First-order Conditional Estimation Research Articles

An interactive dose optimizer based on population pharmacokinetic study to guide dosing of methotrexate in Chinese patients with osteosarcoma.

Osteosarcoma is a rare tumor with an incidence of 4.4 cases per million per year in adolescent. High-dose methotrexate (HD-MTX) is the standard first-line chemotherapeutic agent for osteosarcoma. However, its efficacy can vary significantly among individuals due to wide pharmacokinetic variability. Despite this, only a few population pharmacokinetics (popPK) models based on Chinese patients with osteosarcoma have been reported. Thus, this study aimed to develop a HD-MTX popPK model and an individual model-based dose optimizer for osteosarcoma therapy. A total of 680 MTX serum concentrations from 57 patients with osteosarcoma were measured at the end of MTX infusion and 10h, 24h, 48h, and 72h after the start of infusion. Using the first-order conditional estimation method with NONMEM, a popPK model was estimated. Goodness-of-fit plots, visual predictive checks, and bootstrap analysis were generated to evaluate the final model. A dose optimizer tool was developed based on the validated models using R Shiny. Additionally, clinical data from 12 patients with newly diagnosed osteosarcoma were collected and used as the validation set to preliminarily verify the predictive ability of the popPK model and the dose optimizer tool. Body surface area (BSA) was the most significant covariate for compartment distribution. Creatinine clearance (CrCL) and co-administration of NSAIDs were introduced as predictors for central compartmental and peripheral compartmental clearance, respectively. Co-administration of NSAIDs was associated with significantly higher MTX concentrations at 72h (p = 0.019). The dose optimizer tool exhibited a high consistency in predicting MTX AUC compared to the actual AUC (r = 0.821, p < 0.001) in the validation set. The dose optimizer tool could be used to estimate individual PK parameters, and optimize personalized MTX therapy in particular patients.

Population Pharmacokinetics of Sertraline in Psychiatric and Substance Use Disorders.

This study aimed to characterize the population pharmacokinetics of sertraline in Mexican patients with psychiatric and substance use disorders. Fifty-nine patients (13 to 76 years old) treated with doses of sertraline between 12.5 and 100 mg/day were included. Plasma sertraline concentrations were determined in blood samples and five of the main substances of abuse were determined by rapid tests in urine samples. Demographic, clinical, and pharmacogenetic factors were also evaluated. Population pharmacokinetic analysis was performed using NONMEM software with first-order conditional estimation method. A one-compartment model with proportional residual error adequately described the sertraline concentrations versus time. CYP2D6*2 polymorphism and CYP2C19 phenotypes significantly influenced sertraline clearance, which had a population mean value of 66 L/h in the final model. The absorption constant and volume of distribution were fixed at 0.855 1/h and 20.2 L/kg, respectively. The model explained 11.3% of the interindividual variability in sertraline clearance. The presence of the CYP2D6*2 polymorphism caused a 23.1% decrease in sertraline clearance, whereas patients with intermediate and poor phenotype of CYP2C19 showed 19.06% and 48.26% decreases in sertraline clearance, respectively. The model was internally validated by bootstrap and visual predictive check. Finally, stochastic simulations were performed to propose dosing regimens to achieve therapeutic levels that contribute to improving treatment response.

Population Pharmacokinetic Modeling of Posaconazole in Japanese Patients Receiving Fungal Prophylaxis.

Posaconazole is a vital drug to treat and prevent invasive fungal infections. Several factors, such as sex, body weight, total serum proteins, dietary intake, and severe mucositis, affect posaconazole pharmacokinetics (PKs). However, the relevance of other factors that affect the PKs of posaconazole in hematopoietic stem cell transplantation (HSCT) is unknown. This study explored factors influencing the PKs of posaconazole in HSCT recipients and nontransplant patients with hematological diseases. The authors conducted a single-institution, retrospective study. Forty-two Japanese inpatients receiving oral posaconazole tablets as prophylaxis for fungal infections were enrolled in this study. A one-compartment model with first-order absorption was used as the structural pharmacokinetic model. A population PK (PopPK) analysis was performed using a nonlinear mixed-effects modeling program, using a first-order conditional estimation method with interactions. Perl-speaks-NONMEM and R were used to evaluate the goodness of fit and visualize the output. In 29% of the enrolled patients, the serum concentration of posaconazole was <0.5 mcg/mL, considered the effective range. PopPK analysis revealed that the patient had undergone HSCT within 1 year, diarrhea occurred more than 5 times a day, and aspartate aminotransferase were covariates that influenced apparent clearance (CL/F). The CL/F of posaconazole was 1.43-fold higher after HSCT and 1.26-fold higher during diarrhea. PopPK analysis revealed that HSCT, diarrhea, and aspartate aminotransferase were factors associated with the CL/F of posaconazole. The trough concentration of posaconazole may be below the therapeutic range in a few patients with diarrhea and/or after HSCT. As invasive fungal infections in patients with hematologic diseases can be life-threatening, therapeutic drug monitoring of posaconazole is strongly recommended, and patients should be carefully monitored.

Development of extended pharmacokinetic models for propofol based on measured blood and brain concentrations

Propofol’s pharmacokinetics have been extensively studied using human blood samples and applied to target-controlled infusion systems; however, information on its concentration in the brain remains scarce. Therefore, this study aimed to simultaneously measure propofol plasma and brain concentrations in patients who underwent awake craniotomy and establish new pharmacokinetic model. Fifty-seven patients with brain tumors or brain lesions who underwent awake craniotomy were sequentially assigned to model-building and validating groups. Plasma and brain (lobectomy or uncapping margins) samples were collected at five time-points. The concentration of propofol was measured using high-performance liquid chromatography. Population pharmacokinetic analysis was conducted through a nonlinear mixed-effects modeling program using a first-order conditional estimation method with interactions. Propofol’s brain concentrations were higher than its plasma concentrations. The measured brain concentrations were higher than the effect site concentrations using the previous models. Extended models were constructed based on measured concentrations by incorporating the brain/plasma partition coefficient (Kp value). Extended models showed good predictive accuracy for brain concentrations in the validating group. The Kp value functioned as a factor explaining retention in the brain. Our new pharmacokinetic models and Kp value can predict propofol’s brain and plasma concentrations, contributing to safer and more stable anesthesia.

