Nonlinear Mixed-effects Modeling Research Articles

Predicting [177Lu]Lu-HA-DOTATATE kidney and tumor accumulation based on [68Ga]Ga-HA-DOTATATE diagnostic imaging using semi-physiological population pharmacokinetic modeling

BackgroundPrediction of [177Lu]Lu-HA-DOTATATE kidney and tumor uptake based on diagnostic [68Ga]Ga-HA-DOTATATE imaging would be a crucial step for precision dosing of [177Lu]Lu-HA-DOTATATE. In this study, the population pharmacokinetic (PK) differences between [177Lu]Lu-HA-DOTATATE and [68Ga]Ga-HA-DOTATATE were assessed and subsequently [177Lu]Lu-HA-DOTATATE was predicted based on [68Ga]Ga-HA-DOTATATE imaging.MethodsA semi-physiological nonlinear mixed-effects model was developed for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE, including six compartments (representing blood, spleen, kidney, tumor lesions, other somatostatin receptor expressing organs and a lumped rest compartment). Model parameters were fixed based on a previously developed physiologically based pharmacokinetic model for [68Ga]Ga-HA-DOTATATE. For [177Lu]Lu-HA-DOTATATE, PK parameters were based on literature values or estimated based on scan data (four time points post-injection) from nine patients. Finally, individual [177Lu]Lu-HA-DOTATATE uptake into tumors and kidneys was predicted based on individual [68Ga]Ga-HA-DOTATATE scan data using Bayesian estimates. Predictions were evaluated compared to observed data using a relative prediction error (RPE) for both area under the curve (AUC) and absorbed dose. Lastly, to assess the predictive value of diagnostic imaging to predict therapeutic exposure, individual prediction RPEs (using Bayesian estimation) were compared to those from population predictions (using the population model).ResultsPopulation uptake rate parameters for spleen, kidney and tumors differed by a 0.29-fold (15% relative standard error (RSE)), 0.49-fold (15% RSE) and 1.43-fold (14% RSE), respectively, for [177Lu]Lu-HA-DOTATATE compared to [68Ga]Ga-HA-DOTATATE. Model predictions adequately described observed data in kidney and tumors for both peptides (based on visual inspection of goodness-of-fit plots). Individual predictions of tumor uptake were better (RPE AUC –40 to 28%) compared to kidney predictions (RPE AUC –53 to 41%). Absorbed dose predictions were less predictive for both tumor and kidneys (RPE tumor and kidney –51 to 44% and –58 to 82%, respectively). For most patients, [177Lu]Lu-HA-DOTATATE tumor accumulation predictions based on individual PK parameters estimated from diagnostic imaging outperformed predictions based on population parameters.ConclusionOur semi-physiological PK model indicated clear differences in PK parameters for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE. Diagnostic images provided additional information to individually predict [177Lu]Lu-HA-DOTATATE tumor uptake compared to using a population approach. In addition, individual predictions indicated that many aspects, apart from PK differences, play a part in predicting [177Lu]Lu-HA-DOTATATE distribution.

Mirikizumab Pharmacokinetics in Patients with Moderately to Severely Active Ulcerative Colitis: Results from Phase III LUCENT Studies.

Mirikizumab is a humanized anti-interleukin-23-p19 monoclonal antibody being developed for ulcerative colitis and Crohn's disease. This analysis characterized mirikizumab pharmacokinetics using phase II and III trial data from patients with moderately to severely active ulcerative colitis. Serum pharmacokinetic data in patients receiving mirikizumab 50-1000 mg intravenously every 4 weeks as induction treatment and mirikizumab 200 mg subcutaneously every 4 or 12 weeks as maintenance treatment across three trials (N = 1362) were analyzed using non-linear mixed-effects modeling. Covariate effects on mirikizumab exposure were evaluated using simulation-based estimations. Mirikizumab pharmacokinetics was best described by a linear two-compartment model with first-order absorption. Clearance, volume of distribution for central and peripheral compartments, and half-life were estimated at approximately 0.022 L/h (linear), 3.11 L and 1.69 L, and 9.5 days, respectively. Statistically significant effects of body weight and serum albumin levels on clearance, body weight on central and peripheral volumes of distribution, and body mass index on bioavailability were observed but effects were small relative to random inter-individual variability (% coefficient of variation: 18-64%). The subcutaneous bioavailability of mirikizumab was 48%. Mirikizumab displayed pharmacokinetic characteristics typical of a monoclonal antibody where clearance increased with body weight and decreased with the albumin level, and bioavailability decreased with body mass index. These effects were small relative to random variability, indicating that a dose adjustment for patient factors is not required. ClinicalTrials.gov: NCT02589665 (28 October, 2015), NCT03518086 (8 May, 2018), NCT03524092 (14 May, 2018).

