Population Pharmacokinetic Parameters Research Articles

P7.09: Population Model Confirms Predictable Pharmacokinetic (PK) And Pharmacodynamic (PD) Profile for Apraglutide: Data From Two Randomized Phase 1 Studies

Background: Apraglutide, a novel long-acting glucagon-like peptide-2 (GLP-2) analogue that promotes intestinal growth in animals and increases intestinal absorption, is in Phase III development for the treatment of short bowel syndrome with intestinal failure (SBS-IF). Pharmacokinetic (PK) and pharmacodynamic (PD) characterization revealed a predictable linear PK distribution and elimination kinetics and a dose-dependent PD relationship. A model was created to enable characterization of PK and PD relationships at the population level using plasma citrulline, a biomarker of small intestine functional enterocytic mass. Methods: A population PK/PD model was created by combining PK and citrulline data from two randomized, placebo-controlled, Phase I studies of apraglutide in healthy adult volunteers. In Study 1, 64 volunteers received either a single ascending dose of apraglutide (2.8, 5.7, 11.4, 28.4, or 56 mg), 3 weekly doses of apraglutide (11.4, 28.4, or 56 mg) or placebo by subcutaneous (SC) injection. In Study 2, 24 volunteers received 6 weekly SC administrations of apraglutide (1, 5 or 10 mg) or placebo. A one-compartmental structural model with zero-order absorption and linear clearance was used to describe apraglutide PK. Plasma citrulline levels were described by a turnover model with a synthesis and degradation rate. The effect of apraglutide on citrulline synthesis was modeled with a stimulatory effect on the citrulline synthesis rate using an Emax relationship. Population PK and PD parameters were estimated using the stochastic approximation of expectation-maximization algorithm (Monolix Suite 2019 R1). Inter-subject variability was modelled using log-normal distributions. Simulations included the impact of covariates. Results: Actual PK observations were best matched by a population PK/PD model with a dose covariate on absorption duration and body weight covariates on V1/F and Cl/F. The parameter estimates for a 70-kg individual receiving apraglutide 5 mg SC were an apparent volume of distribution of 31.3 L and time to maximal concentration (T) of 1.39 days. Simulated PK and PD profiles with weekly apraglutide 2.5, 5, or 10 mg sc are shown in Figure 1. The PK/PD model did not indicate any accumulation of apraglutide over time for a weekly administration. Although accumulation of citrulline was apparent during the first 3 weeks of treatment, a steady state concentration was subsequently reached. Conclusions: This population PK/PD model enables prediction of the effect of different apraglutide doses on plasma citrulline levels as well as the impact of covariates, such as body weight, at the population level. This further demonstrates apraglutide’s predictable PK profile with no accumulation during once weekly sc dosing and its ability to induce a dose-dependent citrulline increase.

Population pharmacokinetics of unbound ceftriaxone in a critically ill population.

To develop a reliable 2-compartment population pharmacokinetic (PK) model for unbound ceftriaxone in a critically ill population and determine an optimal dosing regimen. This was a prospective, single-center, observational study of critically ill patients treated with ceftriaxone. Unbound serum ceftriaxone concentrations were measured using validated ultrafiltration and ultra-performance liquid chromatography-tandem mass spectrometry. PK analysis and dosing simulations were performed using an iterative 2-stage Bayesian fitting procedure and Monte Carlo simulations. The PK/pharmacodynamics (PD) target was attained when unbound serum ceftriaxone concentrations exceeded 4 times the minimum inhibitory concentration (MIC) for ≥60% of the dosing interval (ƒT>4xMIC ≥ 60%). 91 patients were enrolled, and 173 unbound ceftriaxone concentrations were acquired. The population PK parameter estimates were hepatic clearance 5.2±0.9L/h/1.85m2, the unbound renal clearance of ceftriaxone divided by the creatinine clearance 0.61±0.24, lean body mass corrected volume of distribution of the central compartment 0.82±0.21L/kg, and intercompartmental distribution rate constant from central to peripheral compartment 0.18±0.08h-1. Dosing simulations predicted ƒT>4 mg/L of 88% (95% CI: 69-100%) for 2,000 mg ceftriaxone once daily and ƒT>4 mg/L of 100% (95% CI: 100-100%) both for 1,000 mg twice daily and continuous infusion of 2,000 mg daily. We developed a reliable population PK model for unbound ceftriaxone in a critically ill population. Dosing simulations revealed ƒT>4 mg/L ≥60% for 1,000mg twice daily and 2,000 mg once daily or by continuous infusion.