Understanding hemoglobin contribution to high-dose methotrexate disposition-population pharmacokinetics in pediatric patients with hematological malignancies.

The aim of the present study was to develop a population pharmacokinetic model for methotrexate (MTX) during high-dose treatment (HDMTX) in pediatric patients with acute lymphoblastic leukemia (ALL) and non-Hodgkin's lymphoma (NHL) and to describe the influence of variability factors. The study included 50 patients of both sexes (aged 1-18years) who received 3 or 5g/m2 of HDMTX. A nonlinear mixed effect modeling approach was applied for data analysis. Parameter estimation was performed by first-order conditional estimation method with interaction (FOCEI), whereas stepwise covariate modeling was used to assess variability factors. The final model is a two-compartment model that incorporates the effect of body surface area and the influence of hemoglobin and serum creatinine on MTX clearance (CL). Population pharmacokinetic values for a typical subject were estimated at 5.75 L/h/m2 for clearance (CL), 21.3 L/m2 for volume of the central compartment (V1), 8.2 L/m2 for volume of the peripheral compartment (V2), and 0.087 L/h/m2 for intercompartmental clearance (Q). According to the final model, MTX CL decreases with increasing serum creatinine, whereas a positive effect was captured for hemoglobin. A difference of almost 32% in MTX CL was observed among patients' hemoglobin values reported in the study. The developed population pharmacokinetic model can contribute to the therapy optimization during HDMTX in pediatric patients with ALL and NHL. In addition to renal function and body weight, it describes the influence of hemoglobin on CL, allowing better understanding of its contribution to the disposition of HDMTX.

Population Pharmacokinetic Modeling of Different Formulations of Inclacumab Using Phase 1 Data in Healthy Participants

Introduction: P-selectin is a cell adhesion molecule that contributes to vaso-occlusive crises (VOCs) in sickle cell disease (SCD). Inclacumab is a recombinant, fully human, immunoglobulin G4 monoclonal antibody that selectively binds to P-selectin to prevent binding with P-selectin glycoprotein ligand-1. Inclacumab was previously evaluated by Roche in clinical trials with healthy participants and patients with cardiovascular disease and is now being developed as a potential treatment to reduce the frequency of VOCs in individuals with SCD. Changes in the manufacturing of inclacumab have resulted in 3 formulations/drug materials: Roche v0.1, Roche v0.2, and Global Blood Therapeutics (GBT). GBT-manufactured inclacumab utilizes a similar formulation and the same cell line as Roche v0.2 (Roche v0.1 utilizes a different cell line), and analytical and nonclinical comparability between Roche v0.2 and GBT inclacumab have been demonstrated (Mihaila et al. Expert Opin Biol Ther 2022). Here we report results from a population pharmacokinetic (PopPK) model developed to compare the pharmacokinetics (PK) of different formulations using data from 4 phase 1 clinical studies in healthy participants administered Roche v0.1, Roche v0.2, or GBT inclacumab. The objectives were to develop a PopPK model to describe inclacumab PK in healthy adult participants and to quantify potential differences in inclacumab PK associated with different formulations/drug materials. Methods: A PopPK model was developed using single- and multiple-dose PK data from healthy participants who received intravenous (IV) inclacumab across 4 studies (BP21112 [Roche v0.1, single ascending dose (SAD)], BP21617 [Roche v0.1, multiple ascending dose], BP28134 [Roche v0.2, SAD], and GBT2104-111 [GBT, SAD]). Evaluable participants had ≥1 measurable postdose concentration with an associated sample time, relevant dosing information prior to each measurable concentration, and no protocol violation that could confound PK analyses. A nonlinear mixed effects model was fit to the inclacumab plasma concentration-time data using first-order conditional estimation with eta-epsilon interaction in NONMEM ® (v7.3). Model selection was based on the plausibility of parameter estimates, goodness-of-fit plots, and the objective function value. The final model was evaluated using a prediction-corrected visual predictive check (pcVPC). Results: The PopPK dataset comprised 145 healthy participants, of which 2622 inclacumab plasma concentrations (84.9%) from 143 participants were evaluable (Roche v0.1: n=68 [47.6%]; Roche v0.2: n=60 [42.0%]; GBT: n=15 [10.5%]). Median (range) age and body weight were 42 (21-63) years and 73.2 (45.8-109) kg, respectively. Nominal doses ranged from 0.03 to 40 mg/kg IV; 23.8% of participants received 3 mg/kg and 29.4% received 20 mg/kg. A 3-compartment disposition model with parallel linear clearance (CL=0.125 L/d) and nonlinear (concentration-dependent; V max=1.19 mg/d; K m=0.784 μg/mL) clearance from the central compartment described the plasma concentration-time data. The effect of drug material was incorporated a priori as relative bioavailability term F in the base model using exploratory analyses of observed exposures. Dosing of Roche v0.1 and Roche v0.2 inclacumab resulted in 23% and 2% higher exposure than GBT inclacumab, respectively. Between-subject variability was estimated for linear clearance, nonlinear clearance, and all volume parameters, and residual error was described using a proportional model (Table). Of the tested covariates, baseline body weight was a statistically significant covariate effect and was included on all linear clearance and volume terms. Model qualification by pcVPC showed good predictive performance of the final model. Conclusions: The PopPK of IV inclacumab in healthy participants was described by a 3-compartment disposition model with parallel linear and nonlinear clearances. Estimated relative exposure of Roche v0.2 and GBT-manufactured inclacumab was similar, indicating comparability in drug exposure. Understanding the relationship between exposure and dose for different formulations facilitates more accurate assessment of safety data across multiple clinical studies. These data provide support for the ongoing phase 3 clinical development in SCD using GBT-manufactured inclacumab without further clinical comparability testing.

