儿童生理药代动力学模型及其在儿科药物研究中的应用

生理药代动力学(physiologically based pharmacokinetic, PBPK)模型是预测药物在特殊人群中的药代动力学、药效学和安全性的重要工具。尤其对于儿童这类不易开展临床试验的人群, PBPK模型的应用更是能有效促进儿科药物的开发以及儿童的临床用药。目前, PBPK模型在儿科药物开发中的主要应用有以下几种:临床试验设计、药物相互作用(drug-drug interaction, DDI)的风险评估和儿童给药剂量的确立等。本综述简介了儿童生理药动学模型在儿科药物研究中的优越性,总结了PBPK模型如何实现从成人到儿童的外推,儿童生理药动学模型的理论基础,建模过程及所要注意的重要生理参数,列举了目前PBPK模型在儿科药物研究中的一些应用实例。最后简述了儿童PBPK模型当前的局限性和未来发展方向。     

Integrating Drug- and Formulation-Related Properties With Gastrointestinal Tract Variability Using a Product-Specific Particle Size Approach: Case Example Ibuprofen

In the present study, an in vitro–in vivo extrapolation of dissolution integrated to a physiologically based pharmacokinetics modeling approach, considering a product-specific particle size distribution and a self-buffering effect of the drug, is introduced and appears to be a promising translational modeling strategy to support drug product development, manufacturing changes and setting clinically relevant specifications for immediate release formulations containing ibuprofen and other weak acids with similar properties.     

Food Effect Projections via Physiologically Based Pharmacokinetic Modeling: Predictive Case Studies

Food can alter the absorption of orally administered drugs. Biopharmaceutics physiologically based pharmacokinetic (PBPK) modeling offers the possibility to simulate a compound's pharmacokinetics under fasted or fed states. To advance the utility of PBPK modeling, with a view to regulatory impact, we have pooled our experience across 4 pharmaceutical companies to propose a general multistep PBPK workflow leveraging pre-existing clinical data for immediate-release formulations of Biopharmaceutics Classification System I and II compounds. With this strategy, we wish to promote pragmatic PBPK approaches for compounds where absorption is well understood, that is, compounds with moderate-to-high permeability that are not substrates for uptake transporters. Five case studies demonstrate how food effect can be well predicted using appropriately established and validated models. The case studies integrate solubility and dissolution data for initial model development and apply a “middle-out” validation with clinical data in one prandial state. Then, whenever possible, a validation against both fasted and fed state data is recommended before application of the models prospectively for to-be-marketed formulations. Thus, when combined with limited clinical data, PBPK models could be used to simulate outcomes for new doses, formulations, or active pharmaceutical ingredient forms, in lieu of a clinical food-effect study.     

Bioequivalence Comparison of Pediatric Dasatinib Formulations and Elucidation of Absorption Mechanisms Through Integrated PBPK Modeling

SPRYCEL^® (Dasatinib) is a Biopharmaceutical Classification System II weakly basic drug that exhibits strong pH-dependent solubility. Dasatinib is currently presented in 2 drug product formulations as an adult immediate release tablet and a pediatric powder for oral suspension. A bioequivalence study comparing the formulations in adult healthy subjects found that overall exposure (AUC_0-24) from suspension treatments was ～9% to 13% lower, Cmax was similar, and median Tmax from powder for oral suspension was ～30 min earlier. To understand the mechanism contributing to this behavior, a combination of biorelevant dissolution studies and physiologically based pharmacokinetic modeling was used to simulate in vivo performance. In vitro biorelevant dissolution confirmed that the rate and extent of release was similar between tablet and suspension formulations (>90% release within first 15 min). Physiologically based pharmacokinetic parameter sensitivity analysis demonstrated particular sensitivity to dosage form gastric residence time. A 12% higher AUC_0-24 was simulated for tablet dosage forms with 10 to 15 min longer gastric transit relative to solutions or suspensions of small particulates (rapid gastric emptying). The corresponding narrow simulated Cmax range also agreed with observed tablet and suspension bioequivalence data. The unique physicochemical properties, absorption characteristics, and inherent differences in dosage form transit behavior are attributed to influence the dasatinib bioequivalence.     

