First-order Elimination Research Articles

Utilizing an Opportunistic Clinical Study and Population-Based Pharmacokinetic Models to Identify Rational Empiric Dosing Regimens for Piperacillin-Tazobactam in Critically Ill Patients.

Determining an effective dosing regimen for piperacillin-tazobactam in critically ill patients is challenging due to substantial pharmacokinetic variability caused by complex pathophysiological changes. To address this need, a prospective clinical study was conducted, which enrolled 112 critically ill patients and employed an opportunistic sampling strategy. Population modeling and simulation were performed to characterize the pharmacokinetics (PK) and probability of target attainment (PTA) of piperacillin-tazobactam under various dosing regimens. Both piperacillin and tazobactam final models were one-compartment models with zero-order input and first-order elimination. Significant covariates included lean body weight for piperacillin and creatinine clearance along with continuous renal replacement therapy (CRRT) for both drugs. Monte Carlo simulations demonstrated that continuous infusion can achieve higher PTA than intermittent and extended infusions. When considering the minimum inhibitory concentration (MIC) of 16 mg/L for Pseudomonas aeruginosa (a frequently encountered bacterial pathogen among critically ill patients) and a PK/PD target of 100% fT >MIC, continuous infusion of 6 g/day is recommended for critically ill patients with a CLcr <60 mL/min, 9 g/day for patients with CLcr in the range of 60 to 129 mL/min, and 12 g/day for patients with a CLcr ≥130 mL/min. In addition, extended infusion represents a good alternative, especially the 3 g q6h or 4 g q6h regimens which can achieve the designated European Committee on Antimicrobial Susceptibility Testing (EUCAST) non-species-related PK/PD breakpoint of 8 mg/L. Our study provided valuable insight into PTA outcomes, which, together with individual renal function of future patients and institution-specific piperacillin susceptibility patterns, may assist physicians when making dosing decisions.

Population pharmacokinetic analysis of quizartinib in patients with newly diagnosed FLT3-internal-tandem-duplication-positive acute myeloid leukemia.

The population pharmacokinetics (PK) of quizartinib and its pharmacologically active metabolite AC886 have been previously described in healthy volunteers (HV) and relapsed/refractory (R/R) FLT3-internal-tandem-duplication-positive (FLT3-IDT-positive) acute myeloid leukemia (AML) patients receiving quizartinib monotherapy. In this analysis, we characterized the population PK of quizartinib and AC886 in newly diagnosed FLT3-ITD-positive AML patients receiving standard induction and consolidation chemotherapy as background treatment, using data from the Phase 3 QuANTUM-First trial and 12 earlier studies. Quizartinib PK were best described by a three-compartment model with sequential zero- and first-order absorption and first-order elimination. A two-compartment model with first-order metabolite formation and first-order elimination best fitted AC886 data. The PK of both moieties showed large interindividual variability (approximately 70% coefficient of variation for systemic clearances). The use of strong cytochrome P450 3A (CYP3A) inhibitors had the largest impact on exposure, increasing the steady-state area under the curve during the dosing interval (AUCss) by 1.8-fold. This is consistent with observations in HV and R/R AML patients and confirms the need for dose adjustments during coadministration. A novel finding in newly diagnosed AML patients was the phase-dependent change in steady-state quizartinib exposure: dose-normalized AUCss values were 0.6-fold during induction, similar during consolidation, and 1.4-fold during continuation compared to R/R AML patients receiving quizartinib monotherapy. The present analysis highlighted the comparison of quizartinib and AC886 PK between newly diagnosed AML patients and previously studied populations, informed dose modifications needed with strong CYP3A inhibitors, and supported the use of derived individual exposure metrics in separate exposure-response analyses.

Population Pharmacokinetics and Dose Optimization of Piperacillin in Infants and Children with Pneumonia.

