic leukemia.

A Whole-Body Physiologically Based Pharmacokinetic Model Characterizing Interplay of OCTs and MATEs in Intestine, Liver and Kidney to Predict Drug-Drug Interactions of Metformin with Perpetrators

Transmembrane transport of metformin is highly controlled by transporters including organic cation transporters (OCTs), plasma membrane monoamine transporter (PMAT), and multidrug/toxin extrusions (MATEs). Hepatic OCT1, intestinal OCT3, renal OCT2 on tubule basolateral membrane, and MATE1/2-K on tubule apical membrane coordinately work to control metformin disposition. Drug–drug interactions (DDIs) of metformin occur when co-administrated with perpetrators via inhibiting OCTs or MATEs. We aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model characterizing interplay of OCTs and MATEs in the intestine, liver, and kidney to predict metformin DDIs with cimetidine, pyrimethamine, trimethoprim, ondansetron, rabeprazole, and verapamil. Simulations showed that co-administration of perpetrators increased plasma exposures to metformin, which were consistent with clinic observations. Sensitivity analysis demonstrated that contributions of the tested factors to metformin DDI with cimetidine are gastrointestinal transit rate > inhibition of renal OCT2 ≈ inhibition of renal MATEs > inhibition of intestinal OCT3 > intestinal pH > inhibition of hepatic OCT1. Individual contributions of transporters to metformin disposition are renal OCT2 ≈ renal MATEs > intestinal OCT3 > hepatic OCT1 > intestinal PMAT. In conclusion, DDIs of metformin with perpetrators are attributed to integrated effects of inhibitions of these transporters.

A New Intestinal Model for Analysis of Drug Absorption and Interactions Considering Physiological Translocation of Contents

Precise prediction of drug absorption is key to the success of new drug development and efficacious pharmacotherapy. In this study, we developed a new absorption model, the advanced translocation model (ATOM), by extending our previous model, the translocation model. ATOM reproduces the translocation of a substance in the intestinal lumen using a partial differential equation with variable dispersion and convection terms to describe natural flow and micromixing within the intestine under not only fasted but also fed conditions. In comparison with ATOM, it was suggested that a conventional absorption model, advanced compartmental absorption and transit model, tends to underestimate micromixing in the upper intestine, and it is difficult to adequately describe movements under the fasted and fed conditions. ATOM explains the observed nonlinear absorption of midazolam successfully, with a minimal number of scaling factors. Furthermore, ATOM considers the apical and basolateral membrane permeabilities of enterocytes separately and assumes compartmentation of the lamina propria, including blood vessels, to consider intestinal blood flow appropriately. ATOM estimates changes in the intestinal availability caused by drug interaction associated with inhibition of CYP3A and P-glycoprotein in the intestine. Additionally, ATOM can estimate the drug absorption in the fed state considering delayed intestinal drug flow. Therefore, ATOM is a useful tool for the analysis of local pharmacokinetics in the gastrointestinal tract, especially for the estimation of nonlinear drug absorption, which may involve various interactions with intestinal contents or other drugs. SIGNIFICANCE STATEMENT: The newly developed advanced translocation model precisely explains various movements of intestinal contents under fasted and fed conditions, which cannot be adequately described by the current physiological pharmacokinetic models.

Current challenges and future perspectives in oral absorption research: An opinion of the UNGAP network

Although oral drug delivery is the preferred administration route and has been used for centuries, modern drug discovery and development pipelines challenge conventional formulation approaches and highlight the insufficient mechanistic understanding of processes critical to oral drug absorption. This review presents the opinion of UNGAP scientists on four key themes across the oral absorption landscape: (1) specific patient populations, (2) regional differences in the gastrointestinal tract, (3) advanced formulations and (4) food-drug interactions. The differences of oral absorption in pediatric and geriatric populations, the specific issues in colonic absorption, the formulation approaches for poorly water-soluble (small molecules) and poorly permeable (peptides, RNA etc.) drugs, as well as the vast realm of food effects, are some of the topics discussed in detail. The identified controversies and gaps in the current understanding of gastrointestinal absorption-related processes are used to create a roadmap for the future of oral drug absorption research.

Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies

Physiologically based pharmacokinetic modelling is well established in the pharmaceutical industry and is accepted by regulatory agencies for the prediction of drug-drug interactions. However, physiologically based pharmacokinetic modelling is valuable to address a much wider range of pharmaceutical applications, and new regulatory impact is expected as its full power is leveraged. As one example, physiologically based pharmacokinetic modelling is already routinely used during drug discovery for in-vitro to in-vivo translation and pharmacokinetic modelling in preclinical species, and this leads to the application of verified models for first-in-human pharmacokinetic predictions. A consistent cross-industry strategy in this application area would increase confidence in the approach and facilitate further learning. With this in mind, this article aims to enhance a previously published first-in-human physiologically based pharmacokinetic model-building strategy. Based on the experience of scientists from multiple companies participating in the GastroPlus™ User Group Steering Committee, new Absorption, Distribution, Metabolism and Excretion knowledge is integrated and decision trees proposed for each essential component of a first-in-human prediction. We have reviewed many relevant scientific publications to identify new findings and highlight gaps that need to be addressed. Finally, four industry case studies for more challenging compounds illustrate and highlight key components of the strategy.