Population Pharmacokinetic and Pharmacodynamic Analysis of Navtemadlin in Patients with Relapsed and Refractory (R/R) Myelofibrosis (MF) and Other Myeloid or Solid Tumor Malignancies

Background:Murine double minute 2 (MDM2), a key negative regulator of the tumor suppressor protein p53, is overexpressed in malignancies such as MF and Merkel cell carcinoma (MCC). Navtemadlin is a potent, selective, orally available MDM2 inhibitor that overcomes MDM2 dysregulation by restoring p53 activity and inducing apoptosis of TP53WT tumors. Navtemadlin has been tested in 21- or 28-day treatment cycles, with 5 or 7 consecutive days of dosing per cycle. Navtemadlin elicits plasma concentration-dependent increases in serum macrophage inhibitory cytokine-1 (MIC-1). An increase in MIC-1 relative to baseline MIC-1 serum concentration is a key pharmacodynamic (PD) marker of response to navtemadlin treatment (Zhang et al. Xenobiotica 2022). A population pharmacokinetic (PK) model was developed, based on patients with R/R MF (N=113, NCT03662126); MCC (N=35, NCT03787602); solid tumors and multiple myeloma (ST/MM N=105, Gluck et al. Invest New Drugs 2019); R/R acute myeloid leukemia (AML, N=35, Erba et al. Blood Adv 2019); and healthy volunteers (HV, N=30, Wong et al. Clin Pharmacol Drug Dev 2022).The objectives wereto characterize navtemadlin PK and covariate effects and compare steady-state (SS) PK and PD across cancer types. Methods:A two-compartment PK model with first-order absorption and elimination was estimated using NONMEM ® (first-order conditional estimation with interaction). Four transit compartments captured absorption. Inter-subject variability was modeled as lognormal. A stepwise covariate search used forward addition (p&amp;lt;0.05) followed by backward elimination (p&amp;lt;0.01). Log-transformed SS MIC-1 ratio to baseline (fold ratio) was tested in a fixed-effects linear regression model with respect to SS exposures, with baseline MIC-1 as the covariate. The final population PK and MIC-1 models were evaluated by inspection of parameter tables, by overlaying model predictions with observed data, and by standard residual diagnostics. Results:The PK estimation used 5,282 concentrations from 318 subjects, including 1,415 concentrations in 113 patients with R/R MF. Tumor type affected absorption rate (median, 0.635/hr in MCC; slower vs other types), apparent clearance (median, 8.90 L/hr in MCC; lower vs other types), and apparent central volume (median, 64.4 L in MCC; similar to AML, but lower vs other types) (Table 1). Accordingly, simulated SS area under the curve (AUCss) differed across populations in the order MCC&amp;gt;AML&amp;gt;MF&amp;gt;ST/MM = HV (Figure 1). Covariate analysis indicated median AUC increased with the inflammation marker C-reactive protein, by 21% at 90 th percentile CRP, and with age, by 5% at 90 th percentile age of 75 y, compared to the median, 66 y. Men had 24% lower relative bioavailability than women. Taking navtemadlin with food slowed absorption by 10% but had no impact on AUCss. Other tested covariates, including body weight, creatinine clearance, aspartate transaminase, alanine transaminase, bilirubin, albumin, alpha 1-acid glycoprotein, race, UGT1A1 genotype, recent ruxolitinib treatment in MF, and CYP3A4 inducer/inhibitor concomitant medications, were not significant. Median MIC-1 fold ratio increased with navtemadlin AUCss. Higher baseline MIC-1 resulted in lower SS MIC-1 fold ratio. Median baseline MIC-1 differed by tumor type. In R/R MF, baseline MIC-1 was 2,297 ng/L and SS fold ratio of MIC-1 was 7.79 (N=91). In MCC, baseline MIC-1 was 1,718 ng/L and SS fold ratio of MIC-1 was 16.7 (N=29). In R/R MF, higher baseline spleen volume was also associated with lower SS MIC-1 fold ratio. Exposure-MIC-1 relationships in R/R MF and MCC were generally similar to other tumor types and HV populations (Allard et al. Hemasphere 2019; Zhang et al. Xenobiotica 2022). Conclusions:Tumor type influenced navtemadlin exposure with simulated exposure in R/R MF patients at the selected Phase 3 dose of 240 mg comparable to exposures in MCC patients at 180 mg, the selected Phase 2 dose for that indication. Cancer-associated inflammation and/or treatment history, as well as age and female sex, may increase navtemadlin exposure. The PD marker MIC-1 responds to navtemadlin in a concentration-dependent fashion. The overall SS fold change of MIC-1 PD responses was lower in disease states or subjects with higher baseline MIC-1. These studies demonstrate potent, dose-dependent PK/PD responses following p53 activation with the novel MDM2 inhibitor, navtemadlin, across diverse tumor types.

Population Pharmacokinetics of Digoxin in Nonagenarian Patients: Optimization of the Dosing Regimen.