Novel subcutaneous cytarabine infusion with the Omnipod system in dogs with meningoencephalomyelitis of unknown etiology.

To investigate the feasibility and pharmacokinetics of cytarabine delivery as a subcutaneous continuous-rate infusion with the Omnipod system. 6 client-owned dogs diagnosed with meningoencephalomyelitis of unknown etiology were enrolled through the North Carolina State University Veterinary Hospital. Cytarabine was delivered at a rate of 50 mg/m2/hour as an SC continuous-rate infusion over 8 hours using the Omnipod system. Plasma samples were collected at 0, 4, 6, 8, 10, 12, and 14 hours after initiation of the infusion. Plasma cytarabine concentrations were measured by high-pressure liquid chromatography. A nonlinear mixed-effects approach generated population pharmacokinetic parameter estimates. The mean peak plasma concentration (Cmax) was 7,510 ng/mL (range, 5,040 to 9,690 ng/mL; SD, 1,912.41 ng/mL), average time to Cmax was 7 hours (range, 4 to 8 hours; SD, 1.67 hours), terminal half-life was 1.13 hours (SD, 0.29 hour), and the mean area under the curve was 52,996.82 hours X μg/mL (range, 35,963.67 to 71,848.37 hours X μg/mL; SD, 12,960.90 hours X μg/mL). Cmax concentrations for all dogs were more than 1,000 ng/mL (1.0 μg/mL) at the 4-, 6-, 8-, and 10-hour time points. An SC continuous-rate infusion of cytarabine via the Omnipod system is feasible in dogs and was able to achieve a steady-state concentration of more than 1 μg/mL 4 to 10 hours postinitiation of cytarabine and a Cmax of 7,510 ng/mL (range, 5,040 to 9,690 ng/mL; SD, 1,912.41 ng/mL). These are comparable to values reported previously with IV continuous-rate infusion administration in healthy research Beagles and dogs with meningoencephalomyelitis of unknown etiology.

Population pharmacokinetic analysis for tisotumab vedotin in patients with locally advanced and/or metastatic solid tumors.

Tisotumab vedotin is an investigational antibody–drug conjugate (ADC) for treatment of solid tumors expressing tissue factor with accelerated approval from the US Food and Drug Administration for treatment of recurrent or metastatic cervical cancer with disease progression during or after chemotherapy. This study describes development of a population pharmacokinetic (PK) model to assess the PK profile of tisotumab vedotin and microtubule‐disrupting agent monomethyl auristatin E (MMAE) using data from 399 patients with solid tumors across four phase I/II trials. The ADC–MMAE model describes ADC and MMAE concentrations following intravenous administration of tisotumab vedotin. This four‐compartment model comprises a two‐compartment ADC model with parallel linear and Michaelis–Menten elimination, a delay compartment, and a one‐compartment MMAE model. Nonspecific linear clearance of ADC was 1.42 L/day, central volume of distribution (V c) was 3.10 L, and median terminal half‐life of ADC was 4.04 days. Apparent clearance of MMAE was 42.8 L/day, and apparent volume of distribution was 2.09 L. Terminal slope of the MMAE concentration–time curve was defined by the delay compartment rate with a half‐life of 2.56 days. Patients with higher body weight and lower albumin concentration had faster ADC clearance. Male patients and those with higher body weight and lower albumin concentration had higher V c. Body weight was the most influential covariate influencing distribution and elimination of ADC and MMAE, thus supporting weight‐based dosing of tisotumab vedotin. Presence of antidrug antibodies (detected in 3.3% of patients) did not affect key PK parameters or exposures for ADC and MMAE.

The efficacy and safety of mizoribine for maintenance therapy in patients with myeloperoxidase anti-neutrophil cytoplasmic antibody (MPO-ANCA)-associated vasculitis: the usefulness of serum mizoribine monitoring.