Physiologically Based Absorption Modelling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Entrectinib

Entrectinib is a potent and selective tyrosine kinase inhibitor (TKI) of TRKA/B/C, ROS1, and ALK with both systemic and CNS activities, which has recently received FDA approval for ROS1 fusion-positive non-small cell lung cancer and NTRK fusion-positive solid tumors. This paper describes the application of a physiologically based biophamaceutics modeling (PBBM) during clinical development to understand the impact of food and gastric pH changes on absorption of this lipophilic, basic, molecule with reasonable permeability but strongly pH-dependent solubility. GastroPlus™ was used to develop a physiologically based pharmacokinetics (PBPK) model integrating in vitro and in silico data and dissolution studies and in silico modelling in DDDPlus™ were used to understand the role of self-buffering and acidulant on formulation performance. Models were verified by comparison of simulated pharmacokinetics for acidulant and non-acidulant containing formulations to clinical data from a food effect study and relative bioavailability studies with and without the gastric acid-reducing agent lansoprazole. A negligible food effect and minor pH-dependent drug-drug interaction for the market formulation were predicted based on biorelevant in vitro measurements, dissolution studies, and in silico modelling and were confirmed in clinical studies. These outcomes were explained as due to the acidulant counteracting entrectinib self-buffering and greatly reducing the effect of gastric pH changes. Finally, sensitivity analyses with the verified model were applied to support drug product quality. PBBM has great potential to streamline late-stage drug development and may have impact on regulatory questions.

Assessment of Pharmacokinetics and Metabolism Profiles of SCH 58261 in Rats Using Liquid Chromatography-Mass Spectrometric Method

5-Amino-7-(2-phenylethyl)-2-(2-furyl)-pyrazolo(4,3-e)-1,2,4-triazolo(1,5-c) pyrimidine (SCH 58261) is one of the new chemical entities that has been developed as an adenosine A_2A receptor antagonist. Although SCH 58261 has been reported to be beneficial, there is little information about SCH 58261 from a drug metabolism or pharmacokinetics perspective. This study describes the metabolism and pharmacokinetic properties of SCH 58261 in order to understand its behaviors in vivo. Rats were used as the in vivo model species. First, an LC-MS/MS method was developed for the determination of SCH 58261 in rat plasma. A GastroPlus™ simulation, in vitro microsomal metabolic stability, and bile duct-cannulated studies were also performed to understand its pharmacokinetic profile. The parameter sensitivity analysis of GastroPlus™ was used to examine the factors that influence exposure when the drug is orally administered. The factors are as follows: permeability, systemic clearance, renal clearance, and liver first-pass effect. In vitro microsomal metabolic stability indicates how much the drug is metabolized. The extrapolated hepatic clearance value of SCH 58261 was 39.97 mL/min/kg, indicating that the drug is greatly affected by hepatic metabolism. In vitro microsomal metabolite identification studies revealed that metabolites produce oxidized and ketone-formed metabolites via metabolic enzymes in the liver. The bile duct-cannulated rat study, after oral administration of SCH 58261, showed that a significant amount of the drug was excreted in feces. These results imply that the drug is not absorbed well in the body after oral administration. Taken together, SCH 58261 showed quite a low bioavailability when administered orally and this was likely due to significantly limited absorption, as well as high metabolism in vivo.

Further Considerations Towards an Effective and Efficient Oncology Drug Discovery DMPK Strategy

BACKGROUND

DMPK data and knowledge are critical in maximising the probability of developing successful drugs via the application of in silico, in vitro and in vivo approaches in drug discovery.

METHODS

The evaluation, optimisation and prediction of human pharmacokinetics is now a mainstay within drug discovery. These elements are at the heart of the 'right tissue' component of AstraZeneca's '5Rs framework' which, since its adoption, has resulted in increased success of Phase III clinical trials. With the plethora of DMPK related assays and models available, there is a need to continually refine and improve the effectiveness and efficiency of approaches best to facilitate the progression of quality compounds for human clinical testing.

RESULTS

This article builds on previously published strategies from our laboratories, highlighting recent discoveries and successes, that brings our AstraZeneca Oncology DMPK strategy up to date. We review the core aspects of DMPK in Oncology drug discovery and highlight data recently generated in our laboratories that have influenced our screening cascade and experimental design. We present data and our experiences of employing cassette animal PK, as well as re-evaluating in vitro assay design for metabolic stability assessments and expanding our use of freshly excised animal and human tissue to best inform first time in human dosing and dose escalation studies.

