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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 (P mucosa ). 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 P mucosa 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 P mucosa 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 P mucosa 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 P mucosa must be considered as well., (© 2024 The Author(s). CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Elinzanetant is a potent and selective dual neurokin-1 (NK-1) and -3 (NK-3) receptor antagonist that is currently developed for the treatment of women with moderate-to-severe vasomotor symptoms (VMS) associated with menopause. Here, we report the development of a population pharmacokinetic (popPK) model for elinzanetant and its principal metabolites based on an integrated dataset from 366 subjects (including 197 women with VMS) collected in 10 phase I or II studies. The pharmacokinetics of elinzanetant and its metabolites could be well described by the popPK model. Within the investigated dose range of 40-160 mg, the oral bioavailability of elinzanetant was dose independent and estimated to be 36.7%. The clearance of elinzanetant was estimated to be 7.26 L/h and the central and peripheral distribution volume were 23.7 and 168 L. No intrinsic or extrinsic influencing factors have been identified in the investigated population other than the effect of a high-fat breakfast on the oral absorption of elinzanetant. The popPK model was then coupled to a pharmacodynamic model to predict occupancies of the NK-1 and NK-3 receptors. After repeated once-daily administration of the anticipated therapeutic dose of 120 mg elinzanetant, the model-predicted median receptor occupancies are >99% for NK-1 and >94.8% for NK-3 during day and night-time, indicating sustained and near-complete inhibition of both target receptors during the dosing interval., (© 2024 The Author(s). CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Since the Open Source Initiative laid the foundation for the open source software environment in 1998, the popularity of free and open source software has been steadily increasing. Model-informed drug discovery and development (MID3), a key component of pharmaceutical research and development, heavily makes use of computational models which can be developed using various software including the Open Systems Pharmacology (OSP) software (PK-Sim/MoBi), a free and open source software tool for physiologically based pharmacokinetic (PBPK) modeling. In this study, we aimed to investigate the impact, application areas, and reach of the OSP software as well as the relationships and collaboration patterns between organizations having published OSP-related articles between 2017 and 2023. Therefore, we conducted a bibliometric analysis of OSP-related publications and a social network analysis of the organizations with which authors of OSP-related publications were affiliated. On several levels, we found evidence for a significant growth in the size of the OSP community as well as its visibility in the MID3 community since OSP's establishment in 2017. Specifically, the annual publication rate of PubMed-indexed PBPK-related articles using the OSP software outpaced that of PBPK-related articles using any software. Our bibliometric analysis and network analysis demonstrated that the expansion of the OSP community was predominantly driven by new authors and organizations without prior connections to the community involving the generation of research clusters de novo and an overall diversification of the network. These findings suggest an ongoing evolution of the OSP community toward a more segmented, diverse, and inclusive network., (© 2024 The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals LLC on behalf of American College of Clinical Pharmacology.)

Objectives: Professional voice users depend on their voice for optimal performance of their profession. The aim of this study was to find out to what extent sucking a placebo and thyme represent an improvement of the voice in professional voice users after vocal loading., Methods: A randomized placebo-controlled clinical double-blind study was conducted with four measurement moments: a premeasurement, immediately after the vocal loading, after the subsequent ingestion of the "thymepearl" (TP) in the experimental group and in the control group the placebo, and after a half-hour break. Finally, 18 subjects were considered, 9 participants in each group., Results: No significant differences in the objective measurements of both groups could be observed. However, significant improvements in subjective measures (perceptions of dry mouth and feeling of hoarseness) could be observed after vocal loading by sucking the thymepearls in direct comparison to the placebo., Conclusions: Sucking the TP can improve subjective sensation after vocal loading compared with placebo, but no differences are seen on objective vocal measures., (Copyright © 2021 The Voice Foundation. Published by Elsevier Inc. All rights reserved.)