The aim of this study was to develop a population pharmacokinetic model of digoxin in patients over 90 years old and to propose an equation for adjusting digoxin dose in this population. We included 326 nonagenarian patients admitted to Severo Ochoa University Hospital (Spain) who received digoxin and were under therapeutic drug monitoring. All data were retrospectively collected, and population modeling was performed with non-linear mixed-effect modeling software (NONMEM®). One- and two-compartment models were tested to calculate digoxin clearance (Cl), volume of distribution (Vd), absorption rate constant (Ka), and bioavailability (bioavailable fraction, F). The covariates were evaluated by stepwise covariate model building, and the final model was internally validated by bootstrap analysis with 1000 resamples. External validation was performed with another population of 95 patients with the same characteristics as the modeling group. The population was 26% males, with a mean age of 93.2 years (90-103 years), mean creatinine 1.11 mg/dL (0.42-3.81 mg/dL), and mean total body weight 61.2 kg (40-100 kg). The pharmacokinetics of digoxin were best described by a one-compartment model (ADVAN2 TRANS2), with first-order conditional estimation with interaction. The covariates with influence on our model were creatinine clearance based on the Cockcroft-Gault equation (CG), serum potassium (K), co-administration of loop diuretics, and sex: Cl/F = 4.55 · (CG/36.4)0.468 · 0.83LD · 1.21SEX; Vd/F = 355 · (K/4.3)-0.849; Ka = 1.22 h-1 [where LD indicates loop diuretics (1 for administered, 0 for otherwise) and SEX indicates patient sex (1 for male, 0 for female)]. Based on our results, we proposed an equation to adjust the digoxin dosing regimen in nonagenarian patients: dose (mg) = 0.144 · (CG/36.4)0.468 · 0.83LD · 1.21SEX. The greatest influence on digoxin clearance came from renal function calculated by the Cockcroft-Gault equation. Vd was decreased by K. The model developed showed a precise predictive performance to be applied for therapeutic drug monitoring.

Population pharmacokinetic analysis of sparsentan in healthy volunteers and patients with focal segmental glomerulosclerosis.

Sparsentan is a single-molecule dual endothelin angiotensin receptor antagonist (DEARA) currently under investigation as a treatment for focal segmental glomerulosclerosis (FSGS) and IgA nephropathy (IgAN). A population pharmacokinetic (PK) analysis was performed to characterize the PKs of sparsentan and to evaluate the impact of FSGS disease characteristics and co-medications as covariates on sparsentan PKs. Blood samples were collected from 236 healthy volunteers, 16 subjects with hepatic impairment, and 194 primary and genetic FSGS patients enrolled in nine studies ranging from phase I to phase III. Sparsentan plasma concentrations were determined using validated liquid chromatography-tandem mass spectrometry with a lower limit of quantitation of 2 ng/mL. Modeling was conducted with the first-order conditional estimation with η-ϵ interaction (FOCE-1) method in NONMEM. A total of 20 covariates were tested using a univariate forward addition and stepwise backward elimination analysis with significance level of p < 0.01 and p < 0.001, respectively. A two-compartment model with first-order absorption and an absorption lag time with proportional plus additive residual error (2 ng/mL) described sparsentan PKs. A 32% increase of clearance due to CYP3A auto-induction occurred at steady-state. Covariates retained in the final model included formulation, cytochrome P450 (CYP) 3A4 inhibitor co-administration, sex, race, creatinine clearance, and serum alkaline phosphatase. Moderate and strong CYP3A4 inhibitors comedications increased area under the concentration-time curve by 31.4% and 191.3%, respectively. This population PK model of sparsentan suggests that dose adjustments may be warranted for patients taking moderate and strong CYP3A4 inhibitors concomitantly, but other covariates analyzed may not require dose adjustments.

Assessment of the nlmixr R package for population pharmacokinetic modeling: A metformin case study.

nlmixr offers first-order conditional estimation (FOCE), FOCE with interaction (FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin's pharmacokinetic data using nlmixr and investigated SAEM and FOCEi's performance with respect to bias and precision of parameter estimates, and robustness to initial estimates. Compartmental models were fitted. The final model was determined based on the objective function value and inspection of goodness-of-fit plots. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100 times and resultant changes evaluated. The absorption kinetics of metformin depend significantly on food status. Under the fasted state, the first-order absorption into the central compartment was preceded by zero-order infusion into the depot compartment, whereas for the fed state, the absorption into the depot was instantaneous followed by first-order absorption from depot into the central compartment. The means of relative mean estimation error (rMEE) ( ) and rRMSE ( ) were 0.48 and 0.35, respectively. All parameter estimates given by SAEM appeared to be narrowly distributed and were close to the true value used for simulation. In contrast, the distribution of estimates from FOCEi were skewed and more biased. When initial estimates were perturbed, FOCEi estimates were more biased and imprecise. nlmixr is reliable for NLMEM. SAEM was superior to FOCEi in terms of bias and precision, and more robust against initial estimate perturbations.

Development of a Population Pharmacokinetic Model for the Diroximel Fumarate Metabolites Monomethyl Fumarate and 2-Hydroxyethyl Succinimide Following Oral Administration of Diroximel Fumarate in Healthy Participants and Patients with Multiple Sclerosis.

