A quantitative modeling framework to understand the physiology of the hypothalamic-pituitary-adrenal axis and interaction with cortisol replacement therapy.

Congenital adrenal hyperplasia (CAH) is characterized by impaired adrenal cortisol production. Hydrocortisone (synthetic cortisol) is the drug-of-choice for cortisol replacement therapy, aiming to mimic physiological cortisol circadian rhythm. The hypothalamic-pituitary-adrenal (HPA) axis controls cortisol production through the pituitary adrenocorticotropic hormone (ACTH) and feedback mechanisms. The aim of this study was to quantify key mechanisms involved in the HPA axis activity regulation and their interaction with hydrocortisone therapy. Data from 30 healthy volunteers was leveraged: Endogenous ACTH and cortisol concentrations without any intervention as well as cortisol concentrations measured after dexamethasone suppression and single dose administration of (i) 0.5-10 mg hydrocortisone as granules, (ii) 20 mg hydrocortisone as granules and intravenous bolus. A stepwise model development workflow was used: A newly developed model for endogenous ACTH and cortisol was merged with a refined hydrocortisone pharmacokinetic model. The joint model was used to simulate ACTH and cortisol trajectories in CAH patients with varying degrees of enzyme deficiency, with or without hydrocortisone administration, and healthy individuals. Time-dependent ACTH-driven endogenous cortisol production and cortisol-mediated feedback inhibition of ACTH secretion processes were quantified and implemented in the model. Comparison of simulated ACTH and cortisol trajectories between CAH patients and healthy individuals showed the importance of administering hydrocortisone before morning ACTH secretion peak time to suppress ACTH overproduction observed in untreated CAH patients. The developed framework allowed to gain insights on the physiological mechanisms of the HPA axis regulation, its perturbations in CAH and interaction with hydrocortisone administration, paving the way towards cortisol replacement therapy optimization.

Combination of Pharmacokinetic and Pathogen Susceptibility Information To Optimize Meropenem Treatment of Gram-Negative Infections in Critically Ill Patients.

Meropenem is one of the most frequently used antibiotics to treat life-threatening infections in critically ill patients. This study aimed to develop a meropenem dosing algorithm for the treatment of Gram-negative infections based on intensive care unit (ICU)-specific resistance data. Antimicrobial susceptibility testing of Gram-negative bacteria obtained from critically ill patients was carried out from 2016 to 2020 at a tertiary care hospital. Based on the observed MIC distribution, stochastic simulations (n = 1,000) of an evaluated pharmacokinetic meropenem model, and a defined pharmacokinetic/pharmacodynamic target (100%T>4×MIC while minimum concentrations were <44.5 mg/L), dosing recommendations for patients with varying renal function were derived. Pathogen-specific MIC distributions were used to calculate the cumulative fraction of response (CFR), and the overall MIC distribution was used to calculate the local pathogen-independent mean fraction of response (LPIFR) for the investigated dosing regimens. A CFR/LPIFR of >90% was considered adequate. The observed MIC distribution significantly differed from the EUCAST database. Based on the 6,520 MIC values included, a three-level dosing algorithm was developed. If the pathogen causing the infection is unknown (level 1), known (level 2), known to be neither Pseudomonas aeruginosa nor Acinetobacter baumannii, or classified as susceptible (level 3), a continuous infusion of 1.5 g daily reached sufficient target attainment independent of renal function. In all other cases, dosing needs to be adjusted based on renal function. ICU-specific susceptibility data should be assessed regularly and integrated into dosing decisions. The presented workflow may serve as a blueprint for other antimicrobial settings.

Microdialysis of Voriconazole and its N-Oxide Metabolite: Amalgamating Knowledge of Distribution and Metabolism Processes in Humans.

