Interoccasion Variability Research Articles

Anticipating Leucovorin Rescue Therapy in Patients with Osteosarcoma through Methotrexate Population Pharmacokinetic Model.

Methotrexate (MTX), which presents high inter-individual variability, is part of the Brazilian Osteosarcoma Treatment Group (BOTG) protocol. This work aimed to develop a MTX population pharmacokinetic model (POPPK) for Brazilian children with osteosarcoma (OS) following the BOTG protocol to guide rescue therapy and avoid toxicity. The model was developed in NONMEM 7.4 (Icon®) using retrospective sparse data from MTX therapeutic drug monitoring of children attending a southern Brazilian public reference hospital. Data were described by a two-compartment model using 216 MTX cycles from 32 patients (5-18 y.o.) with OS who received 12 g/m2 dose/cycle. To explain inter-individual and inter-occasion variability in clearance and peripheral volume, covariates from demographic and biochemical data were evaluated. Serum creatinine was a significant covariate of MTX clearance (14.8 L/h), and the body surface area (BSA) was significant for central compartment volume (82.5 L). Inter-compartmental clearance and volume of peripheral compartment were 0.178 L/h and 5.72 L, respectively. The model adequately describes MTX exposure in Brazilian children with OS. Successful simulations were performed to predict MTX concentrations in pediatric patients above five years old with acute kidney injury and anticipate rescue therapy adjustments.

A fully automatic tool for development of population pharmacokinetic models.

Population pharmacokinetic (PK) models are widely used to inform drug development by pharmaceutical companies and facilitate drug evaluation by regulatory agencies. Developing a population PK model is a multi-step, challenging, and time-consuming process involving iterative manual model fitting and evaluation. A tool for fully automatic model development (AMD) of common population PK models is presented here. The AMD tool is implemented in Pharmpy, a versatile open-source library for pharmacometrics. It consists of different modules responsible for developing the different components of population PK models, including the structural model, the inter-individual variability (IIV) model, the inter-occasional variability (IOV) model, the residual unexplained variability (RUV) model, the covariate model, and the allometry model. The AMD tool was evaluated using 10 real PK datasets involving the structural, IIV, and RUV modules in three sequences. The different sequences yielded generally consistent structural models; however, there were variations in the results of the IIV and RUV models. The final models of the AMD tool showed lower Bayesian Information Criterion (BIC) values and similar visual predictive check plots compared with the available published models, indicating reasonable quality, in addition to reasonable run time. A similar conclusion was also drawn in a simulation study. The developed AMD tool serves as a promising tool for fast and fully automatic population PK model building with the potential to facilitate the use of modeling and simulation in drug development.

Population Pharmacokinetic Analysis of Dolutegravir in Treatment-Experienced Adults Living with HIV-1.

The World Health Organization has recommended the use of dolutegravir (DTG) for both first and second-line antiretroviral treatment in both adults and children down to 4 weeks of age. We developed a population pharmacokinetic(PopPK) model following oral administration of DTG 50 mg QD and 50 mg BID in HIV-infected treatment-experienced adults (607) based on pooled data from four phase 2/3 trials. DTG population pharmacokinetics are described by a one-compartment model with first-order absorption, absorption lag-time, and first-order elimination. The PopPK parameter estimates were apparent oral clearance (CL/F) = 1.00 L/h, apparent volume of distribution (V/F) = 18.9 L, absorption rate constant (Ka) = 1.99 per hour, and absorption lag time = 0.333 h, respectively. The final model included inter-individual and inter-occasion variability on apparent clearance (CL/F). Weight, smoking status, use of metabolic inducers as part of background antiretroviral therapy (ART) classified by their level of induction, use of atazanavir or atazanavir-ritonavir as part of background ART, and albumin level were predictors of CL/F; weight and albumin level were predictors of V/F; and sex and concomitant use of metal cation-containing vitamin/mineral supplements were predictors of relative bioavailability (F). The current model-based analysis suggests that the DTG dose adjustment is not required based on the demographics, laboratory values, smoking status, concomitant use of mild metabolic inducers or inhibitors in the background therapy, or use of metal cation-containing vitamin/mineral supplements because these covariate effects are not predicted to have a clinically relevant impact on safety and efficacy.