Physiologically based pharmacokinetic modeling to predict complex drug–drug interactions: a case study of AZD2327 and its metabolite,competitive and time‐dependent CYP3A inhibitors

4‐{(R)‐(3‐Aminophenyl)[4‐(4‐fluorobenzyl)‐piperazin‐1‐yl]methyl}‐N,N‐diethylbenzamide (AZD2327) is a highly potent and selective agonist of the δ ‐opioid receptor. AZD2327 and N‐deethylated AZD2327 (M1) are substrates of cytochrome P450 3A (CYP3A4) and comprise a complex multiple inhibitory system that causes competitive and time‐dependent inhibition of CYP3A4. The aim of the current work was to develop a physiologically based pharmacokinetic (PBPK) model to predict quantitatively the magnitude of CYP3A4 mediated drug–drug interaction with midazolam as the substrate. Integrating in silico, in vitro and in vivo PK data, a PBPK model was successfully developed to simulate the clinical accumulation of AZD2327 and its primary metabolite. The inhibition of CYP3A4 by AZD2327, using midazolam as a probe drug, was reasonably predicted. The predicted maximum concentration (C_max) and area under the concentration–time curve (AUC) for midazolam were increased by 1.75 and 2.45‐fold, respectively, after multiple dosing of AZD2327, indicating no or low risk for clinically relevant drug–drug interactions (DDI). These results are in agreement with those obtained in a clinical trial with a 1.4 and 1.5‐fold increase in C_max and AUC of midazolam, respectively. In conclusion, this model simulated DDI with less than a two‐fold error, indicating that complex clinical DDI associated with multiple mechanisms, pathways and inhibitors (parent and metabolite) can be predicted using a well‐developed PBPK model. Copyright © 2015 John Wiley & Sons, Ltd.     

Successful Prediction of Human Pharmacokinetics by Improving Calculation Processes of Physiologically Based Pharmacokinetic Approach

The physiologically based pharmacokinetics (PBPK) model is a major mechanistic approach for predicting human pharmacokinetics (PK) using drug-specific and physiological parameters but has been difficult to use for human PK prediction with acceptable accuracy. Here, we report a newly developed PBPK approach that incorporates the mechanism of albumin-mediated membrane penetration in the liver and interspecies correlation for unbound tissue fractions. To verify the utility of our PBPK approach, we used 12 drugs that are mainly eliminated by hepatic metabolism to compare the prediction accuracy with a conventional PBPK approach and to observe human PK parameters. We found the predictive accuracy for total clearance (CL_tot), distribution volume at the steady state (V_ss), elimination half-life (t_1/2), and plasma concentration at the last measurable time point (C_last) of our PBPK approach to show better absolute average fold error and percentage within 2-fold error (1.6-1.8 and 67%-92%, respectively) compared with values obtained from the conventional PBPK approach (2.1-2.4 and 42%-67%, respectively). As our approach can use parameters obtained in early drug screening, it could help accelerate successful nomination of drug candidates by optimizing the pharmacokinetics of new chemical entities by directly using predicted human PK profiles.     

Challenges and opportunities with modelling and simulation in drug discovery and drug development

The benefits of modelling and simulation at the pre-clinical stage of drug development can be realized through formal and realistic integration of data on physicochemical properties, pharmacokinetics, pharmacodynamics, formulation and safety. Such data integration and the powerful combination of physiologically based pharmacokinetic (PBPK) with pharmacokinetic–pharmacodynamic relationship (PK/PD) models provides the basis for quantitative outputs allowing comparisons across compounds and resulting in improved decision-making during the selection process. Such PBPK/PD evaluations provide crucial information on the potency and safety of drug candidates in vivo and the bridging of the PK/PD concept established during the pre-clinical phase to clinical studies. Modelling and simulation is required to address a number of key questions at the various stages of the drug-discovery and -development process. Such questions include the following. (1) What is the expected human PK profile for potential clinical candidate(s)? (2) Is this profile and its associated PD adequate for the given indication? (3) What is the optimal dosing schedule with respect to safety and efficacy? (4) Is a food effect expected? (5) How can formulation be improved and what is the potential benefit? (6) What is the expected variability and uncertainty in the predictions?     