IntroductionDiroximel fumarate (DRF) is a next-generation oral fumarate that is indicated in the USA for relapsing forms of multiple sclerosis (MS). A joint population pharmacokinetic model was developed for the major active metabolite (monomethyl fumarate, MMF) and the major inactive metabolite (2-hydroxyethyl succinimide, HES) of DRF.MethodsMMF and HES data were included from 341 healthy volunteers and 48 patients with MS across 11 phase I and III studies in which DRF was administered as single or multiple doses. Population modeling was performed with NONMEM version 7.3 with the first-order conditional estimation method.ResultsEstimated MMF clearance (CLMMF), volume of distribution, and absorption rate constant (Ka) were 13.5 L/h, 30.4 L, and 5.04 h−1, respectively. CLMMF and HES clearance (CLHES) increased with increasing body weight. CLHES decreased with decreasing renal function. CLMMF and CLHES were 28% and 12% lower in patients with MS than in healthy volunteers, respectively. Ka was reduced in the presence of low-, medium-, and high-fat meals by 37%, 51%, and 67%, respectively, for MMF; and by 34%, 49%, and 62%, respectively, for HES.ConclusionsAge, sex, race, and baseline liver function parameters such as total bilirubin, albumin, and aspartate aminotransferase were not considered to be significant predictors of MMF or HES disposition.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40120-021-00316-6.

An Enterohepatic Recirculation Population Pharmacokinetic and MIC-1 Pharmacokinetic-Pharmacodynamic Model for the MDM2 Inhibitor Navtemadlin (KRT-232) in Healthy Subjects

Background: Murine double minute 2 (MDM2) is the primary negative regulator of the tumor suppressor protein, p53. Navtemadlin (KRT-232), a potent and selective, orally available MDM2 inhibitor restores p53 activity to drive apoptosis of cancer cells in TP53 WT malignancies. Navtemadlin is currently being evaluated in a phase 3 trial of patients with relapsed or refractory myelofibrosis, as well as in numerous phase 1b/2 trials in various hematologic malignancies and solid tumors. Serum macrophage inhibitor cytokine-1 (MIC-1) is a pharmacodynamic (PD) marker of p53-mediated activity in patients treated with navtemadlin (Allard et al. HemaSphere. 2020). Using pharmacokinetic (PK) and PD data from a healthy subject food effect study (Wong et al. Blood. 2020), we developed a population PK (PPK) model that characterized enterohepatic recirculation (EHR) as a half-life extending element in the PK profiles of navtemadlin and its major acyl glucuronide metabolite M1. MIC-1 PD data were incorporated into the model to quantify plasma concentration-driven MIC-1 excursions and to simulate PK and PD across time and dose in healthy subjects.Methods: PPK and PK-PD models were developed using the first-order conditional estimation with interaction (FOCE-I) method in NONMEM 7.4, with model covariates selected using a stepwise forward addition and backward elimination method based on a 5% significance level. Model quality was checked by inspecting model parameters and confidence intervals, as well as standard residual-based and simulation-based diagnostics, and prediction-corrected visual predictive checks. Navtemadlin plasma concentration and MIC-1 serum concentration-time data from the food effect study (KRT-232-105) were modeled (N=30 subjects after a single 60 mg navtemadlin dose). Candidate PPK semi-mechanistic models that described EHR with multi-compartment structures (gut, central, and peripheral compartments for navtemadlin, and central and gallbladder [GB] compartments for M1), first-order elimination, and mealtime effects on GB emptying were tested. Post hoc parameter estimates from the final PPK model were used to generate individual predicted navtemadlin plasma concentrations for the PK-PD model. Based on exploratory plots, the pharmacological mechanism of action of navtemadlin, and a bile acid recycling model (Guiastrennec et al. CPT Pharmacometrics Syst Pharmacol. 2018), an indirect response equation was selected for the MIC-1 effect compartment (Figure 1a).Results: Navtemadlin and M1 plasma concentrations, including a second peak attributed to EHR at ~8-12 h, were well described by a model with central and peripheral compartments, constant basal M1 release rate into bile (KBR BASAL), and incremental mealtime GB emptying rate (KBR MEAL, Figure 1a). Figure 1b shows simulated navtemadlin and M1 amounts in various compartments over time. Median oral clearance of navtemadlin was estimated at 36.35 L/h. Estimated median apparent oral clearance of navtemadlin in healthy subjects was higher than PPK estimates for patients with advanced solid tumors (24.9 L/h [Ma et al. Blood. 2019]). The median central and peripheral volumes of navtemadlin were 159 L and 390 L, respectively. Navtemadlin exposure was higher in healthy female subjects relative to male subjects. Between-subject variability in clearance was 31%. Typical MIC-1 maximum stimulatory effect (S max) was estimated at 6.82, close to the median maximum ratio of MIC-1 to baseline MIC-1 (7.29) in the observed data. SC 50 was estimated at 85.22 ng/mL, with a Hill coefficient of 2.02, indicating a relatively steep increase in MIC-1 serum concentration with increasing navtemadlin concentration. For both PPK and PK-PD models, diagnostic plots confirmed an adequate fit. Subjects with lower baseline MIC-1 had a larger response and reached a maximum MIC-1 concentration later. Older subjects had the largest covariate impact, with a higher MIC-1 response.Conclusion: A two-compartment PPK model with basal and incremental mealtime GB emptying rates captured concentration-time data for navtemadlin and its metabolite M1. EHR was evident and navtemadlin reabsorption following hydrolysis of biliary M1 in the intestine contributed to navtemadlin half-life. An indirect stimulatory PK-PD model effectively described the relationship between navtemadlin and MIC-1 in healthy subjects. [Display omitted] DisclosuresZhang: Certara, Inc.: Current Employment; Milad Pharmaceutical Consulting, LLC.: Ended employment in the past 24 months. Wong: Kartos Therapeutics: Current Employment; AbbVie Biotherapeutics: Current equity holder in publicly-traded company. Slatter: Telios Pharma: Current holder of stock options in a privately-held company; Kartos Therapeutics: Current Employment, Current holder of stock options in a privately-held company; AstraZeneca: Current equity holder in publicly-traded company; Amgen: Divested equity in a private or publicly-traded company in the past 24 months. OffLabel Disclosure:Yes, navtemadlin (KRT-232) is an investigational small molecule MDM2 inhibitor.