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

Model-informed precision dosing (MIPD) frequently uses nonlinear mixed-effects (NLME) models to predict and optimize therapy outcomes based on patient characteristics and therapeutic drug monitoring data. MIPD is indicated for compounds with narrow therapeutic range and complex pharmacokinetics (PK), such as voriconazole, a broad-spectrum antifungal drug for prevention and treatment of invasive fungal infections. To provide guidance and recommendations for evidence-based application of MIPD for voriconazole, this work aimed to (i) externally evaluate and compare the predictive performance of a published so-called 'hybrid' model for MIPD (an aggregate model comprising features and prior information from six previously published NLME models) versus two 'standard' NLME models of voriconazole, and (ii) investigate strategies and illustrate the clinical impact of Bayesian forecasting for voriconazole. A workflow for external evaluation and application of MIPD for voriconazole was implemented. Published voriconazole NLME models were externally evaluated using a comprehensive in-house clinical database comprising nine voriconazole studies and prediction-/simulation-based diagnostics. The NLME models were applied using different Bayesian forecasting strategies to assess the influence of prior observations on model predictivity. The overall best predictive performance was obtained using the aggregate model. However, all NLME models showed only modest predictive performance, suggesting that (i) important PK processes were not sufficiently implemented in the structural submodels, (ii) sources of interindividual variability were not entirely captured, and (iii) interoccasion variability was not adequately accounted for. Predictive performance substantially improved by including the most recent voriconazole observations in MIPD. Our results highlight the potential clinical impact of MIPD for voriconazole and indicate the need for a comprehensive (pre-)clinical database as basis for model development and careful external model evaluation for compounds with complex PK before their successful use in MIPD.

Adalimumab Clearance, Rather Than Trough Level, May Have Greatest Relevance to Crohn's Disease Therapeutic Outcomes Assessed Clinically and Endoscopically.

We postulated that adalimumab [ADA] drug clearance [CL] may be a more critical determinant of therapeutic outcome than ADA concentration. This was tested in Crohn's disease [CD] patients undergoing ADA maintenance treatment. CD patients from four cohorts received ADA induction and started maintenance therapy. Therapeutic outcomes consisted of endoscopic remission [ER], sustained C-reactive protein [CRP] based clinical remission [defined as CRP levels below 3 mg/L in the absence of symptoms], and faecal calprotectin [FC] level below 100 µg/g. Serum albumin, ADA concentration, and anti-drug antibody status were determined using immunochemistry and homogeneous mobility shift assay, respectively. CL was determined using a nonlinear mixed effect model with Bayesian priors. Statistical analysis consisted of Mann-Whitney test and logistic regression with calculation of odds ratio. Repeated event analysis was conducted using a nonlinear mixed effect model. In 237 enrolled patients [median age 40 years, 45% females], median CL was lower in patients achieving ER as compared with those with persistent active endoscopic disease [median 0.247 L/day vs 0.326 L/day, respectively] [p <0.01]. There was no significant difference in ADA concentration between patients in endoscopic remission compared with those with recurrence [median 9.3 µg/mL vs 11.7 µg/mL, respectively]. Sustained CRP-based clinical remission and FC levels below 100 µg/g were generally associated with lower CL and higher ADA concentration. Repeated event analysis confirmed those findings with better performances of CL than concentration in associating with ER and other outcomes. Lower ADA clearance is associated with an improved clinical outcome for patients with Crohn's disease and may be a superior pharmacokinetic measure than concentration.

