Importance of shrinkage in empirical bayes estimates for diagnostics: problems and solutions

Dose finding for ZSP1601 in patients with nonalcoholic steatohepatitis using population pharmacokinetics and exposure-response approach

INTRODUCTION

ZSP1601 is a novel pan-phosphodiesterase inhibitor developed in China specifically for the treatment of nonalcoholic fatty liver disease (NAFLD).

AIM

The aim is to develop a population pharmacokinetic (pop PK) model for ZSP1601 by integrating data from two clinical studies. This undertaking aims to deepen our understanding of the clinical factors that influence ZSP1601 exposure while simultaneously investigating exposure-response (ER) relationships related to efficacy and safety. The goal is to guide formulating optimal dosage strategies in the subsequent phases of clinical trials.

METHODS

Analysis of pooled concentration-time data from 95 subjects, with 2647 observations from two clinical trials involving healthy volunteers and NAFLD patients, employed a nonlinear mixed-effects modeling approach to characterize ZSP1601 pharmacokinetics. Covariate impact on ZSP1601 pharmacokinetics was investigated, and relationships between ZSP1601 exposure, efficacy and safety endpoints were explored.

RESULTS

A two-compartment model featuring sequential zero-order then first-order absorption and first-order elimination effectively described ZSP1601's pharmacokinetic profile. Covariate analyses identified body weight as a statistically significant factor affecting drug central volume, while FED (food consumption) influenced absorption rate constant and duration. The Sigmoid Emax model aptly captured exposure-response relationships for ALT (alanine aminotransferase), AST (aspartate aminotransferase), and LFC (liver fat content) percentage changes relative to baseline and ZSP1601 exposure levels (AUCss) on the 29th day. ZSP1601 exposure levels (Cmax1) exhibited a significant exposure-response relationship with headaches (p < 0.001).

CONCLUSION

The PopPK model and ER analysis, based on available data, comprehensively characterizes ZSP1601's pharmacokinetic, safety and efficacy profile, aiding informed decisions regarding dosage selection for the drug's complete developmental trajectory. The exposure-response (ER) analysis yields quantitative insights into the optimal balance of efficacy and safety within different dosage regimens for patient administration. In light of these findings, the dose regimen of 100 mg administered twice daily is proposed for subsequent clinical investigations.

Does Sample Size, Sampling Strategy, or Handling of Concentrations Below the Lower Limit of Quantification Matter When Externally Evaluating Population Pharmacokinetic Models?

BACKGROUND AND OBJECTIVES

Precision dosing requires selecting the appropriate population pharmacokinetic model, which can be assessed through external evaluations (EEs). The lack of understanding of how different study design factors influence EE study outcomes makes it challenging to select the most suitable model for clinical use. This study aimed to evaluate the impact of sample size, sampling strategy, and handling of concentrations below the lower limit of quantification (BLQ) on the outcomes of EE for four population pharmacokinetic models using vancomycin and tobramycin as examples.

METHODS

Three virtual patient populations undergoing vancomycin or tobramycin therapy were simulated with varying sample size and sampling scenarios. The three approaches used to handle BLQ data were to (1) discard them, (2) impute them as LLOQ/2, or (3) use a likelihood-based approach. EEs were performed with NONMEM and R.

RESULTS

Sample size did not have an important impact on the EE results for a given scenario. Increasing the number of samples per patient did not improve predictive performance for two out of the three evaluated models. Evaluating a model developed with rich sampling did not result in better performance than those developed with regular therapeutic drug monitoring. A likelihood-based method to handle BLQ samples impacted the outcomes of the EE with lower bias for predicted troughs.

CONCLUSIONS

This study suggests that a large sample size may not be necessary for an EE study, and models selected based on TDM may be more generalizable. The study highlights the need for guidelines for EE of population pharmacokinetic models for clinical use.

Quantitative characterization of the effects of fulvestrant alone or in combination with taselisib (PI3Kinase inhibitor) on longitudinal tumor growth in patients with estrogen receptor-positive, HER2-negative, PIK3CA-mutant, advanced or metastatic breast cancer

PURPOSE

Among cases of breast cancer, estrogen receptor-positive (ER +), PIK3CA-mutant, HER2- advanced breast cancer stands as a particularly complex clinical indication where approximately 40% of ER + /HER2- breast carcinomas present mutations in the PIK3CA gene. A significant hurdle in treating ER + breast cancer lies in surmounting the challenges of endocrine resistance. In the clinical setting, a multifaceted approach is essential for this indication, one that not only explores the effectiveness of individual treatments but also delves into the potential gains in therapeutic outcome from combination therapies.

METHODS

In the current study, longitudinal tumor growth inhibition (TGI) models were developed to characterize tumor response over time in postmenopausal women with ER + /HER2- advanced or metastatic breast cancer undergoing treatment with fulvestrant alone or in combination with the PI3K inhibitor, taselisib. Impact of clinically relevant covariates on TGI metrics was assessed to identify patient subsets most likely to benefit from treatment with fulvestrant monotherapy or combination with taselisib.

RESULTS

Tumor growth rate constant (Kg) was found to increase with increasing baseline tumor size and in the absence of baseline endocrine sensitivity. Further, Kg decreased in the absence of baseline liver metastases both in fulvestrant monotherapy and combination therapy with taselisib. Overall, additive/potentially synergistic anti-tumor effects were observed in patients treated with the taselisib-fulvestrant combination.

CONCLUSION

These results have important implications for understanding the therapeutic impact of combination treatment approaches and individualized responses to these treatments. Finally, this work, emphasizes the importance of model informed drug development for targeted cancer therapy.

CLINICAL TRIAL REGISTRATION

NCT02340221 Registered January 16, 2015, NCT01296555 Registered February 14, 2011.

Population Pharmacokinetics and Absolute Oral Bioavailability of Lasalocid after Single Intravenous and Intracrop Administration in Laying Hens

Lasalocid sodium is a polyether carboxylic ionophore agent authorized by the EU for use as a coccidiostat in broilers, turkeys, and pullets up to 16 weeks of age, except for laying hens. However, laying hens are the most common nontarget species exposed to lasalocid sodium, mainly due to cross-contamination from feed mills. This exposure may result in potential drug residue deposition in eggs, which could potentially expose consumers to the drug. The breeds commonly used for commercial egg production in Poland are Isa Brown and Green-legged Partridge hens, which have been found to significantly differ in egg-laying performance. This variability may also affect the pharmacokinetics of lasalocid. Data on lasalocid plasma pharmacokinetics in laying hens are lacking. In this study, we aimed to determine typical population pharmacokinetic parameters, absolute oral bioavailability, and how breed may influence the pharmacokinetics of lasalocid. Twenty-layer hens of the two breeds were used in this study. Lasalocid was administered orally at a single dose of either 1 mg or 5 mg/kg body weight or intravenously at a dose of 1 mg/kg body weight, in a crossover design with a three-week washout period between study periods. Blood samples were collected for 72 h, and lasalocid concentrations were measured using high-performance liquid chromatography with fluorescence detection. A population pharmacokinetic analysis was conducted using nonlinear mixed effects modeling. Standard numerical and graphical criteria were used to select the best model, and a stepwise covariate modeling approach was used to determine any influencing factors. The best model was a three-compartment mammillary model with first-order absorption, transit compartments, and linear elimination. The estimated absolute oral bioavailability was low (36%). It was found that breed significantly influenced not only absorption but also the elimination of lasalocid. This study revealed that lasalocid absorption and elimination varied between the two breeds. This variability in pharmacokinetics may result in breed-related differences in drug residue accumulation in eggs, and ultimately, the risk associated with consumer exposure to drug residues may also vary.

Modeling an evaluation of the efficacy of the novel neuroanalgesic drug mirogabalin for diabetic peripheral neuropathic pain and postherpetic neuralgia therapy

Diabetic peripheral neuropathic pain (DPNP) and postherpetic neuralgia (PHN) are challenging and often intractable complex medical conditions, with a substantial impact on the quality of life. Mirogabalin, a novel voltage-gated Ca2+ channel α2δ ligand, was approved for the indication of DPNP and PHN. However, the time course of effects has not yet been clarified.We aimed to establish pharmacodynamic and placebo effect models of mirogabalin and pregabalin in DPNP and PHN, and to quantitatively compare the efficacy characteristics (maximum efficacy, onset time, and other pharmacodynamic parameters) and safety of mirogabalin and pregabalin. Public databases were comprehensively searched for randomized placebo-controlled clinical trials. A model-based meta-analysis (MBMA) was developed to describe the time course of drug efficacy and placebo effects. Adverse events were compared using a fixed-effects meta-analysis. Sixteen studies including 5,147 participants were eligible for this study. The placebo effect was relatively high and gradually increased with time, and it required at least eight weeks to reach a plateau. The pharmacodynamic model revealed that the maximum pure efficacy for mirogabalin and pregabalin was approximately -7.85 % and -8.86 %, respectively; the efficacy of mirogabalin to relieve DPNP and PHN was not superior to that of pregabalin, and both drugs had similar safety. While the rate constant of the onset rate of pregabalin was approximately thrice as high as that of mirogabalin. In addition, the baseline level of pain was an important factor affecting pregabalin efficacy. These findings are helpful in evaluating the clinical extension value of mirogabalin. They suggest that the high placebo effect and the baseline level of pain should be considered when grouping patients in future research and development of voltage-gated Ca2+ channel neuroanalgesic.

Population Pharmacokinetics of Cabotegravir Following Oral Administration and Long-Acting Intramuscular Injection in Real-World People with HIV

Long-acting cabotegravir has been studied mainly in the stringent framework of clinical trials, which does not necessarily reflect the situation of people with HIV (PWH) in routine clinical settings. The present population pharmacokinetic analysis aims to build real-world reference percentile curves of cabotegravir concentrations, accounting for patient-related factors that may affect cabotegravir exposure. The second objective is to simulate whether dosing interval adjustments of cabotegravir could be considered in specific subpopulations. Overall, 238 PWH contributed to 1,038 cabotegravir levels (186 during the initial oral administration phase and 852 after intramuscular injection). Cabotegravir pharmacokinetics was best described using a one-compartment model with distinct first order-absorption for oral and intramuscular administrations, and identical volume and clearance. Our model showed almost 40% faster absorption and 30% higher clearance than previously reported, resulting in a time to steady-state of 8 months and an elimination half-life of 4.6 weeks for long-acting cabotegravir. Sex and body mass index significantly influenced absorption, and bodyweight affected clearance. Model-based simulations showed that cabotegravir trough concentrations in females were 25% lower 4 weeks after the intramuscular loading dose, but 42% higher during the late maintenance phase. Finally, simulations indicated that in females, despite significantly higher cabotegravir concentrations, longer intervals between injections may not consistently ensure levels above the 4-fold protein-adjusted 90% inhibitory target concentration.