We aimed to determine the piperacillin disposition and optimize the dosing regimens for infants and children with pneumonia. An opportunistic sampling strategy was used in this pharmacokinetic study. High-performance liquid chromatography was used to measure the concentrations of piperacillin in plasma samples. A population pharmacokinetic model was conducted using NONMEM. The pharmacokinetic data of 90 samples from 64 infants and children with pneumonia (age range: 0.09-1.72 years for infants and 2.12-11.10 years for children) were available. A two-compartment model with first-order elimination was the most suitable model to describe the population pharmacokinetics of piperacillin. A covariate analysis indicated that body weight and age were significant factors affecting clearance. Monte Carlo simulations showed that a 50-mg/kg every 8 h or every 12 h dosing regimen results in underdosing. Results both in infants and children showed that an extended infusion (3 h) of various dosing regimens (80, 100, or 130 mg/kg) three times daily or a 300-mg/kg continuous infusion can reach a therapeutic level based on the chosen target for the probability of target attainment threshold of 70%, 80%, and 90% at minimum inhibitory concentration breakpoints of 8 mg/L and 16 mg/L. A population pharmacokinetic model was obtained to evaluate the disposition of piperacillin, and the optimal dosing regimens were provided for use in infants and children with pneumonia.

Pharmacokinetic Modeling and Model-Based Hypothesis Generation for Dose Optimization of Clonidine in Neonates With Neonatal Opioid Withdrawal Syndrome.

The No-POPPY study (NCT03396588), a double-blind, randomized trial compared morphine with clonidine therapy for neonatal opioid withdrawal syndrome (NOWS) and found that the duration of treatment was similar across groups. This is significant because perinatal use of morphine has the potential for neurodevelopmental consequences. Still, the clonidine group reached symptom stabilization (Finnegan score (FS) < 8) later than the morphine group and had a more significant number of patients who required adjunct therapy. However, the mean FS was consistently lower in the clonidine group after day 6. This prompted us to use pharmacokinetic (PK) and parametric time-to-event (TTE) modeling to simulate dosage schedules that may decrease the time to stabilization and reduce the need for adjunct therapy. Population PK (popPK) analysis was conducted, and the final model was a one-compartment model with first-order absorption and elimination, incorporating allometric scaling and age effect on apparent clearance (CL/F) and apparent volume (V/F). The population estimates for CL/F and V/F were 13.6 L/h/70 kg and 416 L/70 kg, respectively, similar to the reported values. A Weibull model described the TTE data best, followed by incorporating predicted average concentrations to yield the final Weibull accelerated failure time model. Simulations of dosing strategies showed that increasing both the starting and maximum doses could potentially shorten the time to stabilization, and thus, length of treatment and hospital stay. Given the hypothesis-generating nature of this analysis, the recommended dosing regimens should be tested prospectively to evaluate their benefits.

Population pharmacokinetic modeling of zavegepant, a calcitonin gene-related peptide receptor antagonist, in healthy adults and patients with migraine.

Zavegepant (ZAVZPRET™) is a high-affinity, selective, small-molecule calcitonin gene-related peptide receptor antagonist available for acute treatment of migraine in adults. A population pharmacokinetic analysis was performed to describe zavegepant plasma concentration-time course, characterize bioavailability, and identify covariates affecting zavegepant exposure. The model was developed and validated using data from 10 phase I clinical studies, wherein zavegepant was administered intravenously, intranasally, or orally to healthy adults and patients with migraine. Plasma concentration-time data were analyzed using nonlinear mixed-effects modeling. A three-compartment model with first-order elimination from the central compartment, and sequential zero- and first-order absorption best described the observed plasma concentration-time course of zavegepant. Bioavailability was 5.1% and 0.65% for intranasal and oral treatment, respectively; absorption rate constants were 5.8 and 0.8 h-1, respectively. Body weight-based empirical allometric scaling was applied using standard exponents (0.75 for clearance and 1 for volume of distribution). Age (range 18-71 years), race, ethnicity, sex, renal function, and co-administration of oral contraceptives or sumatriptan did not significantly change zavegepant pharmacokinetics. Moderate hepatic impairment (Child-Pugh score 7-9) or co-administration of rifampin decreased elimination clearance of oral zavegepant by ~40%. The zavegepant population pharmacokinetic model adequately characterized zavegepant concentration-time profiles, the bioavailability of intranasal and oral zavegepant, as well as the effect of intrinsic and extrinsic factors on zavegepant pharmacokinetics.