Effects of Letermovir and/or Methylprednisolone Coadministration on Voriconazole Pharmacokinetics in Hematopoietic Stem Cell Transplantation: A Population Pharmacokinetic Study.

ObjectiveThe aim of this study was to identify factors affecting blood concentrations of voriconazole following letermovir coadministration using population pharmacokinetic (PPK) analysis in allogeneic hematopoietic stem cell transplant (allo-HSCT) recipients.MethodsThe following data were retrospectively collected: voriconazole trough levels, patient characteristics, concomitant drugs, and laboratory information. PPK analysis was performed with NONMEM® version 7.4.3, using the first-order conditional estimation method with interaction. We collected data on plasma voriconazole steady-state trough concentrations at 216 timepoints for 47 patients. A nonlinear pharmacokinetic model with the Michaelis–Menten equation was applied to describe the relationship between steady-state trough concentration and daily maintenance dose of voriconazole. After stepwise covariate modeling, the final model was evaluated using a goodness-of-fit plot, case deletion diagnostics, and bootstrap methods.ResultsThe maximum elimination rate (Vmax) of voriconazole in patients coadministered letermovir and methylprednisolone was 1.72 and 1.30 times larger than that in patients not coadministered these drugs, respectively, resulting in decreased voriconazole trough concentrations. The developed PPK model adequately described the voriconazole trough concentration profiles in allo-HSCT recipients. Simulations clearly showed that increased daily doses of voriconazole were required to achieve an optimal trough voriconazole concentration (1–5 mg/L) when patients received voriconazole with letermovir and/or methylprednisolone.ConclusionsThe development of individualized dose adjustment is critical to achieve optimal voriconazole concentration, especially among allo-HSCT recipients receiving concomitant letermovir and/or methylprednisolone.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40268-021-00365-0.

Effect of HIV, antiretrovirals, and genetics on methadone pharmacokinetics: Results from the methadone antiretroviral pharmacokinetics study

BackgroundMethadone treatment of opioid use disorder in HIV-infected individuals is complicated by drug-drug interactions. Genetic and other cofactors further contribute to interindividual variability in methadone pharmacokinetics. We used population pharmacokinetics to estimate the effect of drug-drug interactions, genetics, and other cofactors on methadone pharmacokinetics in a methadone maintained population in Vietnam. MethodsPlasma R- and S-methadone levels were measured in 309 methadone maintained individuals just before and 2−5 h following methadone dosing. A linear one-compartment population pharmacokinetic model with first-order conditional estimation with interaction was used to evaluate methadone clearance (CL/F) and volume of distribution (V/F). The influence of covariates on parameter estimates was evaluated using stepwise covariate modeling. Covariates included HIV status, antiretroviral use (efavirenz or nevirapine), weight, BMI, age, methadone dose, and 8 single nucleotide polymorphisms in across the CYP2B6, ABCB1, and NR1I3 genes. ResultsTaking either efavirenz or nevirapine increased R-methadone CL/F 220%. Nevirapine and efavirenz increased S-methadone CL/F by 404% and 273%, respectively. Variants in NR1I3 increased R- and S-methadone CL/F by approximately 20% only in patients taking efavirenz. Different alleles in ABCB1 rs2032582 either increased or decreased R-methadone CL/F by 10%. The CYP 2B6*4 variant decreased S-methadone CL/F by 18%. HIV-infection increased R- and S-methadone CL/F and V/F by 24%–39%. ConclusionsThe HIV antiretrovirals nevirapine and efavirenz significantly increase methadone clearance. Variants inNR1I3 increased the effect of efavirenz on methadone clearance. Other variants affecting methadone CL/F were also confirmed. To our knowledge, this is the first report of HIV itself affecting methadone pharmacokinetics.

Modeling and Simulation for Individualized Therapy of Amisulpride in Chinese Patients with Schizophrenia: Focus on Interindividual Variability, Therapeutic Reference Range and the Laboratory Alert Level.

PurposeTo explain the high inter-individual variability (IIV) and the frequency of exceeding the therapeutic reference range and the laboratory alert level of amisulpride, a population pharmacokinetic (PPK) model in Chinese patients with schizophrenia was built based on therapeutic drug monitoring (TDM) data to guide individualized therapy.Patients and MethodsPlasma concentration data (330 measurements from 121 patients) were analyzed using a nonlinear mixed-effects modeling (NONMEM) approach with first-order conditional estimation with interaction (FOCE I). The concentrations of amisulpride were detected by HPLC-MS/MS. Age, weight, sex, combination medication history and renal function status were evaluated as main covariates. The model was internally validated using goodness-of-fit, bootstrap and normalized prediction distribution error (NPDE). Recommended dosage regimens for patients with key covariates were estimated on the basis of Monte Carlo simulations and the established model.ResultsA one-compartment model with first-order absorption and elimination was found to adequately characterize amisulpride concentration in Chinese patients with schizophrenia. The population estimates of the apparent volume of distribution (V/F) and apparent clearance (CL/F) were 12.7 L and 1.12 L/h, respectively. Age significantly affected the clearance of amisulpride and the final model was as follows: CL/F=1.04×(AGE/32)−0.624 (L/h). To avoid exceeding the laboratory alert level (640 ng/mL), the model-based simulation results showed that the recommended dose of amisulpride was no more than 600 mg/d for patients aged 60 years, 800 mg/d for those aged 40 years and 1200 mg/d for those aged 20 years, respectively.ConclusionDosage optimization of amisulpride can be carried out according to age to reduce the risk of adverse reactions. The model can be used as a suitable tool for designing individualized therapy for Chinese patients with schizophrenia.