Development of a Plasminogen Population PK model supporting prophylactic replacement therapy for Plasminogen deficient patients within the WAPPS-Hemo platform

INTRODUCTION

Plasminogen deficiency is an ultra rare disease whose patients may develop ligneous lesions if untreated. Prophylactic replacement therapy with plasma derived plasminogen, Ryplazim, is efficient in treating lesions and could benefit from pharmacokinetic (PK) tailoring.

AIM

The objectives of this study are to develop, evaluate and integrate into the WAPPS-Hemo platform a Population PK model supporting prophylactic replacement therapy for Plasminogen deficient patients.

METHODS

Population PK modelling and evaluations followed the same protocol performed for factor VIII and IX concentrates. Limited sampling analysis used dosing and sampling scenarios in accordance with recommended treatment for Ryplazim.

RESULTS

The population PK model, derived from 16 participants included in previous clinical studies, was a 2-compartment model whose variability was best described by fat-free mass. Evaluations showed that the model described well the data and Bayesian forecasting in limited sampling environment led to acceptable precision for PK parameters relevant to plasminogen treatment.

CONCLUSION

The model was integrated into the WAPPS-Hemo webservice to help individualize prophylactic treatment in plasminogen deficient patients. Prospective PK data to be collected through the WAPPS-Hemo database will be used to better understand plasminogen PK and improve patient care.

Population Pharmacokinetic Analysis of Atomoxetine and its Metabolites in Children and Adolescents with Attention-Deficit/Hyperactivity Disorder

Atomoxetine (ATX) is a non-stimulant used to treat attention-deficit/hyperactivity disorder (ADHD) and systemic exposure is highly variable due to polymorphic cytochrome P450 2D6 (CYP2D6) activity. The objective of this study was to characterize the time course of ATX and metabolites (4-hydroxyatomoxetine (4-OH); N-desmethylatomoxetine (NDA); and 2-carboxymethylatomoxetine (2-COOH)) exposure following oral ATX dosing in children with ADHD to support individualized dosing. A nonlinear mixed-effect modeling approach was used to analyze ATX, 4-OH, and NDA plasma and urine, and 2-COOH urine profiles obtained over 24-72 hours from children with ADHD (n = 23) following a single oral ATX dose. Demographics and CYP2D6 activity score (AS) were evaluated as covariates. Simulations were performed to explore the ATX dosing in subjects with various CYP2D6 AS. A simultaneous pharmacokinetic modeling approach was used in which a model for ATX, 4-OH, and NDA in plasma and urine, and 2-COOH in urine was developed. Plasma ATX, 4-OH, and NDA were modeled using two-compartment models with first-order elimination. CYP2D6 AS was a significant determinant of ATX apparent oral clearance (CL/F), fraction metabolized to 4-OH, and systemic exposure of NDA. CL/F of ATX varied almost 7-fold across the CYP2D6 AS groups: AS 2: 20.02 L/hour; AS 1: 19.00 L/hour; AS 0.5: 7.47 L/hour; and AS 0: 3.10 L/hour. The developed model closely captures observed ATX, 4-OH, and NDA plasma and urine, and 2-COOH urine profiles. Application of the model shows the potential for AS-based dosing recommendations for improved individualized dosing.

Covariate modeling in pharmacometrics: General points for consideration

Modeling the relationships between covariates and pharmacometric model parameters is a central feature of pharmacometric analyses. The information obtained from covariate modeling may be used for dose selection, dose individualization, or the planning of clinical studies in different population subgroups. The pharmacometric literature has amassed a diverse, complex, and evolving collection of methodologies and interpretive guidance related to covariate modeling. With the number and complexity of technologies increasing, a need for an overview of the state of the art has emerged. In this article the International Society of Pharmacometrics (ISoP) Standards and Best Practices Committee presents perspectives on best practices for planning, executing, reporting, and interpreting covariate analyses to guide pharmacometrics decision making in academic, industry, and regulatory settings.

Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment

Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors before surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Yet neoadjuvant clinical trials are rarely preceded by preclinical testing involving neoadjuvant treatment, surgery, and post-surgery monitoring of the disease. Here we used a mouse model of spontaneous metastasis occurring after surgical removal of orthotopically implanted primary tumors to develop a predictive mathematical model of neoadjuvant treatment response to sunitinib, a receptor tyrosine kinase inhibitor (RTKI). Treatment outcomes were used to validate a novel mathematical kinetics-pharmacodynamics model predictive of perioperative disease progression. Longitudinal measurements of presurgical primary tumor size and postsurgical metastatic burden were compiled using 128 mice receiving variable neoadjuvant treatment doses and schedules (released publicly at https://zenodo.org/records/10607753). A non-linear mixed-effects modeling approach quantified inter-animal variabilities in metastatic dynamics and survival, and machine-learning algorithms were applied to investigate the significance of several biomarkers at resection as predictors of individual kinetics. Biomarkers included circulating tumor- and immune-based cells (circulating tumor cells and myeloid-derived suppressor cells) as well as immunohistochemical tumor proteins (CD31 and Ki67). Our computational simulations show that neoadjuvant RTKI treatment inhibits primary tumor growth but has little efficacy in preventing (micro)-metastatic disease progression after surgery and treatment cessation. Machine learning algorithms that included support vector machines, random forests, and artificial neural networks, confirmed a lack of definitive biomarkers, which shows the value of preclinical modeling studies to identify potential failures that should be avoided clinically.

Pharmacokinetics and exposure-safety relationship of ciprofol for sedation in mechanically ventilated patients in the intensive care unit

Ciprofol (HSK3486) is a newly developed, highly selective γ-aminobutyric acid-A (GABAA) receptor potentiator that is recently approved for a new indication of sedation for patients in the intensive care unit (ICU) in China. This analysis aimed to characterize the population pharmacokinetics (PopPKs) of ciprofol and evaluate the relationship of exposure with hypotension in mechanically ventilated patients in the ICU. A total of 462 subjects with 3918 concentration measurements from two clinical trials of mechanically ventilated patients in the ICU, four clinical trials of elective surgical patients, and six clinical trials of healthy subjects were used in the PopPK analysis. Exposure-safety relationship for hypotension was evaluated based on the data gathered from 112 subjects in two clinical trials of mechanically ventilated patients in the ICU. Ciprofol pharmacokinetics (PKs) was adequately described by a three-compartment linear disposition model with first-order elimination. Body weight, age, sex, blood sampling site (vein vs. arterial), study design (long-term infusion vs. short-term infusion), and patient population (ICU vs. non-ICU) were identified as statistically significant covariates on the PKs of ciprofol. Within the exposure range of the mechanically ventilated ICU patient population, no meaningful association was observed between ciprofol exposure and the incidence of hypotension. These results support the dosing regimen currently used in mechanically ventilated patients in the ICU.

Quantitative Assessment of Drug Efficacy and Emergence of Resistance in Patients with Metastatic Renal Cell Carcinoma Using a Longitudinal Exposure-Tumor Growth Inhibition Model: Apitolisib (Dual PI3K/mTORC1/2 Inhibitor) Versus Everolimus (mTORC1 Inhibitor)

Cancer remains a significant global health challenge, and despite remarkable advancements in therapeutic strategies, poor tolerability of drugs (causing dose reduction/interruptions) and/or the emergence of drug resistance are major obstacles to successful treatment outcomes. Metastatic renal cell carcinoma (mRCC) accounts for 2% of global cancer diagnoses and deaths. Despite the initial success of targeted therapies in mRCC, challenges remain to overcome drug resistance that limits the long-term efficacy of these treatments. Our analysis aim was to develop a semi-mechanistic longitudinal exposure-tumor growth inhibition model for patients with mRCC to characterize and compare everolimus (mTORC1) and apitolisib's (dual PI3K/mTORC1/2) ability to inhibit tumor growth, and quantitate each drug's efficacy decay caused by emergence of tumor resistance over time. Model-estimated on-treatment tumor growth rate constant was 1.7-fold higher for apitolisib compared to everolimus. Estimated half-life for loss of treatment effect over time for everolimus was 16.1 weeks compared to 7.72 weeks for apitolisib, suggesting a faster rate of tumor re-growth for apitolisib patients likely due to the emergence of resistance. Goodness-of-fit plots including visual predictive check indicated a good model fit and the model was able to capture individual tumor size-time profiles. Based on our knowledge, this is the first clinical report to quantitatively assess everolimus (mTORC1) and apitolisib (PI3K/mTORC1/2) efficacy decay in patients with mRCC. These results highlight the difference in overall efficacy of 2 drugs due to the quantified efficacy decay caused by emergence of resistance, and emphasize the importance of model-informed drug development for targeted cancer therapy.

Evaluation of omadacycline dosing regimens in Chinese using population pharmacokinetic-pharmacodynamic analysis

PURPOSE

Omadacycline (PTK-0796) is a first-in-class aminomethylcycline for adult patients with community-acquired bacterial pneumonia (CABP) and acute bacterial skin and skin structure infections (ABSSSI) caused by susceptible pathogens. We investigated the pharmacokinetic (PK) and pharmacodynamic (PD) profile of omadacycline, considering the impact of covariates, particularly ethnicity, on PK and determined the PK/PD cutoff values for dosing regimens.

METHODS

Utilizing nonlinear mixed-effects modeling, we pooled data from 11 clinical trials for PopPK analysis. The first-order conditional estimation with interaction (FOCEI) method in NONMEM facilitated model parameter estimation. Employing a stepwise model selection strategy, with forward addition (P < 0.01) and backward deletion (P < 0.001), we assessed the potential impacts of covariates on omadacycline PK, including baseline age, body weight, sex, race, body mass index, body surface area, baseline albumin, creatine clearance, and formulation. After validating the model through various methods, the final PopPK model underwent Monte Carlo simulations to generate the PK profile for the Chinese population. This enabled AUC calculation and assessment of the probability of target attainment (PTA) and the cumulative fraction of response (CFR) for various dosing regimens and bacterial strains.

RESULTS

Omadacycline's PK can be adequately characterized by a three-compartment model. Body weight, sex, race, and drug formulation statistically influenced its PK. Asians and non-Asians exhibit similar exposure after intravenous infusion, but oral dosing results in much higher exposures than in non-Asians. Monte Carlo simulation indicates that IV-only or IV/PO sequential therapy regimens provide adequate attainment for all major pathogens causing ABSSSI and CABP. PK/PD cutoffs were generally above the MIC90 value of recent clinical isolates from China.