Establishment and validation of a population pharmacokinetic model for apatinib in patients with tumors

ObjectiveThis study aimed to develop a population pharmacokinetic (PPK) model for oral apatinib in Chinese oncology patients and investigate the factors influencing the pharmacokinetics of apatinib.MethodsWe gathered 199 blood concentration monitoring data points from 91 inpatient oncology participants receiving oral apatinib at the Third Affiliated Hospital of Soochow University. Covariates, such as age, gender, body weight, and indices of liver and renal function, were examined to assess their influence on the pharmacokinetic parameters of apatinib. The PPK model was developed using the nonlinear mixed-effects modeling procedure (NONMEM), and model validation was conducted using the bootstrap method and normalized prediction distribution error (NPDE) method.ResultsThe structural model adopted a one-compartment structure with first-order elimination. Notably, aspartate aminotransferase (AST) and the co-administered drug type emerged as primary covariates affecting apatinib clearance (CL/F). The finalized model was expressed as CL/F (L/h) = 56.7 × (AST/26.6)−0.298 × θ, when apatinib was combined with monoclonal antibodies, θ was 1; when combined with paclitaxel, θ was 0.58; when combined with other drugs (e.g., platinum, capecitabine, or the combination of tegafur, gimeracil, and oteracil potassium), θ was 1.60; When used as monotherapy, θ was 1.38. V/F = 674 L, and the absorption rate constant (Ka) was fixed at 0.08 h−1. Bootstrap results affirmed the model’s reliability and stability, while NPDE outcomes attested to the model’s fit.ConclusionOur study successfully established a PPK model for apatinib in oncology patients, revealing that liver function status and co-administered drug types significantly impacted apatinib CL/F. This finding underscored the potential necessity for dose adjustments to optimize efficacy, particularly in patients undergoing different chemotherapy regimens involving apatinib.

Dosing strategy of tacrolimus when co-administered with Wuzhi tablet in renal transplant recipients.

Tacrolimus (TAC) is a first-line immunosuppressant to prevent allograft rejection. Wuzhi tablet is widely used as a TAC-sparing agent in China that could significantly elevate TAC exposure. However, insufficient data support the dose recommendation of TAC when co-administered with Wuzhi. A total of 305 adult renal transplant patients with 2,541 TAC trough concentrations (C0) were enrolled for population pharmacokinetic (PPK) modeling. CYP3A5 polymorphism was genotyped, and corresponding clinical factors were recorded. Nonlinear mixed-effects modeling and Monte Carlo simulation were used for dose recommendation. PK parameters were calculated based on one-compartment model with first-order absorption and elimination. The estimated total clearance (CL/F) and volume of distribution (Vd/F) of TAC were 23.84 L/h and 1,075.96 L, respectively. Wuzhi, CYP3A5 genotype, hematocrit (HCT), and weight were found to have a significant influence on CL/F. CL/F was significantly lower in the individuals who were CYP3A5 non-expressers and received TAC together with Wuzhi. CYP3A5 genotype (expressers or non-expressers), body weight (40-80 kg), and hematocrit (20 - 40%) were selected as the specific clinical scenarios, and the starting dose of TAC ranged from 1.5 to 4.5 mg when co-administered with Wuzhi. We establish a TAC PPK model comprising Wuzhi as a covariate in renal transplant recipients and recommend an initial dose of TAC when co-administered with Wuzhi, which could provide reference for the individualized regimens of TAC.

Population Pharmacokinetic Modelling of Norepinephrine in Healthy Volunteers Prior to and During General Anesthesia.