Impact of Acid-Reducing Agents on Gastrointestinal Physiology and Design of Biorelevant Dissolution Tests to Reflect These Changes

BackgroundOf the various drug therapies that influence gastrointestinal (GI) physiology, one of the most important are the acid-reducing agents (ARAs). Because changes in GI physiology often influence the pharmacokinetics of drugs given orally, there is a need to identify in vitro methods with which such effects can be elucidated.ObjectiveLiterature concerning the effects of ARAs (antacids, H₂-receptor antagonists, and proton pump inhibitors [PPIs]) on GI physiology are reviewed with the aim of identifying conditions under which drugs are released after oral administration in the fasted state. In vitro dissolution tests to mimic the effects in the stomach were designed for H₂-receptor antagonists and PPIs.ConclusionsThe impact of ARAs on GI physiology depends on the type, duration, and amount of ARA administered as well as the location in the GI tract, with greatest impact on gastric physiology. While ARAs have a high impact on the gastric fluid pH and composition, changes in volume, viscosity, surface tension, and gastric emptying appear to be less profound. The proposed dissolution tests enable a ready comparison between dosage form performance in healthy adults and those receiving PPIs or H₂-receptor antagonists.     

A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein‐bound drugs and the impact of errors in plasma protein binding

Predicting the pharmacokinetics of highly protein‐bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration–time profiles for 22 highly protein‐bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well‐stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration–time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2‐fold error was obtained for the terminal elimination half‐life (t_1/2, 100% of drugs), peak plasma concentration (C_max, 100%), area under the plasma concentration–time curve (AUC_0‐t, 95.4%), clearance (CL_h, 95.4%), mean residence time (MRT, 95.4%) and steady state volume (V_ss, 90.9%). The impact of f_up errors on CL_h and V_ss prediction was evaluated. Errors in f_up resulted in proportional errors in clearance prediction for low‐clearance compounds, and in V_ss prediction for high‐volume neutral drugs. For high‐volume basic drugs, errors in f_up did not propagate to errors in V_ss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd.     

Verification of a physiologically based pharmacokinetic model of ritonavir to estimate drug–drug interaction potential of CYP3A4 substrates

Ritonavir is one of several ketoconazole alternatives used to evaluate strong CYP3A4 inhibition potential in clinical drug–drug interaction (DDI) studies. In this study, four physiologically based pharmacokinetic (PBPK) models of ritonavir as an in vivo time‐dependent inhibitor of CYP3A4 were created and verified for oral doses of 20, 50, 100 and 200 mg using the fraction absorbed (F_a) and oral clearance (CL_oral) values reported in the literature, because transporter and CYP enzyme reaction phenotyping data were not available. The models were used subsequently to predict and compare the magnitude of the AUC increase in nine reference DDI studies evaluating the effect of ritonavir at steady‐state on midazolam (CYP3A4 substrate) exposure. Midazolam AUC and C_max ratios were predicted within 2‐fold of the respective observations in seven studies. Simulations of the hepatic and gut CYP3A4 abundance after multiple oral dosing of ritonavir indicated that a 3‐day treatment with ritonavir 100 mg twice daily is sufficient to reach maximal CYP3A4 inhibition and subsequent systemic exposure increase of a CYP3A4 substrate, resulting in the reliable estimation of f_m,CYP3A4. The ritonavir model was submitted as part of the new drug application for Kisqali® (ribociclib) and accepted by health authorities.     