In the past, rifampicin was well-established as strong index CYP3A inducer in clinical drug-drug interaction (DDI) studies. However, due to identified potentially genotoxic nitrosamine impurities, it should not any longer be used in healthy volunteer studies. Available clinical data suggest carbamazepine as an alternative to rifampicin as strong index CYP3A4 inducer in clinical DDI studies. Further, physiologically-based pharmacokinetic (PBPK) modeling is a tool with increasing importance to support the DDI risk assessment of drugs during drug development. CYP3A4 induction properties and the safety profile of carbamazepine were investigated in two open-label, fixed sequence, crossover clinical pharmacology studies in healthy volunteers using midazolam as a sensitive index CYP3A4 substrate. Carbamazepine was up-titrated from 100 mg twice daily (b.i.d.) to 200 mg b.i.d., and to a final dose of 300 mg b.i.d. for 10 consecutive days. Mean area under plasma concentration-time curve from zero to infinity (AUC( 0-∞ )) of midazolam consistently decreased by 71.8% (ratio: 0.282, 90% confidence interval (CI): 0.235-0.340) and 67.7% (ratio: 0.323, 90% CI: 0.256-0.407) in study 1 and study 2, respectively. The effect was adequately described by an internally developed PBPK model for carbamazepine which has been made freely available to the scientific community. Further, carbamazepine was safe and well-tolerated in the investigated dosing regimen in healthy participants. The results demonstrated that the presented design is appropriate for the use of carbamazepine as alternative inducer to rifampicin in DDI studies acknowledging its CYP3A4 inductive potency and safety profile., (© 2023 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Vericiguat (Verquvo; US: Merck, other countries: Bayer) is a novel drug for the treatment of chronic heart failure. Preclinical studies have demonstrated that the primary route of metabolism for vericiguat is glucuronidation, mainly catalyzed by uridine diphosphate-glucuronosyltransferase (UGT)1A9 and to a lesser extent UGT1A1. Whereas a drug-drug interaction (DDI) study of the UGT1A9 inhibitor mefenamic acid showed a 20% exposure increase, the effect of UGT1A1 inhibitors has not been assessed clinically. This modeling study describes a physiologically-based pharmacokinetic (PBPK) approach to complement the clinical DDI liability assessment and support prescription labeling. A PBPK model of vericiguat was developed based on in vitro and clinical data, verified against data from the mefenamic acid DDI study, and applied to assess the UGT1A1 DDI liability by running an in silico DDI study with the UGT1A1 inhibitor atazanavir. A minor effect with an area under the plasma concentration-time curve (AUC) ratio of 1.12 and a peak plasma concentration ratio of 1.04 was predicted, which indicates that there is no clinically relevant DDI interaction anticipated. Additionally, the effect of potential genetic polymorphisms of UGT1A1 and UGT1A9 was evaluated, which showed that an average modest increase of up to 1.7-fold in AUC may be expected in the case of concomitantly reduced UGT1A1 and UGT1A9 activity for subpopulations expressing non-wild-type variants for both isoforms. This study is a first cornerstone to qualify the PK-Sim platform for use of UGT-mediated DDI predictions, including PBPK models of perpetrators, such as mefenamic acid and atazanavir, and sensitive UGT substrates, such as dapagliflozin and raltegravir., (© 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Due to the strong tendency towards poorly soluble drugs in modern development pipelines, enabling drug formulations such as amorphous solid dispersions, cyclodextrins, co-crystals and lipid-based formulations are frequently applied to solubilize or generate supersaturation in gastrointestinal fluids, thus enhancing oral drug absorption. Although many innovative in vitro and in silico tools have been introduced in recent years to aid development of enabling formulations, significant knowledge gaps still exist with respect to how best to implement them. As a result, the development strategy for enabling formulations varies considerably within the industry and many elements of empiricism remain. The InPharma network aims to advance a mechanistic, animal-free approach to the assessment of drug developability. This commentary focuses current status and next steps that will be taken in InPharma to identify and fully utilize 'best practice' in vitro and in silico tools for use in physiologically based biopharmaceutic models., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P-glycoprotein (P-gp) and is therefore recommended for use in clinical drug-drug interaction (DDI) studies. However, as quinidine is also a substrate of CYP3A4 and P-gp, it is susceptible to DDIs involving these proteins. Physiologically-based pharmacokinetic (PBPK) modeling can help to mechanistically assess the absorption, distribution, metabolism, and excretion processes of a drug and has proven its usefulness in predicting even complex interaction scenarios. The objectives of the presented work were to develop a PBPK model of quinidine and to integrate the model into a comprehensive drug-drug(-gene) interaction (DD(G)I) network with a diverse set of CYP3A4 and P-gp perpetrators as well as CYP2D6 and P-gp victims. The quinidine parent-metabolite model including 3-hydroxyquinidine was developed using pharmacokinetic profiles from clinical studies after intravenous and oral administration covering a broad dosing range (0.1-600 mg). The model covers efflux transport via P-gp and metabolic transformation to either 3-hydroxyquinidine or unspecified metabolites via CYP3A4. The 3-hydroxyquinidine model includes further metabolism by CYP3A4 as well as an unspecific hepatic clearance. Model performance was assessed graphically and quantitatively with greater than 90% of predicted pharmacokinetic parameters within two-fold of corresponding observed values. The model was successfully used to simulate various DD(G)I scenarios with greater than 90% of predicted DD(G)I pharmacokinetic parameter ratios within two-fold prediction success limits. The presented network will be provided to the research community and can be extended to include further perpetrators, victims, and targets, to support investigations of DD(G)Is., (© 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The immunosuppressant and narrow therapeutic index drug tacrolimus is metabolized mainly via cytochrome P450 (CYP) 3A4 and CYP3A5. For its pharmacokinetics (PK), high inter- and intra-individual variability can be observed. Underlying causes include the effect of food intake on tacrolimus absorption as well as genetic polymorphism in the CYP3A5 gene. Furthermore, tacrolimus is highly susceptible to drug-drug interactions, acting as a victim drug when coadministered with CYP3A perpetrators. This work describes the development of a whole-body physiologically based pharmacokinetic model for tacrolimus as well as its application for investigation and prediction of (i) the impact of food intake on tacrolimus PK (food-drug interactions [FDIs]) and (ii) drug-drug(-gene) interactions (DD[G]Is) involving the CYP3A perpetrator drugs voriconazole, itraconazole, and rifampicin. The model was built in PK-Sim® Version 10 using a total of 37 whole blood concentration-time profiles of tacrolimus (training and test) compiled from 911 healthy individuals covering the administration of tacrolimus as intravenous infusions as well as immediate-release and extended-release capsules. Metabolism was incorporated via CYP3A4 and CYP3A5, with varying activities implemented for different CYP3A5 genotypes and study populations. The good predictive model performance is demonstrated for the examined food effect studies with 6/6 predicted FDI area under the curve determined between first and last concentration measurements (AUC last ) and 6/6 predicted FDI maximum whole blood concentration (C max ) ratios within twofold of the respective observed ratios. In addition, 7/7 predicted DD(G)I AUC last and 6/7 predicted DD(G)I C max ratios were within twofold of their observed values. Potential applications of the final model include model-informed drug discovery and development or the support of model-informed precision dosing., (© 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Modeling and simulation emerges as a fundamental asset of drug development. Mechanistic modeling builds upon its strength to integrate various data to represent a detailed structural knowledge of a physiological and biological system and is capable of informing numerous drug development and regulatory decisions via extrapolations outside clinically studied scenarios. Herein, physiologically based pharmacokinetic (PBPK) modeling is the fastest growing branch, and its use for particular applications is already expected or explicitly recommended by regulatory agencies. Therefore, appropriate applications of PBPK necessitates trust in the predictive capability of the tool, the underlying software platform, and related models. That has triggered a discussion on concepts of ensuring credibility of model-based derived conclusions. Questions like 'why', 'when', 'what', 'how' and 'by whom' remain open. We seek for harmonization of recent ideas, perceptions, and related terminology. First, we provide an overview on quality assurance of PBPK platforms with the two following concepts. Platform validation: ensuring software integrity, security, traceability, correctness of mathematical models and accuracy of algorithms. Platform qualification: demonstrating the predictive capability of a PBPK platform within a particular context of use. Second, we provide guidance on executing dedicated PBPK studies. A step-by-step framework focuses on the definition of the question of interest, the context of use, the assessment of impact and risk, the definition of the modeling strategy, the evaluation of the platform, performing model development including model building, evaluation and verification, the evaluation of applicability to address the question, and the model application under the umbrella of a qualified platform., (© 2022. The Author(s).)