CONCLUSIONS

In conclusion, the approved regimen for China achieved adequate target attainment for all pathogens typically associated with these infections. The higher oral exposure observed in Asians may enhance efficacy without affecting safety or tolerability.

Population Pharmacokinetics of Ozoralizumab in Patients with Rheumatoid Arthritis

Ozoralizumab is a bispecific NANOBODY compound that binds tumor necrosis factor alpha (TNFα) and human serum albumin. Ozoralizumab inhibits the TNFα physiological activity while maintaining long-term plasma retention owing to its human serum albumin-binding ability. A population pharmacokinetic (PK) model was developed using data from 494 Japanese patients with rheumatoid arthritis in Phase II/III and Phase III trials to assess the effects of potential PK covariates. The ozoralizumab PK after subcutaneous administration was described using a 1-compartment model with first-order absorption and first-order elimination processes. A proportional error model was used for inter- and intra-individual variabilities, with covariance set between inter-individual variabilities of the apparent clearance and apparent distribution volume. Body weight, sex, antidrug antibody status, estimated glomerular filtration rate, and concomitant methotrexate use were identified as covariates for apparent clearance, while body weight and sex were covariates for apparent distribution volume in the final model. Body weight had the greatest effect on the PK of ozoralizumab, while the other covariates had minor effects. When administered at 30 mg every 4 weeks, the predicted steady-state plasma trough concentration in a patient weighing 83.2 kg exceeded the trough concentration required to maintain efficacy of ozoralizumab, and the estimated exposure in a patient weighing 42.5 kg did not exceed the mean exposure at 80 mg, a well-tolerated dose, throughout 52 weeks. We developed a population PK model that adequately described the ozoralizumab PK in Japanese patients with rheumatoid arthritis, and none of the evaluated covariates showed clinically relevant effects on the PK of ozoralizumab.

Pharmacokinetic Modeling and Simulation with Pharmacogenetic Insights Support the Relevance of Therapeutic Drug Monitoring for Myeloablative Busulfan Dosing in Adult HSCT

Therapeutic drug monitoring (TDM) of busulfan (Bu) is well-established in pediatric hematopoietic stem cell transplantation (HSCT), but its use in adults is limited due to a lack of clear recommendations and scarcity of evidence regarding its utility. GSTA1 promoter variants are reported to affect Bu clearance in both adults and pediatric patients. This study aimed to evaluate the value of preemptive genotyping GSTA1 and body composition (obesity) in individualizing Bu dosing in adults, through pharmacokinetic (PK) modeling and simulations. A population pharmacokinetic (PopPK) model was developed and validated with data from 60 adults who underwent HSCT. Simulations assessed different dosing scenarios based on body size metrics and GSTA1 genotypes. Due to the limited number of obese patients in the cohort, the effect of obesity on Bu pharmacokinetics (PK) was evaluated in silico using a physiologically-based pharmacokinetic (PBPK) model and relevant virtual populations from Simcyp software. Patients with at least 1 GSTA1*B haplotype had 17% lower clearance on average. PopPK simulations indicated that adjusting doses based on genotype increased the probability of achieving the target exposure (3.7 to 5.5 mg.h/L) from 53% to 60 % in GSTA1*A homozygous patients, and from 50% to 61% in *B carriers. Still, Approximately 40% of patients would not achieve this therapeutic window without TDM. A 2-sample optimal design was validated for routine model-based Bu first dose AUC0-∞ estimation, and the model was implemented in the Tucuxi user-friendly TDM software. PBPK simulations confirmed body surface area-based doses of 29 to 31 mg/m2/6h as the most appropriate, regardless of obesity status. This study emphasizes the importance of individualized Bu dosing strategies in adults to achieve therapeutic targets. Preemptive genotyping alone may not have a significant clinical impact, and routine TDM may be necessary for optimal transplantation outcomes.

Pharmacokinetics/pharmacodynamics analysis and establishment of optimal dosing regimens using unbound cefmetazole concentration for patients infected with Extended-Spectrum β-lactamase producing Enterobacterales (ESBL-E)

STUDY OBJECTIVE

Establish methods for measuring cefmetazole (CMZ) concentrations conduct a pharmacokinetic/pharmacodynamic (PK/PD) analysis using unbound CMZ concentrations for extended-spectrum β-lactamase producing enterobacterales (ESBL-E) and investigate optimal dosing regimens for not undergoing hemodialysis (non-HD) and undergoing hemodialysis (HD) patients.

DESIGN

Prospective observational study.

PATIENTS

Included patients treated with CMZ who provided written informed consent and were admitted to the Tokyo Bay Urayasu Ichikawa Medical Center between August 2021 and July 2022.

MEASUREMENTS

Total and Unbound CMZ concentration was measured by high-performance liquid chromatography (HPLC) with solid-phase extraction and ultrafiltration.

SETTING

Determining the CMZ dosing regimen involved modified creatinine clearance (CLCR ) with measured body weight (BW) using the Cockcroft-Gault equation. For non-HD patients, blood samples were collected during at least three points. For patients undergoing HD, 1 g was administered via intravenous infusion, or rapid intravenous injection after HD, or 30 min before the end of HD. Blood samples were collected before HD (pre-HD), and 1 and 3 h after starting HD and post-HD. All blood samples were collected at steady-state. Patient information was collected from electronic medical records. An unbound PK model was constructed for the non-HD patients. A nomogram was constructed using Monte Carlo simulations with a 90% probability of target attainment at 70% free time above the minimum inhibitory concentration (MIC). For the HD patients, a nomogram was used to determine the optimal dosing regimen for each HD schedule.

MAIN RESULTS

CMZ measurement methods were established. A model analysis of unbound PK in 37 non-HD patients incorporated creatinine clearance (CLCR ) using the Cockcroft-Gault equation, albumin (ALB) for clearance and body weight (BW) for the volume of distribution. In Monte Carlo simulations, nomograms corresponding to the MIC (known and unknown) were generated for each covariate. Using the nomogram, non-HD patients with an ESBL-E MIC of 8 mg/L, a BW of 60 kg, an ALB of 25 g/L, and a CLCR of 60 mL/min required administration of 2 g every 6 h (1- and 3-h infusions). Unbound PK model parameters were calculated for 7 HD patients, and the optimal dosing regimens following PK/PD were determined for each HD schedule. In HD patients, the regimen after and during HD was established using a treatment that was effective up to an ESBL-E MIC of 4 mg/L.

CONCLUSIONS

The nomogram for CMZ regimens established by PK/PD analysis of measured CMZ concentrations enables optimal CMZ dosing for ESBL-E-infected patients.

Population pharmacokinetic/pharmacodynamic modeling and exposure-response analysis of ciprofol in the induction and maintenance of general anesthesia in patients undergoing elective surgery: A prospective dose optimization study

AIM

This study aimed to establish a population pharmacokinetic and pharmacodynamic (PK-PD) model to explore the optimal maintenance dose and appropriate starting time of maintenance dose after induction of ciprofol and investigate the efficacy and safety of ciprofol for general anesthesia induction and maintenance in patients undergoing elective surgery.

METHOD

A total of 334 subjects with 3092 concentration measurements from nine clinical trials and 115 subjects with 5640 bispectral index (BIS) measurements from two clinical trials were used in the population PK-PD analysis. Exposure-response relationships for both efficacy endpoints (duration of anesthesia successful induction, time to recovery from anesthesia, time to respiratory recovery, and time from discontinuation to the 1st/3rd consecutive Aldrete score ≥ 9) and safety variables (hypotension, bradycardia, and injection site pain) were evaluated based on the data gathered from 115 subjects in two clinical trials.

RESULT

Ciprofol pharmacokinetics (PK) were adequately described by a three-compartment model with first-order elimination from the central compartment and redistribution from the deep and shallow peripheral compartments. An inhibitory sigmoidal Emax model best described the relationship between ciprofol effect-site concentrations and BIS measurements. Body weight, age, sex, blood sampling site, and study type (short-term infusion vs long-term infusion) were identified as statistically significant covariates on the PK of ciprofol. No covariates were found to have a significant effect on the pharmacodynamic (PD) parameters. The PK-PD simulation results showed that the optimal maintenance dose was 0.8 mg/kg/h and the appropriate time to start the maintenance dose was 4-5 mins after the induction dose of ciprofol. Within the exposure range of this study, no meaningful correlations between ciprofol exposures and efficacy or safety endpoints were observed.

CONCLUSION

A population PK-PD model was successfully developed to describe the ciprofol PK and BIS changes. Efficacy was consistent across the exposure range with a well-tolerated safety profile indicating no maintenance dose adjustment is required for patients undergoing elective surgery.

Agreement Between a Colorimetric Assay and Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry for Quantifying Paracetamol Plasma Concentrations

Special populations, like geriatric patients, experience altered paracetamol pharmacokinetics (PK), complicating pain management. More PK research is essential to optimize paracetamol (acetaminophen) dosing. Yet, the reference method ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) is not readily available. Therefore, we aimed to evaluate the agreement between UPLC-MS/MS and the more accessible colorimetric Roche acetaminophen (ACETA) assay in quantifying paracetamol plasma concentrations, to facilitate PK studies and therapeutic drug monitoring for pain management. Patient data and plasma samples were obtained from a prospective study including geriatric patients admitted to the geriatric wards. ACETA and UPLC-MS/MS assays were performed in two separate laboratories. Bland-Altman plot and Passing-Bablok regression were used to assess agreement. Accuracy was evaluated using the McNemar test for a threshold value of 10 mg/L. Population PK modeling was employed to bridge PK data obtained from both methods (NONMEM 7.5). A total of 242 plasma sample pairs were available from 40 geriatric patients (age range, 80-95 years). Paracetamol plasma concentrations from ACETA (median 9.8 [interquartile range 6.1-14.4] mg/L) and UPLC-MS/MS (9.5 [6.2-14.8] mg/L) did not differ significantly (P > 0.05). No significant proportional nor additive bias was observed between both assay methods. The classification accuracy (at threshold 10 mg/L) was 85% (P = 0.414). The conversion factor between ACETA and UPLC-MS/MS was estimated at 1.06 (relative standard error 5%), yet with a 13.4% (relative standard error 23%) interindividual variability. ACETA assay showed no systematic bias in comparison with the UPLC-MS/MS assay in determining paracetamol exposure in geriatric blood samples despite the imprecision.

Population pharmacokinetics of methotrexate and 7-hydroxymethotrexate and delayed excretion in infants and young children with brain tumors

PURPOSE

The objectives of this study were to develop a population pharmacokinetic model of methotrexate (MTX) and its primary metabolite 7-hydroxymethotrexate (7OHMTX) in children with brain tumors, to identify the sources of pharmacokinetic variability, and to assess whether MTX and 7OHMTX systemic exposures were related to toxicity.

