Population Pharmacokinetic Model Research Articles

A Model-Informed Drug Development Approach to Design a Phase 3 Trial of Teverelix Drug Product in Advanced Prostate Cancer Patients with Increased Cardiovascular Risk.

Teverelix drug product (DP) is a parenteral gonadotropin-releasing hormone (GnRH) antagonist that has been successfully tested in phase 2 trials for hormone-sensitive advanced prostate cancer (APC) and benign prostatic hyperplasia (BPH). In previous APC trials, teverelix DP was administered as intramuscular (IM) and subcutaneous (SC) injections, using a loading dose and (in a single trial) a maintenance dose. Our objective was to derive an optimal dosing regimen for phase 3 clinical development, using a pharmacometrics modeling approach. Data from 9 phase 2 studies (229 patients) was utilized to develop a population pharmacokinetic (PK) model that described the concentration profile accommodating both IM and SC routes of administration. A 2-compartment model with sequential first-order absorption (slow and fast) and lag times best described the PK profiles of teverelix following SC and IM administration. An indirect response model with inhibition of production rate was fit to describe testosterone (T) concentrations based on physiological relevance. The final population PK-pharmacodynamic model was used to conduct simulations of various candidate dosing regimens to select the optimal dosing regimen to achieve clinical castration (T<0.5ng/mL by day 28) and to sustain clinical castration for 26 weeks. Model simulation showed that a loading dose of 360mg SC and 180mg IM with a maintenance dose of 360mg SC 6-weekly (Q6W) starting at day 28 can achieve a ≥95% castration rate up to 52 weeks. This dose regimen was selected for phase 3 clinical development, which includes cardiovascular safety assessment in comparison to a GnRH agonist.

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians.

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

Population Pharmacokinetic Modeling of Unbound Meropenem in Patients Undergoing Continuous Renal Replacement Therapy: An Observational Cohort Study.

The most effective dosing strategy of meropenem for patients undergoing continuous renal replacement therapy (CRRT) remains uncertain. This study aimed to analyze the population pharmacokinetics (popPKs) of unbound meropenem and establish an appropriate dosing approach. This prospective study involved 19 patients for the development of a popPK model and an additional 10 for its validation. Ethical approval was obtained. The clearance of unbound meropenem was influenced by the sequential organ failure assessment (SOFA) score [=2.22 × (SOFA score/12)^1.88] and the effluent flow rate from the CRRT device, with an interindividual variability of 44.5%. The volume of distribution was affected by the simplified acute physiology score II [=23.1 × (simplified acute physiology score II/52)^1.54]. Monte Carlo simulations suggested meropenem doses ranging from 1.0 to 3.0 g/d using continuous infusion to achieve a target time above the 4 times of minimum inhibitory concentration of the unbound form (%fT>4×MIC) of 100% for definitive therapy. For empirical therapy, a dose of 1.0 g/d using continuous infusion was recommended to target %fT>MIC of 100%. This study developed a popPK model for unbound meropenem in patients undergoing CRRT and formulated dosing guidelines. UMIN000024321.

Pooled Population Pharmacokinetic Analysis and Dose Recommendations for Ciprofloxacin in Intensive Care Unit Patients with Obesity.

Recent studies have explored the influence of obesity and critical illness on ciprofloxacin pharmacokinetics. However, variation across the subpopulation of individuals with obesity admitted to the intensive care unit (ICU) with varying renal function remains unexamined. This study aims to characterize ciprofloxacin pharmacokinetics in ICU patients with obesity and provide dose recommendations for this special population. Individual patient data of 34 ICU patients with obesity (BMI >30 kg/m2) from four studies evaluating ciprofloxacin pharmacokinetics in ICU patients were pooled and combined with data from a study involving 10 individuals with obesity undergoing bariatric surgery. All samples were collected after intravenous administration. Non-linear mixed effects modeling and simulation were used to develop a population pharmacokinetic model and describe ciprofloxacin exposure in plasma. Model-based dose evaluations were performed using a pharmacokinetic/pharmacodynamic target of AUC/MIC >125. The data from patients with BMI ranging from 30.2 to 58.1 were best described by a two-compartment model with first-order elimination and a proportional error model. The inclusion of Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) as a covariate on clearance reduced inter-individual variability from 57.3% to 38.5% (P <.001). Neither body weight nor ICU admission significantly influenced clearance or volume of distribution. Renal function is a viable predictor for ciprofloxacin clearance in ICU patients with obesity, while critical illness and body weight do not significantly alter clearance. As such, body weight and critical illness do not need to be accounted for when dosing ciprofloxacin in ICU patients with obesity. Individuals with CKD-EPI >60 mL/min/1.73 m2 may require higher dosages for the treatment of pathogens with minimal inhibitory concentration ≥0.25 mg/L.