Finerenone is a nonsteroidal, selective mineralocorticoid receptor antagonist that recently demonstrated its efficacy to delay chronic kidney disease (CKD) progression and reduce cardiovascular events in patients with CKD and type 2 diabetes. Here, we report the development of a physiologically-based pharmacokinetic (PBPK) model for finerenone and its application as a victim drug of cytochrome P450 3A4 (CYP3A4)-mediated drug-drug interactions (DDIs) using the open-source PBPK platform PK-Sim, which has recently been qualified for this application purpose. First, the PBPK model for finerenone was developed using physicochemical, in vitro, and clinical (including mass balance) data. Subsequently, the finerenone model was validated regarding the contribution of CYP3A4 metabolism to total clearance by comparing to observed data from dedicated clinical interaction studies with erythromycin (simulated geometric mean ratios of the area under the plasma concentration-time curve [AUCR] of 3.46 and geometric mean peak plasma concentration ratios [C max Rs] of 2.00 vs. observed of 3.48 and 1.88, respectively) and verapamil (simulated AUCR of 2.91 and C max R of 1.86 vs. observed of 2.70 and 2.22, respectively). Finally, the finerenone model was applied to predict clinically untested DDI studies with various CYP3A4 modulators. An AUCR of 6.31 and a C max R of 2.37 was predicted with itraconazole, of 5.28 and 2.25 with clarithromycin, 1.59 and 1.40 with cimetidine, 1.57 and 1.38 with fluvoxamine, 0.19 and 0.32 with efavirenz, and 0.07 and 0.14 with rifampicin. This PBPK analysis provides a quantitative basis to guide the label and clinical use of finerenone with concomitant CYP3A4 modulators., (© 2021 Bayer AG. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Development and guidance of dosing schemes in children have been supported by physiology-based pharmacokinetic (PBPK) modeling for many years. PBPK models are built on a generic basis, where compound- and system-specific parameters are separated and can be exchanged, allowing the translation of these models from adults to children by accounting for physiological differences. Owing to these features, PBPK modeling is a valuable approach to support clinical decision making for dosing in children. In this analysis, we evaluate pediatric PBPK models for 10 small-molecule compounds that were applied to support clinical decision processes at Bayer for their predictive power in different age groups. Ratios of PBPK-predicted to observed PK parameters for the evaluated drugs in different pediatric age groups were estimated. Predictive performance was analyzed on the basis of a 2-fold error range and the bioequivalence range (ie, 0.8 ≤ predicted/observed ≤ 1.25). For all 10 compounds, all predicted-to-observed PK ratios were within a 2-fold error range (n = 27), with two-thirds of the ratios within the bioequivalence range (n = 18). The findings demonstrate that the pharmacokinetics of these compounds was successfully and adequately predicted in different pediatric age groups. This illustrates the applicability of PBPK for guiding dosing schemes in the pediatric population., (© 2021 The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals LLC on behalf of American College of Clinical Pharmacology.)

The success of applications of physiologically-based pharmacokinetic (PBPK) modeling in drug development and drug labeling has triggered regulatory agencies to demand rigorous demonstration of the predictive capability of the specific PBPK platform for a particular intended application purpose. The effort needed to comply with such qualification requirements exceeds the costs for any individual PBPK application. Because changes or updates of a PBPK platform would require (re-)qualification, a reliable and efficient generic qualification framework is needed. We describe the development and implementation of an agile and sustainable technical framework for automatic PBPK platform (re-)qualification of PK-Sim ® embedded in the open source and open science GitHub landscape of Open Systems Pharmacology. The qualification approach enables the efficient assessment of all aspects relevant to the qualification of a particular purpose and provides transparency and traceability for all stakeholders. As a showcase example for the power and versatility of the qualification framework, we present the qualification of PK-Sim ® for the intended purpose of predicting cytochrome P450 3A4 (CYP3A4)-mediated drug-drug interactions (DDIs). Several perpetrator PBPK models featuring various degrees of CYP3A4 modulation and different types of mechanisms (competitive inhibition, mechanism-based inactivation, and induction) were coupled with a set of PBPK models of sensitive CYP3A4 victim drugs. Simulations were compared to a comprehensive data set of 135 observations from published clinical DDI studies. The platform's overall predictive performance showed reasonable accuracy and precision (geometric mean fold error of 1.4 for both area under the plasma concentration-time curve ratios and peak plasma concentration ratios with/without perpetrator) and suggests that PK-Sim ® can be applied to quantitatively assess CYP3A4-mediated DDI in clinically untested scenarios., (© 2021 Pharmacometrics/Modeling & Simulation, Research & Development, Pharmaceuticals, Bayer AG. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The extent of a drug-drug interaction (DDI) mediated by cytochrome P450 (CYP) 3A inhibitors is highly variable during a dosing interval, as it depends on the temporal course of victim and perpetrator drug concentrations at intestinal and hepatic CYP3A expression sites. Capturing the time course of inhibition is therefore difficult using standard DDI studies assessing changes in area under the curve; thus, a novel design was developed. In a 4-period changeover pilot study, 6 healthy men received intraduodenal or intravenous infusions of the CYP3A substrate midazolam (MDZ) at a rate of 0.26 mg/h for 24 hours. This was combined with intraduodenal or intravenous infusion of the CYP3A inhibitor voriconazole (VRZ), administered at rates of 7.5 mg/h from 8 to 16 hours and of 15 mg/h from 16 to 24 hours, after starting midazolam administration. Plasma and urine concentrations of VRZ, MDZ, and its major metabolites were quantified by liquid chromatography-tandem mass spectrometry and analyzed by semiphysiological population pharmacokinetic nonlinear mixed-effects modeling. A model including mechanism-based inactivation of the metabolizing enzymes (maximum inactivation rate constant k inact , 2.83 h -1 ; dissociation rate constant K I , 9.33 μM) described the pharmacokinetics of VRZ well. By introducing competitive inhibition by VRZ on primary and secondary MDZ metabolism, concentration-time profiles, MDZ and its metabolites were captured appropriately. The model provides estimates of local concentrations of substrate and inhibitor at the major CYP3A expression sites and thus of the respective dynamic extent of inhibition. A combination of intravenous and intraduodenal infusions of inhibitors and substrates has the potential to provide a more accurate assessment of DDIs occurring in both gut wall and liver., (© 2020 The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals LLC on behalf of American College of Clinical Pharmacology.)