METHODS

Patients received 2.5 or 5 g/m2 MTX as a 24-hour infusion and serial samples were analyzed for MTX and 7OHMTX by an LC-MS/MS method. Pharmacokinetic parameters were estimated using nonlinear mixed-effects modeling. Demographics, laboratory values, and genetic polymorphisms were considered as potential covariates to explain the pharmacokinetic variability. Association between MTX and 7OHMTX systemic exposures and MTX-related toxicities were explored using random intercept logistic regression models.

RESULTS

The population pharmacokinetics of MTX and 7OHMTX were adequately characterized using two-compartment models in 142 patients (median 1.91 y; age range 0.09 to 4.94 y) in 513 courses. The MTX and 7OHMTX population clearance values were 4.6 and 3.0 l/h/m2, respectively. Baseline body surface area and estimated glomerular filtration rate were significant covariates on both MTX and 7OHMTX plasma disposition. Pharmacogenetic genotypes were associated with MTX pharmacokinetic parameters but had only modest influence. No significant association was observed between MTX or 7OHMTX exposure and MTX-related toxicity.

CONCLUSIONS

MTX and 7OHMTX plasma disposition were characterized for the first time in young children with brain tumors. No exposure-toxicity relationship was identified in this study, presumably due to aggressive clinical management which led to a low MTX-related toxicity rate.

Population Pharmacokinetic/Pharmacodynamic Analysis of the Glucokinase Activator PB201 in Healthy Volunteers and Patients with Type 2 Diabetes Mellitus: Facilitating the Clinical Development of PB201 in China

PB201 is an orally active, partial glucokinase activator targeting both pancreatic and hepatic glucokinase. As the second glucokinase activator studied beyond phase I, PB201 has demonstrated promising glycemic effects as well as favorable pharmacokinetic (PK) and safety profiles in patients with type 2 diabetes mellitus (T2DM). This study aims to develop a population PK/pharmacodynamic (PD) model for PB201 using the pooled data from nine phase I/II clinical trials conducted in non-Chinese healthy volunteers and a T2DM population and to predict the PK/PD profile of PB201 in a Chinese T2DM population. We developed the PK/PD model using the non-linear mixed-effects modeling approach. All runs were performed using the first-order conditional estimation method with interaction. The pharmacokinetics of PB201 were well fitted by a one-compartment model with saturable absorption and linear elimination. The PD effects of PB201 on reducing the fasting plasma glucose and glycosylated hemoglobin levels in the T2DM population were described by indirect response models as stimulating the elimination of fasting plasma glucose, where the production of glycosylated hemoglobin was assumed to be stimulated by fasting plasma glucose. Covariate analyses revealed enhanced absorption of PB201 by food and decreased systemic clearance with ketoconazole co-administration, while no significant covariate was identified for the pharmacodynamics. The population PK model established for non-Chinese populations was shown to be applicable to the Chinese T2DM population as verified by the PK data from the Chinese phase I study. The final population PK/PD model predicted persistent and dose-dependent reductions in fasting plasma glucose and glycosylated hemoglobin levels in the Chinese T2DM population receiving 50/50 mg, 100/50 mg, and 100/100 mg PB201 twice daily for 24 weeks independent of co-administration of metformin. Overall, the proposed population PK/PD model quantitatively characterized the PK/PD properties of PB201 and the impact of covariates on its target populations, which allows the leveraging of extensive data in non-Chinese populations with the limited data in the Chinese T2DM population to successfully supported the waiver of the clinical phase II trial and facilitate the optimal dose regimen design of a pivotal phase III study of PB201 in China.

Population Pharmacokinetics and Exposure-Response Analysis for the CTLA-4 Inhibitor Tremelimumab in Metastatic NSCLC Patients in the Phase III POSEIDON Study

Blockade of CTLA-4 by tremelimumab combined with anti-PD-L1 durvalumab and chemotherapy provided increased antitumor activity and long-term survival benefits in first-line metastatic non-small cell lung cancer (mNSCLC) in the phase III POSEIDON study. We performed population pharmacokinetic modeling for tremelimumab using data from 1,605 patients across 6 studies (including POSEIDON) in multiple tumors (lung cancer, bladder cancer, malignant mesothelioma, and other solid tumors), and identified a 2-compartment model with linear and time-varying clearance for tremelimumab. Cox proportional hazard regression models were applied to 326 patients with mNSCLC from POSEIDON to evaluate the association between exposure metrics and efficacy end points, adjusting for baseline prognostic covariates. Improved progression-free survival (PFS) and overall survival (OS) in the tremelimumab arm (in combination with durvalumab and chemotherapy) was associated with higher tremelimumab exposure (e.g., minimum concentration at 5th dose (Cmin,dose5 ) and area under the curve at 5th dose (AUCdose5 )). However, further case-matching analyses yielded hazard ratios for the comparison of tremelimumab-treated patients in the Cmin,dose5 quartile 1 (Q1) subgroup with matched chemotherapy-treated patients of 1.04 (95% confidence interval (CI): 0.76-1.44) for OS and 0.99 (95% CI: 0.72-1.36) for PFS, suggesting that the observed apparent exposure-response relationship might be confounded. No relationship between tremelimumab exposure and safety (grade ≥3 treatment-emergent adverse events [AEs], AEs of special interest, or discontinuation due to AEs) was identified. These results support the consistent benefit observed with tremelimumab 75 mg every 3 weeks for up to 5 doses in combination with durvalumab and chemotherapy in POSEIDON as first-line therapy for mNSCLC.

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.

Escitalopram and Sertraline Population Pharmacokinetic Analysis in Pediatric Patients

BACKGROUND AND OBJECTIVE

Escitalopram and sertraline are commonly prescribed for anxiety and depressive disorders in children and adolescents. The pharmacokinetics (PK) of these medications have been evaluated in adults and demonstrate extensive variability, but studies in pediatric patients are limited. Therefore, we performed a population PK analysis for escitalopram and sertraline in children and adolescents to characterize the effects of demographic, clinical, and pharmacogenetic factors on drug exposure.

METHODS

A PK dataset was generated by extracting data from the electronic health record and opportunistic sampling of escitalopram- and sertraline-treated psychiatrically hospitalized pediatric patients aged 5-18 years. A population PK analysis of escitalopram and sertraline was performed using NONMEM. Concentration-time profiles were simulated using MwPharm++ to evaluate how covariates included in the final models influence medication exposure and compared to adult therapeutic reference ranges.

RESULTS

The final escitalopram cohort consisted of 315 samples from 288 patients, and the sertraline cohort consisted of 265 samples from 255 patients. A one-compartment model with a proportional residual error model best described the data for both medications. For escitalopram, CYP2C19 phenotype and concomitant CYP2C19 inhibitors affected apparent clearance (CL/F), and normalizing CL/F and apparent volume of distribution (V/F) to body surface area (BSA) improved estimations. The final escitalopram model estimated CL/F and V/F at 14.2 L/h/1.73 m2 and 428 L/1.73 m2, respectively. For sertraline, CYP2C19 phenotype and concomitant CYP2C19 inhibitors influenced CL/F, and empirical allometric scaling of patient body weight on CL/F and V/F was significant. The final sertraline model estimated CL/F and V/F at 124 L/h/70 kg and 4320 L/70 kg, respectively. Normalized trough concentrations (Ctrough) for CYP2C19 poor metabolizers taking escitalopram were 3.98-fold higher compared to normal metabolizers (151.1 ng/mL vs 38.0 ng/mL, p < 0.0001), and normalized Ctrough for CYP2C19 poor metabolizers taking sertraline were 3.23-fold higher compared to normal, rapid, and ultrarapid metabolizers combined (121.7 ng/mL vs 37.68 ng/mL, p < 0.0001). Escitalopram- and sertraline-treated poor metabolizers may benefit from a dose reduction of 50-75% and 25-50%, respectively, to normalize exposure to other phenotypes.

CONCLUSION

To our knowledge, this is the largest population PK analysis of escitalopram and sertraline in pediatric patients. Significant PK variability for both medications was observed and was largely explained by CYP2C19 phenotype. Slower CYP2C19 metabolizers taking escitalopram or sertraline may benefit from dose reductions given increased exposure.

Population Pharmacokinetics and Exposure-Response Analysis of Tremelimumab 300 mg Single Dose Combined with Durvalumab 1500 mg Q4W (STRIDE) in Patients with Unresectable Hepatocellular Carcinoma

A novel single-dose regimen of 300 mg tremelimumab in combination with durvalumab (STRIDE) has demonstrated a favorable benefit-risk profile in the phase 1/2 Study 22 trial (in patients with unresectable hepatocellular carcinoma, uHCC) and in the phase 3 HIMALAYA study. The current analysis evaluated the population pharmacokinetics (PopPK) of tremelimumab and durvalumab, and the exposure-response (ER) relationship for efficacy and safety of STRIDE in patients with uHCC. Previous PopPK models for tremelimumab and durvalumab were updated using data from previous studies in various cancers combined with data from Study 22 and HIMALAYA. Typical population mean parameters and associated inter- and intra-individual variability were assessed, as was the influence of covariates. Individual exposure metrics were derived from the individual empirical Bayes estimates as drivers for ER analysis related to efficacy and safety from HIMALAYA. The observed pharmacokinetics of tremelimumab in uHCC were well described by a 2-compartment model with both linear and time-dependent clearance. All identified covariates changed tremelimumab PK parameters by <25%, and thus had minimal clinical relevance; similar results were obtained from durvalumab PopPK analysis. None of tremelimumab or durvalumab exposure metrics were significantly associated with overall survival (OS), progression-free survival (PFS), or adverse events. Baseline aspartate aminotransferase and neutrophil-to-lymphocyte ratio (NLR) were associated with OS (P < .001) by the Cox proportional hazards model. No covariate was identified as a significant factor for PFS. No dose adjustment for tremelimumab or durvalumab is needed based on PopPK covariate analyses or ER analyses. Our findings support the novel STRIDE dosing regimen in patients with uHCC.