Advancing Virtual Bioequivalence for Orally Administered Drug Products: Methodology, Real-World Applications and Future Outlook.

Bioequivalence studies are pivotal in generic drug development wherein therapeutic equivalence is provided with an innovator product. However, bioequivalence studies represent significant complexities due to the interplay of multiple factors related to drug, formulation, physiology, and pharmacokinetics. Approaches such as physiologically based biopharmaceutics modeling (PBBM) can enable virtual bioequivalence (VBE) assessment through appropriately developed and validated models. Such models are now being extensively used for bioequivalence risk assessment, internal decision-making, and the evaluation of drug and formulation factors related to bioequivalence. Depiction of the above-mentioned factors through the incorporation of variability and development of a virtual population for bioequivalence assessment is of paramount importance in utilizing such models. In this manuscript, we have portrayed our current understanding of VBE. A detailed explanation was provided with respect to study designs, in vivo variability, and the impact of physiological, drug, and formulation factors on the development of the population for VBE. Furthermore, strategies are suggested to incorporate variability in GastroPlus with an emphasis on intra-subject and inter-occasion variability. Two industrial case studies pertaining to immediate and modified release formulation were portrayed wherein VBE was utilized for decision-making and regulatory justification. Finally, regulatory understanding in the area of VBE, along with future perspectives, was detailed.

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

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. 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. Medians standard deviations of dose-normalised doxorubicinentrapped+free Cmax and AUC0-∞ were 0.342 0.134mg/L and 40.1 18.9mg·h/L, respectively. The median half-life (95h) was 23.5h 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. 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. ClinicalTrials.gov-NCT03387917-January 2, 2018.

Supporting an integrated QTc risk assessment using the hERG margin distributions for three positive control agents derived from multiple laboratories and on multiple occasions.

BackgroundDetermination of a drug's potency in blocking the hERG channel is an established safety pharmacology study. Best practice guidelines have been published for reliable assessment of hERG potency. In addition, a set of plasma concentration and plasma protein binding fraction data were provided as denominators for margin calculations.The aims of the current analysis were five-fold: provide data allowing creation of consistent denominators for the hERG margin distributions of the key reference agents, explore the variation in hERG margins within and across laboratories, provide a hERG margin to 10 ms QTc prolongation based on several newer studies, provide information to use these analyses for reference purposes, and provide recommended hERG margin ‘cut-off’ values. MethodsThe analyses used 12 hERG IC50 ‘best practice’ data sets (for the 3 reference agents). A group of 5 data sets came from a single laboratory. The other 7 data sets were collected by 6 different laboratories. ResultsThe denominator exposure distributions were consistent with the ICH E14/S7B Training Materials. The inter-occasion and inter-laboratory variability in hERG IC50 values were comparable. Inter-drug differences were most important in determining the pooled margin variability. The combined data provided a robust hERG margin reference based on best practice guidelines and consistent exposure denominators. The sensitivity of hERG margin thresholds were consistent with the sensitivity described over the course of the last two decades. ConclusionThe current data provide further insight into the sensitivity of the 30-fold hERG margin ‘cut-off’ used for two decades. Using similar hERG assessments and these analyses, a future researcher can use a hERG margin threshold to support a negative QTc integrated risk assessment.

Pharmacogenetic Testing or Therapeutic Drug Monitoring: A Quantitative Framework.