The life prognosis of elderly patients with myeloperoxidase-anti-neutrophil cytoplasmic antibodies-associated vasculitis (MPO-AAV) has been improved by reducing the corticosteroid or cyclophosphamide dose to avoid opportunistic infection. However, many elderly MPO-AAV patients experience recurrence and renal death. An effective and safer maintenance treatment method is necessary to improve the renal prognosis of MPO-AAV. Patients with MPO-AAV who reached complete or incomplete remission after induction therapy were prospectively and randomly divided into mizoribine (MZR; n = 25) and control (n = 28) groups. The primary endpoint was relapse of MPO-AAV. The patients' serum MZR concentration was measured before (C0) and 3h after taking the MZR. The maximum drug concentration (Cmax) and the serum MZR concentration curves were determined using population pharmacokinetics parameters. We also assessed the relationship between the MZR concentrations and adverse events. The observation period was 12months. Fifty-eight MPO-AAV patients from 16 hospitals in Japan were enrolled. Ten patients relapsed (MZR group, n = 6; control group, n = 4; a nonsignificant between-group difference). Changes in the serum MZR concentration could be estimated for 22 of the 25 MZR-treated patients: 2 of the 11 patients who reached a Cmax of 3μg/mL relapsed, whereas 4 of the 11 patients who did not reach this Cmax relapsed. The treatment of one patient with C0 > 1μg/mL was discontinued due to adverse events. No serious adverse events occurred. There was no significant difference in the recurrence rate of MPO-AAV between treatment with versus without MZR.

Pharmacokinetic and pharmacodynamic simulation for the quantitative risk assessment of linezolid-associated thrombocytopenia.

Linezolid (LZD) may cause thrombocytopenia, which can result in discontinuation of treatment. In this study, the blood LZD trough concentration was estimated based on population pharmacokinetic (PK) parameters derived from two previously published models in the Japanese population to determine the rate of achieving the target trough value when the risk of thrombocytopenia is low and to clarify its relationship with the onset of thrombocytopenia. This study included adult patients hospitalized at Shimane University Hospital, who received LZD treatment for at least 4 days from January 2010 to December 2017. Patients whose platelet count fell below 70% before LZD administration were categorized as the thrombocytopenic group. Patient PK parameters were calculated based on the population PK models described by Matsumoto et al. and Sasaki et al., and these parameters were designated A and B, respectively. Based on these parameters, the rate of achieving an LZD trough concentration of less than 8μg/ml, which is the safety target achievement rate, was calculated using a random simulation for each patient. We further analysed the association between the incidence of thrombocytopenia and patient factors, including safety target achievement rate, through univariate, multivariate, and receiver operating characteristic (ROC) analyses. Patients (n=77) aged 72 ± 11 years and weighing 56.7 ± 10.9kg, with a creatinine clearance (CLcr ) of 60.5 ± 47.2ml/min and a cirrhosis prevalence of 9.1%, were analysed. All patients received LZD at a dose of 600 mg twice daily for a total of 10.9 ± 8.9 days. Univariate analyses revealed significant differences (p < 0.05) in the duration of LZD therapy, serum creatinine, creatinine clearance, LZD clearance, and the safety target achievement rate for parameters A and B between the thrombocytopenic and non-thrombocytopenic groups. A multivariate analysis of these factors stratified with the cutoff values obtained by ROC analysis revealed that the duration of LZD therapy and the safety target achievement rates for parameters A and B were significant factors (odds ratios for duration of LZD therapy: 7.436 [95% confidence interval (CI): 1.918-28.831] and 4.712 [95% CI: 1.567-14.163]; odds ratio for safety target achievement rate: 0.060 [95% CI: 0.016-0.232] and 0.167 [95% CI: 0.056-0.498] for parameters A and B, respectively). When the safety target achievement rates for patients treated with LZD were compared between the thrombocytopenic and non-thrombocytopenic groups, the safety target achievement rate was higher in the non-thrombocytopenic group in both the patients treated with LZD for less than 10 days and those for 10 days or more. Therefore, the safety target achievement rate estimated by the PK/PD simulation may represent to be an important index for risk assessment of LZD-induced thrombocytopenia. The risk of LZD-induced thrombocytopenia, which increased with the duration of LZD therapy, may be predicted using the safety target achievement rate obtained by the blood concentration simulation.

Population Pharmacokinetics of Cyclosporine in Chinese Pediatric Patients With Acquired Aplastic Anemia.