Mechanistic modeling projections of antibody persistence after homologous booster regimens of COVID-19 vaccine Ad26.COV2.S in humans

Mechanistic model-based simulations can be deployed to project the persistence of humoral immune response following vaccination. We used this approach to project the antibody persistence through 24 months from the data pooled across five clinical trials in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-seronegative participants following vaccination with Ad26.COV2.S (5 × 1010 viral particles), given either as a single-dose or a homologous booster regimen at an interval of 2, 3, or 6 months. Antibody persistence was quantified as the percentage of participants with detectable anti-spike binding and wild-type virus neutralizing antibodies. The projected overall 24-month persistence after single-dose Ad26.COV2.S was 70.5% for binding antibodies and 55.2% for neutralizing antibodies, and increased after any homologous booster regimen to greater than or equal to 89.9% for binding and greater than or equal to 80.0% for neutralizing antibodies. The estimated model parameters quantifying the rates of antibody production attributed to short-lived and long-lived plasma cells decreased with increasing age, whereas the rate of antibody production mediated by long-lived plasma cells was higher in women relative to men. Accordingly, a more pronounced waning of antibody responses was predicted in men aged greater than or equal to 60 years and was markedly attenuated following any homologous boosting regimen. The findings suggest that homologous boosting might be a viable strategy for maintaining protective effects of Ad26.COV2.S for up to 24 months following prime vaccination. The estimation of mechanistic modeling parameters identified the long-lived plasma cell pathway as a key contributor mediating antibody persistence following single-dose and homologous booster vaccination with Ad26.COV2.S in different subgroups of recipients stratified by age and sex.

Mechanistic Model Describing the Time Course of Humoral Immunity Following Ad26.COV2.S Vaccination in Non-Human Primates

Mechanistic modeling can be used to describe the time course of vaccine-induced humoral immunity and to identify key biologic drivers in antibody production. We used a six-compartment mechanistic model to describe a 20-week time course of humoral immune responses in 56 non-human primates (NHPs) elicited by vaccination with Ad26.COV2.S according to either a single-dose regimen (1 × 1011 or 5 × 1010 viral particles [vp]) or a two-dose homologous regimen (5 × 1010 vp) given in an interval of 4 or 8 weeks. Humoral immune responses were quantified by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-specific binding antibody concentrations as determined by spike protein-enzyme-linked immunosorbent assay. The mechanistic model adequately described the central tendency and variability of binding antibody concentrations through 20 weeks in all vaccination arms. The estimation of mechanistic modeling parameters revealed greater contribution of the antibody production mediated by short-lived cells as compared with long-lived cells in driving the peak response, especially post second dose when a more rapid peak response was observed. The antibody production mediated by long-lived cells was identified as relevant for generating the first peak and for contributing to the long-term time course of sustained antibody concentrations in all vaccination arms. The findings contribute evidence on the key biologic components responsible for the observed time course of vaccine-induced humoral immunity in NHPs and constitute a step toward defining immune biomarkers of protection against SARS-CoV-2 that might translate across species. SIGNIFICANCE STATEMENT: We demonstrate the adequacy of a mechanistic modeling approach describing the time course of binding antibody concentrations in non-human primates (NHPs) elicited by different dose levels and regimens of Ad26.COV2.S. The findings are relevant for informing the mechanism-based accounts of vaccine-induced humoral immunity in NHPs and translational research efforts aimed at identifying immune biomarkers of protection against SARS-CoV-2 infection.

Population pharmacokinetics of esaxerenone, a novel non-steroidal mineralocorticoid receptor blocker, in patients with essential hypertension, patients with diabetic nephropathy, and healthy volunteers

OBJECTIVES

Esaxerenone is a novel, non-steroidal mineralocorticoid receptor (MR) blocker with improved selectivity and affinity for MR. The objectives of this study were to model the population pharmacokinetics of esaxerenone in a diverse population and to evaluate the effect of covariates on pharmacokinetics parameters.

METHODS

A total of 8263 plasma esaxerenone concentrations from 166 healthy volunteers, 1097 hypertensive patients and 360 patients with diabetic nephropathy were pooled. A three-compartment model with sequential zero- and first-order absorption was used to describe the time-courses of plasma esaxerenone following single and multiple doses once daily for up to 12 weeks. Covariate effects were estimated using the full covariate modeling approach. Clinical relevance of covariates was ascertained using tornado plots.

RESULTS

Esaxerenone was estimated to have high bioavailability (85.3%), low clearance (3.28 L/h) and relatively large distribution volume at steady state (94.8 L). Body weight (-26 to +36%) and coadministration of itraconazole (+64%) or rifampicin (-68%) were associated with a greater influence on esaxerenone exposure.

CONCLUSIONS

The most influential covariates on esaxerenone exposure were coadministrations of itraconazole and rifampicin, followed by body weight. The clinical relevance of effects of renal impairment, mild to moderate hepatic impairment, and age is limited.

Population pharmacokinetics of oxcarbazepine active metabolite in Chinese children with epilepsy

Oxcarbazepine (OXC) is an antiepileptic drug whose efficacy is largely attributed to its monohydroxy derivative metabolite (MHD). Nevertheless, there exists significant inter-individual variability in both the pharmacokinetics and therapeutic response of this drug. The objective of this study is to explore the impact of patients' characteristics and genetic variants on MHD clearance in a population pharmacokinetic (PPK) model of Chinese pediatric patients with epilepsy. The PPK model was developed using a nonlinear mixed effects modeling method based on 231 MHD plasma concentrations obtained from 185 children with epilepsy. The one-compartment model and combined residual model were established to describe the pharmacokinetics of MHD. Forward addition and backward elimination were employed to evaluate the impact of covariates on the model parameters. The model was evaluated using goodness-of-fit, bootstrap, visual predictive checks, and normalized prediction distribution errors. In the two final PPK models, age, estimated glomerular filtration rate (eGFR), and a combined genotype of six variants (rs1045642, rs2032582, rs7668282, rs2396185, rs2304016, rs1128503) were found to significantly reduce inter-individual variability for MHD clearance. The inter-individual clearance equals to 1.38 × (Age/4.74)0.29 × (eGFR/128.66)0.25 × eθABCB-UGT-SCN-INSR for genetic variants included model and 1.30 × (Age/4.74)0.30 × (eGFR/128.66)0.23 for model without genetic variants. The precision of all parameters was deemed acceptable, and the model exhibited good predictability while remaining stable and effective.    Conclusion: Age, eGFR, and genotype may play a significant role in MHD clearance in children with epilepsy. The developed PPK models hold potential utility in facilitating oxcarbazepine dose adjustment in pediatric patients. What is Known: • The adjustment of the oxcarbazepine regimen remains difficult due to the considerable inter- and intra-individual variability of oxcarbazepine pharmacokinetics. • Body weight and co-administration with enzyme-inducing antiepileptic drugs emerge as the most influential factors contributing to the pharmacokinetics of MHD. What is New: • A positive correlation was observed between eGFR and the clearance of MHD in pediatric patients with epilepsy. • We explored the influence of genetic polymorphisms on MHD clearance and identified a combined genotype (ABCB-UGT-SCN-INSR) that exhibited a significant association with MHD concentration.

Population pharmacokinetics of topiramate in Chinese children with epilepsy

OBJECTIVE

Topiramate, a broad-spectrum antiepileptic drug, exhibits substantial inter-individual variability in both its pharmacokinetics and therapeutic response. The aim of this study was to investigate the influence of patient characteristics and genetic variants on topiramate clearance using population pharmacokinetic (PPK) models in a cohort of Chinese pediatric patients with epilepsy.

METHOD

The PPK model was constructed using a nonlinear mixed-effects modeling approach, utilizing a dataset comprising 236 plasma concentrations of topiramate obtained from 181 pediatric patients with epilepsy. A one-compartment model combined with a proportional residual model was employed to characterize the pharmacokinetics of topiramate. Covariate analysis was performed using forward addition and backward elimination to assess the influence of covariates on the model parameters. The model was thoroughly evaluated through goodness-of-fit analysis, bootstrap, visual predictive checks, and normalized prediction distribution errors. Monte Carlo simulations were utilized to devise topiramate dosing strategies.

RESULT

In the final PPK models of topiramate, body weight, co-administration with oxcarbazepine, and a combined genotype of GKIR1-UGT (GRIK1 rs2832407, UGT2B7 rs7439366, and UGT1A1 rs4148324) were identified as significant covariates affecting the clearance (CL). The clearance was estimated using the formulas CL (L/h) = 0.44 × (BW⁄11.7)0.82 × eOXC for the model without genetic variants and CL (L/h) = 0.49 × (BW⁄11.7)0.81 × eOXC × eGRIK1-UGT for the model incorporating genetic variants. The volume of distribution (Vd) was estimated using the formulas Vd (L) = 6.6 × (BW⁄11.7). The precision of all estimated parameters was acceptable. Furthermore, the model demonstrated good predictability, exhibiting stability and effectiveness in describing the pharmacokinetics of topiramate.

CONCLUSION

The clearance of topiramate in pediatric patients with epilepsy may be subject to the influence of factors such as body weight, co-administration with oxcarbazepine, and genetic polymorphism. In this study, PPK models were developed to better understand and account for these factors, thereby improving the precision and individualization of topiramate therapy in children with epilepsy.

Population pharmacokinetic analysis of lopinavir in HIV negative individuals exposed to SARS-CoV-2: a COPEP (COronavirus Post-Exposure Prophylaxis) sub-study

BACKGROUND

Lopinavir/ritonavir (LPV/r) is a drug traditionally used for the treatment of HIV that has been repurposed as a potential post-exposure prophylaxis agent against COVID-19 in the COronavirus Post-Exposure Prophylaxis (COPEP) study. The present analysis aims to evaluate LPV levels in individuals exposed to SARS-CoV-2 versus people living with HIV (PLWH) by developing a population pharmacokinetic (popPK) model, while characterizing external and patient-related factors that might affect LPV exposure along with dose-response association.

METHODS

We built a popPK model on 105 LPV concentrations measured in 105 HIV-negative COPEP individuals exposed to SARS-CoV-2, complemented with 170 LPV concentrations from 119 PLWH followed in our routine therapeutic drug-monitoring programme. Published LPV popPK models developed in PLWH and in COVID-19 patients were retrieved and validated in our study population by mean prediction error (MPE) and root mean square error (RMSE). The association between LPV model-predicted residual concentrations (Cmin) and the appearance of the COVID-19 infection in the COPEP participants was investigated.

RESULTS

A one-compartment model with linear absorption and elimination best described LPV concentrations in both our analysis and in the majority of the identified studies. Globally, similar PK parameters were found in all PK models, and provided close MPEs (from -19.4% to 8.0%, with a RMSE of 3.4% to 49.5%). No statistically significant association between Cmin and the occurrence of a COVID-19 infection could be detected.

CONCLUSION

Our analysis indicated that LPV circulating concentrations were similar between COPEP participants and PLWH, and that published popPK models described our data in a comparable way.