Individualized Delivery of Vancomycin by Model-Informed Bayesian Dosing Approach to Maintain an AUC24 Target in Critically Ill Patients

Introduction: Monitoring of AUC24 was updated recommendation in the guideline for the therapeutic drug monitoring (TDM) of vancomycin in Chinese pharmacological society published in 2020. Vancomycin pharmacokinetic profiles are diverse and unique in critically ill patients because of the drastic variability of the patients’ physiological parameters, while the study for population pharmacokinetic (PPK) models in Chinese critically ill patients has been rarely reported. The objectives of this study were to construct a PPK model to describe the pharmacokinetic characteristics of vancomycin in critically ill patients and to individualize vancomycin dosing by model-informed Bayesian estimation for maintenance of AUC24 target at 400–650 mg h/L recommended by the 2020 guideline. Methods: Vancomycin with different dosing was administered intravenously over 1 h for critically ill patients, TDM was started at 48 h or 72 h since initiation of vancomycin therapy for patients. Blood samples were collected from patients for trough concentrations or Cmax. Vancomycin concentrations were determined by high-performance liquid chromatography method with ultraviolet detection. PPK model was performed using the nonlinear mixed-effect model (NONMEM®). Individual PK parameters for critically ill patients treated with vancomycin were estimated using a post hoc empirical Bayesian method based on the final PPK model. AUC24 was calculated as the total daily dose divided by the clearance (L/h). Results: The PPK of vancomycin was determined by a one-compartment model with creatinine clearance as fixed effects. The PK estimates in the final model generally agreed with the median estimates and were contained within the 95% CI generated from the bootstrap results, indicating good precision and stability in the final model. The visual predictive check plots showed the adequate predictive performance of the final PK model and supported a good model fit. The model-informed Bayesian estimation was used to predict the AUC24 of critically ill patient by the acquired TDM results, and the dosing adjustment by maintenance of AUC24 at 400–650 mg h/L had made a great therapeutic effect for the case. Conclusion: This study established a PPK model of vancomycin in Chinese critically ill patients, and individualized dosing of vancomycin by model-informed Bayesian estimation to maintain an AUC24 target at 400–650 mg h/L has been successfully applied in clinic. This result supports the continued use of model-informed Bayesian estimation to vancomycin treatment in critically ill patients.

Population Pharmacokinetic Analysis Supports Initiation Treatment and Bridging from Sublingual Buprenorphine to Subcutaneous Administration of a Buprenorphine Depot (CAM2038) in the Treatment of Opioid Use Disorder.

In treating opioid use disorder (OUD), subcutaneous (SC) extended-release buprenorphine (BPN) depots, e.g.,CAM2038, have been shown to provide smaller and less frequent fluctuations in BPN plasma concentrations and pharmacodynamic responses, improve outcomes, reduce treatment burden, and lower risks of misuse and diversion compared to daily sublingual (SL) BPN. This analysis characterized the pharmacokinetics (PK) of BPN following intravenous and SL administration, and administration of SC CAM2038 weekly and monthly. Pharmacokinetic data from two Phase 1 and two Phase 2 trials in healthy participants and participants with OUD, respectively, were used to develop a population PK model using non-linear mixed effects modelling. The analysis included data from 252 participants and 10,658 BPN observations. The disposition of BPN was best described by a three-compartment model with first-order elimination, and absorption of SL BPN and SC CAM2038 weekly and monthly by dual parallel absorption pathways. Model diagnostics indicated good predictive performance of BPN concentrations. Buprenorphine plasma concentration-time profiles were simulated for treatment initiation, switching from SL BPN to CAM2038 weekly and monthly, and tapering after interrupting treatment with CAM2038. Simulations predicted CAM2038 weekly and monthly doses that provided BPN plasma maximum concentration (Cmax) and trough concentration (Ctrough) values at steady state within those observed following SL BPN administration. This population PK model supports the use of CAM2038 doses as individualized treatment for OUD across different treatment stages, including initiation, switching from SL BPN according to established dose conversion schedules, and tapering. ISRCTN41550730 (05/19/2014), ISRCTN24987553 (07/29/2014), NCT02611752 (11/23/2015), NCT02710526 (03/16/2016).