PURPOSE: Voriconazole is an essential antifungal drug whose complex pharmacokinetics with high interindividual variability impedes effective and safe therapy. By application of the minimally-invasive sampling technique microdialysis, interstitial space fluid (ISF) concentrations of VRC and its potentially toxic N-oxide metabolite (NO) were assessed to evaluate target-site exposure for further elucidating VRC pharmacokinetics. METHODS: Plasma and ISF samples of a clinical trial with an approved VRC dosing regimen were analyzed for VRC and NO concentrations. Concentration-time profiles, exposure assessed as area-under-the-curve (AUC) and metabolic ratios of four healthy adults in plasma and ISF were evaluated regarding the impact of multiple dosing and CYP2C19 genotype. RESULTS: VRC and NO revealed distribution into ISF with AUC values being ≤2.82- and 17.7-fold lower compared to plasma, respectively. Intraindividual variability of metabolic ratios was largest after the first VRC dose administration while interindividual variability increased with multiple dosing. The CYP2C19 genotype influenced interindividual differences with a maximum 6- and 24-fold larger AUCNO/AUCVRC ratio between the intermediate and rapid metabolizer in plasma and ISF, respectively. VRC metabolism was saturated/auto-inhibited indicated by substantially decreasing metabolic concentration ratios with increasing VRC concentrations and after multiple dosing. CONCLUSION: The feasibility of the simultaneous microdialysis of VRC and NO in vivo was demonstrated and provided new quantitative insights by leveraging distribution and metabolism processes of VRC in humans. The exploratory analysis suggested substantial dissimilarities of VRC and NO pharmacokinetics in plasma and ISF. Ultimately, a thorough understanding of target-site pharmacokinetics might contribute to the optimization of personalized VRC dosing regimens.

Microdialysis of Drug and Drug Metabolite: a Comprehensive In Vitro Analysis for Voriconazole and Voriconazole N-oxide.

PURPOSE: Voriconazole is a therapeutically challenging antifungal drug associated with high interindividual pharmacokinetic variability. As a prerequisite to performing clinical trials using the minimally-invasive sampling technique microdialysis, a comprehensive in vitro microdialysis characterization of voriconazole (VRC) and its potentially toxic N-oxide metabolite (NO) was performed. METHODS: The feasibility of simultaneous microdialysis of VRC and NO was explored in vitro by investigating the relative recovery (RR) of both compounds in the absence and presence of the other. The dependency of RR on compound combination, concentration, microdialysis catheter and study day was evaluated and quantified by linear mixed-effects modeling. RESULTS: Median RR of VRC and NO during individual microdialysis were high (87.6% and 91.1%). During simultaneous microdialysis of VRC and NO, median RR did not change (87.9% and 91.1%). The linear mixed-effects model confirmed the absence of significant differences between RR of VRC and NO during individual and simultaneous microdialysis as well as between the two compounds (p > 0.05). No concentration dependency of RR was found (p = 0.284). The study day was the main source of variability (46.3%) while the microdialysis catheter only had a minor effect (4.33%). VRC retrodialysis proved feasible as catheter calibration for both compounds. CONCLUSION: These in vitro microdialysis results encourage the application of microdialysis in clinical trials to assess target-site concentrations of VRC and NO. This can support the generation of a coherent understanding of VRC pharmacokinetics and its sources of variability. Ultimately, a better understanding of human VRC pharmacokinetics might contribute to the development of personalized dosing strategies.

Quantification of persister formation of Escherichia coli leveraging electronic cell counting and semi-mechanistic pharmacokinetic/pharmacodynamic modelling.

BACKGROUND: Persister formation of Escherichia coli under fluoroquinolone exposure causes treatment failure and promotes emergence of resistant strains. Semi-mechanistic pharmacokinetic/pharmacodynamic modelling of data obtained from in vitro infection model experiments comprehensively characterizes exposure-effect relationships, providing mechanistic insights. OBJECTIVES: To quantify persister formation of E. coli under levofloxacin exposure and to explain the observed growth-kill behaviour, leveraging electronic cell counting and pharmacokinetic/pharmacodynamic modelling. METHODS: Three fluoroquinolone-resistant clinical E. coli isolates were exposed to levofloxacin in static and dynamic in vitro infection model experiments. Complementary to plate counting, bacterial concentrations over time were quantified by electronic cell counting and amalgamated in a semi-mechanistic pharmacokinetic/pharmacodynamic model (1281 bacterial and 394 levofloxacin observations). RESULTS: Bacterial regrowth was observed under exposure to clinically relevant dosing regimens in the dynamic in vitro infection model. Electronic cell counting facilitated identification of three bacterial subpopulations: persisters, viable cells and dead cells. Two strain-specific manifestations of the levofloxacin effect were identified: a killing effect, characterized as a sigmoidal Emax model, and an additive increase in persister formation under levofloxacin exposure. Significantly different EC50 values quantitatively discerned levofloxacin potency for two isolates displaying the same MIC value: 8 mg/L [EC50 = 17.2 (95% CI = 12.6-23.8) mg/L and 8.46 (95% CI = 6.86-10.3) mg/L, respectively]. Persister formation was most pronounced for the isolate with the lowest MIC value (2 mg/L). CONCLUSIONS: The developed pharmacokinetic/pharmacodynamic model adequately characterized growth-kill behaviour of three E. coli isolates and unveiled strain-specific levofloxacin potencies and persister formation. The mimicked dosing regimens did not eradicate the resistant isolates and enhanced persister formation to a strain-specific extent.