Population pharmacokinetics, dosing optimization and clinical outcomes of biapenem in patients with sepsis

Introduction: Biapenem is a carbapenem antibiotic widely used in Asia, can be used for the treatment of adults and children with infections due to susceptible bacteria. Although biapenem is utilized in the treatment of a diverse range of bacterial infections, current pharmacokinetic data in the context of septic populations remain limited. Consequently, our research aims to evaluate the pharmacokinetics and efficacy of biapenem within a septic population to optimize biapenem therapy.Methods: In this study, we characterized the pharmacokinetics of biapenem in septic patients using a population pharmacokinetic (PPK) approach. The clinical PK data to develop the PPK model were obtained from 317 septic patients admitted to Nanjing Drum Tower Hospital between 2018 and 2022. All patients were randomized to the modeling and validation cohorts at a 3:1 ratio, with PPK modeling and validation performed utilizing the NONMEM software.Results: The model found to best describe the available data was a two-compartment PPK model with first-order elimination characterized by the parameters clearance (CL), central volume (V1), peripheral volume (V2), and intercompartmental clearance (Q). A covariate analysis identified that creatinine clearance (CLCR) was a significant covariate influencing biapenem CL, while blood urea nitrogen (BUN) was a significant covariate influencing biapenem Q. Accoding to the clinical outcome analyses, 70% of the time that the free antimicrobial drug concentration exceeds the MIC (fT&amp;gt;MIC) is associated with favourable clinical outcomes. The PPK model was then used to perform Monte Carlo simulations to evaluate the probability of attaining 70% fT&amp;gt;MIC.Conclusions: A final PPK model of biapenem was established for patients with sepsis. The current daily dosage regimen of 1.2 g may insufficient to achieve 70% fT&amp;gt;MIC in septic patients. The dosage regimen of 600 mg every 6 h appears to be the optimal choice.

Evaluation of Published Population Pharmacokinetic Models to Inform Tacrolimus Therapy in Adult Lung Transplant Recipients.

The applicability of currently available tacrolimus population pharmacokinetic models in guiding dosing for lung transplant recipients is unclear. In this study, the predictive performance of relevant tacrolimus population pharmacokinetic models was evaluated for adult lung transplant recipients. Data from 43 lung transplant recipients (1021 tacrolimus concentrations) administered an immediate-release oral formulation of tacrolimus were used to evaluate the predictive performance of 17 published population pharmacokinetic models for tacrolimus. Data were collected from immediately after transplantation up to 90 days after transplantation. Model performance was evaluated using (1) prediction-based assessments (bias and imprecision) of individual predicted tacrolimus concentrations at the fourth dosing based on 1 to 3 previous dosings and (2) simulation-based assessment (prediction-corrected visual predictive check; pcVPC). Both assessments were stratified based on concomitant azole antifungal use. Model performance was clinically acceptable if the bias was within ±20%, imprecision was ≤20%, and the 95% confidence interval of bias crossed zero. In the presence of concomitant antifungal therapy, no model showed acceptable performance in predicting tacrolimus concentrations at the fourth dosing (n = 33), and pcVPC plots displayed poor model fit to the data set. However, this fit slightly improved in the absence of azole antifungal use, where 4 models showed acceptable performance in predicting tacrolimus concentrations at the fourth dosing (n = 33). Although none of the evaluated models were appropriate in guiding tacrolimus dosing in lung transplant recipients receiving concomitant azole antifungal therapy, 4 of these models displayed potential applicability in guiding dosing in recipients not receiving concomitant azole antifungal therapy. However, further model refinement is required before the widespread implementation of such models in clinical practice.