Population pharmacokinetics of Amisulpride in Chinese patients with schizophrenia with external validation: the impact of renal function

Introduction: Amisulpride is primarily eliminated via the kidneys. Given the clear influence of renal clearance on plasma concentration, we aimed to explicitly examine the impact of renal function on amisulpride pharmacokinetics (PK) via population PK modelling and Monte Carlo simulations. Method: Plasma concentrations from 921 patients (776 in development and 145 in validation) were utilized. Results: Amisulpride PK could be described by a one-compartment model with linear elimination where estimated glomerular filtration rate, eGFR, had a significant influence on clearance. All PK parameters (estimate, RSE%) were precisely estimated: apparent volume of distribution (645 L, 18%), apparent clearance (60.5 L/h, 2%), absorption rate constant (0.106 h-1, 12%) and coefficient of renal function on clearance (0.817, 10%). No other significant covariate was found. The predictive performance of the model was externally validated. Covariate analysis showed an inverse relationship between eGFR and exposure, where subjects with eGFR= 30 mL/min/1.73 m2 had more than 2-fold increase in AUC, trough and peak concentration. Simulation results further illustrated that, given a dose of 800 mg, plasma concentrations of all patients with renal impairment would exceed 640 ng/mL. Discussion: Our work demonstrated the importance of renal function in amisulpride dose adjustment and provided a quantitative framework to guide individualized dosing for Chinese patients with schizophrenia.

Significant Effects of Renal Function on Mycophenolic Acid Total Clearance in Pediatric Kidney Transplant Recipients with Population Pharmacokinetic Modeling

BACKGROUND AND OBJECTIVES

Mycophenolic acid (MPA) is an immunosuppressant commonly prescribed in pediatric kidney transplantation to prevent graft rejection. Large variabilities in MPA plasma exposures have been observed in this population, which could result in severe adverse effects. The majority of the MPA pharmacokinetic data have been reported in adult populations, whereas information in pediatric patients is still very limited. The objective of this study was to establish a novel, nonlinear mixed-effects model for MPA and investigate the clinical variables affecting MPA population pharmacokinetics in pediatric kidney transplant recipients.

METHODS

Data were collected retrospectively from pediatric kidney transplant patients (≤ 18 years when MPA concentrations were initially collected; on oral administration of mycophenolate mofetil) in Calgary, Alberta, Canada. Nonlinear mixed-effect modeling was conducted using stochastic approximation expectation-maximization in Monolix 2021R2 (Lixoft SAS, France) to determine population pharmacokinetic estimates, interindividual variabilities, and interoccasional variabilities. Covariate models were constructed using the Model Proposal function in Monolix in conjunction with a systematic stepwise inclusion/elimination protocol. The best model was selected based on objective function values, relative standard errors, goodness-of-fit plots, prediction-corrected visual predictive checks, and numerical predictive checks.

RESULTS

A total of 50 pediatric kidney transplant patients (25 female) with 219 MPA plasma concentration-time profiles were included. The average age (± standard deviation) and posttransplant time for the sample population were 12.8 ± 4.8 years and 762 ± 1160 days, respectively. The majority of study subjects (i.e., > 85% based on all occasions) were co-administered tacrolimus. A two-compartment, first-order absorption with lag time and linear elimination structural model with lognormal distributed proportional residual errors best described the MPA concentration-time data. The absorption rate constant (2.52 h-1 or 0.042 min-1), lag time (0.166 h or 9.96 min), volumes of distributions of the central (22.8 L) and peripheral (216 L) compartments, and intercompartment clearance (17.6 L h-1 or 0.293 L min-1) were consistent with literature values; whereas total MPA clearance (0.72 L h-1 or 0.012 L min-1) was relatively reduced, likely due to the general lack of cyclosporine interactions and the stabilized graft functions from significantly longer posttransplant time in our sample population. Of the clinical variables tested, only estimated glomerular filtration rate (eGFR) was identified a significant covariate affecting total MPA clearance with a positive, exponential relationship. The final population pharmacokinetic model was successfully evaluated/validated using a variety of complementary methods.

CONCLUSION

We have successfully constructed and validated a novel population pharmacokinetic model of MPA in pediatric kidney transplant patients. A positive, nonlinear relationship between eGFR and total MPA clearance identified in our model is likely attributed to multiple concurrent mechanisms, which warrant further systematic investigations.

Longitudinal estimated glomerular filtration rate (eGFR) modeling in long-term renal function to inform clinical trial design in kidney transplantation

Kidney transplantation is the preferred treatment for individuals with end-stage kidney disease. From a modeling perspective, our understanding of kidney function trajectories after transplantation remains limited. Current modeling of kidney function post-transplantation is focused on linear slopes or percent decline and often excludes the highly variable early timepoints post-transplantation, where kidney function recovers and then stabilizes. Using estimated glomerular filtration rate (eGFR), a well-known biomarker of kidney function, from an aggregated dataset of 4904 kidney transplant patients including both observational studies and clinical trials, we developed a longitudinal model of kidney function trajectories from time of transplant to 6 years post-transplant. Our model is a nonlinear, mixed-effects model built in NONMEM that captured both the recovery phase after kidney transplantation, where the graft recovers function, and the long-term phase of stabilization and slow decline. Model fit was assessed using diagnostic plots and individual fits. Model performance, assessed via visual predictive checks, suggests accurate model predictions of eGFR at the median and lower 95% quantiles of eGFR, ranges which are of critical clinical importance for assessing loss of kidney function. Various clinically relevant covariates were also explored and found to improve the model. For example, transplant recipients of deceased donors recover function more slowly after transplantation and calcineurin inhibitor use promotes faster long-term decay. Our work provides a generalizable, nonlinear model of kidney allograft function that will be useful for estimating eGFR up to 6 years post-transplant in various clinically relevant populations.

Population Pharmacokinetic Analysis of Perampanel in Portuguese Patients Diagnosed with Refractory Epilepsy

Perampanel is a promising antiepileptic drug (AED) for refractory epilepsy treatment due to its innovative mechanism of action. This study aimed to develop a population pharmacokinetic (PopPK) model to be further used in initial dose optimization of perampanel in patients diagnosed with refractory epilepsy. A total of seventy-two plasma concentrations of perampanel obtained from forty-four patients were analyzed through a population pharmacokinetic approach by means of nonlinear mixed effects modeling (NONMEM). A one-compartment model with first-order elimination best described the pharmacokinetic profiles of perampanel. Interpatient variability (IPV) was entered on clearance (CL), while the residual error (RE) was modeled as proportional. The presence of enzyme-inducing AEDs (EIAEDs) and body mass index (BMI) were found as significant covariates for CL and volume of distribution (V), respectively. The mean (relative standard error) estimates for CL and V of the final model were 0.419 L/h (5.56%) and 29.50 (6.41%), respectively. IPV was 30.84% and the proportional RE was 6.44%. Internal validation demonstrated an acceptable predictive performance of the final model. A reliable population pharmacokinetic model was successfully developed, and it is the first enrolling real-life adults diagnosed with refractory epilepsy.

Predictive Factors of Piperacillin Exposure and the Impact on Target Attainment after Continuous Infusion Administration to Critically Ill Patients

Critically ill patients undergo significant pathophysiological changes that affect antibiotic pharmacokinetics. Piperacillin/tazobactam administered by continuous infusion (CI) improves pharmacokinetic/pharmacodynamic (PK/PD) target attainment. This study aimed to characterize piperacillin PK after CI administration of piperacillin/tazobactam in critically ill adult patients with preserved renal function and to determine the empirical optimal dosing regimen. A total of 218 piperacillin concentrations from 106 patients were simultaneously analyzed through the population PK approach. A two-compartment linear model best described the data. Creatinine clearance (CL_CR) estimated by CKD-EPI was the covariate, the most predictive factor of piperacillin clearance (CL) interindividual variability. The mean (relative standard error) parameter estimates for the final model were: CL: 12.0 L/h (6.03%); central and peripheral compartment distribution volumes: 20.7 L (8.94%) and 62.4 L (50.80%), respectively; intercompartmental clearance: 4.8 L/h (26.4%). For the PK/PD target of 100% fT_>1×MIC, 12 g of piperacillin provide a probability of target attainment > 90% for MIC < 16 mg/L, regardless of CL_CR, but higher doses are needed for MIC = 16 mg/L when CL_CR > 100 mL/min. For 100% fT_>4×MIC, the highest dose (24 g/24 h) was not sufficient to ensure adequate exposure, except for MICs of 1 and 4 mg/L. Our model can be used as a support tool for initial dose guidance and during therapeutic drug monitoring.

Quantifying Antibody Persistence After a Single Dose of COVID-19 Vaccine Ad26.COV2.S in Humans Using a Mechanistic Modeling and Simulation Approach

Understanding persistence of humoral immune responses elicited by vaccination against coronavirus disease 2019 (COVID-19) is critical for informing the duration of protection and appropriate booster timing. We developed a mechanistic model to characterize the time course of humoral immune responses in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-seronegative adults after primary vaccination with the Janssen COVID-19 vaccine, Ad26.COV2.S. The persistence of antibody responses was quantified through mechanistic modeling-based simulations. Two biomarkers of humoral immune responses were examined: SARS-CoV-2 neutralizing antibodies determined by wild-type virus neutralization assay (wtVNA) and spike protein-binding antibodies determined by indirect spike protein enzyme-linked immunosorbent assay (S-ELISA). The persistence of antibody responses was defined as the period of time during which wtVNA and S-ELISA titers remained above the lower limit of quantification. A total of 442 wtVNA and 1,185 S-ELISA titers from 82 and 220 participants, respectively, were analyzed following administration of a single dose of Ad26.COV2.S (5 × 10¹⁰ viral particles). The mechanistic model adequately described the time course of observed wtVNA and S-ELISA serum titers and its associated variability up to 8 months following vaccination. Mechanistic model-based simulations show that single-dose Ad26.COV2.S elicits durable but waning antibody responses up to 24 months following immunization. Of the estimated model parameters, the production rate of memory B cells was decreased in older adults relative to younger adults, and the antibody production rate mediated by long-lived plasma cells was increased in women relative to men. A steeper waning of antibody responses was predicted in men and in older adults.