Which Analysis Approach Is Adequate to Leverage Clinical Microdialysis Data? A Quantitative Comparison to Investigate Exposure and Reponse Exemplified by Levofloxacin.

PURPOSE: Systematic comparison of analysis methods of clinical microdialysis data for impact on target-site drug exposure and response. METHODS: 39 individuals received a 500 mg levofloxacin short-term infusion followed by 24-h dense sampling in plasma and microdialysate collection in interstitial space fluid (ISF). ISF concentrations were leveraged using non-compartmental (NCA) and compartmental analysis (CA) via (ii) relative recovery correction at midpoint of the collection interval (midpoint-NCA, midpoint-CA) and (ii) dialysate-based integrals of time (integral-CA). Exposure and adequacy of community-acquired pneumonia (CAP) therapy via pharmacokinetic/pharmacodynamic target-attainment (PTA) analysis were compared between approaches. RESULTS: Individual AUCISF estimates strongly varied for midpoint-NCA and midpoint-CA (≥52.3%CV) versus integral-CA (≤32.9%CV) owing to separation of variability in PK parameters (midpoint-CA = 46.5%-143%CVPK, integral-CA = 26.4%-72.6%CVPK) from recovery-related variability only in integral-CA (41.0%-50.3%CVrecovery). This also led to increased variability of AUCplasma for midpoint-CA (56.0%CV) versus midpoint-NCA and integral-CA (≤33.0%CV), and inaccuracy of predictive model performance of midpoint-CA in plasma (visual predictive check). PTA analysis translated into 33% of evaluated patient cases being at risk of incorrectly rejecting recommended dosing regimens at CAP-related epidemiological cut-off values. CONCLUSIONS: Integral-CA proved most appropriate to characterise clinical pharmacokinetics- and microdialysis-related variability. Employing this knowledge will improve the understanding of drug target-site PK for therapeutic decision-making.

Therapeutic drug monitoring of oral targeted antineoplastic drugs.

PURPOSE: This review provides an overview of the current challenges in oral targeted antineoplastic drug (OAD) dosing and outlines the unexploited value of therapeutic drug monitoring (TDM). Factors influencing the pharmacokinetic exposure in OAD therapy are depicted together with an overview of different TDM approaches. Finally, current evidence for TDM for all approved OADs is reviewed. METHODS: A comprehensive literature search (covering literature published until April 2020), including primary and secondary scientific literature on pharmacokinetics and dose individualisation strategies for OADs, together with US FDA Clinical Pharmacology and Biopharmaceutics Reviews and the Committee for Medicinal Products for Human Use European Public Assessment Reports was conducted. RESULTS: OADs are highly potent drugs, which have substantially changed treatment options for cancer patients. Nevertheless, high pharmacokinetic variability and low treatment adherence are risk factors for treatment failure. TDM is a powerful tool to individualise drug dosing, ensure drug concentrations within the therapeutic window and increase treatment success rates. After reviewing the literature for 71 approved OADs, we show that exposure-response and/or exposure-toxicity relationships have been established for the majority. Moreover, TDM has been proven to be feasible for individualised dosing of abiraterone, everolimus, imatinib, pazopanib, sunitinib and tamoxifen in prospective studies. There is a lack of experience in how to best implement TDM as part of clinical routine in OAD cancer therapy. CONCLUSION: Sub-therapeutic concentrations and severe adverse events are current challenges in OAD treatment, which can both be addressed by the application of TDM-guided dosing, ensuring concentrations within the therapeutic window.

CYP2D6 phenotype explains reported yohimbine concentrations in four severe acute intoxications.