Intraoperation hypotension (IOH) is commonly observed in patients undergoing surgery under general anesthesia, and even a brief episode of IOH can lead to unfavorable outcomes. To reduce the risk, blood pressure is closely measured during general anesthesia, and norepinephrine (NE) is frequently administered if hypotension is detected. Despite its routine application, information on the dose-exposure-response relationship of NE remains limited. Additionally, quantification of the influence of general anesthesia on the pharmacokinetics (PK) of NE is lacking. In this study, we aimed to describe NE PK in healthy volunteers and the influence of general anesthesia on its PK. A single-center, cross-over study was conducted in healthy volunteers. The volunteers received a step-up NE dosing scheme (0.04, 0.08, 0.12, 0.16 and 0.20 mcg-1/kg-1/min-1) first in the awake state and then under general anesthesia. General anesthesia was administered using a propofol/remifentanil Eleveld target-controlled infusion. During general anesthesia, a 30-second electrical stimulus was given as surrogate for surgical incision to the volunteers at each dosage step. Blood samples were drawn before the initial dosing and after each dosing step, and plasma NE, propofol and remifentanil concentrations were subsequently determined. A population PK model was developed using non-linear mixed effects modelling. Simulations were conducted to predict the plasma NE concentration in patients at different measured propofol concentrations. A total of 1219 samples were analyzed from 36 volunteers. A two-compartment model with a first-order elimination best described the data. Weight, age, and session effect (awake vs general anesthesia) were identified as relevant covariates on the clearance (CL) of NE. A 10% decrease in NE CL was observed after general anesthesia induction. This difference between sessions is better explained by the measured concentration of propofol, rather than the anticipated impact of cardiac output. The estimated post-stimulation NE concentration is 0.66 nmol/L-1 (95% CI 0.06-1.20 nmol/L-1) lower than the pre-stimulation NE concentration. Model simulation indicates that patients at a higher measured propofol concentration (e.g., 6 mcg/mL-1) exhibited higher NE concentrations (95% PI 18.10-43.89 nmol/L-1) than patients at a lower measured propofol concentration (e.g., 3 mcg/mL-1) (95% PI 16.81-38.91 nmol L-1). The NE PK is well described with a two-compartment model with a first-order elimination. NE CL exhibiting a 10% decrease under general anesthesia, with this difference being attributed to the measured concentration of propofol. The impact of stimulation on NE PK under general anesthesia is very limited. NL9312.

Population pharmacokinetics/pharmacodynamics of minocycline plus rifampicin in patients with complicated skin and skin structure infections caused by MRSA.

The population pharmacokinetics/pharmacodynamics (PK/PD) of minocycline, rifampicin and linezolid in patients with complicated skin and soft tissue infections (cSSTIs) caused by MRSA are described. Samples were collected in a Phase 4 study of oral minocycline plus rifampicin versus linezolid showing minocycline plus rifampicin to be non-inferior to linezolid. Antibiotics were assayed by HPLC or LC-MS, and a population PK model was developed using Pmetrics. The association between PK/PD indices and patient outcomes was explored. A three-compartment model (with an absorption compartment) with first-order input and elimination best described the data for the three drugs. No covariates were included in the final model. The population median values (95% credibility limits) of the clearance and volume of distribution were 7.412 L/h (5.121-8.361) and 14.155 L (6.799-33.901) for minocycline, 5.683 L/h (3.703-7.726) and 7.736 L (6.031-8.948) for rifampicin, and 1.970 L/h (1.326-2.499) and 20.169 L (12.857-32.629) for linezolid, respectively. Maximum a posteriori probability-Bayesian estimation plots of observed versus predicted had a slope of 0.999 r20.967 for minocycline, slope 0.998 r20.769 for rifampicin and slope 0.998 r20.895 for linezolid. PK/PD indices were not related to clinical outcome. Taking a translational minocycline fAUC24h/MIC target of >0.5 for minocycline in the presence of rifampicin, 96% (49/51) of patients reached the target. Population PK models of minocycline, rifampicin and linezolid were developed in patients with MRSA cSSTI and almost all patients reached the predefined PD index targets. As a result, neither AUC, MIC nor the AUC/MIC ratio could be related to clinical outcome.

Comprehensive population pharmacokinetic modelling of sugemalimab, an anti-programmed death-ligand 1 (PD-L1) human monoclonal antibody, in patients with solid tumours or lymphomas across multiple Phase I-III studies.

The aim of this study was to develop a population pharmacokinetics model for sugemalimab, a monoclonal antibody that targets programmed death-ligand 1 (PD-L1), using data from Phase I-III trials and to assess clinical factors affecting sugemalimab exposure. A nonlinear mixed-effect modelling approach was employed to analyse pooled data from nine studies involving 1628 subjects to characterize the PopPK of sugemalimab. This investigation examined the influence of various covariates on sugemalimab pharmacokinetics (PK), encompassing demographics, baseline hepatic and renal function-related covariates, and others (including anti-drug antibody [ADA], combination treatment, Eastern Cooperative Oncology Group [ECOG] performance score, tumour burden and tumour type). Estimation accuracy and predictive ability of the final model were evaluated using various methods. The influence of covariates on sugemalimab exposure was assessed by simulation from the final model. A two-compartment model with first-order elimination and time-varying clearance effectively described the PK of sugemalimab. Covariate analyses revealed significant relationships between sugemalimab clearance and body weight, albumin, gender, ADA, tumour burden and tumour type. The statistically significant covariates on central volume were body weight, albumin, gender and tumour type. No significant relationships were found in the final model for age, race, alanine aminotransferase, aspartate aminotransferase, creatinine, total bilirubin, alkaline phosphatase, combination treatment, creatinine clearance, ECOG, renal function or hepatic function. All significant covariates demonstrated less than a 20% effect on sugemalimab exposure. The PopPK model adequately described the pharmacokinetic profile of sugemalimab with no clinically meaningful impact observed on its exposure across all covariates. Dose adjustment does not appear to be necessary.