Pharmacogenetic profiling and therapeutic drug monitoring (TDM) have both been proposed to manage inter-individual variability (IIV) in drug exposure. However, determining the most effective approach for estimating exposure for a particular drug remains a challenge. This study aimed to quantitatively assess the circumstances in which pharmacogenetic profiling may outperform TDM in estimating drug exposure, under three sources of variability (IIV, inter-occasion variability [IOV], and residual unexplained variability [RUV]). Pharmacokinetic models were selected from the literature corresponding to drugs for which pharmacogenetic profiling and TDM are both clinically considered approaches for dose individualization. The models were used to simulate relevant drug exposures (trough concentration or area under the curve [AUC]) under varying degrees of IIV, IOV, and RUV. Six drug cases were selected from the literature. Model-based simulations demonstrated that the percentage of patients for whom pharmacogenetic exposure prediction is superior to TDM differs for each drug case: tacrolimus (11.0%), tamoxifen (12.7%), efavirenz (49.2%), vincristine (49.6%), risperidone (48.1%), and 5-fluorouracil (5-FU) (100%). Generally, in the presence of higher unexplained IIV in combination with lower RUV and IOV, exposure was best estimated by TDM, whereas, under lower unexplained IIV in combination with higher IOV or RUV, pharmacogenetic profiling was preferred. For the drugs with relatively low RUV and IOV (e.g., tamoxifen and tacrolimus), TDM estimated true exposure the best. Conversely, for drugs with similar or lower unexplained IIV (e.g., efavirenz or 5-FU, respectively) combined with relatively high RUV, pharmacogenetic profiling provided the most accurate estimate for most patients. However, genotype prevalence and the relative influence of genotypes on the PK, as well as the ability of TDM to accurately estimate AUC with a limited number of samples, had an impact. The results could be used to support clinical decision making when considering other factors, such as the probability for severe side effects.

A Population Pharmacokinetic Study to Compare a Novel Empagliflozin L-Proline Formulation with Its Conventional Formulation in Healthy Subjects.

Empagliflozin is a sodium-glucose cotransporter 2 (SGLT2) inhibitor that is commonly used for the treatment of type 2 diabetes mellitus (T2DM). CKD-370 was newly developed as a cocrystal formulation of empagliflozin with co-former L-proline, which has been confirmed to be bioequivalent in South Korea. This study aimed to quantify the differences in the absorption phase and pharmacokinetic (PK) parameters of two empagliflozin formulations in healthy subjects by using population PK analysis. The plasma concentration data of empagliflozin were obtained from two randomized, open-label, crossover, phase 1 clinical studies in healthy Korean subjects after a single-dose administration. A population PK model was constructed by using a nonlinear mixed-effects (NLME) approach (Monolix Suite 2021R1). Interindividual variability (IIV) and interoccasion variability (IOV) were investigated. The final model was evaluated by goodness-of-fit (GOF) diagnostic plots, visual predictive checks (VPCs), prediction errors, and bootstrapping. The PK of empagliflozin was adequately described with a two-compartment combined transit compartment model with first-order absorption and elimination. Log-transformed body weight significantly influenced systemic clearance (CL) and the volume of distribution in the peripheral compartment (V2) of empagliflozin. GOF plots, VPCs, prediction errors, and the bootstrapping of the final model suggested that the proposed model was adequate and robust, with good precision at different dose strengths. The cocrystal form did not affect the absorption phase of the drug, and the PK parameters were not affected by the different treatments.

Population Pharmacokinetic Modeling for Twice-Daily Intravenous Busulfan in a Large Cohort of Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation-A 10-Year Single-Center Experience.