The indole alkaloid yohimbine is an alpha-2 receptor antagonist used for its sympathomimetic effects. Several cases of yohimbine intoxication have been reported and the most recent one involved four individuals taking a yohimbine-containing drug powder. All individuals developed severe intoxication symptoms and were admitted to the hospital. Even though all individuals were assumed to have taken the same dose of the drug powder, toxicology analyses revealed yohimbine blood concentrations of 249-5631 ng/mL, amounting to a 22-fold difference. The reason for this high variability remained to be elucidated. We used recently reported knowledge on the metabolism of yohimbine together with state-of-the art nonlinear mixed-effects modelling and simulation and show that a patient's cytochrome P450 2D6 (CYP2D6) phenotype can explain the large differences observed in the measured concentration after intake of the same yohimbine dose. Our findings can be used both for the identification of safe doses in therapeutic use of yohimbine and for an explanation of individual cases of overdosing.

Novel insights into the complex pharmacokinetics of voriconazole: a review of its metabolism.

Voriconazole, a second-generation triazole frequently used for the prophylaxis and treatment of invasive fungal infections, undergoes complex metabolism mainly involving various (polymorphic) cytochrome P450 enzymes in humans. Although high inter- and intraindividual variability in voriconazole pharmacokinetics have been observed and the therapeutic range for this compound is relatively narrow, the metabolism of voriconazole has not been fully elucidated yet. The available literature data investigating the multiple different pathways and metabolites are extremely unbalanced and thus the absolute or relative contribution of the different pathways and enzymes involved in the metabolism of voriconazole remains uncertain. Furthermore, other factors such as nonlinear pharmacokinetics caused by auto-inhibition or -induction and polymorphisms of the metabolizing enzymes hinder safe and effective voriconazole dosing in clinical practice and have not yet been studied sufficiently. This review aimed at amalgamating the available literature on the pharmacokinetics of voriconazole in vitro and in vivo, with a special focus on metabolism in adults and children, in order to congregate an overall landscape of the current body of knowledge and identify knowledge gaps, opening the way towards further research in order to foster the understanding, towards better therapeutic dosing decisions.

Results of a Multicenter Population Pharmacokinetic Study of Ciprofloxacin in Children with Complicated Urinary Tract Infection.

Resistance rates for ciprofloxacin, which is labeled for treating complicated urinary tract infections in children, are rapidly rising. As there is limited knowledge on developmental pharmacology of ciprofloxacin, the primary aim of this study was to develop a population pharmacokinetic model for ciprofloxacin in children treated for complicated urinary tract infections. Children to whom ciprofloxacin was prescribed, intravenous (10 to 15 mg/kg body weight every 12 h) or per os (15 to 20 mg/kg every 12 h), were enrolled. One hundred eight serum and 119 urine samples were obtained during 10 intravenous and 13 oral courses of ciprofloxacin in 22 patients (age range, 0.31 to 15.51 years). A one-compartment model best described our data. Fat-free mass and glomerular filtration rate (estimated by a formula using cystatin C and creatinine), standardized for body surface area, were significant covariates for ciprofloxacin clearance. In our population, ciprofloxacin clearance is 0.16 to 0.43 liter/h/kg of body weight, volume of distribution 0.06 to 2.88 liters/kg, and bioavailability 59.6%. All of our patients had a clinical cure of their infection. Based on target attainment simulations across doses, all children reached the pharmacodynamic target for Enterobacteriaceae, but on average only 53% did for Pseudomonas aeruginosa and 3% for Staphylococcus aureus, at the 15-mg/kg oral dose. For treating urinary tract infections caused by Pseudomonas aeruginosa, oral doses should be at least 20 mg/kg. Furthermore, in our population, fat-free mass and kidney function should be considered, as they prove to be significant covariates for ciprofloxacin clearance and, hence, exposure. (This study has been registered at ClinicalTrials.gov under identifier NCT02598362.).

Claiming desmopressin therapeutic equivalence in children requires pediatric data: a population PKPD analysis.