The Utility of Mixed Effects Models in the Evaluation of Complex Genomic Traits In Vitro.

In pharmacogenomic studies, the use of human liver microsomes as a model system to evaluate the impact of complex genomic traits (i.e., linkage-disequilibrium patterns, coding, and non-coding variation, etc.) on efficiency of drug metabolism is challenging. To accurately predict the true effect size of genomic traits requires large richly sampled datasets representative of the study population. Moreover, the acquisition of this data can be labor-intensive if the study design or bioanalytical methods are not high throughput, and it is potentially unfeasible if the abundance of sample needed for experiments is limited. To overcome these challenges, we developed a novel strategic approach using non-linear mixed effects models (NLME) to determine enzyme kinetic parameters for individual liver specimens using sparse data. This method can facilitate evaluation of the impact that complex genomic traits have on the metabolism of xenobiotics in vitro when tissue and other resources are limited. In addition to facilitating the accrual of data, it allows for rigorous testing of covariates as sources of kinetic parameter variability. In this in silico study, we present a practical application of such an approach using previously published in vitro cytochrome P450 (CYP) 2D6 data and explore the impact of sparse sampling, and experimental error on known kinetic parameter estimates of CYP2D6 mediated formation of 4-hydroxy-atomoxetine in human liver microsomes. SIGNIFICANCE STATEMENT: This study presents a novel non-linear mixed effects model (NLME)-based framework for evaluating the impact of complex genomic traits on saturable processes described by a Michaelis-Menten kinetics in vitro using sparse data. The utility of this approach extends beyond gene variant associations, including determination of covariate effects on in vitro kinetic parameters and reduced demand for precious experimental material.

Pharmacokinetic modelling of orally administered cannabidiol and implications for medication control in horses.

Cannabidiol (CBD) products gain increasing popularity amongst animal owners and veterinarians as an alternative remedy for treatment of stress, inflammation or pain in horses. Whilst the use of cannabinoids is banned in equine sports, there is limited information available concerning CBD detection times in blood or urine. The aim of this study was to determine the pharmacokinetic properties of CBD following oral administration in the horse to assist doping control laboratories with interpreting CBD analytical results. Part 1: dose escalation study: Single oral administration of three escalating doses of CBD paste (0.2 mg/kg, n = 3 horses; 1 mg/kg, n = 3; 3 mg/kg, n = 5) with >7 days wash-out periods in between. Part 2: multiple dose study: oral administration of CBD paste (3 mg/kg, n = 6) twice daily for 15 days. Multiple blood and urine samples were collected daily throughout both studies. Following study part 2, blood and urine samples were collected for 2 weeks to observe the elimination phase. Concentrations of CBD, its metabolites and further cannabinoids were evaluated using gas-chromatography/tandem-mass-spectrometry. Pharmacokinetic parameters were assessed via two approaches: population pharmacokinetic analysis using a nonlinear mixed-effects model and non-compartmental analysis. AUC0-12 h and Cmax were tested for dose proportionality. During the elimination phase, the CBD steady-state urine to serum concentration ratio (Rss) was calculated. Oral CBD medication was well-tolerated in horses. Based on population pharmacokinetics, a three-compartment model with zero-order absorption most accurately described the pharmacokinetic properties of CBD. High volumes of distribution into peripheral compartments and high concentrations of 7-carboxy-CBD were observed in serum. Non-compartmental analysis identified a Cmax of 12.17 ± 2.08 ng/mL after single administration of CBD (dose: 3 mg/kg). AUC0-12 h showed dose proportionality, increase for Cmax leveled off at higher doses. Following multiple doses, the CBD terminal half-life was 161.29 ± 43.65 h in serum. Rss was 4.45 ± 1.04. CBD is extensively metabolized and shows high volumes of tissue distribution with a resulting extended elimination phase. Further investigation of the potential calming and anti-inflammatory effects of CBD are required to determine cut-off values for medication control using the calculated Rss.

Use of Danish National Somatic Cell Count Data to Assess the Need for Dry-Off Treatment in Holstein Dairy Cattle.