Improving prediction of tacrolimus concentration using a combination of population pharmacokinetic modeling and machine learning in chinese renal transplant recipients

AimsThe population pharmacokinetic (PPK) model-based machine learning (ML) approach offers a novel perspective on individual concentration prediction. This study aimed to establish a PPK-based ML model for predicting tacrolimus (TAC) concentrations in Chinese renal transplant recipients.MethodsConventional TAC monitoring data from 127 Chinese renal transplant patients were divided into training (80%) and testing (20%) datasets. A PPK model was developed using the training group data. ML models were then established based on individual pharmacokinetic data derived from the PPK basic model. The prediction performances of the PPK-based ML model and Bayesian forecasting approach were compared using data from the test group.ResultsThe final PPK model, incorporating hematocrit and CYP3A5 genotypes as covariates, was successfully established. Individual predictions of TAC using the PPK basic model, postoperative date, CYP3A5 genotype, and hematocrit showed improved rankings in ML model construction. XGBoost, based on the TAC PPK, exhibited the best prediction performance.ConclusionThe PPK-based machine learning approach emerges as a superior option for predicting TAC concentrations in Chinese renal transplant recipients.

Population Pharmacokinetics and Limited Sampling Strategy of Mycophenolate Mofetil for Indian Patients with Lupus Nephritis

Background: Mycophenolic acid is widely used to treat lupus nephritis (LN). However, it exhibits complex pharmacokinetics with large interindividual variability. This study aimed to develop a population pharmacokinetic (popPK) model and a 3-sample limited sampling strategy (LSS) to optimize therapeutic drug monitoring in Indian patients with LN. Methods: Five blood samples from each LN patient treated with mycophenolic acid were collected at steady-state predose and 1, 2, 4, and 6 hours postdose. Demographic parameters were tested as covariates to explain interindividual variability. PopPK analysis was performed using Monolix and the stochastic approximation expectation-maximization algorithm. An LSS was derived from 500 simulated pharmacokinetic (PK) profiles using maximum a posteriori Bayesian estimation to estimate individual PK parameters and area under the curve (AUC). The LSS-calculated AUC was compared with the AUC calculated using the trapezoidal rule and all the simulated samples. Results: A total of 51 patients were included in this study. Based on the 245 mycophenolic acid concentrations, a 1-compartmental model with double absorption using gamma distributions best fitted the data. None of the covariates improved the model significantly. The model was internally validated using diagnostic plots, prediction-corrected visual predictive checks, and bootstrapping. The best LSS included samples at 1, 2, and 4 hours postdose and exhibited good performances in an external dataset (root mean squared error, 21.9%; mean bias, −4.20%). Conclusions: The popPK model developed in this study adequately estimated the PK of mycophenolic acid in adult Indian patients with LN. This simple LSS can optimize TDM based on the AUC in routine practice.

Anti-T-lymphocyte globulin exposure is associated with acute graft-versus-host disease and relapse in pediatric acute lymphoblastic leukemia patients undergoing hematopoietic stem cell transplantation: a multinational prospective study.

Anti T-lymphocyte globulin (ATLG) is used in hematopoietic stem cell transplantation (HSCT) to prevent graft-versus-host disease (GvHD) and graft failure. To date, insight in ATLG pharmacokinetics and -dynamics (PK/PD) is limited, and population PK (POPPK) models are lacking. In this prospective study, we describe ATLG POPPK using NONMEM® and the impact of ATLG exposure on clinical outcome and immune reconstitution in a homogeneous cohort of pediatric acute lymphoblastic leukemia (ALL) patients transplanted with a matched unrelated donor and receiving uniform ATLG dosing. Based on 121 patients and 812 samples for POPPK analysis, a two-compartmental model with parallel linear and non-linear clearance and bodyweight as covariate, best described the ATLG concentrationtime data. The level of ATLG exposure (day active ATLG day 16 8.2%, p.

Estimation of linezolid exposure in patients with hepatic impairment using machine learning based on a population pharmacokinetic model.