Reaching target exposure of busulfan-based conditioning prior to hematopoietic stem cell transplantation is vital for favorable therapy outcomes. Yet, a wide inter-patient and inter-occasion variability in busulfan exposure has been reported, especially in children. We aimed to identify factors associated with the variability of busulfan pharmacokinetics in 124 consecutive patients transplanted at the University Children's Hospital Zurich between October 2010 and February 2020. Clinical data and busulfan plasma levels after twice-daily intravenous administration were analyzed retrospectively by population pharmacokinetic modeling. The volume of distribution correlated with total body water. The elimination rate constant followed an age-dependent maturation function, as previously suggested, and correlated with the levels of serum albumin. Acute lymphoblastic leukemia reduced busulfan clearance by 20%. Clearance significantly decreased by 17% on average from the start to the third day of busulfan administration, in agreement with other studies. An average reduction of 31% was found in patients with hemophagocytic lymphohistiocytosis and X-linked lymphoproliferative disease. In conclusion, we demonstrate that in addition to known factors, underlying disease and serum albumin significantly impact busulfan pharmacokinetics in pediatric patients; yet, substantial unexplained variability in some patients remained. Thus, we consider repeated pharmacokinetic assessment essential to achieve the desired target exposure in twice-daily busulfan administration.

CYP3A5*3 and CYP3A4*22 Cluster Polymorphism Effects on LCP-Tac Tacrolimus Exposure: Population Pharmacokinetic Approach.

The aim of the study is to develop a population pharmacokinetic (PopPK) model and to investigate the influence of CYP3A5/CYP3A4 and ABCB1 single nucleotide polymorphisms (SNPs) on the Tacrolimus PK parameters after LCP-Tac formulation in stable adult renal transplant patients. The model was developed, using NONMEM v7.5, from full PK profiles from a clinical study (n = 30) and trough concentrations (C0) from patient follow-up (n = 68). The PK profile of the LCP-Tac formulation was best described by a two-compartment model with linear elimination, parameterized in elimination (CL/F) and distributional (CLD/F) clearances and central compartment (Vc/F) and peripheral compartment (Vp/F) distribution volumes. A time-lagged first-order absorption process was characterized using transit compartment models. According to the structural part of the base model, the LCP-Tac showed an absorption profile characterized by two transit compartments and a mean transit time of 3.02 h. Inter-individual variability was associated with CL/F, Vc/F, and Vp/F. Adding inter-occasion variability (IOV) on CL/F caused a statistically significant reduction in the model minimum objective function MOFV (p < 0.001). Genetic polymorphism of CYP3A5 and a cluster of CYP3A4/A5 SNPs statistically significantly influenced Tac CL/F. In conclusion, a PopPK model was successfully developed for LCP-Tac formulation in stable renal transplant patients. CYP3A4/A5 SNPs as a combined cluster including three different phenotypes (high, intermediate, and poor metabolizers) was the most powerful covariate to describe part of the inter-individual variability associated with apparent elimination clearance. Considering this covariate in the initial dose estimation and during the therapeutic drug monitoring (TDM) would probably optimize Tac exposure attainments.

Predictive Potential of Cmax Bioequivalence in Pilot Bioavailability/Bioequivalence Studies, through the Alternative ƒ2 Similarity Factor Method.

Pilot bioavailability/bioequivalence (BA/BE) studies are downsized trials that can be conducted prior to the definitive pivotal trial. In these trials, 12 to 18 subjects are usually enrolled, although, in principle, a sample size is not formally calculated. In a previous work, authors recommended the use of an alternative approach to the average bioequivalence methodology to evaluate pilot studies' data, using the geometric mean (Gmean) ƒ2 factor with a cut off of 35, which has shown to be an appropriate method to assess the potential bioequivalence for the maximum observed concentration (Cmax) metric under the assumptions of a true Test-to-Reference Geometric Mean Ratio (GMR) of 100% and an inter-occasion variability (IOV) in the range of 10% to 45%. In this work, the authors evaluated the proposed ƒ2 factor in comparison with the standard average bioequivalence in more extreme scenarios, using a true GMR of 90% or 111% for truly bioequivalent formulations, and 80% or 125% for truly bioinequivalent formulations, in order to better derive conclusions on the potential of this analysis method. Several scenarios of pilot BA/BE crossover studies were simulated through population pharmacokinetic modelling, accounting for different IOV levels. A redefined decision tree is proposed, suggesting a fixed sample size of 20 subjects for pilot studies in the case of intra-subject coefficient of variation (ISCV%) > 20% or unknown variability, and suggesting the assessment of study results through the average bioequivalence analysis, and additionally through Gmean ƒ2 factor method in the case of the 90% confidence interval (CI) for GMR is outside the regulatory acceptance bioequivalence interval of [80.00-125.00]%. Using this alternative approach, the certainty levels to proceed with pivotal studies, depending on Gmean ƒ2 values and variability scenarios tested (20-60% IOV), were assessed, which is expected to be helpful in terms of the decision to proceed with pivotal bioequivalence studies.