Standards for model-based early bactericidal activity analysis and sample size determination in tuberculosis drug development

Background: A critical step in tuberculosis (TB) drug development is the Phase 2a early bactericidal activity (EBA) study which informs if a new drug or treatment has short-term activity in humans. The aim of this work was to present a standardized pharmacometric model-based early bactericidal activity analysis workflow and determine sample sizes needed to detect early bactericidal activity or a difference between treatment arms. Methods: Seven different steps were identified and developed for a standardized pharmacometric model-based early bactericidal activity analysis approach. Non-linear mixed effects modeling was applied and different scenarios were explored for the sample size calculations. The sample sizes needed to detect early bactericidal activity given different TTP slopes and associated variability was assessed. In addition, the sample sizes needed to detect effect differences between two treatments given the impact of different TTP slopes, variability in TTP slope and effect differences were evaluated. Results: The presented early bactericidal activity analysis approach incorporates estimate of early bactericidal activity with uncertainty through the model-based estimate of TTP slope, variability in TTP slope, impact of covariates and pharmacokinetics on drug efficacy. Further it allows for treatment comparison or dose optimization in Phase 2a. To detect early bactericidal activity with 80% power and at a 5% significance level, 13 and 8 participants/arm were required for a treatment with a TTP-EBA_0-14 as low as 11 h when accounting for variability in pharmacokinetics and when variability in TTP slope was 104% [coefficient of variation (CV)] and 22%, respectively. Higher sample sizes are required for smaller early bactericidal activity and when pharmacokinetics is not accounted for. Based on sample size determinations to detect a difference between two groups, TTP slope, variability in TTP slope and effect difference between two treatment arms needs to be considered. Conclusion: In conclusion, a robust standardized pharmacometric model-based EBA analysis approach was established in close collaboration between microbiologists, clinicians and pharmacometricians. The work illustrates the importance of accounting for covariates and drug exposure in EBA analysis in order to increase the power of detecting early bactericidal activity for a single treatment arm as well as differences in EBA between treatments arms in Phase 2a trials of TB drug development.

Population PK and Semimechanistic PK/PD Modeling and Simulation of Relugolix Effects on Testosterone Suppression in Men with Prostate Cancer

Relugolix, the first orally active, nonpeptide gonadotropin-releasing hormone receptor antagonist, is approved in the United States and the European Union for the treatment of adult patients with advanced prostate cancer. The recommended dosing regimen is a 360-mg loading dose followed by a 120-mg daily dose. Relugolix and testosterone concentration data and clinical information from two phase I studies, two phase II studies, and the phase III safety and efficacy study (HERO) were used to develop a population pharmacokinetic (PopPK) model and a semimechanistic population pharmacokinetic/pharmacodynamic (PopPK/PD) model that characterized relugolix exposure and its relationship to testosterone concentrations. Age, body weight, and Black/African American race had at most minimal effects on relugolix exposure or testosterone concentrations with no clinical relevance. Simulations using the PopPK/PD model confirmed the recommended dosing regimen of relugolix, with the median simulated testosterone concentrations predicted to achieve castration levels (< 50 ng/dL) and profound castration levels (< 20 ng/dL) by day 2 and day 9, respectively, and demonstrated that 97.3% and 85.5% of the patients remained at castration levels (< 50 ng/dL) upon temporary interruption of treatment for 7 days and 14 days, respectively. Collectively, simulations based on the PopPK and PopPK/PD models were consistent with actual data from clinical studies, reflecting the high predictiveness of the models and supporting the reliability of model-based simulations. These models can be used to provide guidance regarding dosing recommendations under various circumstances (e.g., temporary interruption of treatment, if needed) for relugolix.

Comparison of toxicokinetic properties of eleven analogues of Bisphenol A in pig after intravenous and oral administrations

Due to the restrictions of its use, Bisphenol A (BPA) has been replaced by many structurally related bisphenols (BPs) in consumer products. The endocrine disrupting potential similar to that of BPA has been described for several bisphenols, there is therefore an urgent need of toxicokinetic (TK) data for these emerging BPs in order to evaluate if their internal exposure could increase the risk of endocrine disruption. We investigated TK behaviors of eleven BPA substitutes (BPS, BPAF, BPB, BPF, BPM, BPZ, 3-3BPA, BP4-4, BPAP, BPP, and BPFL) by intravenous and oral administrations of mixtures of them to piglets and serial collection of blood over 72 h and urine over 24 h, to evaluate their disposition. Data were analyzed using nonlinear mixed-effects modeling and a comparison was made with TK predicted by the generic model HTTK package. The low urinary excretion of some BPs, in particular BPM, BPP and BPFL, is an important aspect to consider in predicting human exposure based on urine biomonitoring. Despite their structural similarities, for the same oral dose, all BPA analogues investigated showed a higher systemic exposure (area under the plasma concentration-time curve (AUC) of the unconjugated Bisphenol) than BPA (2 to 4 fold for 3-3BPA, BPAF, BPB and BPZ, 7-20 fold for BP4-4, BPAP, BPP, BPFL, BPF and BPM and 150 fold for BPS) due mainly to a considerable variation of oral bioavailability (proportion of BP administered by oral route that attains the systemic circulation unchanged). Given similarities in the digestive tract between pigs and humans, our TK data suggest that replacing BPA with some of its alternatives, particularly BPS, will likely lead to higher internal exposure to potential endocrine disruptive compounds. These findings are crucial for evaluating the risk of human exposure to these emerging BPs.

Bayesian forecasting of tumor size metrics and overall survival

The tumor size ratio (TSR), time-to-tumor growth (TTG), and tumor growth rate (kG) are frequently suggested as model-based predictors of overall survival (OS) for different types of tumors. When the tumor metrics are applied in forecasting of the outcome for individual patients at an early stage, the tumor data might be sparse resulting in imprecise prediction. This simulation study aimed to investigate how the tumor follow-up data and estimation approaches influence the accuracy in the tumor size metrics and the predicted hazard of death for individual patients. Longitudinal tumor size and OS data were simulated using tumor growth inhibition and Weibull distribution models, respectively. Based on the model and increasing measurement durations, the accuracy (defined as 80-125% of the simulated "true" value) in individual metrics and hazard was computed. TSR week 6 (TSRw6) accuracy was adequate for 91% of the patients when tumor size was measured up to 12 weeks. For TTG and kG metrics, the highest accuracy observed was lower (43 and 77%, respectively) and occurred later (42 and 60 weeks, respectively). The simultaneous (joint) and sequential estimation approaches resulted in similar accuracies, however, in general, the sequential approach where individual tumor size parameters are fixed, demonstrated inferior estimation properties. The TSRw6 and the model-predicted tumor time course (absolute or relative change) had better forecasting properties than TTG or kG. The population pharmacokinetic (PK) parameters and data approach performed similarly or better than the simultaneous approach and had a better accuracy in estimating individuals' hazard of death than the individual PK parameters method.

A Survey of Population Pharmacokinetic Reports Submitted to the USFDA: An Analysis of Common Issues in NDA and BLA from 2012 to 2021

BACKGROUND AND OBJECTIVE

Population pharmacokinetic (PopPK) analysis is one of the important components of regulatory submission. The purpose of this study was to survey PopPK analysis reports in new drug applications (NDAs) and biological licensing applications (BLAs) submitted to the US Food and Drug Administration (FDA) and to retrieve the information regarding PopPK-related issues in the US FDA review reports.

METHODS

We surveyed NDAs and BLAs over the period from 2012 to 2022 from Drug@FDA databases and extracted the review reports from the website. We explored the issues identified in these reports and sorted them into four categories: (i) data used for PopPK analysis, (ii) base model development, (iii) final model development, and (iv) model evaluation. The percentage of the issues in each category and the total issues were calculated.

RESULTS

Data from a total of 317 applications were analyzed. Of these, 122 applications had at least one PopPK-related issue, and the count went up to 168 issues. The proportion of issues for each category was ranked as follows: model evaluation (39%, 65 of 168), final model development (34%, 57 of 168), data used for PopPK analysis (14%, 24 of 168), and base model development (13%, 22 of 168). The most common issues were related to the goodness-of-fit plots, covariate selection, and high shrinkage of ETA, accounting for 17.9%, 15.5%, and 11.3% of the total issues, respectively.

CONCLUSION

The findings from this study may help the applicant understand the FDA's thinking on the PopPK analysis.

Population-based cellular kinetic characterization of ciltacabtagene autoleucel in subjects with relapsed or refractory multiple myeloma

The aims of this work were to develop a population pharmacokinetic (PK) model for chimeric antigen receptor (CAR) transgene after single intravenous infusion administration of ciltacabtagene autoleucel in adult patients with relapsed or refractory multiple myeloma. CAR transgene level in blood were measured by quantitative polymerase chain reaction (qPCR) from 97 subjects in a phase Ib/II CARTITUDE-1 study (NCT03548207), with a targeted cilta-cel dose of 0.75 × 10⁶ (range 0.5-1.0 × 10⁶ ) CAR positive viable T-cells per kg body weight. The population PK model development was primarily guided by the current mechanistic understanding of CAR-T kinetics and the principles of building a parsimonious model. Cilta-cel PK was adequately described by a two-compartment model (with a fast and a slow apparent decline rate from each compartment, respectively) and a chain of four transit compartments with a lag time empirically representing the process from infused CAR-T cell to measurable CAR transgene. No apparent relationship was observed between cilta-cel dose (i.e., the actual number of CAR positive viable T-cells infused), given the narrow dose range, and the observed transgene level. Based on covariate search and subgroup analysis of maximum systemic CAR transgene level (C_max ) and area under curve from the first dose to day 28 (AUC_0-28d ), none of the investigated subjects' demographics, baseline characteristics, and manufactured product characteristics had significant effects on cilta-cel PK. The developed model is deemed robust and adequate for enabling subsequent exposure-safety and exposure-efficacy analyses.

Model-based population pharmacokinetic analysis of tislelizumab in patients with advanced tumors

Tislelizumab, a humanized immunoglobulin G4 monoclonal antibody, is a programmed cell death protein 1 (PD-1) inhibitor designed to minimize Fc gamma receptor binding on macrophages to limit antibody-dependent phagocytosis, a potential mechanism of resistance to anti-PD-1 therapy. The pharmacokinetic (PK) profile of tislelizumab was analyzed with population PK modeling using 14,473 observed serum concentration data points from 2596 cancer patients who received intravenous (i.v.) tislelizumab at 0.5-10 mg/kg every 2 weeks or every 3 weeks (q3w), or a 200 mg i.v. flat dose q3w in 12 clinical studies. Tislelizumab exhibited linear PK across the dose range tested. Baseline body weight, albumin, tumor size, tumor type, and presence of antidrug antibodies were identified as significant covariates on central clearance, whereas baseline body weight, sex, and age significantly affected central volume of distribution. Sensitivity analysis showed that these covariates did not have clinically relevant effects on tislelizumab PK. Other covariates evaluated, including race (Asian vs. White), lactate dehydrogenase, estimated glomerular filtration rate, renal function categories, hepatic function measures and categories, Eastern Cooperative Oncology Group performance status, therapy (monotherapy vs. combination therapy), and line of therapy did not show a statistically significant impact on tislelizumab PK. These results support the use of tislelizumab 200 mg i.v. q3w without dose adjustment in a variety of patient subpopulations.