To investigate the pharmacokinetic changes of linezolid in patients with hepatic impairment and to explore a method to predict linezolid exposure. Patients withhepatic impairment who received linezolid were recruited. A population pharmacokinetic model (PPK) was then built using NONMEM software. And based on the final model, virtual patients with rich concentration values was constructed through Monte Carlo simulations (MCS), which were used to build machine learning (ML) models to predict linezolid exposure levels. Finally, we investigated the risk factors for thrombocytopenia in patients included. A PPK model with population typical values of 3.83 L/h and 34.1 L for clearance and volume of distribution was established, and the severe hepatic impairment was identified as a significant covariate of clearance. Then, we built a series of ML models to predict the area under 0-24h concentration-time curve (AUC0-24) of linezolid based on virtual patients from MCS. The results showed that the Xgboost models showed the best predictive performance and were superior to the methods for estimating linezolid AUC0-24 based on though concentration or daily dose. Finally, we found that baseline platelet count, linezolid AUC0-24, and combination with fluoroquinolones were independent risk factors for thrombocytopenia, and based on this, we proposed a method for calculating the toxicity threshold of linezolid. In this study, we successfully constructed a PPK model for patients with hepatic impairment and used ML algorithm to estimate linezolid AUC0-24 based on limited data. Finally, we provided a method to determine the toxicity threshold of linezolid.

Population pharmacokinetic modelling of primaquine exposures in lactating women and breastfed infants

Current guidelines advise against primaquine treatment for breastfeeding mothers to avoid the potential for haemolysis in infants with G6PD deficiency. To predict the haemolytic risk, the amount of drug received from the breast milk and the resulting infant drug exposure need to be characterised. Here, we develop a pharmacokinetic model to describe the drug concentrations in breastfeeding women using venous, capillary, and breast milk data. A mother-to-infant model is developed to mimic the infant feeding pattern and used to predict their drug exposures. Primaquine and carboxyprimaquine exposures in infants are <1% of the exposure in mothers. Therefore, even in infants with the most severe G6PD deficiency variants, it is highly unlikely that standard doses of primaquine (0.25-1 mg base/kg once daily given to the mother for 1-14 days) would cause significant haemolysis. After the neonatal period, primaquine should not be restricted for breastfeeding women (Clinical Trials Registration: NCT01780753).

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

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 thelowerlimit of quantification (BLQ) on the outcomes of EE for four population pharmacokinetic models using vancomycin and tobramycin as examples. 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. 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. 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.

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

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. 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. 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. 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. 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.

External validation of population pharmacokinetic models of tacrolimus in Thai adult liver transplant recipients.

Several population pharmacokinetic models of tacrolimus in liver transplant patients were built, and their predictability was evaluated in their settings. However, the extrapolation in the prediction was unclear. This study aimed to evaluate the predictive performance of published tacrolimus models in adult liver transplant recipients using data from the Thai population as an external dataset. The selected published models were systematically searched and evaluated for their quality. The external dataset of patients who underwent the first liver transplant and received immediate-release tacrolimus was used to assess the predictive performance of each selected model. Trough concentrations between 3 and 6months were retrospectively collected to evaluate the predictability of each model using prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. Sixty-seven patients with 360 trough concentrations and eight selected published models were included in this study. None of the models met the predictive precision criteria in prediction-based diagnostics. Meanwhile, four published population pharmacokinetic models showed a normal distribution in NPDE testing. Regarding Bayesian forecasting, all models improved their forecasts with at least one prior information data point. Bayesian forecasting is more accurate and precise than other testing methods for predicting drug concentrations. However, none of the evaluated models provides satisfactory predictive performance for generalization to Thai liver transplant patients. This underscores the need for future research to develop population PK models tailored to the Thai population. Such efforts should consider the inclusion of nonlinear pharmacokinetics and region-specific factors, including genetic variability, to improve model accuracy and applicability.

Population pharmacokinetic modelling and simulation of tranexamic acid in adult trauma patients.

The aim of this study is to describe the disposition of tranexamic acid (TXA) in adult trauma patients and derive a dosing regimen that optimizes exposure based on a predefined exposure target. We performed a population pharmacokinetic (popPK) analysis of participants enrolled in the Tranexamic Acid Mechanisms and Pharmacokinetics in Traumatic Injury (TAMPITI) trial (≥18 years with traumatic injury, given ≥1 blood product and/or requiring immediate transfer to the operating room) who were randomized to a single dose of either 2 or 4g of TXA ≤2h from time of injury. PopPK analysis was conducted using nonlinear mixed-effects modelling (NONMEM). Simulations were then performed using the final model to generate estimated plasma TXA concentrations in 1000 simulated participants. Dosing schemes were evaluated to determine maintenance of TXA plasma concentrations >10mg/L for ≥8h after administration of the initial dose. TXA PK was best described by a two-compartment model with proportional residual error and allometric scaling on all parameters. Platelet count, skeletal muscle oxygen saturation measured by near-infrared spectroscopy and interleukin-8 concentration were significant covariates on TXA clearance. Based on simulations, a 2g IV bolus dose, repeated 3h later, best achieved the target exposure. According to simulations from a popPK model of TXA, a 2g IV bolus with a repeated dose 3h later would be most likely to maintain concentrations >10mg/L for 8h in >95% of adult trauma patients and should be considered for patients with ongoing haemorrhage.