Microdialysis as a safe and feasible method to study target-site piperacillin-tazobactam disposition in septic piglets and children

ObjectivesKnowledge on the tissue penetration of piperacillin-tazobactam in children with sepsis is lacking. In this study, the feasibility and performance of microdialysis experiments were explored in septic piglets and children as part of a translational research project. MethodsMultiple-day microdialysis investigations were performed in muscle tissue of 22 piglets (of which 11 were septic) and 6 children with sepsis. An in vitro experiment preceded the (pre)clinical trials to derive optimal experimental settings and calibration technique. Linear mixed-effects models quantified the impact of sepsis on relative recovery (RR) and intercatheter, interindividual, interoccasion, and residual variability. ResultsIn vivo microdialysis was well tolerated in piglets and children, with no significant adverse events reported. Using identical experimental settings, lower RR values were recorded in healthy and septic piglets (range: piperacillin, 17.2–29.1% and tazobactam, 23.5–29.1%) compared with the in vitro experiment (piperacillin, 43.3% and tazobactam, 55.3%), and there were unacceptably low values in children with sepsis (<10%). As a result, methodological changes were made in the pediatric trial. Realistic tissue concentration-time curves were derived in piglets and children. In piglets, sepsis reduced the RR. The greatest contributors to RR variability were residual (>40%) and interoccasion (>30%) variability. The internal standard method was the preferred calibration technique in both piglets and children. ConclusionsMicrodialysis is a safe and applicable method for the measurement of tissue drug concentrations in piglets and children. This study demonstrated the impact of experimental settings, sepsis, and target population on individual RR.

Model based assessment of food and acid reducing agent effects on oral absorption of mezigdomide (CC-92480), a novel cereblon E3 ligase modulator.

Mezigdomide is a novel cereblon E3 ligase modulator (CELMoD) agent with enhanced autonomous cell-killing activity in multiple myeloma (MM) cells, and promising immunomodulatory and antitumor activity in patients with MM. We developed a population pharmacokinetics (PKs) model for mezigdomide in healthy subjects (HSs), and quantified effects of high-fat meal and proton pump inhibitor (PPI) on human disposition parameters. Plasma concentrations from 64 HS in two phase I clinical studies (NCT03803644 and NCT04211545) were used to develop a population PK model. The HSs received single oral doses of 0.4-3.2 mg mezigdomide with full PK profiles collected. A two-compartment linear PK model with first-order absorption and lag time best described mezigdomide PK profiles in HSs. The population PK parameters of absorption rate constant, lag time, central volume of distribution, clearance, peripheral volume of distribution, and intercompartmental clearance were estimated to be 1.18 h-1 (interoccasion variability [IOV]: 65%), 0.423 h (IOV: 31%), 440 L (interindividual variability [IIV]: 63%), 35.1 L/h (IIV: 40%), 243 L (IIV: 26%), and 36.8 L/h (IIV: 26%), respectively. High-fat meal increased oral bioavailability by ~30% and PPI co-administration decreased oral bioavailability by ~64%. Mezigdomide demonstrated a linear dose-exposure relationship in HSs. The PK model suggests a modest effect of high-fat meal, and a substantial effect of PPIs on mezigdomide oral bioavailability. This population PK model enables data integration across studies to identify important covariate effects and is being used to guide dose selection in clinical study designs for mezigdomide in patients with MM.

Modelling changes in the pharmacokinetics of tacrolimus during pregnancy after kidney transplantation: A retrospective cohort study.