Population pharmacokinetics of tacrolimus whole blood and peripheral blood mononuclear cell concentrations in stable kidney-transplanted patients.

Therapeutic drug monitoring of tacrolimus based on whole blood drug concentrations is routinely performed. The concentration of tacrolimus in peripheral blood mononuclear cells (PMBCs) is likely to better reflect drug exposure at the treatment target site. We aimed to describe the relationship between tacrolimus whole blood and PBMC concentrations, and the influence of patient characteristics on this relationship by developing a population pharmacokinetic model. We prospectively enrolled 63 stable adult kidney-transplanted patients and collected dense (12-h, n = 18) or sparse (4-h, n = 45) pharmacokinetic profiles of tacrolimus. PBMCs were isolated from whole blood (Ficoll density gradient centrifugation), and drug concentrations in whole blood and PBMCs were analysed using liquid chromatography-mass spectrometry. Patient genotype (CYP3A4/5, ABCB1, NR1I2) was assessed with PCR. Population pharmacokinetic modelling and statistical evaluation was performed using NONMEM. Tacrolimus whole blood concentrations were well described using a two-compartment pharmacokinetic model with a lag-time and first-order absorption and elimination. Tacrolimus PBMC concentrations were best estimated from whole blood concentrations with the use of a scaling factor, the ratio of whole blood to PBMC concentrations (RC:PBMC), which was the extent of tacrolimus distribution into PBMC. CYP3A5*1 non-expressors and NR1I2-25 385T allele expressors demonstrated higher RC:PBMC ratios of 42.4% and 60.7%, respectively. Tacrolimus PBMC concentration could not be accurately predicted from whole blood concentrations and covariates because of significant residual unexplained variability in the distribution of tacrolimus into PBMCs and may need to be measured directly if required for future studies.

Population pharmacokinetic model of ABL001/CTX-009 (anti-VEGF/DLL4) in adult cancer patients with solid tumor.

ABL001/CTX-009 is a bispecific antibody targeting delta-like ligand-4 and vascular endothelial growth factor A. In this study, we developed a population pharmacokinetic (PK) model of ABL001/CTX-009 in patients with solid tumors. A total of 712 plasma concentrations from 30 patients with relapsed or refractory solid tumors were collected from a phase 1 study (NCT03292783). A population PK model was developed using a nonlinear mixed-effect method and was evaluated by graphical and numerical methods. Using the model, the steady-state concentrations were simulated to compare weight-based and fixed-dose regimens and to find optimal dosing intervals. The PK of ABL001/CTX-009 was well described by a two-compartment model with a parallel first-order and Michaelis-Menten elimination kinetics. Body weight was selected as a significant covariate on V1. Model evaluation results suggested that the model was adequate and robust with good precision. Simulations after administrations of fixed or weight-based doses showed similar plasma concentrations. Additionally, 10 mg/kg for every other week and 15 mg/kg for every three-week administration showed comparable plasma concentrations. In conclusion, the model well described the plasma concentrations of ABL001/CTX-009 in patients with solid tumors. The simulation suggested that weight-based dose and fixed dose can provide equivalent systemic exposure.

Population Pharmacokinetics Modeling and Simulation of Deutenzalutamide, A Novel Androgen Receptor Antagonist, in Patients With Metastatic Castration-Resistant Prostate Cancer.

Deutenzalutamide is a new molecular entity androgen receptor antagonist. The primary aim of this study was to develop a population pharmacokinetic model of deutenzalutamide and evaluate effects of intrinsic and extrinsic factors on pharmacokinetics. A nonlinear mixed-effects modeling approach was performed to develop the population pharmacokinetic of deutenzalutamide using data from 1 Phase I trial of deutenzalutamide. Goodness-of-fit plots, prediction-corrected visual predictive check, and bootstrap analysis were carried out to evaluate the final model. Simulation for the developed model was used to evaluate the covariate effects on the pharmacokinetics of deutenzalutamide. A 2-compartment model with first-order absorption and elimination from the central compartment was established for deutenzalutamide. The final covariate included body weight on peripheral compartment volume. This is the first research developing the population pharmacokinetic model of deutenzalutamide in patients with metastatic castration-resistant prostate cancer, and it is expected to support the future clinical administration of deutenzalutamide.