CONCLUSION

Application of our updated drug-drug interaction and central nervous system drug exposure strategies are exemplified, as is the impact of physiologically based pharmacokinetic and pharmacokinetic-pharmacodynamic modelling for human predictions.

Critical Impact of Drug-Drug Interactions via Intestinal CYP3A in the Risk Assessment of Weak Perpetrators Using Physiologically Based Pharmacokinetic Models

A great deal of effort has been being made to improve the accuracy of the prediction of drug-drug interactions (DDIs). In this study, we addressed CYP3A-mediated weak DDIs, in which a relatively high false prediction rate was pointed out. We selected 17 orally administered drugs that have been reported to alter area under the curve (AUC) of midazolam, a typical CYP3A substrate, 0.84-1.47 times. For weak CYP3A perpetrators, the predicted AUC ratio mainly depends on intestinal DDIs rather than hepatic DDIs because the drug concentration in the enterocytes is higher. Thus, DDI prediction using simulated concentration-time profiles in each segment of the digestive tract was made by physiologically based pharmacokinetic (PBPK) modeling software GastroPlus. Although mechanistic static models tend to overestimate the risk to ensure the safety of patients, some underestimation is reported about PBPK modeling. Our in vitro studies revealed that 16 out of 17 tested drugs exhibited time-dependent inhibition (TDI) of CYP3A, and the subsequent DDI simulation that ignored these TDIs provided false-negative results. This is considered to be the cause of past underestimation. Inclusion of the DDI parameters of all the known DDI mechanisms, reversible inhibition, TDI, and induction, which have opposite effects on midazolam AUC, to PBPK model was successful in improving predictability of the DDI without increasing false-negative prediction as trade-off. This comprehensive model-based analysis suggests the importance of the intestine in assessing weak DDIs via CYP3A and the usefulness of PBPK in predicting intestinal DDIs. SIGNIFICANCE STATEMENT: Although drug-drug interaction (DDI) prediction has been extensively performed previously, the accuracy of prediction for weak interactions via CYP3A has not been thoroughly investigated. In this study, we simulate DDIs considering drug concentration-time profile in the enterocytes and discuss the importance and the predictability of intestinal DDIs about weak CYP3A perpetrators.

Simultaneously predict pharmacokinetic interaction of rifampicin with oral versus intravenous substrates of cytochrome P450 3A/P‑glycoprotein to healthy human using a semi-physiologically based pharmacokinetic model involving both enzyme and transporter turnover

Several reports demonstrated that rifampicin affected pharmacokinetics of victim drugs following oral more than intravenous administration. We aimed to establish a semi-physiologically based pharmacokinetic (semi-PBPK) model involving both enzyme and transporter turnover to simultaneously predict pharmacokinetic interaction of rifampicin with oral versus intravenous substrates of cytochrome P450 (CYP) 3A4/P‑glycoprotein (P-GP) in human. Rifampicin was chosen as the CYP3A /P-GP inducer. Thirteen victim drugs including P-GP substrates (digoxin and talinolol), CYP3A substrates (alfentanil, midazolam, nifedipine, ondansetron and oxycodone), dual substrates of CYP3A/P-GP (quinidine, cyclosporine A, tacrolimus and verapamil) and complex substrates (S-ketamine and tramadol) were chosen to investigate drug-drug interactions (DDIs) with rifampicin. Corresponding parameters were cited from literatures. Before and after multi-dose of oral rifampicin, the pharmacokinetic profiles of victim drugs for oral or intravenous administration to human were predicted using the semi-PBPK model and compared with the observed values. Contribution of both CYP3A and P-GP induction in intestine and liver by rifampicin to pharmacokinetic profiles of victim drugs was investigated. The predicted pharmacokinetic profiles of drugs before and after rifampicin administration accorded with the observations. The predicted pharmacokinetic parameters and DDIs were successful, whose fold-errors were within 2. It was consistent with observations that the DDIs of rifampicin with oral victim drugs were larger than those with intravenous victim drugs. DDIs of rifampicin with CYP3A or P-GP substrates following oral versus intravenous administration to human were successfully predicted using the developed semi-PBPK model.