Pregnancy after kidney transplantation is realistic but immunosuppressants should be continued to prevent rejection. Tacrolimus is safe during pregnancy and is routinely dosed based on whole-blood predose concentrations. However, maintaining these concentrations is complicated as physiological changes during pregnancy affect tacrolimus pharmacokinetics. The aim of this study was to describe tacrolimus pharmacokinetics throughout pregnancy and explain the changes by investigating covariates in a population pharmacokinetic model. Data of pregnant women using a twice-daily tacrolimus formulation following kidney transplantation were retrospectively collected from 6 months before conception, throughout gestation and up to 6 months postpartum. Pharmacokinetic analysis was performed using nonlinear mixed effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. The final model was evaluated using goodness-of-fit plots, visual predictive checks and a bootstrap analysis. A total of 260 whole-blood tacrolimus predose concentrations from 14 pregnant kidney transplant recipients were included. Clearance increased during pregnancy from 34.5 to 41.7L/h, by 15, 19 and 21% in the first, second and third trimester, respectively, compared to prior to pregnancy. This indicates a required increase in the tacrolimus dose by the same percentage to maintain the prepregnancy concentration. Haematocrit and gestational age were negatively correlated with tacrolimus clearance (P≤ 0.01), explaining 18% of interindividual and 85% of interoccasion variability in oral clearance. Tacrolimus clearance increases during pregnancy, resulting in decreased exposure to tacrolimus, which is explained by gestational age and haematocrit. To maintain prepregnancy target whole-blood tacrolimus predose concentrations during pregnancy, increasing the dose is required.

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

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. 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. 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. 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.

A semimechanistic pharmacokinetic/pharmacodynamic model for alanine aminotransferase-based hepatotoxicity of methotrexate in paediatric patients with acute lymphoid leukaemia.

Methotrexate (MTX) is recognized for its potential to induce hepatotoxicity, commonly manifested by elevated alanine aminotransferase (ALT) levels. However, the quantitative relationship between the pharmacokinetics (PK) of MTX and ALT-based hepatotoxicity remains unclear. This study aimed to develop a semimechanistic PK/pharmacodynamic (PD) model to characterize the MTX-induced hepatotoxicity based on ALT in paediatric patients with acute lymphoid leukaemia. A retrospective study was conducted on paediatric patients who received high-dose (3-5g/m2 ) MTX treatment. MTX concentrations were assessed at 24-h intervals until the concentration dropped below 0.1μmol/L. ALT concentrations were measured both before and after MTX administration. A population PK model was initially developed, which was later connected to a semimechanistic hepatotoxicity model. The PK model was developed using 354 MTX concentrations obtained from 51 patients, while the PD model was constructed using 379 ALT concentrations collected from 48 patients. The optimal PK model for MTX consisted of a 2-compartment structure, where body surface area served as a covariate for clearance and central volume of distribution. An indirect response model coupled to a liver injury signal transduction model was developed to describe the dynamics of ALT after MTX administration. The drug effect was adequately described by a linear model, exhibiting considerable interoccasion variability for each treatment session. No significant covariates were identified to have an impact on the PD parameters. A semimechanistic model was developed to describe ALT-based hepatotoxicity of MTX, and it has the potential to serve as a valuable tool for characterizing drug-induced hepatotoxicity.

Cefepime Population Pharmacokinetics, Antibacterial Target Attainment, and Estimated Probability of Neurotoxicity in Critically Ill Patients.