Cyclosporine (CsA) is a component of the first-line treatment for acquired aplastic anemia (acquired AA) in pediatric patients. This study aimed to develop a population pharmacokinetic (PK) model of CsA in Chinese pediatric patients with acquired AA to inform individual dosage regimens. A total of 681 CsA whole blood concentrations and laboratory data of 157 pediatric patients with acquired AA were retrospectively collected from two hospitals in Shanghai. A nonlinear mixed-effect model approach was used to build the population PK model. Potential covariate effects of age, body weight, and biochemical measurements (renal and liver functions) on CsA PK disposition were evaluated. Model fit was assessed using the basic goodness of fit and a visual predictive check. The CsA concentration data were accurately described using a two-compartment disposition model with first-order absorption and elimination. Body weight value was implemented as a fixed allometric function on all clearance and volume of distribution parameters. Total bilirubin level was identified as a significant covariate on apparent clearance (CL/F), with a 1.07% reduction per 1 nmol/L rise in total bilirubin level. The final estimates for CL/F and central volume (Vc/F) were 29.1 L/h and 325 L, respectively, for a typical 28 kg child. Other covariates (e.g., gender, age, albumin, hemoglobin, hematocrit, serum creatinine, and concomitant medication) did not significantly affect the PK properties of CsA. This population PK model, along with a maximum a posteriori Bayesian approach, could estimate individual PK parameters in pediatric patients with acquired AA to conduct individual CsA therapy.

Semi-mechanistic population pharmacokinetics analysis reveals distinct CYP2C19 dependency in the bioactivation of vicagrel and clopidogrel to active metabolite M15–2

AimsVicagrel is a novel antiplatelet drug used to mitigate clopidogrel resistance due to CYP2C19 polymorphism. This study aimed to develop a semi-mechanistic population pharmacokinetic (PopPK) model to characterize the pharmacokinetic (PK) profile of M15-2, the active metabolite of vicagrel and clopidogrel, and to evaluate the influence of CYP2C19 polymorphisms and other covariates in healthy subjects and patients with acute coronary syndrome (ACS) after oral administration. MethodsThe analysis utilized data from 213 subjects, including 178 healthy subjects and 35 patients, from five clinical trials. PopPK modeling and simulation were used to estimate PopPK parameters and evaluate the impact of covariates. ResultsThe M15-2 PK profiles were well characterized by a model incorporating transit compartments, two-compartment parent models and two-compartment M15-2 models for both vicagrel and clopidogrel. The parameter estimates indicated the dose fraction of vicagrel that formed M15-2 was approximately 20-fold that of clopidogrel. Covariate analysis identified a significant effect of CYP2C19 on M15-2 apparent clearance (CL/F) and apparent volume of distribution (V3/F) for clopidogrel but only CL/F for vicagrel. The analysis suggested that the nonlinear PK of M15-2 for clopidogrel was due the first-step bioactivation of clopidogrel to 2-oxoclopidogrel. ConclusionThe model illustrated the bioactivation of vicagrel is more efficient and less dependent on CYP2C19 than that of clopidogrel. M15-2 is formed in a linear process from vicagrel, versus a nonlinear and less predictable process from clopidogrel. Advantages in both PK and pharmacogenetics suggest that vicagrel may reduce the complexity of currently recommended CYP2C19-based dosage adjustment for clopidogrel.

Population pharmacokinetic of paracetamol and atorvastatin with co-administration of semaglutide.

Semaglutide is a glucagon‐like‐peptide‐1 (GLP‐1) analogue marketed for once‐weekly subcutaneous administration for type 2 diabetes mellitus. Like other long‐acting GLP‐1 analogues, semaglutide reduces gastric emptying and, potentially, alters the rate of absorption of orally co‐administered drugs. The objective of the current analysis was to evaluate the effects on the gastric emptying rate caused by semaglutide on pharmacokinetic model parameters of paracetamol and atorvastatin in healthy subjects. Non‐linear mixed effect modeling was used to estimate population pharmacokinetic model parameters of paracetamol and atorvastatin after single doses with or without semaglutide. The absorption rate (ka) of paracetamol decreased by 53% when co‐administered with semaglutide. For atorvastatin, ka and transit compartment rate (ktr) decreased by 72% and 91%, respectively. Thus, gastric emptying, measured as T50, i.e., drug disappearance from the absorption compartments, showed an additional 5‐min delay for paracetamol and a 67‐min delay for atorvastatin when co‐administered with semaglutide. Semaglutide affected pharmacokinetic model parameters of paracetamol and atorvastatin, and minor quantitative differences in gastric emptying between placebo vs. semaglutide administration were observed. However, these effects of semaglutide were considered not to be of clinical relevance.

Pharmacokinetic/Pharmacodynamic Target Attainment of Vancomycin, at Three Reported Infusion Modes, for Methicillin-Resistant Staphylococcus aureus (MRSA) Bloodstream Infections in Critically Ill Patients: Focus on Novel Infusion Mode.