Background: Treatment of patients with solid tumors and KRAS mutations remains disappointing. One option is the combined inhibition of pathways involved in RAF-MEK-ERK and PI3K-AKT-mTOR., Methods: Patients with relapsed solid tumors were treated with escalating doses of everolimus (E) 2.5-10.0 mg/d in a 14-day run-in phase followed by combination therapy with sorafenib (S) 800 mg/d from day 15. KRAS mutational status was assessed retrospectively in the escalation phase. Extension phase included KRAS-mutated non-small-cell lung cancer (NSCLC) only. Pharmacokinetic analyses were accompanied by pharmacodynamics assessment of E by FDG-PET. Efficacy was assessed by CT scans every 6 weeks of combination., Results: Of 31 evaluable patients, 15 had KRAS mutation, 4 patients were negative for KRAS mutation, and the KRAS status remained unknown in 12 patients. Dose-limiting toxicity (DLT) was not reached. The maximum tolerated dose (MTD) was defined as 7.5 mg/d E + 800 mg/d S due to toxicities at previous dose level (10 mg/d E + 800 mg/d S) including leucopenia/thrombopenia III° and pneumonia III° occurring after the DLT interval. The metabolic response rate in FDG-PET was 17% on day 5 and 20% on day 14. No patient reached partial response in CT scan. Median progression free survival (PFS) and overall survival (OS) were 3.25 and 5.85 months, respectively., Conclusions: Treatment of patients with relapsed solid tumors with 7.5 mg/d E and 800 mg/d S is safe and feasible. Early metabolic response in FDG-PET was not confirmed in CT scan several weeks later. The combination of S and E is obviously not sufficient to induce durable responses in patients with KRAS-mutant solid tumors., (© 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Voriconazole, a first-line antifungal drug, exhibits nonlinear pharmacokinetics (PK), together with large interindividual variability but a narrow therapeutic range, and markedly inhibits cytochrome P450 (CYP) 3A4 in vivo. This causes difficulties in selecting appropriate dosing regimens of voriconazole and coadministered CYP3A4 substrates., Objective: This study aimed to investigate the metabolism of voriconazole in detail to better understand dose- and time-dependent alterations in the PK of the drug, to provide the model basis for safe and effective use according to CYP2C19 genotype, and to assess the potential of voriconazole to cause drug-drug interactions (DDIs) with CYP3A4 substrates in more detail., Methods: In vitro assays were carried out to explore time-dependent inhibition (TDI) of CYP3A4 by voriconazole. These results were combined with 93 published concentration-time datasets of voriconazole from clinical trials in healthy volunteers to develop a whole-body physiologically based PK (PBPK) model in PK-Sim ® . The model was evaluated quantitatively with the predicted/observed ratio of the area under the plasma concentration-time curve (AUC), maximum concentration (C max ), and trough concentrations for multiple dosings (C trough ), the geometric mean fold error, as well as visually with the comparison of predicted with observed concentration-time datasets over the full range of recommended intravenous and oral dosing regimens., Results: The result of the half maximal inhibitory concentration (IC 50 ) shift assay indicated that voriconazole causes TDI of CYP3A4. The PBPK model evaluation demonstrated a good performance of the model, with 71% of predicted/observed aggregate AUC ratios and all aggregate C max ratios from 28 evaluation datasets being within a 0.5- to 2-fold range. For those studies reporting CYP2C19 genotype, 89% of aggregate AUC ratios and all aggregate C max ratios were inside a 0.5- to 2-fold range of 44 test datasets. The results of model-based simulations showed that the standard oral maintenance dose of voriconazole 200 mg twice daily would be sufficient for CYP2C19 intermediate metabolizers (IMs; *1/*2, *1/*3, *2/*17, and *2/*2/*17) to reach the tentative therapeutic range of > 1-2 mg/L to < 5-6 mg/L for C trough , while 400 mg twice daily might be more suitable for rapid metabolizers (RMs; *1/*17, *17/*17) and normal metabolizers (NMs; *1/*1). When the model was integrated with independently developed CYP3A4 substrate models (midazolam and alfentanil), the observed AUC change of substrates by voriconazole was inside the 90% confidence interval of the predicted AUC change, indicating that CYP3A4 inhibition was appropriately incorporated into the voriconazole model., Conclusions: Both the in vitro assay and model-based simulations support TDI of CYP3A4 by voriconazole as a pivotal characteristic of this drug's PK. The PBPK model developed here could support individual dose adjustment of voriconazole according to genetic polymorphisms of CYP2C19, and DDI risk management. The applicability of modeling results for patients remains to be confirmed in future studies.

Background: Drug-drug interactions (DDIs) and drug-gene interactions (DGIs) pose a serious health risk that can be avoided by dose adaptation. These interactions are investigated in strictly controlled setups, quantifying the effect of one perpetrator drug or polymorphism at a time, but in real life patients frequently take more than two medications and are very heterogenous regarding their genetic background., Objectives: The first objective of this study was to provide whole-body physiologically based pharmacokinetic (PBPK) models of important cytochrome P450 (CYP) 2C8 perpetrator and victim drugs, built and evaluated for DDI and DGI studies. The second objective was to apply these models to describe complex interactions with more than two interacting partners., Methods: PBPK models of the CYP2C8 and organic-anion-transporting polypeptide (OATP) 1B1 perpetrator drug gemfibrozil (parent-metabolite model) and the CYP2C8 victim drugs repaglinide (also an OATP1B1 substrate) and pioglitazone were developed using a total of 103 clinical studies. For evaluation, these models were applied to predict 34 different DDI studies, establishing a CYP2C8 and OATP1B1 PBPK DDI modeling network., Results: The newly developed models show a good performance, accurately describing plasma concentration-time profiles, area under the plasma concentration-time curve (AUC) and maximum plasma concentration (C max ) values, DDI studies as well as DGI studies. All 34 of the modeled DDI AUC ratios (AUC during DDI/AUC control) and DDI C max ratios (C max during DDI/C max control) are within twofold of the observed values., Conclusions: Whole-body PBPK models of gemfibrozil, repaglinide, and pioglitazone have been built and qualified for DDI and DGI prediction. PBPK modeling is applicable to investigate complex interactions between multiple drugs and genetic polymorphisms.

Food and Drug Administration submissions of physiologically based pharmacokinetic (PBPK) modeling and simulation of small-molecule drugs document the relevance of pediatric drug development and, in particular, information on dosing strategies in children. The most relevant prerequisite for reliable PBPK-based translation of adult pharmacokinetics of a small molecule to children is knowledge of the drug-specific absorption, distribution, metabolism, and elimination (ADME) processes in adults together with existing information about ontogeny of ADME processes relevant for the drug. All mechanisms driving a drug's clearance are of specific importance. For other drug modalities, our knowledge of ADME processes and ontogeny is still limited. More research is required, for example, to understand why some therapeutic proteins show complex differences in pharmacokinetics between adults and children, whereas other proteins seem to follow simple allometric scaling rules. Ontogeny information originates from various sources, such as (semi)quantitative mRNA expression, in vitro activity data, and deconvolution of in vivo pharmacokinetic data. The workflow for pediatric predictions is well described in several articles documenting successful translation from adults to children. The technical hurdles for PBPK modeling are low. State-of-the-art PBPK modeling software tools provide integrated pediatric translation workflows. For example, PK-Sim and MoBi are freely available as fully transparent open-source software via Open Systems Pharmacology (OSP). With the latest 2019 software release, version 8.0, OSP even provides a fully integrated technical framework for the qualification (and requalification) of any specific intended PBPK use in line with Food and Drug Administration and European Medicines Agency PBPK guidance. Qualification packages for pediatric translation are available on the OSP platform., (© 2019, The American College of Clinical Pharmacology.)