Cefepime has been reported to cause concentration-related neurotoxicity, especially in critically ill patients with renal failure. This evaluation aimed to identify a dosing regimen providing a sufficient probability of target attainment (PTA) and the lowest justifiable risk of neurotoxicity in critically ill patients. A population pharmacokinetic model was developed based on plasma concentrations over four consecutive days obtained from 14 intensive care unit (ICU) patients. The patients received a median dose of 2,000 mg cefepime by 30-min intravenous infusions with dosing intervals of every 8 h (q8h) to q24h. A time that the free drug concentration exceeds the MIC over the dosing interval (fT>MIC) of 65% and an fT>2×MIC of 100% were defined as treatment targets. Monte Carlo simulations were carried out to identify a dosing regimen for a PTA of 90% and a probability of neurotoxicity not exceeding 20%. A two-compartment model with linear elimination best described the data. Estimated creatinine clearance was significantly related to the clearance of cefepime in nondialysis patients. Interoccasion variability on clearance improved the model, reflecting dynamic clearance changes. The evaluations suggested combining thrice-daily administration as an appropriate choice. In patients with normal renal function (creatinine clearance, 120 mL/min), for the pharmacodynamics target of 100% fT>2×MIC and a PTA of 90%, a dose of 1,333 mg q8h was found to be related to a probability of neurotoxicity of ≤20% and to cover MICs up to 2 mg/L. Continuous infusion appears to be superior to other dosing regimens by providing higher efficacy and a low risk of neurotoxicity. The model makes it possible to improve the predicted balance between cefepime efficacy and neurotoxicity in critically ill patients. (This study has been registered at ClinicalTrials.gov under registration no. NCT01793012).

Abstract CT243: Clinical trial simulation to inform dose selection of zilurgisertib, an ALK2 inhibitor, in patients with anemia due to myelofibrosis (MF)

Abstract Disease-associated anemia is reported in over one-third of patients at MF diagnosis and can be exacerbated by currently available MF therapies. Further, anemia is associated with poor prognosis in MF. Activation of activin receptor-like kinase (ALK)-2 (also known as ACVR1) may contribute to MF-associated anemia via up-regulated levels of hepcidin. Zilurgisertib (INCB000928) is a potent and selective ALK2 inhibitor that has demonstrated dose-dependent improvement in hemoglobin levels in a cancer-induced anemia mouse model, in which maximum hemoglobin increase was observed when zilurgisertib trough concentration covered pSMAD IC50 for at least half of the dosing interval. Zilurgisertib is being evaluated as monotherapy or in combination with ruxolitinib in a phase 1/2 dose-escalation and -expansion study in patients with anemia due to MF (NCT04455841). The objective of the current study is to use modeling and simulation, which integrate both preclinical and clinical data, to inform dose finding for the ongoing phase 1/2 trial in MF patients. Population (Pop) PK analyses were conducted using a total of 3089 zilurgisertib plasma concentrations from 161 healthy subjects in 3 completed phase 1 studies: a single ascending dose study (64 subjects, 10-500 mg), a multiple ascending dose study (59 subjects, 50-400 mg QD and 300 mg BID), and a drug-drug interaction study (38 subjects, 100 mg single dose of zilurgisertib alone). A nonlinear mixed-effects modeling approach in Monolix software was used for the analyses. Zilurgisertib PK were well-characterized by a 3-compartment model with nonlinear clearance and inter-occasion variability on absorption rate constant and bioavailability. The diagnostic plots and visual predictive check demonstrated that the model appropriately characterized the zilurgisertib plasma concentrations. Because zilurgisertib PK are similar between MF patients and healthy subjects, as suggested by available PK data in MF patients receiving doses up to 200 mg, the pop PK model developed with data from healthy subjects was used to simulate steady-state exposures in MF patients receiving 200 to 600 mg daily dose. Simulation results showed that daily doses of ≥600 mg would result in &amp;gt;90% of patients achieving exposure similar to the observed exposure associated with maximum efficacy in the mouse model. The conclusions from this clinical trial simulation support the decision to continue dose escalation in MF patients receiving zilurgisertib monotherapy. Citation Format: Yan-ou Yang, Hong Yang, Betty Lamothe, Matthew Stubbs, Amanda McBride, Francis Seguy, Kevin Rockich, Jay Getsy, Phillip Wang, Xiang Liu, Jeff Jackson, Ekaterine Asatiani, Xuejun Chen. Clinical trial simulation to inform dose selection of zilurgisertib, an ALK2 inhibitor, in patients with anemia due to myelofibrosis (MF) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT243.