PURPOSE: For a new formulation of a drug, only pharmacokinetic bioequivalence with the original formulation has to be demonstrated in healthy, young adults. However, "children are not small adults," and to guarantee a safe and effective treatment, age-adapted drug development is required. Desmopressin, a vasopressin analogue prescribed for nocturnal enuresis in children, was studied as an example formulation first developed in adults and then extrapolated to a pediatric indication. METHODS: Population pharmacokinetic and pharmacodynamic modeling was used to analyze previously published desmopressin data of 18 children suffering from nocturnal enuresis. The main objective was the comparison of the therapeutic equivalence of two desmopressin formulations: tablet and lyophilisate. The measurements for pharmacokinetics and pharmacodynamics were respectively plasma desmopressin concentration and urine osmolality and diuresis. RESULTS: The half maximal inhibitory concentration for inhibition of urine production was 0.7 pg/mL lower for the lyophilisate than for the tablet. The effect of formulation on the half maximal inhibitory concentration seems to suggest that the 120-µg lyophilisate has a more pronounced effect on the urine volume and osmolality than the 200-µg tablet, even when the same exposure is achieved. CONCLUSIONS: A new indirect response model for desmopressin was constructed and validated, using a previously built pharmacokinetic model and additional pharmacodynamic data. In order to draw solid conclusions regarding the efficacy and safety of desmopressin in children, pharmacokinetics and pharmacodynamics data should be analyzed together. This study adds proof to potential differences in pediatric and adult pharmacokinetic and pharmacodynamic properties of desmopressin and exemplifies the need for pediatric clinical trials, not only for every new drug but also for every new formulation.

The use of PBPK modeling across the pediatric age range using propofol as a case.

The project SAFEPEDRUG aims to provide guidelines for drug research in children, based on bottom-up and top-down approaches. Propofol, one of the studied model compounds, was selected because it is extensively metabolized in liver and kidney, with an important role for the glucuronidation pathway. Besides, being a lipophilic molecule, it is distributed into fat tissues, from where it redistributes into the systemic circulation. In the past, both bottom-up (Physiologically based pharmacokinetic, PBPK) and top-down approaches (population pharmacokinetic, popPK) were applied to describe its pharmacokinetics (PK). In this work, a combination of the two was used to check their performance to describe PK in children and neonates (both term and preterm) using propofol as a case compound. First, in vitro data was generated in human liver microsomes and recombinant enzymes and used to develop an adult PBPK model in Simcyp®. Activity adjustment factors (AAFs) were calculated to account for differences between in vitro and in vivo enzyme activity. Clinical data were analyzed using a 3-compartment model in NONMEM. These data were used to construct a retrograde PBPK model and for qualification of the PBPK models. Once an accurate in vivo clearance was obtained accounting for the contribution of the different metabolic pathways, the resulting PBPK models were challenged with new data for qualification. After that, the constructed adult PPBK model for propofol was extrapolated to the pediatric population. Both the default built-in and in vivo derived ontogeny functions were used to do so. The models were qualified by comparing their predicted PK parameters to published values, and by comparison of predicted concentration-time profiles to available clinical data. Clearance values were predicted well, especially when compared with values obtained from trials where long-term sampling was applied, whereas volume of distribution was lower compared to the most common popPK model predictions. Concentration-time profiles were predicted well up until and including the preterm neonatal population. In this work, it was thus shown that PBPK can be used to predict the PK up to and including the preterm neonatal population without the use of pediatric in vivo data. This work adds weight to the need for further development of PBPK models, especially regarding distribution modeling and the use of in vivo derived ontogeny functions.

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians.

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

Bayesian framework for multi-source data integration-Application to human extrapolation from preclinical studies.

In preclinical investigations, for example, in in vitro, in vivo, and in silico studies, the pharmacokinetic, pharmacodynamic, and toxicological characteristics of a drug are evaluated before advancing to first-in-man trial. Usually, each study is analyzed independently and the human dose range does not leverage the knowledge gained from all studies. Taking into account all preclinical data through inferential procedures can be particularly interesting in obtaining a more precise and reliable starting dose and dose range. Our objective is to propose a Bayesian framework for multi-source data integration, customizable, and tailored to the specific research question. We focused on preclinical results extrapolated to humans, which allowed us to predict the quantities of interest (e.g. maximum tolerated dose, etc.) in humans. We build an approach, divided into four steps, based on a sequential parameter estimation for each study, extrapolation to human, commensurability checking between posterior distributions and final information merging to increase the precision of estimation. The new framework is evaluated via an extensive simulation study, based on a real-life example in oncology. Our approach allows us to better use all the information compared to a standard framework, reducing uncertainty in the predictions and potentially leading to a more efficient dose selection.