In Denmark, PCR testing of dairy cattle is commonly used to select animals for the antibacterial treatment of intramammary infection (IMI) during the dry-off period. IMI is associated with a high somatic cell count (SCC), routinely recorded for milk quality control for most commercial dairy herds. This study aimed to compare SCC curves over the lactation among dairy cows with positive vs. negative PCR test results for four major IMI pathogens. Data from 133,877 PCR-tested Holstein cows from 1364 Danish conventional dairy herds were used to fit a nonlinear mixed-effects model using a modified four-parameter Wilmink function. We stratified the data into first, second, third or fourth and later parity and fitted Wilmink curves to all SCC observations between 6 and 305 days in milk. The PCR tests were taken before dry-off at the end of the lactation to investigate which animals qualified for selective dry cow therapy. A PCR Ct-value of 37 and below was used to determine if an animal was PCR positive for any of the following IMI pathogens: Staphylococcus aureus, Streptococcus agalactiae, Str. dysgalactiae and Str. uberis. Our findings showed that mean SCC curve fits were higher for PCR-positive animals in all four parity groups and across lactations. The use of SCC data fitted to the entire lactation for multiple lactations enabled quantification of overall differences in SCC curves between cattle with and without detected IMI, adjusted for parity group and stage of lactation. These findings are relevant to the use of SCC to support treatment decisions.

Population pharmacokinetics of dexamethasone in critically ill COVID-19 patients: Does inflammation play a role?

PurposeThe aim of this study is to design a population pharmacokinetic study to gain a deeper understanding of the pharmacokinetics of dexamethasone in critically ill COVID-19 patients in order to identify relevant covariates that can be used to personalize dosing regimens. MethodsBlood samples from critically ill patients receiving fixed-dose intravenous dexamethasone (6 mg/day) for the treatment of COVID-19 were sampled in a retrospective pilot study. The data were analyzed using Nonlinear Mixed Effects Modeling (NONMEM) software for population pharmacokinetic analysis and clinically relevant covariates were selected and evaluated. ResultsA total of 51 dexamethasone samples from 18 patients were analyzed and a two-compartment model fit the data best. The mean population estimates were 2.85 L/h (inter-individual-variability 62.9%) for clearance, 15.4 L for the central volume of distribution, 12.3 L for the peripheral volume of distribution and 2.1 L/h for the inter-compartmental distribution clearance. The covariate analysis showed a significant negative correlation between dexamethasone clearance and CRP. ConclusionsDexamethasone PK parameters in ICU COVID patients were substantially different from those from non-ICU non-COVID patients, and inflammation may play an important role in dexamethasone exposure. This finding suggests that fixed-dose dexamethasone over several days may not be appropriate for ICU COVID patients.

Population pharmacokinetic modeling and dosing simulation of avalglucosidase alfa for selecting alternative dosing regimen in pediatric patients with late-onset pompe disease

Avalglucosidase alfa (AVAL) was approved in the United States (2021) for patients with late-onset Pompe disease (LOPD), aged ≥ 1 year. In the present study, pharmacokinetic (PK) simulations were conducted to propose alternative dosing regimens for pediatric LOPD patients based on a bodyweight cut-off. Population PK (PopPK) analysis was performed using nonlinear mixed effect modeling approach on pooled data from three clinical trials with LOPD patients, and a phase 2 study (NCT03019406) with infantile-onset Pompe disease (IOPD: 1–12 years) patients. A total of 2257 concentration-time points from 91 patients (LOPD, n = 75; IOPD, n = 16) were included in the analysis. The model was bodyweight dependent allometric scaling with time varying bodyweight included on clearance and distribution volume. Simulations were performed for two dosing regimens (20 mg/kg or 40 mg/kg) with different bodyweight cut-off (25, 30, 35 and 40 kg) by generating virtual pediatric (1–17 years) and adult patients. Corresponding simulated individual exposures (maximal concentration, Cmax and area under the curve in the 2-week dosing interval, AUC2W), and distributions were calculated. It was found that dosing of 40 mg/kg and 20 mg/kg in pediatric patients < 30 kg and ≥ 30 kg, respectively, achieved similar AVAL exposure (based on AUC2W) to adult patients receiving 20 mg/kg. PK simulations conducted on the basis of this model provided supporting data for the currently approved US labelling for dosing adapted bodyweight in LOPD patients ≥ 1 year by USFDA.