Conjunction of semi-mechanistic in vitro-in vivo modeling and population pharmacokinetics as a tool for virtual bioequivalence analysis - a case study for a BCS class II drug

Virtual bioequivalence trial (VBE) simulations based on (semi)mechanistic in vitro-in vivo (IVIV) modeling have gained a huge interest in the pharmaceutical industry. Sophisticated commercially available software allows modeling variable drug fates in the gastrointestinal tract (GIT). Surprisingly, the between-subject and inter-occasion variability (IOV) of the distribution volumes and clearances are ignored or simplified, despite substantially contributing to varied plasma drug concentrations. The paper describes a novel approach for IVIV-based VBE by using population pharmacokinetics (popPK). The data from two bioequivalence trials with a poorly soluble BCS class II drug were analyzed retrospectively. In the first trial, the test drug product (biobatch 1) did not meet the bioequivalence criteria, but after a reformulation, the second trial succeeded (biobatch 2). The popPK model was developed in the Monolix software (Lixoft SAS, Simulation Plus) based on the originator’s plasma concentrations. The modified Noyes-Whitney model was fitted to the results of discriminative biorelevant dissolution tests of the two biobatches and seven other reformulations. Then, the IVIV model was constructed by joining the popPK model with fixed drug disposition parameters, the drug dissolution model, and mechanistic approximation of the GIT transit. It was used to simulate the drug concentrations at different IOV levels of the primary pharmacokinetic parameters and perform the VBE. Estimated VBE success rates for both biobatches well reflected the outcomes of the bioequivalence trials. The predicted 90% confidence intervals for the area under the time-concentration curves were comparable with the observed values, and the 10% IOV allowed the closest approximation to the clinical results. Simulations confirmed that a significantly lower maximum drug concentration for biobatch 1 was responsible for the first clinical trial’s failure. In conclusion, the proposed workflow might aid formulation screening in generic drug development.

Population pharmacokinetic dosimetry model using imaging data to assess variability in pharmacokinetics of 177 Lu-PSMA-617 in prostate cancer patients.

Studies to evaluate and optimize [177 Lu]Lu-PSMA treatment focus primarily on individual patient data. A population pharmacokinetic (PK) dosimetry model was developed to explore the potential of using imaging data as input for population PK models and to characterize variability in organ and tumor uptake of [177 Lu]Lu-PSMA-617 in patients with low volume metastatic prostate cancer. Simulations were performed to identify the effect of dose adjustments on absorbed doses in salivary glands and tumors. A six-compartment population PK model was developed, consisting of blood, salivary gland, kidneys, liver, tumor, and a lumped compartment representing other tissue (compartment 1-6, respectively), based on data from 10 patients who received [177 Lu]Lu-PSMA-617 (2 cycles, ~ 3 and ~ 6GBq). Data consisted of radioactivity levels (decay corrected) in blood and tissues (9 blood samples and 5 single photon emission computed tomography/computed tomography scans). Observations in all compartments were adequately captured by individual model predictions. Uptake into salivary glands was saturable with an estimated maximum binding capacity (Bmax ) of 40.4MBq (relative standard error 12.3%) with interindividual variability (IIV) of 59.3% (percent coefficient of variation [CV%]). IIV on other PK parameters was relatively minor. Tumor volume was included as a structural effect on the tumor uptake rate constant (k15 ), where a two-fold increase in tumor volume resulted in a 1.63-fold increase in k15 . In addition, interoccasion variability on k15 improved the model fit (43.5% [CV%]). Simulations showed a reduced absorbed dose per unit administered activity for salivary glands after increasing radioactivity dosing from 3 to 6GBq (0.685 Gy/GBq vs. 0.421 Gy/GBq, respectively). All in all, population PK modeling could help to improve future radioligand therapy research.