Quality Assurance of PBPK Modeling Platforms and Guidance on Building, Evaluating, Verifying and Applying PBPK Models Prudently under the Umbrella of Qualification: Why, When, What, How and By Whom?

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.

CYP3A4-mediated effects of rifampicin on the pharmacokinetics of vilaprisan and its UGT1A1-mediated effects on bilirubin glucuronidation in humans.

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.

Optimization of linezolid therapy in the critically ill: the effect of adjusted infusion regimens.

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).

Predictors of Inadequate Linezolid Concentrations after Standard Dosing in Critically Ill Patients.

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.).

Comparison of Pantoprazole Concentrations in Simultaneous Cerebrospinal Fluid and Serum Samples.

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.

In-Depth Analysis of the Selection of PBPK Modeling Tools: Bibliometric and Social Network Analysis of the Open Systems Pharmacology Community.

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.

Applied physiologically-based pharmacokinetic modeling to assess uridine diphosphate-glucuronosyltransferase-mediated drug-drug interactions for Vericiguat.

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.

Assessment of the CYP3A4 Induction Potential by Carbamazepine: Insights from Two Clinical DDI Studies and PBPK Modeling.

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.

Physiologically based pharmacokinetic modeling of tacrolimus for food-drug and CYP3A drug-drug-gene interaction predictions.

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 (AUClast ) and 6/6 predicted FDI maximum whole blood concentration (Cmax ) ratios within twofold of the respective observed ratios. In addition, 7/7 predicted DD(G)I AUClast and 6/7 predicted DD(G)I Cmax 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.

Physiologically-based pharmacokinetic modeling of quinidine to establish a CYP3A4, P-gp, and CYP2D6 drug-drug-gene interaction network.

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.

Leveraging the use of in vitro and computational methods to support the development of enabling oral drug products: An InPharma commentary.

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.

Palliative care consultation service and palliative care unit: why do we need both?

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.

Recommending early integration of palliative care - does it work?

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.

Drug interactions in palliative care--it's more than cytochrome P450.

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.

Physiologically-based pharmacokinetic modeling to predict CYP3A4-mediated drug-drug interactions of finerenone.

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 [Cmax Rs] of 2.00 vs. observed of 3.48 and 1.88, respectively) and verapamil (simulated AUCR of 2.91 and Cmax 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 Cmax 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.

A generic framework for the physiologically-based pharmacokinetic platform qualification of PK-Sim and its application to predicting cytochrome P450 3A4-mediated drug-drug interactions.

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.

Predictive Performance of Physiology-Based Pharmacokinetic Dose Estimates for Pediatric Trials: Evaluation With 10 Bayer Small-Molecule Compounds in Children.

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.

A Novel Study Design Using Continuous Intravenous and Intraduodenal Infusions of Midazolam and Voriconazole for Mechanistic Quantitative Assessment of Hepatic and Intestinal CYP3A Inhibition.

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 kinact , 2.83 h-1 ; dissociation rate constant KI , 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.

A Physiologically Based Pharmacokinetic Model of Voriconazole Integrating Time-Dependent Inhibition of CYP3A4, Genetic Polymorphisms of CYP2C19 and Predictions of Drug-Drug Interactions.

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 (Cmax), and trough concentrations for multiple dosings (Ctrough), 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 (IC50) 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 Cmax 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 Cmax 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 Ctrough, 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.

Sorafenib and everolimus in patients with advanced solid tumors and KRAS-mutated NSCLC: A phase I trial with early pharmacodynamic FDG-PET assessment.

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.