ObjectiveThe study aimed to evaluate and compare the pharmacokinetic/pharmacodynamic (PK/PD) exposure to vancomycin in the novel optimal two-step infusion (OTSI) vs. intermittent infusion (II) vs. continuous infusion (CI) mode, for MRSA bloodstream infections occurring in critical patients.MethodsWith PK/PD modeling and Monte Carlo simulations, the PK/PD exposure of 15 OTSI, 13 II, and 6 CI regimens for vancomycin, at 1, 2, 3, 4, 5, and 6 g daily dose, was evaluated. Using the Monte Carlo simulations, the vancomycin population PK parameters derived from critical patients, the PD parameter for MRSA isolates [i.e., minimum inhibitory concentration (MIC)], and the dosing parameters of these regimens were integrated into a robust mdel of vancomycin PK/PD index, defined as a ratio of the daily area under the curve (AUC0–24) to MIC (i.e., AUC0–24/MIC), to estimate the probability of target attainment (PTA) of these regimens against MRSA isolates with an MIC of 0.5, 1, 2, 4, and 8 mg/L in patients with varying renal function. The PTA at an AUC0–24/MIC ratio of >400, 400–600, and >600 was estimated. A regimen with a PTA of ≥90% at an AUC0–24/MIC ratio of 400–600, which is supposed to maximize both efficacy and safety, was considered optimal.ResultsAt the same daily dose, almost only the OTSI regimens showed a PTA of ≥90% at an AUC0–24/MIC ratio of 400–600, and this profile seems evident especially in patients with creatinine clearance (CL cr) of ≥60 ml/min and for isolates with an MIC of ≤2 mg/L. However, for patients with CL cr of <60 ml/min and for isolates with an MIC of ≥4 mg/L, the II regimens often displayed a higher or even ≥90% PTA at an AUC0–24/MIC ratio of >400 and of >600. The CI regimens frequently afforded a reduced PTA at an AUC0–24/MIC ratio of >400 and of >600, regardless of CL cr and MIC.ConclusionsThe data indicated that the OTSI regimens allowed preferred PK/PD exposure in terms of both efficacy and safety, and thus should be focused more on, especially in patients with CL cr of ≥60 ml/min and for isolates with an MIC of ≤2 mg/L.

Application of SHAP values for inferring the optimal functional form of covariates in pharmacokinetic modeling.

In population pharmacokinetic (PK) models, interindividual variability is explained by implementation of covariates in the model. The widely used forward stepwise selection method is sensitive to bias, which may lead to an incorrect inclusion of covariates. Alternatives, such as the full fixed effects model, reduce this bias but are dependent on the chosen implementation of each covariate. As the correct functional forms are unknown, this may still lead to an inaccurate selection of covariates. Machine learning (ML) techniques can potentially be used to learn the optimal functional forms for implementing covariates directly from data. A recent study suggested that using ML resulted in an improved selection of influential covariates. However, how do we select the appropriate functional form for including these covariates? In this work, we use SHapley Additive exPlanations (SHAP) to infer the relationship between covariates and PK parameters from ML models. As a case‐study, we use data from 119 patients with hemophilia A receiving clotting factor VIII concentrate peri‐operatively. We fit both a random forest and a XGBoost model to predict empirical Bayes estimated clearance and central volume from a base nonlinear mixed effects model. Next, we show that SHAP reveals covariate relationships which match previous findings. In addition, we can reveal subtle effects arising from combinations of covariates difficult to obtain using other methods of covariate analysis. We conclude that the proposed method can be used to extend ML‐based covariate selection, and holds potential as a complete full model alternative to classical covariate analyses.

Abstract 2022: Model-informed pediatric drug development: oral vinorelbine in low-grade glioma as a case study