The biological challenges and pharmacological opportunities of orally administered nanomedicine delivery

Nano-scale formulations are being developed to improve the delivery of orally administered medicines, and the interactions between nanoformulations and the gastrointestinal luminal, mucosal and epithelial environment is currently being investigated. The mucosal surface of the gastrointestinal tract is capable of trapping and eliminating large particles and pathogens as part of the natural defences of the body, it is becoming clearer that nanoformulation properties such as particle size, charge, and shape, as well as mucous properties such as viscoelasticity, thickness, density, and turn-over time are all relevant to these interactions. However, progress has been slow to utilise this information to produce effective mucous-penetrating particles. Areas covered: This review focuses on delivery method of nanomedicines both into and across the gastrointestinal mucosal surface, and aims to summarise the biological barriers that exist to successful oral nanomedicine delivery and how these barriers may be investigated and overcome. Expert commentary: Despite successes in the laboratory, no nanotechnology-enabled products are currently in clinical use which either specifically target the intestinal mucous surface or cross the epithelial barrier intact. New nanomedicine-based treatments of local diseases (intestinal cancer, inflammation, infection) and systemic diseases are advancing towards clinical use, and offer genuine opportunities to improve therapy.

Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 2. Rational Bioavailability Design by Global Sensitivity Analysis To Identify Properties Affecting Bioavailability

When medicinal chemists need to improve oral bioavailability (%F) during lead optimization, they systematically modify compound properties mainly based on their own experience and general rules of thumb. However, at least a dozen properties can influence %F, and the difficulty of multiparameter optimization for such complex nonlinear processes grows combinatorially with the number of variables. Furthermore, strategies can be in conflict. For example, adding a polar or charged group will generally increase solubility but decrease permeability. Identifying the 2 or 3 properties that most influence %F for a given compound series would make %F optimization much more efficient. We previously reported an adaptation of physiologically based pharmacokinetic (PBPK) simulations to predict %F for lead series from purely computational inputs within a 2-fold average error. Here, we run thousands of such simulations to generate a comprehensive "bioavailability landscape" for each series. A key innovation was recognition that the large and variable number of p K_a's in drug molecules could be replaced by just the two straddling the isoelectric point. Another was use of the ZINC database to cull out chemically inaccessible regions of property space. A quadratic partial least squares regression (PLS) accurately fits a continuous surface to these thousands of bioavailability predictions. The PLS coefficients indicate the globally sensitive compound properties. The PLS surface also displays the %F landscape in these sensitive properties locally around compounds of particular interest. Finally, being quick to calculate, the PLS equation can be combined with models for activity and other properties for multiobjective lead optimization.

Physiologically Based Oral Absorption Modelling to Study Gut-Level Drug Interactions

Physiologically based oral absorption models are in silico tools primarily used to guide formulation development and project the clinical performance of formulation variants. This commentary briefly discusses additional oral absorption model applications, focusing on gut-level drug interactions. Gut-level drug interactions can involve drug degradation, metabolic enzymes, transporters, gastrointestinal motility modulators, acid-reducing agents, and food. The growth in publications reporting physiologically based oral absorption model utilization and successful pharmacokinetic prediction (e.g., after acid-reducing agents or food coadministration) indicate that oral absorption models have achieved a level of maturity within the industry particularly over the past 15 years. Provided appropriate data and model validation, oral absorption modeling/simulation may serve as a surrogate for clinical studies by providing both mechanistic and quantitative understanding of oral delivery considerations on pharmacokinetics.

Simulating Intestinal Transporter and Enzyme Activity in a Physiologically Based Pharmacokinetic Model for Tenofovir Disoproxil Fumarate

Tenofovir disoproxil fumarate (TDF), a prodrug of tenofovir, has oral bioavailability (25%) limited by intestinal transport (P-glycoprotein), and intestinal degradation (carboxylesterase). However, the influence of luminal pancreatic enzymes is not fully understood. Physiologically based pharmacokinetic (PBPK) modeling has utility for estimating drug exposure from in vitro data. This study aimed to develop a PBPK model that included luminal enzyme activity to inform dose reduction strategies. TDF and tenofovir stability in porcine pancrelipase concentrations was assessed (0, 0.48, 4.8, 48, and 480 U/ml of lipase; 1 mM TDF; 37°C; 0 to 30 min). Samples were analyzed using mass spectrometry. TDF stability and permeation data allowed calculation of absorption rates within a human PBPK model to predict plasma exposure following 6 days of once-daily dosing with 300 mg of TDF. Regional absorption of drug was simulated across gut segments. TDF was degraded by pancrelipase (half-lives of 0.07 and 0.62 h using 480 and 48 U/ml, respectively). Previously reported maximum concentration (C_max; 335 ng/ml), time to C_max (T_max; 2.4 h), area under the concentration-time curve from 0 to 24 h (AUC_0-24; 3,045 ng · h/ml), and concentration at 24 h (C₂₄; 48.3 ng/ml) were all within a 0.5-fold difference from the simulated C_max (238 ng/ml), T_max (3 h), AUC_0-24 (3,036 ng · h/ml), and C₂₄ (42.7 ng/ml). Simulated TDF absorption was higher in duodenum and jejunum than in ileum (p<0.05). These data support that TDF absorption is limited by the action of intestinal lipases. Our results suggest that bioavailability may be improved by protection of drug from intestinal transporters and enzymes, for example, by coadministration of enzyme-inhibiting agents or nanoformulation strategies.