Fifty-Eight Years and Counting: High-Impact Publishing in Computational Pharmaceutical Sciences and Mechanism-Based Modeling

With this issue of the Journal of Pharmaceutical Sciences, we celebrate the nearly 6 decades of contributions to mechanistic-based modeling and computational pharmaceutical sciences. Along with its predecessor, The Journal of the American Pharmaceutical Association: Scientific Edition first published in 1911, JPharmSci has been a leader in the advancement of pharmaceutical sciences beginning with its inaugural edition in 1961. As one of the first scientific journals focusing on pharmaceutical sciences, JPharmSci has established a reputation for publishing high-quality research articles using computational methods and mechanism-based modeling. The journal’s publication record is remarkable. With over 15,000 articles, 3000 notes, and more than 650 reviews from industry, academia, and regulatory agencies around the world, JPharmSci has truly been the leader in advancing pharmaceutical sciences.     

Mechanistic Physiologically Based Pharmacokinetic Modeling of the Dissolution and Food Effect of a Biopharmaceutics Classification System IV Compound—The Venetoclax Story

Venetoclax, a selective B-cell lymphoma-2 inhibitor, is a biopharmaceutics classification system class IV compound. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to mechanistically describe absorption and disposition of an amorphous solid dispersion formulation of venetoclax in humans. A mechanistic PBPK model was developed incorporating measured amorphous solubility, dissolution, metabolism, and plasma protein binding. A middle-out approach was used to define permeability. Model predictions of oral venetoclax pharmacokinetics were verified against clinical studies of fed and fasted healthy volunteers, and clinical drug interaction studies with strong CYP3A inhibitor (ketoconazole) and inducer (rifampicin). Model verification demonstrated accurate prediction of the observed food effect following a low-fat diet. Ratios of predicted versus observed C_max and area under the curve of venetoclax were within 0.8- to 1.25-fold of observed ratios for strong CYP3A inhibitor and inducer interactions, indicating that the venetoclax elimination pathway was correctly specified. The verified venetoclax PBPK model is one of the first examples mechanistically capturing absorption, food effect, and exposure of an amorphous solid dispersion formulated compound. This model allows evaluation of untested drug-drug interactions, especially those primarily occurring in the intestine, and paves the way for future modeling of biopharmaceutics classification system IV compounds.     

Prediction of Phase I single-dose pharmacokinetics using recombinant cytochromes P450 and physiologically based modelling

1. Ten compounds from the Merck Research Laboratories pipeline were selected to evaluate the utility of using intrinsic clearance derived from recombinantly expressed cytochromes P450 (CYP) and physiologically based pharmacokinetic modelling to predict Phase I pharmacokinetics using simCYP. The compounds selected were anticipated to be eliminated predominantly by P450 metabolism.

2. There was a reasonable agreement between the predicted and actual clinical exposure with 80% of the predicted exposures being within three-fold of the observed values. Furthermore, prediction of C(t) (plasma concentration at a specified time point) and T_max were acceptable with greater than or equal to 70% of the predicted data being within three-fold of the observed values. However, prediction of C_max was unreliable and may have been due to error in predicting the time-dependent change in volume of distribution and/or error in estimating absorption rate.

3. Although it is acknowledged that research is needed to improve predictive performance, the data presented are supportive of using recombinant P450 intrinsic clearance and physiologically based pharmacokinetic modelling to predict Phase I pharmacokinetics for compounds eliminated by P450 metabolism.

     

Preincubation With Everolimus and Sirolimus Reduces Organic Anion-Transporting Polypeptide (OATP)1B1- and 1B3-Mediated Transport Independently of mTOR Kinase Inhibition: Implication in Assessing OATP1B1- and OATP1B3-Mediated Drug-Drug Interactions