This study provides whole-body physiologically-based pharmacokinetic models of the strong index cytochrome P450 (CYP)1A2 inhibitor and moderate CYP3A4 inhibitor fluvoxamine and of the sensitive CYP1A2 substrate theophylline. Both models were built and thoroughly evaluated for their application in drug-drug interaction (DDI) prediction in a network of perpetrator and victim drugs, combining them with previously developed models of caffeine (sensitive index CYP1A2 substrate), rifampicin (moderate CYP1A2 inducer), and midazolam (sensitive index CYP3A4 substrate). Simulation of all reported clinical DDI studies for combinations of these five drugs shows that the presented models reliably predict the observed drug concentrations, resulting in seven of eight of the predicted DDI area under the plasma curve (AUC) ratios (AUC during DDI/AUC control) and seven of seven of the predicted DDI peak plasma concentration (C max ) ratios (C max during DDI/C max control) within twofold of the observed values. Therefore, the models are considered qualified for DDI prediction. All models are comprehensively documented and publicly available, as tools to support the drug development and clinical research community., (© 2019 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Aims: The primary aim of the present study was to quantify the effects of rifampicin, a strong cytochrome P450 (CYP) 3A4 inducer, on the pharmacokinetics of the new selective progesterone receptor modulator, vilaprisan. In addition, the effects of rifampicin on the glucuronidation of bilirubin, an endogenous UDP-glucuronosyltransferase family 1 member A1 (UGT1A1) substrate, were explored., Methods: This was an open-label, two-period study in 12 healthy postmenopausal women. Subjects received a single oral dose of vilaprisan 4 mg in each period. In period 2, administration of vilaprisan was preceded and followed by rifampicin 600 mg day -1 . A subtherapeutic dose of midazolam (1 mg) was coadministered with vilaprisan to monitor CYP3A4 induction. Details of the administration and sampling schedule were optimized by means of a physiologically based pharmacokinetic model. Plasma concentrations of vilaprisan, midazolam, and 1'- hydroxy-midazolam were measured and rifampicin-associated changes in the glucuronidation of bilirubin were determined., Results: As predicted by our model, the coadministration of rifampicin was associated with a substantial decrease in exposure to vilaprisan and midazolam - indicated by the following point estimates (90% confidence intervals) for the area under the plasma concentration-time curve from zero to the time of the last quantifiable concentration ratio with or without rifampicin: 0.040 (0.0325, 0.0505) for vilaprisan and 0.144 (0.117, 0.178) for midazolam. Further, it was associated with an increase in bilirubin glucuronidation, indicating that UGT1A1 was induced., Conclusions: The exposure to vilaprisan was reduced by 96%. Such a reduction is likely to render the drug therapeutically ineffective. Therefore, it is recommended that the use of strong CYP3A4 inducers is avoided when taking vilaprisan., (© 2018 The British Pharmacological Society.)

According to current US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidance documents, physiologically based pharmacokinetic (PBPK) modeling is a powerful tool to explore and quantitatively predict drug-drug interactions (DDIs) and may offer an alternative to dedicated clinical trials. This study provides whole-body PBPK models of rifampicin, itraconazole, clarithromycin, midazolam, alfentanil, and digoxin within the Open Systems Pharmacology (OSP) Suite. All models were built independently, coupled using reported interaction parameters, and mutually evaluated to verify their predictive performance by simulating published clinical DDI studies. In total, 112 studies were used for model development and 57 studies for DDI prediction. 93% of the predicted area under the plasma concentration-time curve (AUC) ratios and 94% of the peak plasma concentration (C max ) ratios are within twofold of the observed values. This study lays a cornerstone for the qualification of the OSP platform with regard to reliable PBPK predictions of enzyme-mediated and transporter-mediated DDIs during model-informed drug development. All presented models are provided open-source and transparently documented., (© 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Objectives: Insufficient linezolid levels, which are associated with a poorer outcome, are often observed in ICU patients who receive standard dosing. Although strategies to overcome these insufficient levels have been discussed, appropriate alternative dosing regimens remain to be identified., Methods: Various infusion regimens (1200-3600 mg/day; q6h, q8h, q12h and continuous) were simulated in 67 000 ICU patients. The probability of attaining pharmacodynamic targets ( T >MIC ≥85%, AUC/MIC ≥100, cumulative fraction of response for Staphylococcus aureus and Enterococcus spp., PTA for an MIC of 0.5-4 mg/L) as well as the avoidance of toxic concentrations and concentrations constantly below the MIC (lack of antibiotic effect) or inside a mutant selection window (resistance development) were evaluated., Results: Best target attainment according to T >MIC was observed for continuous infusions, followed by q6h, q8h and q12h. A substantially reduced target attainment was observed in patients with acute respiratory distress syndrome (ARDS). In patients without ARDS, 1200 mg/day was insufficient irrespective of the regimen, while a dose of 1400 mg/day administered q6h or by continuous infusions provided an acceptable target attainment (e.g. cumulative fraction of response with regards to T >MIC  ≥93%). Higher rates of potentially toxic trough concentrations (28% versus 12%) and concentrations constantly inside the mutant selection window (15% versus <0.1%) were observed with continuous infusions compared with q6h infusions (1400 mg/day, patients without ARDS)., Conclusions: Irrespective of the regimen, 1200 mg/day linezolid might be insufficient for the treatment of ICU patients. Patients without ARDS might particularly benefit from q6h infusions with increased daily doses (e.g. 1400 mg/day)., (© The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: The objective of this study was to examine the inhibitory potential of darifenacin, fesoterodine, oxybutynin, propiverine, solifenacin, tolterodine and trospium chloride on the seven major human cytochrome P450 enzymes (CYP) by using a standardized and validated seven-in-one cytochrome P450 cocktail inhibition assay., Methods: An in vitro cocktail of seven highly selective probe substrates was incubated with human liver microsomes and varying concentrations of the seven test compounds. The major metabolites of the probe substrates were simultaneously analysed using a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. Enzyme kinetics were estimated by determining IC 50 and K i values via nonlinear regression. Obtained K i values were used for predictions of potential clinical impact of the inhibition using a static mechanistic prediction model., Results: In this study, 49 IC 50 experiments were conducted. In six cases, IC 50 values lower than the calculated threshold for drug-drug interactions (DDIs) in the gut wall were observed. In these cases, no increase in inhibition was determined after a 30 min preincubation. Considering a typical dosing regimen and applying the obtained K i values of 0.72 µM (darifenacin, 15 mg daily) and 7.2 µM [propiverine, 30 mg daily, immediate release (IR)] for the inhibition of CYP2D6 yielded a predicted 1.9-fold and 1.4-fold increase in the area under the curve (AUC) of debrisoquine (CYP2D6 substrate), respectively. Due to the inhibition of the particular intestinal CYP3A4, the obtained K i values of 14 µM of propiverine (30 mg daily, IR) resulted in a predicted doubling of the AUC for midazolam (CYP3A4 substrate)., Conclusions: In vitro / in vivo extrapolation based on pharmacokinetic data and the conducted screening experiments yielded similar effects of darifenacin on CYP2D6 and propiverine on CYP3A4 as obtained in separately conducted in vivo DDI studies. As a novel finding, propiverine was identified to potentially inhibit CYP2D6 at clinically occurring concentrations., Competing Interests: Conflict of interest statement: The authors declare that there is no conflict of interest.