Abstract Objectives:Defining a safe and effective dose in children is one of the biggest challenges in pediatric drug development. Pharmacometric tools are proposed as powerful quantitative techniques to leverage and integrate the collected data from pediatric clinical trials. Here we demonstrate and discuss the applications of nonlinear mixed effects (NLME) models through a detailed example of oral vinorelbine (VNR) in pediatric cancers.Methods:A multicentric, open-label, single-arm intervention phase II study was conducted. Patients with recurrent/progressive Low-Grade Glioma (LGG), were included. Patients received 60 mg/m² of oral VNR on days 1, 8 and 15 during the first 28-day treatment cycle and 80 mg/m² from cycle 2 to 12. Population pharmacokinetic (PK) analysis was performed using a NLME modeling approach on Monolix®. Fifty SNPs on PK-related genes were genotyped. The Influence of demographic, biological and pharmacogenetic covariates on VNR PK parameters was investigated using a stepwise multivariate procedure.Results:PK analysis included 36 patients with a median age (range) of 11 (6-17) years. A three-compartments model, with a delayed double zero-order absorption and a linear elimination, best described VNR pharmacokinetics. Typical population estimates (between-subject variability, between-occasion variability) for the apparent central volume of distribution (Vc/F) and elimination rate constant (k10) were 803 L (47%, 41%) and 0.60 h-1 (18%, 16%), respectively. Lower area under the concentration-time curve (AUC) levels were observed among children in comparison to adults. Following covariate analysis, BSA, leukocytes count, and ABCB1-rs2032582 SNP showed a dramatic impact on Vc/F. Additionally, ABCG2-rs2725264 A/G or G/G carriers and UGT2B7-rs7668258 T/T carriers showed higher k10 values. Conversely, age and sex had no significant effect on VNR PK.Conclusion:Higher doses may be necessary for children with LGG. A personalized dosing strategy, using BSA, leukocytes and ABCB1-rs2032582 SNP, could help to optimize the efficacy/toxicity balance of VNR in children. Model-informed drug development enabled efficiently a better understanding of PK of oral VNR in children and identifying several factors likely to explain the variability in VNR exposure and subsequent clinical outcomes. Citation Format: Mourad HAMIMED, Pierre LEBLOND, Aurélie DUMONT, Florence GATTACCECA, Emmanuelle TRESCH-BRUNEEL, Alicia PROBST, Pascal CHASTAGNER, Anne PAGNIER, Emilie DE CARLI, Natacha ENTZ-WERLÉ, Jacques GRILL, Isabelle AERTS, Didier FRAPPAZ, Anne-Isabelle BERTOZZI-SALAMON, Caroline SOLAS, Nicolas ANDRÉ, Joseph Ciccolini. Model-informed pediatric drug development: oral vinorelbine in low-grade glioma as a case study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2022.

Machine learning algorithms to estimate everolimus exposure trained on simulated and patient pharmacokinetic profiles.

Everolimus is an immunosuppressant with a small therapeutic index and large between‐patient variability. The area under the concentration versus time curve (AUC) is the best marker of exposure but measuring it requires collecting many blood samples. The objective of this study was to train machine learning (ML) algorithms using pharmacokinetic (PK) profiles from kidney transplant recipients, simulated profiles, or both types, and compare their performance for everolimus AUC0‐12h estimation using a limited number of predictors, as compared to an independent set of full PK profiles from patients, as well as to the corresponding maximum a posteriori Bayesian estimates (MAP‐BE). XGBoost was first trained on 508 patient interdose AUCs estimated using MAP‐BE, and then on 500–10,000 rich interdose PK profiles simulated using previously published population PK parameters. The predictors used were: predose, ~1 h, and ~2 h whole blood concentrations, differences between these concentrations, relative deviations from theoretical sampling times, morning dose, patient age, and time elapsed since transplantation. The best results were obtained with XGBoost trained on 5016 simulated profiles. AUC estimation achieved in an external dataset of 114 full‐PK profiles was excellent (root mean squared error [RMSE] = 10.8 μg*h/L) and slightly better than MAP‐BE (RMSE = 11.9 μg*h/L). Using more profiles (n = 10,035) did not improve the ML algorithm performance. The contribution of mixing patient and simulated profiles was significant only when they were in balanced numbers, with ~500 for each (RMSE = 12.5 μg*h/L), compared with patient data alone (RMSE = 18.0 μg*h/L).

Population pharmacokinetics of polymyxin B and dosage strategy in critically ill patients with/without continuous renal replacement therapy

Polymyxin B is served as a last-line agent for Carbapenem-resistant organisms (CRO) infections. This study aimed to establish a population pharmacokinetic (PK) model in patients with/without continuous renal replacement therapy (CRRT), to investigate the relationship between clinical covariates and polymyxin B PK parameters, and to optimize polymyxin B dosing regimens. Blood samples were obtained for each patient at steady state. The plasma concentrations of polymyxin B were determined using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Population PK models were developed using Pirana program and Monte Carlo simulations were conducted. A total of 63 patients accounting for 189 blood samples were included and divided into modeling (n = 49) and validation (n = 14) groups. A two-compartment model described the data well. CRRT, creatinine clearance (CLCR) and Sequential Organ Failure Assessment (SOFA) score were identified as significant covariates of polymyxin B clearance. Monte Carlo simulations indicated that a maintain dose of 75–100 mg q12h was required to meet the target drug exposure in patients receiving CRRT with SOFA ≤ 11 (minimum inhibitory concentration ≤ 1 mg·L−1). For patients without CRRT, dosage strategy should be adjusted on the basis of different renal functions and SOFA scores. This is the first population PK study that demonstrated CRRT, CLCR and SOFA score had significant effects on polymyxin B clearance in critically ill patients with/without CRRT. More PK data are urgently needed to clarify polymyxin B PK characteristics in patients with/without CRRT.