Population pharmacokinetics of intravenous daptomycin in critically ill patients: implications for selection of dosage regimens.

Daptomycin is gaining prominence for the treatment of methicillin-resistant Staphylococcus aureus infections. However, the dosage selection for daptomycin in critically ill patients remains uncertain, especially in Chinese patients. This study aimed to establish the population pharmacokinetics of daptomycin in critically ill patients, optimize clinical administration plans, and recommend appropriate dosage for critically ill patients in China. The study included 64 critically ill patients. Blood samples were collected at the designated times. The blood daptomycin concentration was determined using validated liquid chromatography-tandem mass spectrometry. A nonlinear mixed-effects model was applied for the population pharmacokinetic analysis and Monte Carlo simulations of daptomycin. The results showed a two-compartment population pharmacokinetic model of daptomycin in critically ill adult Han Chinese patients. Monte Carlo simulations revealed that a daily dose of 400mg of daptomycin was insufficient for the majority of critically ill adult patients to achieve the anti-infective target. For critically ill adult patients with normal renal function (creatinine clearance rate >90mL/min), the probability of achieving the target only reached 90% when the daily dose was increased to 700mg. For patients undergoing continuous renal replacement therapy (CRRT), 24h administration of 500mg met the pharmacodynamic goals and did not exceed the safety threshold in most patients. Therefore, considering its efficacy and safety, intravenous daptomycin doses are best scaled according to creatinine clearance, and an increased dose is recommended for critically ill patients with hyperrenalism. For patients receiving CRRT, medication is recommended at 24h intervals.

CYP2D6 Phenotype Influences Pharmacokinetic Parameters of Venlafaxine: Results from a Population Pharmacokinetic Model in Older Adults with Depression.

In this study, we aimed to improve upon a published population pharmacokinetic (PK) model for venlafaxine (VEN) in the treatment of depression in older adults, then investigate whether CYP2D6 metabolizer status affected model-estimated PK parameters of VEN and its active metabolite O-desmethylvenlafaxine. The model included 325 participants from a clinical trial in which older adults with depression were treated with open-label VEN (maximum 300 mg/day) for 12 weeks and plasma levels of VEN and O-desmethylvenlafaxine were assessed at weeks 4 and 12. We fitted a nonlinear mixed-effect PK model using NONMEM to estimate PK parameters for VEN and O-desmethylvenlafaxine adjusted for CYP2D6 metabolizer status and age. At both lower doses (up to 150 mg/day) and higher doses (up to 300 mg/day), CYP2D6 metabolizers impacted PK model-estimated VEN clearance, VEN exposure, and active moiety (VEN + O-desmethylvenlafaxine) exposure. Specifically, compared with CYP2D6 normal metabolizers, (i) CYP2D6 ultra-rapid metabolizers had higher VEN clearance; (ii) CYP2D6 intermediate metabolizers had lower VEN clearance; (iii) CYP2D6 poor metabolizers had lower VEN clearance, higher VEN exposure, and higher active moiety exposure. Overall, our study showed that including a pharmacogenetic factor in a population PK model could increase model fit, and this improved model demonstrated how CYP2D6 metabolizer status affected VEN-related PK parameters, highlighting the importance of genetic factors in personalized medicine.

The Impact of Spironolactone Co-administration on Cyclosporin Initial Dosage Optimization for Pediatric Refractory Nephrotic Syndrome.