Use of a PK/PD Model to Select Cetagliptin Dosages for Patients with Type 2 Diabetes in Phase 3 Trials.

Cetagliptin is a novel dipeptidyl peptidase-4 (DPP-4) inhibitor developed for the treatment of patients with type 2 diabetes (T2D). Several phase 1 studies have been conducted in China. Modelling and simulation were used to obtain cetagliptin dose for phase 3 trials in T2D patients. A pharmacokinetic (PK)/pharmacodynamic (PD) model and model-based analysis of the relationship between hemoglobin A1c (HbA1c) and dosage was explored to guide dose selection of cetagliptin for phase 3 trials. The PK/PD data were derived from four phase 1 clinical studies, and sitagliptin 100 mg was employed as a positive control in studies 1, 3, and 4. The PK profiles of cetagliptin were well described by a two-compartment model with first-order absorption, saturated efflux, and first-order elimination. The final PD model was a sigmoid maximum inhibitory efficacy (Emax) model with the Hill coefficient. The final model accurately captured cetagliptin PK/PD, demonstrated by goodness-of-fit plots. Based on weighted average inhibition (WAI), the relationship between HbA1c and dose was well displayed. Cetagliptin 50 mg once daily or above as monotherapy or as add-on therapy appeared more effective in HbA1c reduction than sitagliptin 100 mg. Cetagliptin 50 mg or 100 mg once daily was selected as the dose for phase 3 trials of cetagliptin in T2D patients. The PK/PD model supports dose selection of cetagliptin for phase 3 trials. A model‑informed approach can be used to replace a dose-finding trial and accelerate cetagliptin's development.

Dosing of Venetoclax in Pediatric Patients with Relapsed Acute Myeloid Leukemia: Analysis of Developmental Pharmacokinetics and Exposure-Response Relationships

This work aimed to characterize the pharmacokinetics and exposure-response relationships of venetoclax in pediatric patients with relapsed or refractory (R/R) acute myeloid leukemia (AML) to identify venetoclax doses to be administered to pediatric patients in the phase 3 study. Data from 121 patients across three phase 1 studies enrolling pediatric patients with R/R malignancies were utilized to develop a population pharmacokinetic model to describe venetoclax pharmacokinetics in pediatric patients. Individual patient average venetoclax plasma concentration up to the event of interest, derived based on the population pharmacokinetics analysis, was used to evaluate the exposure-response relationships to efficacy (complete response) and safety (neutropenia and thrombocytopenia) endpoints for patients with AML who received venetoclax in combination with azacitidine, decitabine, or cytarabine (n = 36). The population pharmacokinetic model was then used to simulate exposures in pediatric age- and weight-based subgroups to identify the venetoclax doses for pediatric patients. The pharmacokinetic data were adequately described by the two-compartment population pharmacokinetic model with first-order absorption and elimination. The model accounted for cytochrome P450 3A developmental changes using a maturation function and incorporated allometric scaling to account for growth and body size effect. Weight was identified as a statistically significant covariate on clearance and volume of distribution and retained in the final model. Population pharmacokinetic estimates were comparable to previously reported estimates in adults. Exposure-response analyses suggested that the clinical efficacy of venetoclax in combination with high-dose cytarabine (HDAC) is maximized at 600 mg adult-equivalent, and higher doses are unlikely to enhance clinical efficacy. Venetoclax 600 mg adult-equivalent was selected for further development in combination with HDAC. Additionally, venetoclax 400 mg adult-equivalent was selected for bridging/maintenance therapy in combination with azacitidine. Flat exposure-response relationships were observed with Grade ≥3 neutropenia and thrombocytopenia. Doses were selected based on weight (allometric scaling) for children aged ≥2 years old and based on weight and CYP3A ontogeny for children aged <2 years. The selected age- and weight-based dosing scheme of venetoclax is projected to achieve venetoclax exposures in pediatric subgroups comparable to those observed in adults receiving venetoclax 400 mg or 600 mg. This work characterized the pharmacokinetics and exposure-response relationships of venetoclax in pediatric patients and guided the selection of pediatric dosing regimens in support of the venetoclax phase 3 trial in pediatric AML (NCT05183035). NCT03236857, NCT03181126, and NCT03194932.