Population pharmacokinetic analysis of tepotinib, an oral MET kinase inhibitor, including data from the VISION study

PurposeTepotinib is a highly selective, potent, mesenchymal–epithelial transition factor (MET) inhibitor, approved for the treatment of non-small cell lung cancer (NSCLC) harboring MET exon 14 skipping. Objectives of this population pharmacokinetic (PK) analysis were to evaluate the dose–exposure relationship of tepotinib and its major circulating metabolite, MSC2571109A, and to identify the intrinsic/extrinsic factors that are predictive of PK variability.MethodsData were included from 12 studies in patients with cancer and in healthy participants. A sequential modeling approach was used to analyze the parent and metabolite data, including covariate analyses. Potential associations between observed covariates and PK parameters were illustrated using bootstrap analysis-based forest plots.ResultsA two-compartment model with sequential zero- and first-order absorption, and a first-order elimination from the central compartment, best described the plasma PK of tepotinib in humans across the dose range of 30–1400 mg. The bioavailability of tepotinib was shown to be dose dependent, although bioavailability decreased primarily at doses above the therapeutic dose of 500 mg. The intrinsic factors of race, age, sex, body weight, mild/moderate hepatic impairment and mild/moderate renal impairment, along with the extrinsic factors of opioid analgesic and gefitinib intake, had no relevant effect on tepotinib PK. Tepotinib has a long effective half-life of ~ 32 h.ConclusionsTepotinib shows dose proportionality up to at least the therapeutic dose, and time-independent clearance with a profile appropriate for once-daily dosing. None of the covariates identified had a clinically meaningful effect on tepotinib exposure or required dose adjustments.

Population pharmacokinetics analyses of rifampicin in adult and children populations: A systematic review.

Rifampicin has become an essential component as the first-line therapy for pulmonary tuberculosis (PTB). Several population pharmacokinetic (PK) studies on rifampicin in adult and child populations have been studied previously, therefore the aims of the systematic review were (i) to summarize the relevant published studies and significant covariates that influence the PK of rifampicin across different populations, and (ii) to identify any knowledge gap that requires additional research in the future. A total of 121 relevant population PK articles were systematically identified using PubMed and Scopus from inception to October 2021. Review articles, in-vitro and physiological methods, animal studies and noncompartmental analysis were excluded. Nineteen studies, of which 16 involved adults, two involved children, and one involved both adults and children, were included in the review. The structural model of rifampicin can be described as one compartment with a transient compartment absorption model and first-order elimination in most of the studies. Pharmaceutical formulation, body weight, gender, pregnancy status, diabetes and nutritional supplementation were found to be the significant covariates that affect the PK parameters. External validation of the developed PK model was only conducted in two studies. The source of variability for PK parameters of rifampicin remains inconsistent and poorly understood even though there were many potential covariates investigated in the selected studies. Exploring other possible factors and implementing a strict sampling strategy by considering the induction effects might uncover precise and reliable information. Furthermore, external validation should be frequently conducted to produce better predictability of model performance.

Effect of turmeric supplementation on the pharmacokinetics of paclitaxel in breast cancer patients: A study with population pharmacokinetics approach.

Turmeric is one of the most used herbal supplements among cancer patients. It reportedly modulates the function of CYP450 enzymes and drug transporters. This study investigates the effect of turmeric on the pharmacokinetics of paclitaxel in breast cancer patients. This is a prospective longitudinal study with 60 breast cancer patients on treatment with single-agent paclitaxel and turmeric. The patients were followed up for two consecutive chemotherapy cycles, and their blood samples were collected, first without turmeric (first cycle) and the next after a 21-day concomitant administration of 2 g/day turmeric (second cycle). Plasma samples were quantified for paclitaxel concentration using High Performance Liquid Chromatograph with UV detector (HPLC-UV) method. The sparse concentration-time data of paclitaxel were subjected to population pharmacokinetic modeling, and then noncompartmental analysis (NCA) was performed on the simulated data to estimate the pharmacokinetic parameters of paclitaxel, before and after turmeric supplementation, for comparisons. The population pharmacokinetic parameters of paclitaxel differed from before to after turmeric supplementation. NCA of simulated concentration-time profiles showed a statistically significant reduction of 7.7% and 12.1% in AUCinf and Cmax, respectively. Given the small magnitude of the changes in pharmacokinetic parameters, the observed changes are not clinically relevant. Thereby, turmeric at the recommended dose can be combined safely with paclitaxel.