Clarithromycin is a substrate and mechanism-based inhibitor of cytochrome P450 (CYP) 3A4 as well as a substrate and competitive inhibitor of P-glycoprotein (P-gp) and organic anion-transporting polypeptides (OATP) 1B1 and 1B3. Administered concomitantly, clarithromycin causes drug-drug interactions (DDI) with the victim drugs midazolam (CYP3A4 substrate) and digoxin (P-gp substrate). The objective of the presented study was to build a physiologically based pharmacokinetic (PBPK) DDI model for clarithromycin, midazolam, and digoxin and to exemplify dosing adjustments under clarithromycin co-treatment. The PBPK model development included an extensive literature search for representative PK studies and for compound characteristics of clarithromycin, midazolam, and digoxin. Published concentration-time profiles were used for model development (training dataset), and published and unpublished individual profiles were used for model evaluation (evaluation dataset). The developed single-compound PBPK models were linked for DDI predictions. The full clarithromycin DDI model successfully predicted the metabolic (midazolam) and transporter (digoxin) DDI, the acceptance criterion (0.5 ≤ AUC ratio,predicted /AUC ratio,observed  ≤ 2) was met by all predictions. During co-treatment with 250 or 500 mg clarithromycin (bid), the midazolam and digoxin doses should be reduced by 74 to 88% and by 21 to 22%, respectively, to ensure constant midazolam and digoxin exposures (AUC). With these models, we provide highly mechanistic tools to help researchers understand and characterize the DDI potential of new molecular entities and inform the design of DDI studies with potential CYP3A4 and P-gp substrates.

Adequate linezolid blood concentrations have been shown to be associated with an improved clinical outcome. Our goal was to assess new predictors of inadequate linezolid concentrations often observed in critically ill patients. Fifty-two critically ill patients with severe infections receiving standard dosing of linezolid participated in this prospective observational study. Serum samples (median, 32 per patient) were taken on four consecutive days, and total linezolid concentrations were quantified. Covariates influencing linezolid pharmacokinetics were identified by multivariate analysis and a population pharmacokinetic model. Target attainment (area under the concentration-time curve over 12 h [AUC12]/MIC ratio of >50; MIC = 2 mg/liter) was calculated for both the study patients and a simulated independent patient group (n = 67,000). Target attainment was observed for only 36% of the population on both days 1 and 4. Independent covariates related to significant decreases of linezolid concentrations included higher weight, creatinine clearance rates, and fibrinogen and antithrombin concentrations, lower concentrations of lactate, and the presence of acute respiratory distress syndrome (ARDS). Linezolid clearance was increased in ARDS patients (by 82%) and in patients with elevated fibrinogen or decreased lactate concentrations. In simulated patients, most covariates, including fibrinogen and lactate concentrations and weight, showed quantitatively minor effects on target attainment (difference of ≤9% between the first and fourth quartiles of the respective parameters). In contrast, the presence of ARDS had the strongest influence, with only ≤6% of simulated patients reaching this target. In conclusion, the presence of ARDS was identified as a new and strong predictor of insufficient linezolid concentrations, which might cause treatment failure. Insufficient concentrations might also be a major problem in patients with combined alterations of other covariate parameters. (This study has been registered at ClinicalTrials.gov under registration number NCT01793012.)., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

Background: Pantoprazole is a proton pump inhibitor drug mainly used for treating peptic diseases. Adverse effects of pantoprazole in the occasional central nervous system (CNS) include headache, vertigo and sleep disturbances. Data in rats suggest that proton pumps are expressed in the inner ear and in the epithelium of the choroid plexus, which would be a potential target to mediate such proton pump inhibitor effects., Methods: To assess the distribution of pantoprazole into the human CNS despite its low lipophilicity (log p = 0.5), we quantified pantoprazole concentrations by liquid chromatography/tandem mass spectrometry in serum and cerebrospinal fluid retain samples withdrawn simultaneously. Twenty-six sample pairs were obtained from 23 neurological patients with therapeutic administration of pantoprazole prior to sampling., Results: Median (interquartile range) serum concentration of total pantoprazole was 142 ng/ml (30.8-622). Cerebrospinal fluid concentration of total pantoprazole was 2.79 ng/ml (1.59-7.3) and reached 2.0% (1.0-4.5%) of simultaneous serum concentrations., Conclusion: This value corresponds to the unbound fraction of pantoprazole in serum reported previously and indicates that pantoprazole CNS concentrations are high enough to exert some effects on possible CNS targets., (© 2016 S. Karger AG, Basel.)

Introduction: Direct and time-dependent inhibition (TDI) of cytochrome P450 enzymes (CYP) raises drug safety concerns and has major implications in drug development. This study describes the development of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) based screening tool to simultaneously assess both the direct and the time-dependent inhibitory potential of xenobiotics on the seven major CYPs using a two-step approach., Methods: The in vitro cocktail of FDA recognized model substrates was incubated with human liver microsomes (HLM) and consisted of caffeine (CYP1A2), bupropion (CYP2B6), rosiglitazone (CYP2C8), tolbutamide (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6) and midazolam (CYP3A4). Direct and time-dependent inhibitory profiles of direct and time-dependent reference inhibitors for each CYP were studied. For validation, the results were compared to those obtained with the traditional single substrate approach. Statistical uncertainty was quantified using the bootstrap method., Results: The direct inhibition assay showed an acceptable fold bias of 1.35 (geometric mean fold absolute deviation, range 1.01-2.61) in the IC50 values for the cocktail assay compared to the single substrate results with no trend for under- or overestimation. Using a single point inactivation assay to assess TDI, we were able to identify all seven tested time-dependent reference inhibitors, without any false negatives., Discussion: The presented design enhances throughput by assessing the seven major CYPs simultaneously and allows for detection of and discrimination between direct and time-dependent CYP inhibition via IC50 and single point inactivation experiments. For the latter, a threshold of 10% TDI is proposed for carrying out more detailed inactivation kinetic experiments., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Inhaled epinephrine is a potential alternative to self-administered intramuscular epinephrine in imminent anaphylactic reactions. The objective was to develop a pharmacokinetic-pharmacodynamic model describing exposure and effects on heart rate of inhaled epinephrine. Data from a 4-phase cross-over clinical trial in 9 healthy volunteers including 0.3 mg intramuscular epinephrine, two doses of inhaled epinephrine (4 mg/mL solution administered during [mean] 18 and 25 min, respectively) using a mobile pocket inhaler, and an inhaled placebo were analyzed using mixed-effects modeling. Inhaled epinephrine was available almost immediately and more rapidly than via the intramuscular route (absorption half-live 29 min). Epinephrine plasma concentrations declined rapidly after terminating inhalation (elimination half-life 4.1 min) offering the option to stop exposure in case of adverse events. While the expected maximum concentration was higher for inhaled epinephrine, this was not associated with safety concerns due to only moderate additional hemodynamic effects compared to intramuscular administration. Bioavailability after inhalation (4.7%) was subject to high interindividual and interoccasional variability highlighting that training of inhalation would be essential for patients. The proposed model suggests that the use of a highly concentrated epinephrine solution via inhalation may offer an effective treatment option in anaphylaxis, while efficacy in patients remains to be shown., (Copyright © 2015 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.)