Prediction of pharmacokinetics and drug-drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach: A case study of caffeine and ciprofloxacin

Over the last decade, physiologically based pharmacokinetics (PBPK) application has been extended significantly not only to predicting preclinical/human PK but also to evaluating the drug-drug interaction (DDI) liability at the drug discovery or development stage. Herein, we describe a case study to illustrate the use of PBPK approach in predicting human PK as well as DDI using in silico, in vivo and in vitro derived parameters. This case was composed of five steps such as: simulation, verification, understanding of parameter sensitivity, optimization of the parameter and final evaluation. Caffeine and ciprofloxacin were used as tool compounds to demonstrate the “fit for purpose” application of PBPK modeling and simulation for this study. Compared to caffeine, the PBPK modeling for ciprofloxacin was challenging due to several factors including solubility, permeability, clearance and tissue distribution etc. Therefore, intensive parameter sensitivity analysis (PSA) was conducted to optimize the PBPK model for ciprofloxacin. Overall, the increase in C_max of caffeine by ciprofloxacin was not significant. However, the increase in AUC was observed and was proportional to the administered dose of ciprofloxacin. The predicted DDI and PK results were comparable to observed clinical data published in the literatures. This approach would be helpful in identifying potential key factors that could lead to significant impact on PBPK modeling and simulation for challenging compounds.

Forecasting oral absorption across biopharmaceutics classification system classes with physiologically based pharmacokinetic models

OBJECTIVES

The aim of this study was (1) to determine how closely physiologically based pharmacokinetic (PBPK) models can predict oral bioavailability using a priori knowledge of drug-specific properties and (2) to examine the influence of the biopharmaceutics classification system class on the simulation success.

METHODS

Simcyp Simulator, GastroPlus^™ and GI-Sim were used. Compounds with published Biowaiver monographs (bisoprolol (BCS I), nifedipine (BCS II), cimetidine (BCS III), furosemide (BCS IV)) were selected to ensure availability of accurate and reproducible data for all required parameters. Simulation success was evaluated with the average fold error (AFE) and absolute average fold error (AAFE). Parameter sensitivity analysis (PSA) to selected parameters was performed.

KEY FINDINGS

Plasma concentration-time profiles after intravenous administration were forecast within an AAFE < 3. The addition of absorption processes resulted in more variability in the prediction of the plasma profiles, irrespective of biopharmaceutics classification system (BCS) class. The reliability of literature permeability data was identified as a key issue in the accuracy of predicting oral drug absorption.

CONCLUSION

For the four drugs studied, it appears that the forecasting accuracy of the PBPK models is related to the BCS class (BCS I > BCS II, BCS III > BCS IV). These results will need to be verified with additional drugs.

Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine

Personalized medicine strives to deliver the 'right drug at the right dose' by considering inter-person variability, one of the causes for therapeutic failure in specialized populations of patients. Physiologically-based pharmacokinetic (PBPK) modeling is a key tool in the advancement of personalized medicine to evaluate complex clinical scenarios, making use of physiological information as well as physicochemical data to simulate various physiological states to predict the distribution of pharmacokinetic responses. The increased dependency on PBPK models to address regulatory questions is aligned with the ability of PBPK models to minimize ethical and technical difficulties associated with pharmacokinetic and toxicology experiments for special patient populations. Subpopulation modeling can be achieved through an iterative and integrative approach using an adopt, adapt, develop, assess, amend, and deliver methodology. PBPK modeling has two valuable applications in personalized medicine: (1) determining the importance of certain subpopulations within a distribution of pharmacokinetic responses for a given drug formulation and (2) establishing the formulation design space needed to attain a targeted drug plasma concentration profile. This review article focuses on model development for physiological differences associated with sex (male vs. female), age (pediatric vs. young adults vs. elderly), disease state (healthy vs. unhealthy), and temporal variation (influence of biological rhythms), connecting them to drug product formulation development within the quality by design framework. Although PBPK modeling has come a long way, there is still a lengthy road before it can be fully accepted by pharmacologists, clinicians, and the broader industry.