Delay differential equations based models in NONMEM.

Delay differential equations (DDEs) are commonly used in pharmacometric models to describe delays present in pharmacokinetic and pharmacodynamic data analysis. Several DDE solvers have been implemented in NONMEM 7.5 for the first time. Two of them are based on algorithms already applied elsewhere, while others are extensions of existing ordinary differential equations (ODEs) solvers. The purpose of this tutorial is to introduce basic concepts underlying DDE based models and toshow how they can be developed using NONMEM. The examples include previously published DDE models such as logistic growth, tumor growth inhibition, indirect response with precursor pool, rheumatoid arthritis, and erythropoiesis-stimulating agents. We evaluated the accuracy of NONMEM DDE solvers, their ability to handle stiff problems, and their performance in parameter estimation using both first-order conditional estimation (FOCE) and the expectation-maximization (EM) method. NONMEM control streams and excerpts from datasets are provided for all discussed examples. All DDE solvers provide accurate and precise solutions with the number of significant digits controlled by the error tolerance parameters. For estimation of population parameters, the EM method is more stable than FOCE regardless of the DDE solver.

Abstract CT123: Population pharmacokinetics of ripretinib in patients with advanced malignancies

Abstract Ripretinib is a tyrosine kinase inhibitor (TKI) indicated for the treatment of adult patients with advanced gastrointestinal stromal tumor (GIST) who have received prior treatment with 3 or more kinase inhibitors, including imatinib. In a phase 1 study (NCT02571036), the maximum tolerated dose was not reached at doses up to 200 mg twice daily (BID). Ripretinib 150 mg BID intrapatient dose escalation regimen was offered to patients in the phase 1 and 3 trials (INVICTUS, NCT03353753) after radiologic progression at 150 mg once daily (QD). The BID dose was well tolerated with a similar safety profile to the 150 mg QD (approved dose regimen). In this analysis, the population pharmacokinetics (popPK) of ripretinib and DP-5439, a metabolite TKI with in vitro activity and exposure similar to ripretinib, were characterized and potential covariates influencing exposure were evaluated. The popPK models were developed for ripretinib and DP-5439 using 5284 and 5160 quantifiable concentrations, respectively, from 350 patients pooled from the phase 1 and INVICTUS phase 3 studies. Models were estimated using first-order conditional estimation with interaction method in NONMEM® (version 7.3; ICON, Hanover, MD, USA) and evaluated based on standard goodness-of-fit metrics. A covariate analysis was conducted to assess the sources of variability in ripretinib pharmacokinetics (PK) using a full model approach with backward elimination (significance level = 0.005). Tested covariates included age, body weight, sex, race, tumor type, prior gastrectomy, and mild hepatic impairment and mild to moderate renal impairment. Ripretinib oral PK was well described by a 2-compartment model with zero-order drug release at the absorption site followed by first-order absorption with a modest, linear dose-dependent decrease in relative bioavailability and linear elimination. A high-fat meal was predicted to increase the ripretinib AUC by 36% at 150 mg QD relative to the fasted state. The only covariate effect retained in the final popPK model for ripretinib was 29% lower apparent clearance in females compared with males, resulting in a 40% higher AUC in females. No other covariates were identified for ripretinib. The resulting effect on DP-5439 was similar. PK exposure in patients with mild hepatic impairment or mild to moderate renal impairment was similar to that in patients with normal organ function. There were no clinically meaningful differences in the PK of ripretinib based on age, race, body weight, or tumor type. Based on the safety profile of ripretinib observed in patients with advanced GIST and PK variability, the effects of sex, fasted state, and prior gastrectomy on ripretinib PK were not considered clinically significant. Therefore, ripretinib can be taken with or without food by all patients and no dose adjustment is recommended for patients with mild hepatic impairment or patients with mild to moderate renal impairment. Citation Format: Suzanne George, Filip Janku, Ping Chi, Margaret von Mehren, Neeta Somaiah, Hans Gelderblom, Robin L. Jones, Martine Allard, Adekemi Taylor, Xiaoyan Li, Julie Meade, Vienna Reichert, Rodrigo Ruiz-Soto, Jing Wang, Michael C. Heinrich. Population pharmacokinetics of ripretinib in patients with advanced malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr CT123.

Elucidating Exposure-Response (Safety and Efficacy) of ADCT-402 (Loncastuximab Tesirine), a Novel Pyrrolobenzodiazepine-Containing Antibody Drug Conjugate, for Recommended Phase 2 Dose Determination in Patients with Relapsed or Refractory Non-Hodgkin Lymphoma