Treatment with erlotinib, an epidermal growth factor receptor tyrosine kinase inhibitor used for treating non-small-cell lung cancer (NSCLC) and other cancers, is frequently associated with adverse events (AE). We present a modeling and simulation framework for the most common erlotinib-induced AE, rash, and diarrhea, providing insights into erlotinib toxicity. We used the framework to investigate the safety of high-dose erlotinib pulses proposed to limit acquired resistance while treating NSCLC. Continuous-time Markov models were developed using rash and diarrhea AE data from 39 NSCLC patients treated with erlotinib (150 mg/day). Exposure and different covariates were investigated as predictors of variability. Rash was also tested as a survival predictor. Models developed were used in a simulation analysis to compare the toxicities of different regimens, including the previously mentioned pulsed strategy. Probabilities of experiencing rash or diarrhea were found to be highest early during treatment. Rash, but not diarrhea, was positively correlated with erlotinib exposure. In contrast with some common understandings, radiotherapy decreased transitioning to higher rash grades by 81% (p < 0.01), and experiencing rash was not correlated with positive survival outcomes. Model simulations predicted that the proposed pulsed regimen (1600 mg/week + 50 mg/day remaining week days) results in a maximum of 20% of the patients suffering from severe rash throughout the treatment course in comparison to 12% when treated with standard dosing (150 mg/day). In conclusion, the framework demonstrated that radiotherapy attenuates erlotinib-induced rash, providing an opportunity to use radiotherapy and erlotinib together, and demonstrated the tolerability of high-dose pulses intended to address acquired resistance to erlotinib.

Introduction: Pharmacostatistical models can quantify different relationships and improve decision making in personalized medicine and drug development. Our objectives were to develop models describing non-small-cell lung cancer (NSCLC) dynamics during first-line treatment with erlotinib, and survival of the cohort., Methods: Data from patients with advanced NSCLC (n = 39) treated first-line with erlotinib (150 mg/day) were analyzed using nonlinear mixed effects modeling. Exposure-driven disease-drug models were built to describe tumor metabolic and proliferative dynamics evaluated by positron emission tomography (PET) using 2'-deoxy-2'-[F]fluoro-D-glucose (FDG) and 3'-[F]fluoro-3'-deoxy-L-thymidine (FLT), respectively, at baseline, weeks 1 and 6 after starting erlotinib treatment. A parametric time-to-event model was built to describe overall survival (OS). Demographics, histology, mutational, smoking, and baseline performance statuses were tested for their effects on models developed, in addition to tumor dynamics on survival., Results: An exponential relationship described progression, and a concentration-driven drug effect model described erlotinib effect. An activating epidermal growth factor receptor (EGFR) mutation increased the drug effect as assessed using FDG-PET by 2.19-fold (95% confidence interval [CI]:1.35-4.44). An exponential distribution described the times-to-death distribution. Baseline FDG uptake (p=0.0005; hazard ratio [HR] =1.26 for every unit increase, 95%CI: 1.13-1.42) and relative change in FDG uptake after 1 week of treatment (p=0.0073; HR=0.84 for every 10% drop, 95%CI: 0.71-0.91) were significant OS predictors irrespective of the EGFR mutational status. FLT-PET was statistically less significant than FDG-PET for OS prediction., Conclusion: Models describing tumor dynamics and survival of advanced NSCLC patients first-treated with erlotinib were developed. The impacts of different covariates were quantified.

Diurnal changes in the activity of drug metabolizing enzymes may contribute to the variability in drug disposition and drug effects. The aim of this study was to quantify the circadian rhythmicity exhibited by hepatic CYP3A. A 10 μg/kg intravenous bolus dose, followed by a 30-hour 4 μg/kg/h intravenous infusion of midazolam, used as a probe substrate for hepatic CYP3A activity, was administered to 16 healthy volunteers (8 males and 8 females). Blood samples were drawn hourly for 24 hours after achieving steady state, and plasma concentrations of midazolam and its main metabolite 1-OH midazolam were determined. Population pharmacokinetic analysis was performed using nonlinear mixed effects modeling. One-compartment pharmacokinetic models best described midazolam and 1-OH midazolam pharmacokinetic disposition. An unequivocal but minor diurnal pattern was identified in the midazolam plasma concentration profiles, which was described using a cosine function with a 24-hours period. The fluctuation in the relative CYP3A activity ranged between 10% above average around 15:00, and 10% below average around 03:00. None of the covariates tested had a significant impact on the parameters estimated. Although a diurnal pattern in hepatic CYP3A activity was identified, its magnitude suggests that it is small and without clinical significance for drug therapy., (© 2014, The American College of Clinical Pharmacology.)

Background: Accurate predictions of cytochrome P450 (CYP) 3A-mediated drug-drug interactions (DDIs) account for dynamic changes of CYP3A activity at both major expression sites (liver and gut wall) by considering the full pharmacokinetic profile of the perpetrator and the substrate. Physiological-based in vitro-in vivo extrapolation models have become of increasing interest. However, due to discrepancies between the predicted and observed magnitude of DDIs, the role of models fully based on in vivo data is still essential., Objective: The primary objective of this study was to develop a coupled dynamic model for the interaction of the CYP3A inhibitor voriconazole and the prototypical CYP3A substrate midazolam., Methods: Raw concentration data were obtained from a DDI study. Ten subjects were given either no pretreatment (control) or voriconazole twice daily orally. Midazolam was given either intravenously or orally after the last voriconazole dose and during control phases. Data analysis was performed by the population pharmacokinetic approach using non-linear mixed effects modelling (NONMEM 7.2.0). Model evaluation was performed using visual predictive checks and bootstrap analysis., Results: A semiphysiological model was able to describe the pharmacokinetics of midazolam, its major metabolite and voriconazole simultaneously. By considering the temporal disposition of all three substances in the liver and gut wall, a time-varying CYP3A inhibition process was implemented. Only the incorporation of hypothetical enzyme site compartments resulted in an adequate fit, suggesting a sustained inhibitory effect through accumulation. Novel key features of this analysis are the identification of (1) an apparent sustained inhibitory effect by voriconazole due to a proposed quasi accumulation at the enzyme site, (2) a significantly reduced inhibitory potency of intravenous voriconazole for oral substrates, (3) voriconazole as a likely uridine diphosphate glucuronosyltransferase (UGT) 2B inhibitor and (4) considerable sources of interindividual variability., Conclusion: The proposed semiphysiological modelling approach generated a mechanistic description of the complex DDI occurring at major CYP3A expression sites and thus may serve as a powerful tool to maximise information acquired from clinical DDI studies. The model has been shown to draw precise and accurate predictions. Therefore, simulations based on this kind of models may be used for various clinical scenarios to improve pharmacotherapy.