Population pharmacokinetics analysis in Lixoft Monolix softwares

The article has discussed a step-by-step algorithm for developing population pharmacokinetics models in the Lixoft Monolix software. Features of population pharmacokinetics study’s methodology have described. Special attention is paid to the advantages of the compartmental approach and nonlinear mixed effects modeling in study of pharmacokinetics. Methods for estimating population pharmacokinetic parameters and its implementation in software are described.

Population pharmacokinetic and exposure-response analyses from ALTA-1L: Model-based analyses supporting the brigatinib dose in ALK-positive NSCLC.

The ALK in Lung Cancer Trial of brigAtinib in First Line (ALTA‐1L) compared brigatinib versus crizotinib in anaplastic lymphoma kinase (ALK) inhibitor‐naive patients with ALK+ non‐small cell lung cancer (NSCLC). A population pharmacokinetic (PK) model was used to estimate brigatinib exposures for exposure‐efficacy and exposure‐safety analyses in ALTA‐1L. A previously developed population PK model for brigatinib was applied to estimate brigatinib PK parameters. Relationships between static (time‐independent) and dynamic (time‐varying) exposure metrics and efficacy (progression‐free survival [PFS], objective response rate [ORR], and intracranial ORR [iORR]) and safety outcomes (selected grade ≥2 and grade ≥3 adverse events [AEs]) were evaluated using logistic regression and time‐to‐event analyses. There were no meaningful differences in brigatinib PK in the first‐line and second‐line settings, supporting use of the previous population PK model for the first‐line population. Exposure‐response analyses showed no significant effect of time‐varying brigatinib exposure on PFS. Brigatinib exposure was not significantly related to ORR, but higher exposure was associated with higher iORR (odds ratio: 1.13, 95% confidence interval: 1.01–1.28, p = 0.049). Across the observed median exposure (5th–95th percentile) at steady state for 180 mg once daily, the predicted probability of iORR was 0.83 (0.58–0.99). AEs significantly associated with higher exposure were elevated lipase (grade ≥3) and amylase (grade ≥2). Time to first brigatinib dose reduction was not related to exposure. These results support the benefit‐risk profile of first‐line brigatinib 180 mg once daily (7‐day lead‐in dose at 90 mg once daily) in patients with ALK+ NSCLC.

Influence of NAT2 Genotype and Maturation on Isoniazid Exposure in Low-Birth-Weight and Preterm Infants With or Without Human Immunodeficiency Virus (HIV) Exposure.

Isoniazid (INH) metabolism depends on the N-acetyl transferase 2 (NAT2) enzyme, whose maturation process remains unknown in low birth weight (LBW) and preterm infants. We aimed to assess INH exposure and safety in infants receiving oral tuberculosis prevention. This population pharmacokinetics (PK) analysis used INH and N-acetyl-isoniazid (ACL) concentrations in infants (BW ≤ 4kg), including preterm, with follow-up for 6 months. PK parameters were described using nonlinear mixed effects modeling. Simulations were performed to assess INH exposure and optimal dosing regimens, using 2 targets: Cmax at 3-6mg/L and area under the curve (AUC) ≥ 10.52mg h/L. We included 57 infants (79% preterm, 84% LBW) in the PK analysis, with a median (range) gestational age of 34 (28.7-39.4) weeks. At the time of sampling, postnatal age was 2.3 (0.2-7.3) months and weight (WT) was 3.7 (0.9-9.3) kg. NAT2 genotype was available in 43 (75.4%) patients (10 slow, 26 intermediate, and 7 fast metabolizers). Ninety percent of NAT2 maturation was attained by 4.4 post-natal months. WT, postmenstrual age, and NAT2 genotype significantly influenced INH exposure, with a 5-fold difference in AUC between slow and fast metabolizers for the same dose. INH appeared safe across the broad range of exposure for 61 infants included in the safety analysis. In LBW/preterm infants, INH dosing needs frequent adjustment to account for growth and maturation. Pharmacogenetics-based dosing regimens is the most powerful approach to deliver safe and equalized exposures for all infants, because NAT2 genotype highly impacts INH pharmacokinetic variability.