Organic anion transporting polypeptides (OATP)1B1 and OATP1B3 mediate hepatic uptake of many drugs including lipid-lowering statins. Current studies determined the OATP1B1/1B3-mediated drug-drug interaction (DDI) potential of mammalian target of rapamycin (mTOR) inhibitors, everolimus and sirolimus, using R-value and physiologically based pharmacokinetic models. Preincubation with everolimus and sirolimus significantly decreased OATP1B1/1B3-mediated transport even after washing and decreased inhibition constant values up to 8.3- and 2.9-fold for OATP1B1 and both 2.7-fold for OATP1B3, respectively. R-values of everolimus, but not sirolimus, were greater than the FDA-recommended cutoff value of 1.1. Physiologically based pharmacokinetic models predict that everolimus and sirolimus have low OATP1B1/1B3-mediated DDI potential against pravastatin. OATP1B1/1B3-mediated transport was not affected by preincubation with INK-128 (10 μM, 1 h), which does however abolish mTOR kinase activity. The preincubation effects of everolimus and sirolimus on OATP1B1/1B3-mediated transport were similar in cells before preincubation with vehicle control or INK-128, suggesting that inhibition of mTOR activity is not a prerequisite for the preincubation effects observed for everolimus and sirolimus. Nine potential phosphorylation sites of OATP1B1 were identified by phosphoproteomics; none of these are the predicted mTOR phosphorylation sites. We report the everolimus/sirolimus-preincubation-induced inhibitory effects on OATP1B1/1B3 and relatively low OATP1B1/1B3-mediated DDI potential of everolimus and sirolimus.     

A Physiologic Model for Simulating Gastrointestinal Flow and Drug Absorption in Rats

PURPOSE: The development of a physiologically based absorption model for orally administered drugs in rats is described. METHODS: Unlike other models that use a multicompartmental approach, the GI tract is modeled as a continuous tube with spatially varying properties. The mass transport through the intestinal lumen is described via an intestinal transit function. The only substance-specific input parameters of the model are the intestinal permeability coefficient and the solubility in the intestinal fluid. With this physiologic and physicochemical information, the complete temporal and spatial absorption profile can be calculated. RESULTS: A first performance test using portal concentration data published in the literature yielded an excellent agreement between measured and simulated temporal absorption profiles in the portal vein. Furthermore, the dose dependence of a compound with solubility-limited fraction dose absorbed in rats (chlorothiazide) could be adequately described by the model. CONCLUSIONS: The continuous absorption model is well suited to simulate drug flow and absorption in the GI tract of rats.     

A physiologically based pharmacokinetic/pharmacodynamic modeling approach for drug-drug interaction evaluation of warfarin enantiomers with sorafenib

Sorafenib was suggested to cause drug-drug interaction (DDI) with the common anticoagulant, warfarin based on published studies. The inhibition on CYP2C9 enzyme was thought to be the mechanism, but further studies are warranted. Thus, a mechanistic PBPK/PD model for warfarin enantiomers was developed to predict DDI potential with sorafenib, aiming at providing reference for the rational use of both drugs.PBPK models of warfarin enantiomers were constructed by Simcyp software. A mechanistic PK/PD model was built in NONMEM software. PBPK model of sorafenib was fitted via a top-down method. The final PBPK/PD model of warfarin enantiomers was verified and validated by different dosing regimens, ethnicities and genetic polymorphisms, and used to perform DDI simulations between warfarin racemate and sorafenib among general populations and sub-populations with various CYP2C9 and VKORC1 genotypes. Results suggested low DDI risk between warfarin and sorafenib for general populations. Potentially serious consequence was seen for those carrying both CYP2C9 12 and 13 and VKORC1 A/A genotypes.This PBPK/PD modeling approach for warfarin enantiomers enabled DDI evaluation with sorafenib. Close monitoring and warfarin dosage adjustment were recommended for patients carrying mutant genotypes. The novel model could be applied to investigate other drugs that may interact with warfarin.     

Differential pharmacokinetic drug-drug interaction potential of eletriptan between oral and subcutaneous routes

Abstract

1. Pharmacokinetic drug-drug interaction (DDI) data is important from a label claim either in combination drug usage or in polypharmacy situation.

2. Eletriptan undergoes first pass related metabolism through CYP3A4 enzyme to form pharmacologically active N-desmethyl metabolite.

3. Differential DDI interaction of the concomitant oral dosing of ketoconazole (20.1?mg/kg), a CYP3A4 inhibitor, with oral (4.2?mg/kg) or subcutaneous dose (2.1?mg/kg) of eletriptan was evaluated in male Sprague Dawley rats. Serial pharmacokinetic samples were collected and simultaneously analysed for eletriptan/N-desmethyl eletriptan using validated assay. Non-compartmentally derived pharmacokinetic parameters for various treatments were analysed statistically.