Minimal mathematical model for glycation of albumin

BackgroundGlycated albumin (GA) is often described as a reflection of glucose exposure over the past 2–4 weeks. We examined the scale of the operative interval for changes in %GA from the perspective of a theoretical model for GA formation, by simulating the time course of changes in %GA after changes in glucose. MethodsProbability of survival of albumin (A) was according to first-order elimination based on t1/2 of 17 days. Probability of formation of GA from A per unit time was proportional to glucose (G) and a glycation rate constant, k, deduced from reference values for %GA vs. G. We then simulated the kinetics of changes in %GA for conditions in which a prior steady-state (constant G) was followed by a step change in G. ResultsThe glycation rate constant k was 9.79e-4/d/(mmol/L). We simulated changes in %GA for two scenarios involving step changes in G at time = 0: A. from 10 mmol/L to 15 mmol/L (%GA ultimately moves from 19.3% to 26.4%); B. from 15 mmol/L to 10 mmol/L (%GA ultimately moves from 26.4% to 19.3%). For both scenarios, the fractional transition of %GA between respective starting points and ultimate endpoints was after 30 days approximately 80% of the ultimate full transition. ConclusionsModel-based calculations support the description of %GA as a reflection of G over the past 4–6 weeks, longer than the period of 2–4 weeks that is commonly cited.

Population pharmacokinetics and exposure–response relationships of maribavir in transplant recipients with cytomegalovirus infection

Maribavir is approved for management of post-transplant cytomegalovirus (CMV) infections refractory and/or resistant to CMV therapies at a dose of 400 mg twice daily (BID). Population pharmacokinetic (PopPK) and exposure–response analyses were conducted to support the appropriateness of 400 mg BID dosing. A PopPK model was developed using non-linear mixed-effects modeling with pooled maribavir plasma concentration–time data from phase 1 and 2 studies (from 100 mg up to 1200 mg as single or repeated doses) and the phase 3 SOLSTICE study (400 mg BID). Exposure–response analyses were performed for efficacy, safety, and viral resistance based on data collected in the SOLSTICE study. Maribavir PK after oral administration was adequately described by a two-compartment model with first-order elimination, first-order absorption, and an absorption lag-time. There was no evidence that maribavir PK was affected by age, sex, race, diarrhea, vomiting, disease characteristics, or concomitant use of histamine H2 blockers, or proton pump inhibitors. In the SOLSTICE study, higher maribavir exposure was not associated with increased probability of achieving CMV DNA viremia clearance, nor with reduced probability of treatment-emergent maribavir-resistant CMV mutations. A statistically significant association with maribavir exposure was identified for taste disturbance, fatigue, and treatment-emergent serious adverse events, while transplant type, enrollment region, CMV DNA level at baseline, and/or CMV resistance at baseline were identified as additional risk factors for these safety outcomes. In conclusion, the findings of these PopPK and exposure–response analyses provide further support for the recommended maribavir dose of 400 mg BID.

Population pharmacokinetic and dose-response models of nepadutant, a selective antagonist of the NK2 receptors, in infants with colic.

The aim of the current analyses was to develop a population pharmacokinetic model for nepadutant in infants with colic, and a pharmacokinetic-pharmacodynamic model based on observations of duration of crying and fussing following oral nepadutant administration in infants (3-25 weeks) with colic. The models were developed based on data obtained at baseline and following treatment with placebo, nepadutant 0.1mg/kg or nepadutant 0.5mg/kg administered for 7days. A continuous response variable, duration of crying and fussing in minutes within 2h interval, was assembled based on records from "baby's day" diary. The pharmacokinetics of nepadutant was described by a one-compartment model with first-order absorption and elimination with body weight as a structural covariate incorporated allometrically. For an infant weighing 5.3kg, the estimated apparent clearance was 68.6L/h (12% relative standard error) and exhibited large variability (78% coefficient of variation). The pharmacokinetic-pharmacodynamic model described (i) a circadian rhythm in the response with lowest and highest observations at 4a.m. and 9p.m., respectively, (ii) a placebo effect increasing and flattening out with time in an exponential manner, and (iii) a statistically significant (P < .01) linearly increasing response with dose. The observed and model predicted relative change in response from baseline was -35% and -28% (95% prediction interval -36%; -19%) following placebo, and -44% and -36% (-46%; -27%) after 0.5mg/kg. Population pharmacokinetic and dose-response models were successfully developed characterizing the available nepadutant pharmacokinetics and duration of crying and fussing data in infants.