▪Introduction: ADCT-402 (loncastuximab tesirine) is an antibody-drug conjugate (ADC) composed of a humanized CD19-specific IgG1 antibody stochastically conjugated to a pyrrolobenzodiazepine (PBD) dimer cytotoxin via a cleavable maleimide linker. In this Phase 1 dose escalation trial of heavily pre-treated patients with B-cell non-Hodgkin lymphoma (NHL), loncastuximab tesirine (Lonca-T) 15 to 200 µg/kg was administered every 3 weeks (q3w) by intravenous infusion. The dose and pharmacokinetic (PK) exposure of Lonca-T were modeled as drivers of safety (treatment-emergent adverse events [TEAEs]) and efficacy (reduction in tumor size) for the determination of the Recommended Phase 2 Dose (RP2D).Methods:Concentrations of PBD-conjugated antibody (Ab) in serum were determined using a validated electrochemiluminescence immunoassay, then analyzed by population PK methodology using NONMEM (version 7.3, first-order conditional estimation). Associations between exposure (dose and Bayesian-estimated individual-patient exposure metrics) and the maximum severity of early (Cycle 1) and early or later (all cycles) TEAEs were evaluated for overall TEAEs, anemia, platelets, neutrophils, hemoglobin, fatigue, edema and pleural effusion. Associations of dose and PK with maximum change from baseline tumor size were also determined to identify potential relationships between exposure and activity (complete response plus partial response). For the PK population, drug concentrations were described using the log-transformed both sides approach with a 3-compartment open model and zero-order infusion. In the final population model, gender was retained as a covariate on central volume of distribution.Results: Data from 44 patients (28 males and 16 females) were included in the population PK model. Patients had a mean (range) age of 67 years (24-85) and weight of 87 kg (42-143). A positive relationship was apparent for maximum severity TEAEs, anemia, and thrombocytopenia both in Cycle 1 and in later cycles. A positive relationship was evident for neutropenia, edema and pleural effusion in later cycles only. For patients with and without Grade 3/4 TEAEs, median (5th, 95th percentile) PBD-conjugated Ab area under the curve (AUC) was 13.6 mg*Day/L (0.359, 40.8), and 6.33 mg*Day/L (0.308, 35.0), respectively. Increased exposure to Lonca-T in Cycle 1 was associated with decreased tumor size, with the model giving a dosage of 120 µg/kg q3w as a median minimum dose necessary for requisite efficacy. To achieve at least a 50% tumor size reduction from baseline, the median (min, max) PBD-conjugated Ab AUC was ~66 mg*Day/L (4.69, 294), which is close to the median AUC values of 63.9 and 66.9 mg*Day/L from patients in the 120 and 200 µg/kg cohorts, respectively.Conclusions: By quantitating the differences between exposure associated with grade of a given TEAE and the exposure necessary for efficacy, an optimal dose of Lonca-T associated with an acceptable set of toxicity thresholds was preliminarily identified. Since this trial is ongoing, supplemental pending data will be incorporated into the model, particularly for the 150 µg/kg dose, for an alternate dosage frequency (q6w), for individual patient CD19 status at baseline, and for NHL subtype, to provide the rationale for dosage and regimen selection and definition of the RP2D. DisclosuresO'Connor:ADC Therapeutics: Research Funding. Kahl:Seattle Genetics: Consultancy; ADC Therapeutics: Research Funding; Celgene: Consultancy; Gilead: Consultancy; Genentech: Consultancy. Hamadani:Takeda, Otsuka, MedImmune, Merck, ADC Therapeutics: Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau; Celgene, Cellerant, Jansen, MedImmune: Consultancy. Caimi:Celgene: Speakers Bureau; ADC Therapeutics: Research Funding. Reid:ADC Therapeutics, Millennium: Research Funding. Feingold:ADC Therapeutics: Employment, Other: Potential equity interest. Havenith:ADC Therapeutics: Employment, Other: Stock option interest. He:ADC Therapeutics: Employment, Other: Potential equity interest. Mould:Projections Research Inc, a consulting company for pharmaceutical industry: Consultancy. Freedman:Projections Research Inc, Gerson Lerhrman Group: Consultancy; Freedman patent: Patents & Royalties. Boni:ADC Therapeutics: Employment, Other: Potential equity interest.

Nonlinear Mixed Effects Modeling of Deterministic and Stochastic Dynamical Systems in Wolfram Mathematica

Nonlinear mixed effects (NLME) modeling is a powerful tool to analyze time-series data from several individual entities in an experiment. In this paper, we give a brief overview of a package for NLME modeling in Wolfram Mathematica entitled NLMEModeling, implementing the first-order conditional estimation method with sensitivity equation-based gradients for parameter estimation. NLMEModeling supports mixed effects modeling of dynamical systems where the underlying dynamics are described by either ordinary or stochastic differential equations combined with observation equations with flexible observation error models. Moreover, NLMEModeling is a user-friendly package with functionality for parameter estimation, model diagnostics (such as goodness-of-fit analysis and visual predictive checks), and model simulation. The package is freely available and provides an extensible add-on to Wolfram Mathematica.

15182 Population pharmacokinetic modeling and simulations for GBR 830, a first-in-class humanized monoclonal antibody inhibiting OX40, to support clinical development in patients with moderate to severe atopic dermatitis

GBR 830 is a monoclonal antibody against OX40, a costimulatory receptor present on activated T cells that are responsible for effector and memory immune responses. The safety and tolerability of single and repeated administration of GBR 830 has been demonstrated in phase 1 studies with healthy subjects and a phase 2a proof-of-concept study with patients who had moderate to severe atopic dermatitis (AD). To support pharmacokinetic (PK)-based dose selection for clinical development, a population PK model was developed using data from these completed studies (phase 1, PoC), with a total of 120 subjects contributing 1960 observations. Data were modeled employing NONMEM 7.3 using a first-order conditional estimation with interaction method. Intravenous (IV) and subcutaneous (SC) serum profiles were integrated into a 2-compartment model with linear clearance. Covariates (body weight, anti-drug antibody [ADA] status, disease [AD], age, sex, and race) were evaluated graphically before selecting for formal testing. Model parameters included systemic clearance (CL), intercompartmental clearance (Q), central (Vc) and peripheral (Vp) volumes, first order absorption from SC injection compartment (KA) and associated between-subject variability (BSV). Body weight was found to be the most important covariate influencing PK, followed by ADA. Final population parameter estimates were derived and model goodness-of-fit was assessed. The predictability was confirmed by prospective simulations of repeat IV infusions. Due to lack of rodent cross-reactivity for GBR 830, or any available surrogate antibody, dose regimen selection for an ongoing phase 2b study (NCT03568162) relied upon PK simulations to achieve a Ctrough that matched human whole-blood receptor occupancy.