4. After oral eletriptan in presence of ketoconazole, C_max (40 vs. 32?ng/mL alone) and AUC_inf (81 vs. 24?ng.h/mL alone) of eletriptan increased; the formation of N-desmethyl eletriptan decreased (C_max=1.1?ng/mL, 3.9%) with ketoconazole as compared to without treatment (C_max=3.7?ng/mL, 11.2%). After subcutaneous eletriptan in presence of ketoconazole, there was no change in C_max (153 vs.152?ng/mL) or AUC_inf (267 vs. 266?ng.h/mL) of eletriptan. Formation of N-desmethyl eletriptan after the subcutaneous dose was determined at few intermittent time points with/without ketoconazole.

5. Preclinical data support differential DDI of eletriptan when dosed oral vs. subcutaneous, which need to be evaluated in a clinical setting.     

Whole‐body physiologically based pharmacokinetic population modelling of oral drug administration: inter‐individual variability of cimetidine absorption

Objectives Inter‐individual variability of gastrointestinal physiology and transit properties can greatly influence the pharmacokinetics of an orally administered drug in vivo. To predict the expected range of pharmacokinetic plasma concentrations after oral drug administration, a physiologically based pharmacokinetic population model for gastrointestinal transit and absorption was developed and evaluated. Methods Mean values and variability measures of model parameters affecting the rate and extent of cimetidine absorption, such as gastric emptying, intestinal transit times and effective surface area of the small intestine, were obtained from the literature. Various scenarios incorporating different extents of inter‐individual physiological variability were simulated and the simulation results were compared with experimental human study data obtained after oral cimetidine administration of four different tablets with varying release kinetics. Key findings The inter‐individual variability in effective surface area was the largest contributor to absorption variability. Based on in‐vitro dissolution profiles, the mean plasma cimetidine concentration–time profiles as well as the inter‐individual variability could be well described for three cimetidine formulations. In the case of the formulation with the slowest dissolution kinetic, model predictions on the basis of the in‐vitro dissolution profile underestimated the plasma exposure. Conclusions The model facilitates predictions of the inter‐individual pharmacokinetic variability after oral drug administration for immediate and extended‐release formulations of cimetidine, given reasonable in‐vitro dissolution kinetics.     

Advances and challenges in PBPK modeling – Analysis of factors contributing to the oral absorption of atazanavir,a poorly soluble weak base

Many active pharmaceutical ingredients (APIs) exhibit a highly variable pharmacokinetic (PK) profile. This behavior may be attributable to pre-absorptive, absorptive and/or post-absorptive factors. Pre-absorptive factors are those related to dosage form disintegration, drug dissolution, supersaturation, precipitation and gastric emptying. Absorptive factors are involved with drug absorption and efflux mechanisms, while drug distribution and clearance are post-absorptive factors. This study aimed to investigate the relative influence of the aforementioned parameters on the pharmacokinetic profile of atazanavir, a poorly soluble weakly basic compound with highly variable pharmacokinetics. The pre-absorptive behavior of the drug was examined by applying biorelevant in vitro tests to reflect upper gastrointestinal behavior in the fasted and fed states. The in vitro results were implemented, along with permeability and post-absorptive data obtained from the literature, into physiologically based pharmacokinetic (PBPK) models. Sensitivity analysis of the resulting plasma profiles revealed that the pharmacokinetic profile of atazanavir is affected by an array of factors rather than one standout factor. According to the in silico model, pre-absorptive and absorptive factors had less impact on atazanavir bioavailability compared to post-absorptive parameters, although active drug efflux and extraction appear to account for the sub-proportional pharmacokinetic response to lower atazanavir doses in the fasted state. From the PBPK models it was concluded that further enhancement of the formulation would bring little improvement in the pharmacokinetic response to atazanavir. This approach may prove useful in assessing the potential benefits of formulation enhancement of other existing drug products on the market.