Rutin and Physalis peruviana Extract: Population Pharmacokinetics in New Zealand Rabbits

Background/Objectives: An extract of calyces from Physalis peruviana with hypoglycemic activity is being considered as a potential herbal medicine. Preclinical pharmacokinetics (PK) studies of the extract in rats, focusing on plasma concentrations of its main compound, rutin, and its metabolites, revealed PK interactions in the extract matrix that improved the absorption of rutin metabolites compared to the pure compound, among other PK effects. This research aimed to study the PK of rutin alone and in the extract and assess potential PK interactions in the extract matrix on the flavonoid and its metabolites in rabbits, a nonrodent species; Methods: Animals received pure rutin or extract orally and intravenously. The PK analysis used noncompartmental and population pharmacokinetics (popPK) methods, and simple allometry was applied to predict human PK parameters; Results: The rutin concentration–time profile fit a two-compartment model with first-order elimination, while its metabolites fit a double first-order absorption model. The extract matrix led to increased absorption, distribution, and elimination of rutin as well as increased bioavailability of its metabolites in rabbits; Conclusions: The popPK model defined the equations for PK parameters describing these findings, and the increased volume of distribution and clearance of rutin was maintained in human predictions. These results will support the development of a new herbal medicine.

Pharmacokinetic and Pharmacodynamic Interaction of Finerenone with Diltiazem, Fluconazole, and Ritonavir in Rats.

Finerenone, a novel selective non-steroidal mineralocorticoid receptor antagonist, has been indicated in chronic kidney disease associated with type 2 diabetes mellitus. Considering the potential complications of diabetes, finerenone can be co-administered with various drugs, including fluconazole, diltiazem, and ritonavir. Given that finerenone is a substrate of cytochrome P450 (CYP) 3A4, the concurrent administration of finerenone with CYP3A4 inhibitors (diltiazem or fluconazole or ritonavir) could potentially lead to drug interactions, which may cause adverse events such as hyperkalemia. No studies have investigated interactions between finerenone and diltiazem or fluconazole or ritonavir. Therefore, this study aims to investigate the pharmacokinetic interaction of finerenone with diltiazem or fluconazole or ritonavir and to evaluate the impact of fluconazole on the pharmacodynamics of finerenone. The pharmacokinetic study included four rat groups (n=8 rats/group), including a control group (finerenone alone) and test groups (finerenone pretreated with diltiazem or fluconazole or ritonavir) using both non-compartment analysis (NCA) and population pharmacokinetic (pop-PK) modeling. The pop-PK model was developed using non-linear mixed-effects modeling in NONMEM® (version 7.5.0). In the pharmacodynamic study, serum potassium (K+) levels were measured to assess the effects of fluconazole on finerenone-induced hyperkalemia. The NCA results indicated that the area under the plasma concentration-time curve (AUC) of finerenone increased by 1.86- and 1.95-fold when coadministered with fluconazole and ritonavir, respectively. In contrast, diltiazem did not affect the pharmacokinetics of finerenone. The pharmacokinetic profiles of finerenone were best described by a one-compartment disposition with first-order elimination and dual first-order absorption kinetics. The pop-PK modeling results demonstrated that the apparent clearance of finerenone decreased by 50.3% and 49.2% owing to the effects of fluconazole and ritonavir, respectively. Additionally, the slow absorption rate, which represents the absorption in the distal intestinal tract of finerenone, increased by 55.7% due to the effect of ritonavir. Simultaneously, a pharmacodynamic study revealed that finerenone in the presence of fluconazole caused a significant increase in K+ levels compared with finerenone alone. Coadministration of finerenone with fluconazole or ritonavir increased finerenone exposure in rats. Additionally, the administration of finerenone in the presence of fluconazole resulted in elevated K+ levels in rats. Further clinical studies are required to validate these findings.