Physiologically Based Absorption Modeling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Alectinib

Alectinib, a lipophilic, basic, anaplastic lymphoma kinase (ALK) inhibitor with very low aqueous solubility, has received Food and Drug Administration-accelerated approval for the treatment of patients with ALK+ non-small-cell lung cancer. This paper describes the application of physiologically based absorption modeling during clinical development to predict and understand the impact of food and gastric pH changes on alectinib absorption. The GastroPlus^™ software was used to develop an absorption model integrating in vitro and in silico data on drug substance properties. Oral pharmacokinetics was simulated by linking the absorption model to a disposition model fit to pharmacokinetic data obtained after an intravenous infusion. Simulations were compared to clinical data from a food effect study and a drug-drug interaction study with esomeprazole, a gastric acid-reducing agent. Prospective predictions of a positive food effect and negligible impact of gastric pH elevation were confirmed with clinical data, although the exact magnitude of the food effect could not be predicted with confidence. After optimization of the absorption model with clinical food effect data, a refined model was further applied to derive recommendations on the timing of dose administration with respect to a meal. The application of biopharmaceutical absorption modeling is an area with great potential to further streamline late stage drug development and with impact on regulatory questions.

Evaluation of the GastroPlus™ Advanced Compartmental and Transit (ACAT) Model in Early Discovery

PURPOSE

The aim of this study was to evaluate the oral exposure predictions obtained early in drug discovery with a generic GastroPlus Advanced Compartmental And Transit (ACAT) model based on the in vivo intravenous blood concentration-time profile, in silico properties (lipophilicity, pKa) and in vitro high-throughput absorption-distribution-metabolism-excretion (ADME) data (as determined by PAMPA, solubility, liver microsomal stability assays).

METHODS

The model was applied to a total of 623 discovery molecules and their oral exposure was predicted in rats and/or dogs. The predictions of Cmax, AUClast and Tmax were compared against the observations.

RESULTS

The generic model proved to make predictions of oral Cmax, AUClast and Tmax within 3-fold of the observations for rats in respectively 65%, 68% and 57% of the 537 cases. For dogs, it was respectively 77%, 79% and 85% of the 124 cases. Statistically, the model was most successful at predicting oral exposure of Biopharmaceutical Classification System (BCS) class 1 compounds compared to classes 2 and 3, and was worst at predicting class 4 compounds oral exposure.

CONCLUSION

The generic GastroPlus ACAT model provided reasonable predictions especially for BCS class 1 compounds. For compounds of other classes, the model may be refined by obtaining more information on solubility and permeability in secondary assays. This increases confidence that such a model can be used in discovery projects to understand the parameters limiting absorption and extrapolate predictions across species. Also, when predictions disagree with the observations, the model can be updated to test hypotheses and understand oral absorption.

Predicting Drug Extraction in the Human Gut Wall: Assessing Contributions from Drug Metabolizing Enzymes and Transporter Proteins using Preclinical Models

Intestinal metabolism can limit oral bioavailability of drugs and increase the risk of drug interactions. It is therefore important to be able to predict and quantify it in drug discovery and early development. In recent years, a plethora of models-in vivo, in situ and in vitro-have been discussed in the literature. The primary objective of this review is to summarize the current knowledge in the quantitative prediction of gut-wall metabolism. As well as discussing the successes of current models for intestinal metabolism, the challenges in the establishment of good preclinical models are highlighted, including species differences in the isoforms; regional abundances and activities of drug metabolizing enzymes; the interplay of enzyme-transporter proteins; and lack of knowledge on enzyme abundances and availability of empirical scaling factors. Due to its broad specificity and high abundance in the intestine, CYP3A is the enzyme that is frequently implicated in human gut metabolism and is therefore the major focus of this review. A strategy to assess the impact of gut wall metabolism on oral bioavailability during drug discovery and early development phases is presented. Current gaps in the mechanistic understanding and the prediction of gut metabolism are highlighted, with suggestions on how they can be overcome in the future.

In vitro anticancer properties and biological evaluation of novel natural alkaloid jerantinine B

Natural products play a pivotal role in medicine especially in the cancer arena. Many drugs that are currently used in cancer chemotherapy originated from or were inspired by nature. Jerantinine B (JB) is one of seven novel Aspidosperma indole alkaloids isolated from the leaf extract of Tabernaemontana corymbosa. Preliminary antiproliferative assays revealed that JB and JB acetate significantly inhibited growth and colony formation, accompanied by time- and dose-dependent apoptosis induction in human cancer cell lines. JB significantly arrested cells at the G2/M cell cycle phase, potently inhibiting tubulin polymerisation. Polo-like kinase 1 (PLK1; an early trigger for the G2/M transition) was also dose-dependently inhibited by JB (IC50 1.5 µM). Furthermore, JB provoked significant increases in reactive oxygen species (ROS). Annexin V+ cell populations, dose-dependent accumulation of cleaved-PARP and caspase 3/7 activation, and reduced Bcl-2 and Mcl-1 expression confirm apoptosis induction. Preclinical in silico biopharmaceutical assessment of JB calculated rapid absorption and bioavailability >70%. Doses of 8-16 mg/kg JB were predicted to maintain unbound plasma concentrations >GI50 values in mice during efficacy studies. These findings advocate continued development of JB as a potential chemotherapeutic agent.