Initial dosage optimisation of cyclosporine in Chinese paediatric patients undergoing allogeneic haematopoietic stem cell transplantation based on population pharmacokinetics: a retrospective study

ObjectiveImproved understanding of cyclosporine A (CsA) pharmacokinetics in children undergoing allogeneic haematopoietic stem cell transplantation (allo-HSCT) is crucial for effective prevention of acute graft-versus-host disease and medication safety. The aim...

Nonlinear Mixed-Effect Models to Describe Growth Curves of Pepper Fruits in Eight Cultivars Including Group Effects

Evaluating the behavior of fruit width and length characters throughout the pepper crop cycle is essential for researchers in decision-making aimed at developing appropriate management techniques and harvesting fruits at proper growth stages. The Nonlinear Mixed-Effect Models (NLME) method is recommended to jointly model the residuals and the entire database, including group effects, to describe growth curves. This work compared four nonlinear equations (Gompertz, Logistic, Richards, and von Bertalanffy) by including groups (pepper and bell pepper) to describe the pepper genotypes’ length and width growth. Of the eight genotypes used, three were bell pepper, and five were pepper. For each, fruit length and width were measured in 10 periods. According to the fit-quality measures studied, the best model for adjusting the length of the fruit was the Richards (Radj.2=0.9960), while for the width, it was the Logistic (Radj.2=0.9957). The estimated random effects showed that for asymptotic length and time to the inflection point presented a correlation of 0.75, indicating a positive association between these traits. For width, however, this result was different: −0.02. NLME adjustment allowed efficient prediction of values and efficient characterization of the studied genotypes, proving to be an efficient method for longitudinal data.

Modeling Height–Diameter Relationship Using Artificial Neural Networks for Durango Pine (Pinus durangensis Martínez) Species in Mexico

The total tree height (h) and diameter at breast height (dbh) relationship is an essential tool in forest management and planning. Nonlinear mixed effect modeling (NLMEM) has been extensively used, and lately the artificial neural network (ANN) and the resilient backpropagation artificial neural network (RBPANN) approach has been a trending topic for modeling this relationship. The objective of this study was to evaluate and contrast the NLMEN and RBPANN approaches for modeling the h-dbh relationship for the Durango pine species (Pinus durangensis Martínez) for both training and testing datasets in a mixed-species forest in Mexico. The knowledge of this relationship is important for forest management and planning in Mexican Forestry. The total dataset considered 1000 plots (each plot 0.10 ha) (11,472 measured trees) randomly selected from 14,390 temporary forest inventory plots and the dataset was randomly divided into two parts: 50% for training and 50% for testing. An unsupervised clustering analysis was used to group the dataset into 10 cluster-groups based on the k-means clustering method. An RBPANN was performed for tangent hyperbolicus (RBPANN-tanh), softplus (RBPANN-softplus), and logistic (RBPANN-logistic) activation functions in the cross product of the covariate or neurons and the weights for the ANN analysis. Also, a different vector of hidden layers was used for training of ANNs. For both training and testing, 10 classical statistics (e.g., RMSE, AIC, BIC, and logLik) were computed for the residual values and to assess the approaches for the h-dbh relationship. For training and testing, the ANN approach outperformed the NLMEM approach, and the RBPANN-tanh had the best performance in both the training and testing of ANNs.

Pharmacokinetics and safety of prolonged paracetamol treatment in neonates: An interventional cohort study.