Background: Patients at the end of life often receive numerous medications for symptom management. In contrast to all other clinical situations, the aim of pharmacotherapy is strictly focused on quality of life., Objective: The primary aims of this study were to assess the potential for drug-drug interactions (DDIs) in patients at the very end of life by identifying drug combinations and risk factors associated with a high risk of DDIs; and evaluate the clinical relevance of the potential DDIs in this unique patient population. Secondary objectives were to increase prescriber awareness and to derive a comprehensive framework for physicians to minimize DDIs in this specific setting of end-of-life care., Materials and Methods: Charts of 364 imminently dying inpatients of two hospices were reviewed retrospectively. Drugs prescribed during the last 2 weeks of life were screened for DDIs by the electronic database of the Federal Union of German Associations of Pharmacists, which classifies DDIs by therapeutic measures required to reduce possible adverse events according to the ORCA system (OpeRational ClAssification of Drug Interactions)., Results: Potential DDIs were detected in 223 patients (61%). In a multivariate analysis, polypharmacy was the major predictor for DDIs (odds ratio 1.5, 95% CI 1.4, 1.6). The drugs most commonly involved in therapeutically relevant potential DDIs were antipsychotics, antiemetics (e.g. metoclopramide, antihistamines), antidepressants, insulin, glucocorticoids, cardiovascular drugs and, in particular, NSAIDs. The most prevalent potential adverse effects were pharmacodynamically additive anticholinergic, antidopaminergic, cardiac (QT interval prolongation) and NSAID-associated toxicity (e.g. gastrointestinal, renal)., Conclusion: In the context of end-of-life care, the clinical relevance of DDIs differs from other clinical settings. Most DDIs can be prevented if the prescribing physician considers a few therapeutic principles. Specifically, this concerns the awareness of futile and high-risk medications, as well as rational alternatives.

Objective: This study aims to identify the combination of substances with high potential for drug interactions in a palliative care setting and to provide concise recommendations for physicians., Methods: We used a retrospective systematic chart analysis of 200 consecutive inpatients. The recently developed and internationally advocated classification system OpeRational ClAssification of Drug Interactions was applied using the national database of the Federal Union of German Associations of Pharmacists. Charts of patients with potential for severe DDIs were examined manually for clinical relevance., Results: In 151 patients (75%) a total of 631 potential drug interactions were identified. Opioids (exception: methadone), non-opioids (exception: non-steroidal anti-inflammatory drugs), benzodiazepines, proton-pump inhibitors, laxatives, co-analgesics (exception: carbamazepine) and butylscopolamine were generally safe. High potential for drug interactions included combinations of scopolamine, neuroleptics, metoclopramide, antihistamines, non-steroidal anti-inflammatory drugs, (levo-) methadone, amitriptyline, carbamazepine and diuretics. The manual analyses of records from eight patients with risk for severe drug interactions provided no indicator for clinical relevance in these specific patients. Drug interactions attributed to the cytochrome pathway played a minor role (exception: carbamazepine)., Conclusion: Most relevant drug interactions can be expected with: (i) drugs (inter-) acting via histamine, acetylcholine or dopamine receptors; and (ii) Non-steroidal anti-inflammatory drugs. Even in last hours of life the combination of substances (e.g. anticholinergics) may produce relevant drug interactions (e.g. delirium)., Perspective: Data on the potential for drug-drug interactions in palliative case is extremely scarce, but drug interactions can be limited if a few facts are considered. A synopsis of the findings of these studies is presented as concise recommendation to minimize drug interactions.

Background: In 2006, our comprehensive cancer center decided to implement early integration (EI) of palliative care (PC) by (a) literally adopting the WHO definition of PC into cancer care guidelines and (b) providing a PC consulting team (PCST) to provide EI on in- and outpatient wards. The experience with this approach was assessed to identify shortcomings., Methods: A retrospective systematic chart analysis of a 2-year period was performed., Results: A total of 862 patients were treated (May 2006-April 2008). Many patients consulted by the PCST for the first time were already in a reduced performance status (ECOG 3 & 4: 40%) or experiencing burdening symptoms (i.e., dyspnoea 27%). After the first year (period A; "getting started"), the overall prevalence of symptoms identified on first PC contact decreased from seven to three, (p < 0.001) as well as surrogate measures for advanced disease (i.e., frailty: from 63% to 33%; CI: [-36%; -23%], p < 0.001)., Conclusion: Surrogate measures (symptom burden, performance status) indicate that PC was integrated earlier in the course of the disease after a 1-year phase of "getting started" with EI. Yet, the WHO recommendation alone was too vague to successfully trigger EI of PC. Therefore, the authors advocate the provision of disease specific guidelines to institutionalize EI of PC. Such guidelines have been developed for 19 different malignancies and are presented separately.

Background: Palliative care (PC) infrastructure has developed differently around the globe. Whereas some institutions consider the palliative care unit (PCU) a valuable component, others report that the sole provision of a state-of-the art palliative care consultation service (PCCS) suffices to adequately care for the severely ill and dying., Objective: To aid institutional planning, this study aimed at gathering patient data to distinguish assignments of a concomitantly run PCU and PCCS at a large hospital and academic medical center., Methods: Demographics, Eastern Cooperative Oncology Group performance status, symptom/problem burden, discharge modality, and team satisfaction with care for all 601 PCU and 851 PCCS patients treated in 2009 and 2010 were retrospectively analyzed., Results: Patients admitted to the PCU versus those consulted by the PCCS: (a) had a significantly worse performance status (odds ratio [OR], 1.48); (b) were significantly more likely to suffer from severe symptoms and psychosocial problems (OR, 2.05), in particular concerning physical suffering and complexity of care; and (c) were significantly much more likely to die during hospital stay (OR, 11.03). For patients who were dying or in other challenging clinical situations (suffering from various severe symptoms), self-rated team satisfaction was significantly higher for the PCU than the PCCS., Conclusion: This study presents a direct comparison between patients in a PCU and a PCCS. Results strongly support the hypothesis that the coexistence of both institutions in one hospital contributes to the goal of ensuring optimal high-quality PC for patients in complex and challenging clinical situations.