Quantitative aspects of drug permeation across in vitro and in vivo barriers

The kinetics of permeation across epithelial and endothelial cell sheets and across cell membranes is determinant for the pharmacokinetics of a drug. In vitro transport experiments with cultured cells or artificial barriers have tremendously improved the predictability of the in vivo behaviour of tested compounds. This article focuses on the parameters and calculation methods that are used to describe permeation quantitatively, with a focus on in vitro experiments and the prediction of intestinal absorption and blood-brain barrier passage. It shows under which in vitro experimental conditions standard calculations are adequate and under which conditions equations should be adapted to the experimental details. The impact of volume differences between donor and receiver compartments, pH gradients, addition of albumin, accumulation in the barrier and unidirectional transport by an efflux transporter on the results is shown in simulations. The article should make researchers aware of experimental factors that affect the outcome of a permeation experiment and how to account for this during data analysis. Finally, strategies to predict the in vivo behaviour of a compound based on the in vitro data are discussed. The goal of the article is to support researchers in choosing experimental conditions and calculation methods that deliver appropriate and reproducible results in permeation studies in vitro.

Cytochrome P450 time-dependent inhibition and induction: advances in assays, risk analysis and modelling

INTRODUCTION

It is widely accepted that current practice of polypharmacy inevitably increases the incidence of drug-drug interactions (DDIs). Serious DDIs are a major liability for new molecular entities entering the pharmaceutical market. Various strategies are employed to avoid problematic compounds for clinical development. Progress made with reversible CYP DDIs has prompted a switch to study and model time-dependent inhibition and induction interactions.

AREAS COVERED

An overview of popular experimental practices is presented with discussion of techniques and algorithms used to analyse the clinical DDI risk. Emphasis is placed on the transition from early, simple static equations, via more complex net mechanistic, static models to dynamic approaches involving multiple perpetrators and metabolites, simultaneous inhibition and induction.

EXPERT OPINION

Inclusion of the more conservative terms for parameters required for DDI evaluation may eliminate promising chemical space, encourages poor practice and hampers innovation. Breakthroughs have originated from understanding of 'outliers' from such analyses where CYP enzyme-transporter interplay may be involved. The role of key transporters in drug disposition is firmly established as the chemistry required to address new targets deviates from traditional 'drug-like' space. Attempts to model more complex interactions for substrates of both CYP enzymes and drug transporters are still in their infancy and will benefit from dynamic modelling.

Parameterization of small intestinal water volume using PBPK modeling

To facilitate accurate predictions of oral drug disposition, mechanistic absorption models require optimal parameterization. Furthermore, parameters should maintain a biological basis to establish confidence in model predictions. This study will serve to calculate an optimal parameter value for small intestinal water volume (SIWV) using a model-based approach. To evaluate physiologic fidelity, derived volume estimates will be compared to experimentally-based SIWV determinations. A compartmental absorption and transit (CAT) model, created in Matlab-Simulink®, was integrated with a whole-body PBPK model, developed in PK-SIM 5.2®, to provide predictions of systemic drug disposition. SIWV within the CAT model was varied between 52.5mL and 420mL. Simulations incorporating specific SIWV values were compared to pharmacokinetic data from compounds exhibiting solubility induced non-proportional changes in absorption using absolute average fold-error. Correspondingly, data pertaining to oral administration of acyclovir and chlorothiazide were utilized to derive estimates of SIWV. At 400mg, a SIWV of 116mL provided the best estimates of acyclovir plasma concentrations. A similar SIWV was found to best depict the urinary excretion pattern of chlorothiazide at a dose of 100mg. In comparison, experimentally-based estimates of SIWV within adults denote a central tendency between 86 and 167mL. The derived SIWV (116mL) represents the optimal parameter value within the context of the developed CAT model. This result demonstrates the biological basis of the widely utilized CAT model as in vivo SIWV determinations correspond with model-based estimates.

Analysis of the impact of controlled release formulations on oral drug absorption, gut wall metabolism and relative bioavailability of CYP3A substrates using a physiologically-based pharmacokinetic model