To investigate the pharmacokinetics and safety of prolonged paracetamol use (>72 h) for neonatal pain. Neonates were included if they received paracetamol orally or intravenously for pain treatment. A total of 126 samples were collected. Alanine aminotransferase and bilirubin were measured as surrogate liver safety markers. Paracetamol and metabolites were measured in plasma. Pharmacokinetic parameters for the parent compound were estimated with a nonlinear mixed-effects model. Forty-eight neonates were enrolled (38 received paracetamol for >72 h). Median gestational age was 38 weeks (range 25-42), and bodyweight at inclusion was 2954 g (range 713-4750). Neonates received 16 doses (range 4-55) over 4.1days (range 1-13.8). The median (range) dose was 10.1mg/kg (2.9-20.3). The median oxidative metabolite concentration was 14.6μmol/L (range 0.12-113.5) and measurable >30 h after dose. There was no significant difference (P > .05) between alanine aminotransferase and bilirubin measures at <72 h or >72 h of paracetamol treatment or the start and end of the study. Volume of distribution and paracetamol clearance for a 2.81-kg neonate were 2.99 L (% residual standard error = 8, 95% confidence interval 2.44-3.55) and 0.497 L/h (% residual standard error = 7, 95% confidence interval 0.425-0.570), respectively. Median steady-state concentration from the parent model was 50.3μmol/L (range 30.6-92.5), and the half-life was 3.55 h (range 2.41-5.65). Our study did not provide evidence of paracetamol-induced liver injury nor changes in metabolism in prolonged paracetamol administration in neonates.

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

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. 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. 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 Lh-1 or 0.293 Lmin-1) were consistent with literature values; whereas total MPA clearance (0.72 Lh-1 or 0.012 Lmin-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. 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.

Saliva as a noninvasive sampling matrix for therapeutic drug monitoring of intravenous busulfan in Chinese patients undergoing hematopoietic stem cell transplantation: A prospective population pharmacokinetic and simulation study.

Therapeutic drug monitoring (TDM) of busulfan (BU) is currently performed by plasma sampling in patients undergoing hematopoietic stem cell transplantation (HSCT). Saliva samples are considered a noninvasive TDM matrix. Currently, no salivary population pharmacokinetics (PopPKs) model for BU available. This study aimed to develop a PopPK model that can describe the relationship between plasma and saliva kinetics in patients receiving intravenous BU. The performance of the model in predicting the area under the concentration-time curve at steady state (AUCss ) based on saliva samples is evaluated. Sixty-six patients with HSCT were recruited and administered 0.8 mg/kg BU intravenously. A PopPK model for saliva and plasma was developed using the nonlinear mixed effects model. Bayesian maximum a posteriori (MAP) optimization was used to estimate the model's predictive performance. Plasma and saliva PKs were adequately described with a one-compartment model and a scaled central compartment. Body surface area correlated positively with both clearance and apparent volume of distribution (Vd), whereas alkaline phosphatase correlated negatively with Vd. Simulations demonstrated that the percentage root mean squared prediction error and lower and upper limits of agreements reduced to 10.02% and -16.96% to 22.86% based on five saliva samples. Saliva can be used as an alternative matrix to plasmain TDM of BU. The AUCss can be predicted from saliva concentration by Bayesian MAP optimization, which can be used to design personalized dosing for BU.

Modelling the effects of ration on individual growth of Oncorhynchus tshawytscha under controlled conditions.

Fed aquaculture is one of the fastest growing and most valuable food production industries in the world. The efficiency with which farmed fish convert feed into biomass influences both environmental impact and economic revenue. Salmonid species, such as king salmon (Oncorhynchus tshawytscha), exhibit high levels of plasticity in vital rates such as feed intake and growth rates. Accurate estimations of individual variability in vital rates are important for production management. The use of mean trait values to evaluate feeding and growth performance can mask individual-level differences that potentially contribute to inefficiencies. Here, we apply a cohort integral projection model (IPM) framework to investigate individual variation in growth performance of 1625 individually tagged king salmon fed one of three distinct rations of 60%, 80% and 100% satiation and tracked over a duration of 276 days. To capture the observed sigmoidal growth of individuals, we compared a non-linear mixed-effects (logistic) model to a linear model used within the IPM framework. Ration significantly influenced several aspects of growth, both at the individual and at the cohort level. Mean final body mass and mean growth rate increased with ration, however, variance in body mass and feed intake also increased significantly over time. Trends in mean body mass and individual body mass variation were captured by both logistic and linear models, suggesting the linear model to be suitable for use in the IPM. We also observed that higher rations resulted in a decreasing proportion of individuals reaching the cohort's mean body mass or larger by the end of the experiment. This suggests that, in the present experiment, feeding to satiation did not produce the desired effects of efficient, fast, and uniform growth in juvenile king salmon. While monitoring individuals through time is challenging in commercial aquaculture settings, recent technological advances combined with an IPM approach could provide new scope for tracking growth performance in experimental and farmed populations. Using the IPM framework might allow the exploration of other size-dependent processes affecting vital rate functions, such as competition and mortality. This article is protected by copyright. All rights reserved.