Population pharmacokinetics of everolimus in adult liver transplant patients: Comparison to tacrolimus disposition and extrapolation to pediatrics

Everolimus has recently been used to prevent graft rejection in liver transplantation and reduces the incidence of kidney dysfunction caused by calcineurin inhibitors. In this study, a population pharmacokinetic analysis was conducted to improve the individualization of everolimus therapy. Japanese post-liver transplant patients whose blood everolimus concentrations were measured between March 2018 and December 2020 were included in this study. A nonlinear mixed-effect modeling program was used to explore covariates that affect everolimus pharmacokinetics. Individual everolimus pharmacokinetic parameters estimated by the post-hoc Bayesian analysis using the final model were compared with the tacrolimus dose per trough concentration (D/C) ratio in each patient. The final model was extrapolated to pediatric liver transplant patients for external evaluation. A total of 937 concentrations from 87 adult patients were used in the model-building process. Everolimus clearance was significantly affected by the estimated glomerular filtration rate, concomitant use of fluconazole, sex, as well as total daily dose of everolimus (TDM effect). The estimated individual apparent clearance of everolimus by the post-hoc Bayesian analysis was moderately correlated with the D/C ratio of tacrolimus in each patient (R²  = 0.330, p < 0.0001). The estimation accuracy in pediatric patients was considerably high, except for one infant out of 13 patients. In conclusion, population pharmacokinetic analysis clarified several significant covariates for everolimus pharmacokinetics in liver transplant patients. Everolimus pharmacokinetics moderately correlated with tacrolimus pharmacokinetics and could be extrapolated from adult to pediatric patients by body size correction, except for infants.

Population Pharmacokinetic/Pharmacodynamic Modelling of Daptomycin for Schedule Optimization in Patients with Renal Impairment

The aims of this study are (i) to develop a population pharmacokinetic/pharmacodynamic model of daptomycin in patients with normal and impaired renal function, and (ii) to establish the optimal dose recommendation of daptomycin in clinical practice. Several structural PK models including linear and non-linear binding kinetics were evaluated. Monte Carlo simulations were conducted with a fixed combination of creatinine clearance (30–90 mL/min/1.73 m²) and body weight (50–100 kg). The final dataset included 46 patients and 157 daptomycin observations. A two-compartment model with first-order peripheral distribution and elimination kinetics assuming non-linear protein-binding kinetics was selected. The bactericidal effect for Gram+ strains with MIC ≤ 0.5 mg/L could be achieved with 5–12 mg/kg daily daptomycin based on body weight and renal function. The administration of 10–17 mg/kg q48 h daptomycin allows to achieve bactericidal effect for Gram+ strains with MIC ≤ 1 mg/L. Four PK samples were selected as the optimal sampling strategy for an accurate AUC estimation. A quantitative framework has served to characterize the non-linear binding kinetics of daptomycin in patients with normal and impaired renal function. The impact of different dosing regimens on the efficacy and safety outcomes of daptomycin treatment based on the unbound exposure of daptomycin and individual patient characteristics has been evaluated.

Population pharmacokinetics of mycophenolate mofetil in pediatric patients early after liver transplantation

Objective: To investigate the factors influencing the pharmacokinetics of mycophenolate mofetil (MMF) in pediatric patients after liver transplantation, and to establish a population pharmacokinetics model, which can provide a reference for clinical dosage adjustment.

Methods: A prospective study in a single center was performed on pediatric patients who were administrated with mycophenolate mofetil dispersible tablets (MMFdt) for at least 4 days after liver transplantation continuously. Blood samples were collected in ethylene diamine tetraacetic acid anticoagulant tubes before dosing and 0.5, 1, 2, 4, 8, and 12 h after the morning intake of MMFdt. The concentrations of mycophenolic acid (MPA) in plasma were assayed with a validated reverse-phase high-performance liquid chromatography method. UGT1A8 518C > G, UGT1A9 -275T > A, UGT1A9 -2152C > T, UGT2B7 211G > T, SLC O 1B1 521T > C polymorphism were determined by Sanger sequencing. Nonlinear mixed effects modeling was used to establish the population pharmacokinetics (PPK) model. The predictability and stability of the model were internally evaluated by the goodness of fit plots, visual prediction check, normalized prediction errors, and bootstraps.

Results: A two-compartment model with first-order absorption and first-order elimination was established with 115 MPA concentrations from 20 pediatric patients. The final model were: CL/F (L/h) = 14.8×(WT/7.5)^0.75×(DOSE/11.16)^0.452×е^0.06, Ka (h⁻¹) = 2.02×(WT/7.5)^−0.25, Vc/F (L) = 6.01×(WT/7.5), Vp/F (L) = 269 (fixed), Q/F (L/h) = 15.4×(WT/7.5)^0.75×е^1.39. Where CL/F was the apparent clearance rate, Ka was the absorption rate constant, Vc/F was the apparent distribution volume of the central compartment, Vp/F was the apparent distribution volume of the peripheral compartment, Q/F was the atrioventricular clearance rate, WT was the body weight of the subject, and DOSE was the MMFdt administered dose. The model indicated there was large inter-individual variability in CL/F and Q/F after multiple dosing of MMFdt. Internal evaluation results showed that the final model had good stability and prediction performance.

Conclusion: A stable and predictive population pharmacokinetic model of MMFdt in pediatric patients after the early stage of liver transplantation was established. The pediatric patient’s weight and the dose of MMFdt can be a reference to adjust the MMFdt dose.

Population pharmacokinetics of cabotegravir following administration of oral tablet and long-acting intramuscular injection in adult HIV-1-infected and uninfected subjects

AIM

To characterize cabotegravir population pharmacokinetics using data from phase 1, 2 and 3 studies and evaluate the association of intrinsic and extrinsic factors with pharmacokinetic variability.

METHODS

Analyses were implemented in NONMEM and R. Concentrations below the quantitation limit were modelled with likelihood-based approaches. Covariate relationships were evaluated using forward addition (P < .01) and backward elimination (P < .001) approaches. The impact of each covariate on trough and peak concentrations was evaluated through simulations. External validation was performed using prediction-corrected visual predictive checks.

RESULTS

The model-building dataset included 23 926 plasma concentrations from 1647 adult HIV-1-infected (72%) and uninfected (28%) subjects in 16 studies at seven dose levels (oral 10-60 mg, long-acting [LA] intramuscular injection 200-800 mg). A two-compartment model with first-order oral and LA absorption and elimination adequately described the data. Clearances and volumes were scaled to body weight. Estimated relative bioavailability of oral to LA was 75.6%. Race and age were not significant covariates. LA absorption rate constant (KALA ) was 50.9% lower in females and 47.8% higher if the LA dose was given as two split injections. KALA decreased with increasing BMI and decreasing needle length. Clearance was 17.4% higher in current smokers. The impact of any covariate was ≤32% on trough and peak concentrations following LA administration. The final model adequately predicted 5097 plasma concentrations from 647 subjects who were not included in the model-building dataset.

CONCLUSIONS

A cabotegravir population pharmacokinetic model was developed that can be used to inform dosing strategies and future study design. No dose adjustment based on subject covariates is recommended.

Genetic determinants of apixaban plasma levels and their relationship to bleeding and thromboembolic events

Apixaban is a direct oral anticoagulant, a factor Xa inhibitor, used for the prevention of ischemic stroke in patients with atrial fibrillation. Despite using recommended dosing a few patients might still experience bleeding or lack of efficacy that might be related to inappropriate drug exposure. We conducted a genome-wide association study using data from 1,325 participants in the pivotal phase three trial of apixaban with the aim to identify genetic factors affecting the pharmacokinetics of apixaban. A candidate gene analysis was also performed for pre-specified variants in ABCB1, ABCG2, CYP3A4, CYP3A5, and SULT1A1, with a subsequent analysis of all available polymorphisms within the candidate genes. Significant findings were further evaluated to assess a potential association with clinical outcome such as bleeding or thromboembolic events. No variant was consistently associated with an altered apixaban exposure on a genome-wide level. The candidate gene analyses showed a statistically significant association with a well-known variant in the drug transporter gene ABCG2 (c.421G &gt; T, rs2231142). Patients carrying this variant had a higher exposure to apixaban [area under the curve (AUC), beta = 151 (95% CI 59–243), p = 0.001]. On average, heterozygotes displayed a 5% increase of AUC and homozygotes a 17% increase of AUC, compared with homozygotes for the wild-type allele. Bleeding or thromboembolic events were not significantly associated with ABCG2 rs2231142. This large genome-wide study demonstrates that genetic variation in the drug transporter gene ABCG2 is associated with the pharmacokinetics of apixaban. However, the influence of this finding on drug exposure was small, and further studies are needed to better understand whether it is of relevance for ischemic and bleeding events.

Tumor growth inhibition modeling to support the starting dose for dacomitinib

Dacomitinib is a second-generation, irreversible EGFR tyrosine kinase inhibitor for first-line treatment of patients with metastatic non-small cell lung cancer and EGFR-activating mutations. A high rate of dose reductions in the pivotal trial led to an observed inverse exposure-response (ER) relationship with the primary end points. Three ER models were developed to determine if the starting dose from the pivotal trial, 45 mg once daily (q.d.) dose, is appropriate: a longitudinal logistic regression model for adverse event-related dose changes, a Claret tumor growth inhibition (TGI) model, and a Cox model for progression-free survival (PFS) based on the TGI model predictions. This analysis included 266 patients taking dacomitinib with a starting dose of 45 mg (N = 250) or 30 mg (N = 16) q.d. The ER relationships with the time-varying exposure metrics, most recent maximum plasma concentration (C_max ) and average concentration (C_avg ) from the first dose, were established for the dose reduction and TGI models, respectively. The TGI model characterized the tumor inhibition over time with constant growth rate (k_L  = 0.0012 years^-1 ) and highly variable kill rate (k_D  = 1.002 years^-1 /[μg/L]^θcavg , coefficient of variation [CV] = 89%) and drug resistance (λ = 14.47 years^-1 , CV = 96%) leading to prolonged tumor shrinkage. The ER relationship was characterized using an exposure parameter with a power parameterization (θcavg = 0.454, p < 0.0001). The Cox model found that baseline tumor size (p = 0.0166) and week 8 tumor shrinkage rate (p = 0.0726) were the best predictors of PFS. Simulations of dose reductions and drug interruptions on tumor shrinkage over time showed greater and more prolonged tumor shrinkage with a starting dose of 45 mg q.d.