Population pharmacokinetics of TLD-1, a novel liposomal doxorubicin, in a phase I trial.

STUDY OBJECTIVES: TLD-1 is a novel pegylated liposomal doxorubicin (PLD) formulation aiming to optimise the PLD efficacy-toxicity ratio. We aimed to characterise TLD-1's population pharmacokinetics using non-compartmental analysis and nonlinear mixed-effects modelling. METHODS: The PK of TLD-1 was analysed by performing a non-compartmental analysis of longitudinal doxorubicin plasma concentration measurements obtained from a clinical trial in 30 patients with advanced solid tumours across a 4.5-fold dose range. Furthermore, a joint parent-metabolite PK model of doxorubicinentrapped, doxorubicinfree, and metabolite doxorubicinol was developed. Interindividual and interoccasion variability around the typical PK parameters and potential covariates to explain parts of this variability were explored. RESULTS: Medians  ± standard deviations of dose-normalised doxorubicinentrapped+free Cmax and AUC0-∞ were 0.342 ± 0.134 mg/L and 40.1 ± 18.9 mg·h/L, respectively. The median half-life (95 h) was 23.5 h longer than the half-life of currently marketed PLD. The novel joint parent-metabolite model comprised a one-compartment model with linear release (doxorubicinentrapped), a two-compartment model with linear elimination (doxorubicinfree), and a one-compartment model with linear elimination for doxorubicinol. Body surface area on the volumes of distribution for free doxorubicin was the only significant covariate. CONCLUSION: The population PK of TLD-1, including its release and main metabolite, were successfully characterised using non-compartmental and compartmental analyses. Based on its long half-life, TLD-1 presents a promising candidate for further clinical development. The PK characteristics form the basis to investigate TLD-1 exposure-response (i.e., clinical efficacy) and exposure-toxicity relationships in the future. Once such relationships have been established, the developed population PK model can be further used in model-informed precision dosing strategies. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov-NCT03387917-January 2, 2018.

Nonlinear Mixed-Effects Model of Z-Endoxifen Concentrations in Tamoxifen-Treated Patients from the CEPAM Cohort.

Tamoxifen is widely used in patients with hormone receptor-positive breast cancer. The polymorphic enzyme CYP2D6 is primarily responsible for metabolic activation of tamoxifen, resulting in substantial interindividual variability of plasma concentrations of its most important metabolite, Z-endoxifen. The Z-endoxifen concentration thresholds below which tamoxifen treatment is less efficacious have been proposed but not validated, and prospective trials of individualized tamoxifen treatment to achieve Z-endoxifen concentration thresholds are considered infeasible. Therefore, we aim to validate the association between Z-endoxifen concentration and tamoxifen treatment outcomes, and identify a Z-endoxifen concentration threshold of tamoxifen efficacy, using pharmacometric modeling and simulation. As a first step, the CYP2D6 Endoxifen Percentage Activity Model (CEPAM) cohort was created by pooling data from 28 clinical studies (> 7,000 patients) with measured endoxifen plasma concentrations. After cleaning, data from 6,083 patients were used to develop a nonlinear mixed-effect (NLME) model for tamoxifen and Z-endoxifen pharmacokinetics that includes a conversion factor to allow inclusion of studies that measured total endoxifen but not Z-endoxifen. The final parent-metabolite NLME model confirmed the primary role of CYP2D6, and contributions from body weight, CYP2C9 phenotype, and co-medication with CYP2D6 inhibitors, on Z-endoxifen pharmacokinetics. Future work will use the model to simulate Z-endoxifen concentrations in patients receiving single agent tamoxifen treatment within large prospective clinical trials with long-term survival to identify the Z-endoxifen concentration threshold below which tamoxifen is less efficacious. Identification of this concentration threshold would allow personalized tamoxifen treatment to improve outcomes in patients with hormone receptor-positive breast cancer.

Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data.