Modeling Free Branch Growth with the Competition Index for a Larix principis-rupprechtii Plantation

Competition among free branches in the tree canopy is an important factor influencing branch length growth. Therefore, there is a need to quantify this competition and to understand the impact of the regression technique on the predictive accuracy of the growth of free branch length (GFBL) model in a Larix principis-rupprechtii plantation. This study focused on an L. principis-rupprechtii plantation in Saihanba Mechanized Forest Farm. Five competition indices based on 2176-branch data points from 76 trees were used to quantify the branch competition, and three regression techniques (nonlinear least squares (NLS), nonlinear mixed-effects model (NLME), and nonlinear quantile regression (NQR)) were used to construct the GFBL model including the branch competition index. The results showed that the Chapman–Richards growth function, including the diameter at breast height (DBH) and depth of branch into crown (DINC), was the optimal equation for describing the GFBL in the studied L. principis-rupprechtii plantation. The branch competition index (CI) was found to be optimal for quantifying the branch competition when used with the maximum value parameter (a0) of the Chapman–Richards growth function. The three parameter estimation methods were compared, and the NLME, which included the CI, was found to have the highest predictive accuracy. The results of this study can act as a reference for improving the management, assessing the management effectiveness, and enhancing the quality of L. principis-rupprechtii plantations.

Population Target-Mediated Pharmacokinetic/Pharmacodynamic Modeling to Evaluate SPI-62 Exposure and Hepatic 11β-Hydroxysteroid Dehydrogenase Type 1 (HSD-1) Inhibition in Healthy Adults.

SPI-62 is a small-molecule 11β-hydroxysteroid dehydrogenase type 1 (HSD-1) inhibitor exhibiting complicated nonlinear pharmacokinetics (PK) in human. Previously, we developed a target-mediated drug disposition (TMDD) model to characterize the substantial nonlinear PK of SPI-62. The aim of the current analysis was to perform population PK/PD analysis to further link SPI-62 exposure (i.e., PK) with its response (i.e., inhibition of hepatic HSD-1 activity) to gain a quantitative understanding of the SPI-62 dose-exposure-response relationship. PK and PD data from the first-in-human (FIH) clinical trials, including single ascending dose (SAD) and multiple ascending dose (MAD) studies, were used for model development. During the model development process, the final model selection was based on biological and physiological plausibility, goodness-of-fit plots, stability of parameter estimates, and objective function value. The nonlinear-mixed effect modeling (NONMEM) software was used for both the implementation of the PK/PD model and model simulation. SPI-62 plasma levels and hepatic HSD-1 inhibition over time following various dose regimens were simulated. The final model was a two-compartment TMDD model component for SPI-62 and an inhibitory Imax model component for hepatic HSD-1 activity. The TMDD-hepatic PD model that we established adequately characterized all remarkable PK and PD behaviors of SPI-62, such as extremely low plasma exposures following the first low doses, nonlinear PK turned into linear PK after repeated low doses, and substantial and long-lasting hepatic HSD-1 inhibition following low doses. SPI-62 was estimated to bind to the target with a second-order association rate constant (Kon) of 8.43 nM-1h-1 and first-order dissociation rate constant (Koff) value of 0.229 h-1, indicating that SPI-62 binds rapidly to, and dissociates slowly from, its pharmacological target. The estimated target capacity (Rtot) of 5460 nmol corresponds to approximately 2.2 mg of SPI-62, which comports well with the dose range in which PK nonlinearity is prominent. Model simulation results reveal that a 6 mg once-daily regimen can lead to long-lasting and substantial hepatic HSD-1 inhibition. A population TMDD-PD model that explains SPI-62 nonlinear PK and hepatic HSD-1 inhibition following different dose regimens in healthy adults was successfully established. Our simulation results provide a solid foundation for model-informed development of SPI-62.