Controlled release (CR) formulations are usually designed to achieve similar exposure (AUC) levels as the marketed immediate release (IR) formulation. However, the AUC is often lower following CR compared to IR formulations. There are a few exceptions when the CR formulations have shown higher AUC. This study investigated the impact of CR formulations on oral drug absorption and CYP3A4-mediated gut wall metabolism. A review of the current literature on relative bioavailability (Frel) between CR and IR formulations of CYP3A substrates was conducted. This was followed by a systematic analysis to assess the impact of the release characteristics and the drug-specific factors (including metabolism and permeability) on oral bioavailability employing a physiologically-based pharmacokinetic (PBPK) modelling and simulation approach. From the literature review, only three CYP3A4 substrates showed higher Frel when formulated as CR. Several scenarios were investigated using the PBPK approach; in most of them, the oral absorption of CR formulations was lower as compared to the IR formulations. However, for highly permeable compounds that were CYP3A4 substrates the reduction in absorption was compensated by an increase in the fraction that escapes from first pass metabolism in the gut wall (FG), where the magnitude was dependent on CYP3A4 affinity. The systematic simulations of various interplays between different parameters demonstrated that BCS class 1 highly-cleared CYP3A4 substrates can display up to 220% higher relative bioavailability when formulated as CR compared to IR, in agreement with the observed data collected from the literature. The results and methodology of this study can be employed during the formulation development process in order to optimize drug absorption, especially for CYP3A4 substrates.

Physiologically based pharmacokinetic modelling to predict single- and multiple-dose human pharmacokinetics of bitopertin

BACKGROUND

Bitopertin (RG1678) is a glycine reuptake inhibitor currently in phase 3 trials for treatment of schizophrenia. This paper describes the use of physiologically based pharmacokinetic (PBPK) modelling and preclinical data to gain insights into and predict bitopertin clinical pharmacokinetics.

METHODS

Simulations of pharmacokinetics were initiated early in the drug discovery stage by integrating physicochemical properties and in vitro measurements into a PBPK rat model. Comparison of pharmacokinetics predicted by PBPK modelling with those measured after intravenous and oral dosing in rats and monkeys showed a good match and thus increased confidence that a similar approach could be applied for human prediction. After comparison of predicted plasma concentrations with those measured after single oral doses in the first clinical study, the human model was refined and then applied to simulate multiple-dose pharmacokinetics.

RESULTS

Clinical plasma concentrations measured were in good agreement with PBPK predictions. Predicted area under the plasma concentration-time curve (AUC) was within twofold of the observed mean values for all dose levels. Maximum plasma concentration (C max) at higher doses was well predicted but approximately twofold below observed values at the lower doses. A slightly less than dose-proportional increase in both AUC and C max was observed, and model simulations indicated that when the dose exceeded 50 mg, solubility limited the fraction of dose absorbed. Refinement of the absorption model with additional solubility and permeability measurements further improved the match of simulations to observed single-dose data. Simulated multiple-dose pharmacokinetics with the refined model were in good agreement with observed data.

CONCLUSIONS

Clinical pharmacokinetics of bitopertin can be well simulated with a mechanistic PBPK model. This model supports further clinical development and provides a valuable repository for pharmacokinetic knowledge gained about the molecule.

Prediction of drug disposition on the basis of its chemical structure

The chemical structure of any drug determines its pharmacokinetics and pharmacodynamics. Detailed understanding of relationships between the drug chemical structure and individual disposition pathways (i.e., distribution and elimination) is required for efficient use of existing drugs and effective development of new drugs. Different approaches have been developed for this purpose, ranging from statistics-based quantitative structure-property (or structure-pharmacokinetic) relationships (QSPR) analysis to physiologically based pharmacokinetic (PBPK) models. This review critically analyzes currently available approaches for analysis and prediction of drug disposition on the basis of chemical structure. Models that can be used to predict different aspects of disposition are presented, including: (a) value of the individual pharmacokinetic parameter (e.g., clearance or volume of distribution), (b) efficiency of the specific disposition pathway (e.g., biliary drug excretion or cytochrome P450 3A4 metabolism), (c) accumulation in a specific organ or tissue (e.g., permeability of the placenta or accumulation in the brain), and (d) the whole-body disposition in the individual patients. Examples of presented pharmacological agents include "classical" low-molecular-weight compounds, biopharmaceuticals, and drugs encapsulated in specialized drug-delivery systems. The clinical efficiency of agents from all these groups can be suboptimal, because of inefficient permeability of the drug to the site of action and/or excessive accumulation in other organs and tissues. Therefore, robust and reliable approaches for chemical structure-based prediction of drug disposition are required to overcome these limitations. PBPK models are increasingly being used for prediction of drug disposition. These models can reflect the complex interplay of factors that determine drug disposition in a mechanistically correct fashion and can be combined with other approaches, for example QSPR-based prediction of drug permeability and metabolism, pharmacogenomic data and tools, pharmacokinetic-pharmacodynamic modeling approaches, etc. Moreover, the PBPK models enable detailed analysis of clinically relevant scenarios, for example the effect of the specific conditions on the time course of the analyzed drug in the individual organs and tissues, including the site of action. It is expected that further development of such combined approaches will increase their precision, enhance the effectiveness of drugs, and lead to individualized drug therapy for different patient populations (geriatric, pediatric, specific diseases, etc.).