Cyclosporin has been used for the treatment of pediatric refractory nephrotic syndrome (PRNS). However, the narrow therapeutic window and large pharmacokinetic variability make it difficult to individualize cyclosporin administration. Meanwhile, spironolactone has been reported to affect cyclosporin metabolism in PRNS patients. This study aims to explore the initial dosage optimization of cyclosporin in PRNS based on the impact of spironolactone co-administration. Monte Carlo simulation based on a previously established cyclosporin population pharmacokinetic model for PRNS was used to design cyclosporin dosing regimen. In this study, the probability of drug concentration reaching the target and the convenience of times of administration were considered comprehensively. The optimal administration regimen in PRNS without spironolactone was 6, 5, 4 and 3 mg/kg cyclosporin split into two doses for the body weight of 5-8, 8-18, 18-46 and 46-70 kg, respectively. The optimal administration regimen in PRNS with spironolactone was 4, 3, 2 mg/kg cyclosporin split into two doses for body weight of 5-14, 14-65, and 65-70 kg, respectively. The cyclosporin dosing regimen for PRNS based on Monte Carlo simulation was systematically developed and the initial dosage optimization of cyclosporin in PRNS was recommended for the first time.

Pharmacokinetics, Pharmacodynamics, and Anti-Nociceptive Effects of Buprenorphine Following Transdermal Administration to Horses

ObjectiveThis study describes the pharmacokinetics and pharmacodynamics, including antinociceptive effects, of a transdermal buprenorphine solution in horses. It was hypothesized that transdermal application would lead to sustained blood concentrations and antinociceptive effects with fewer adverse effects compared to intravenous (IV) injection. Study DesignProspective non-randomized 4-part parallel experimental study. AnimalsEight horses, three mares and five geldings, aged 6 to 12 years. MethodsHorses were given incremental doses of 15, 30, and 45 μg kg-1 buprenorphine transdermal solution and a single IV dose of 5 μg kg-1 buprenorphine with a two week washout period between treatments. Concentrations of buprenorphine were determined in plasma using liquid chromatography-tandem mass spectrometry and modeled using a nonlinear mixed effects population pharmacokinetic model to determine pharmacokinetic parameters. Pharmacodynamic effects, including changes in locomotor activity, heart rate, body temperature, gastrointestinal borborygmi, thermal and mechanical nociceptive thresholds were recorded. Mixed effects analysis of variance and post hoc comparisons were performed using a Bonferroni multiple comparison adjustment to assess differences in pharmacodynamic parameters between baseline and each time point within each dose group and between dose groups at the same time point. ResultsTransdermal application of buprenorphine resulted in low systemic concentrations relative to IV injection. Bioavailability following transdermal application was 11%. Thermal nociceptive thresholds were significantly (p < 0.05) increased (4.3–10.7% relative to baseline) for up to 72 hours in the IV dose group, but only sporadically in the transdermal dose groups (2.5–9.9% relative to baseline). Changes in locomotor activity, heart rate and borborygmi varied over time and with dose. Conclusions and Clinical RelevanceLimited thermal antinociceptive effects were observed at the transdermal doses studied likely due to limited absorption relative to IV dosing. Future studies may be directed toward investigating antinociceptive effects of higher transdermal doses and different application sites.

Population pharmacokinetics of butorphanol following intramuscular administration to exercised thoroughbred horses.

Butorphanol is commonly administered, both by the intravenous and intramuscular routes, to racehorses to facilitate handling for diagnostic procedures. As the administration of butorphanol for therapeutic purposes is considered appropriate, in order to avoid inadvertent positive drug tests, a thorough understanding of the pharmacokinetics of this drug is necessary. In the current study, 12, exercised Thoroughbred horses were administered a single intramuscular dose of 0.1 mg/kg butorphanol, and serum and urine samples were collected at various times post drug administration for determination of butorphanol concentrations using a highly sensitive liquid chromatography tandem mass spectrometry method. Serum data were modeled using a nonlinear mixed effect population PK model. The maximum concentration (Cmax) and time to maximum concentration (Tmax) were 139.9 ± 72.8 ng/mL and 0.43 ± 0.44 h (mean ± SD), respectively. Although likely not clinically relevant, but important for drug testing purposes, a prolonged terminal phase was observed, yielding a terminal half-life of 7.67 ± 1.86 h. Using the blood screening limits proposed by the Horseracing Integrity and Welfare Unit, the detection time for intramuscular administration of butorphanol was estimated to be 96 h.