BACKGROUND AND OBJECTIVES: Model-informed precision dosing (MIPD) frequently uses nonlinear mixed-effects (NLME) models to predict and optimize therapy outcomes based on patient characteristics and therapeutic drug monitoring data. MIPD is indicated for compounds with narrow therapeutic range and complex pharmacokinetics (PK), such as voriconazole, a broad-spectrum antifungal drug for prevention and treatment of invasive fungal infections. To provide guidance and recommendations for evidence-based application of MIPD for voriconazole, this work aimed to (i) externally evaluate and compare the predictive performance of a published so-called 'hybrid' model for MIPD (an aggregate model comprising features and prior information from six previously published NLME models) versus two 'standard' NLME models of voriconazole, and (ii) investigate strategies and illustrate the clinical impact of Bayesian forecasting for voriconazole. METHODS: A workflow for external evaluation and application of MIPD for voriconazole was implemented. Published voriconazole NLME models were externally evaluated using a comprehensive in-house clinical database comprising nine voriconazole studies and prediction-/simulation-based diagnostics. The NLME models were applied using different Bayesian forecasting strategies to assess the influence of prior observations on model predictivity. RESULTS: The overall best predictive performance was obtained using the aggregate model. However, all NLME models showed only modest predictive performance, suggesting that (i) important PK processes were not sufficiently implemented in the structural submodels, (ii) sources of interindividual variability were not entirely captured, and (iii) interoccasion variability was not adequately accounted for. Predictive performance substantially improved by including the most recent voriconazole observations in MIPD. CONCLUSION: Our results highlight the potential clinical impact of MIPD for voriconazole and indicate the need for a comprehensive (pre-)clinical database as basis for model development and careful external model evaluation for compounds with complex PK before their successful use in MIPD.

C-Reactive Protein as an Early Predictor of Efficacy in Advanced Non-Small-Cell Lung Cancer Patients: A Tumor Dynamics-Biomarker Modeling Framework.

In oncology, longitudinal biomarkers reflecting the patient's status and disease evolution can offer reliable predictions of the patient's response to treatment and prognosis. By leveraging clinical data in patients with advanced non-small-cell lung cancer receiving first-line chemotherapy, we aimed to develop a framework combining anticancer drug exposure, tumor dynamics (RECIST criteria), and C-reactive protein (CRP) concentrations, using nonlinear mixed-effects models, to evaluate and quantify by means of parametric time-to-event models the significance of early longitudinal predictors of progression-free survival (PFS) and overall survival (OS). Tumor dynamics was characterized by a tumor size (TS) model accounting for anticancer drug exposure and development of drug resistance. CRP concentrations over time were characterized by a turnover model. An x-fold change in TS from baseline linearly affected CRP production. CRP concentration at treatment cycle 3 (day 42) and the difference between CRP concentration at treatment cycles 3 and 2 were the strongest predictors of PFS and OS. Measuring longitudinal CRP allows for the monitoring of inflammatory levels and, along with its reduction across treatment cycles, presents a promising prognostic marker. This framework could be applied to other treatment modalities such as immunotherapies or targeted therapies allowing the timely identification of patients at risk of early progression and/or short survival to spare them unnecessary toxicities and provide alternative treatment decisions.

Model-Informed Target Morning 17α-Hydroxyprogesterone Concentrations in Dried Blood Spots for Pediatric Congenital Adrenal Hyperplasia Patients.

Monitoring cortisol replacement therapy in congenital adrenal hyperplasia (CAH) patients is vital to avoid serious adverse events such as adrenal crises due to cortisol underexposure or metabolic consequences due to cortisol overexposure. The less invasive dried blood spot (DBS) sampling is an advantageous alternative to traditional plasma sampling, especially in pediatric patients. However, target concentrations for important disease biomarkers such as 17α-hydroxyprogesterone (17-OHP) are unknown using DBS. Therefore, a modeling and simulation framework, including a pharmacokinetic/pharmacodynamic model linking plasma cortisol concentrations to DBS 17-OHP concentrations, was used to derive a target morning DBS 17-OHP concentration range of 2-8 nmol/L in pediatric CAH patients. Since either capillary or venous DBS sampling is becoming more common in the clinics, the clinical applicability of this work was shown by demonstrating the comparability of capillary and venous cortisol and 17-OHP concentrations collected by DBS sampling, using a Bland-Altman and Passing-Bablok analysis. The derived target morning DBS 17-OHP concentration range is a first step towards providing improved therapy monitoring using DBS sampling and adjusting hydrocortisone (synthetic cortisol) dosing in children with CAH. In the future, this framework can be used to assess further research questions, e.g., target replacement ranges for the entire day.