Published Pharmacokinetic Model Research Articles

Interpreting hydroxychloroquine blood levels for medication non-adherence: a pharmacokinetic study

ObjectiveCharacterise the relationship between hydroxychloroquine (HCQ) blood levels and the number of missed doses, accounting for dosage, dose timing and the large variability in pharmacokinetics (PK) between patients.MethodsWe externally validated...

Evaluation of model-based bioequivalence approach for single sample pharmacokinetic studies.

In a traditional pharmacokinetic (PK) bioequivalence (BE) study, a two-way crossover study is conducted, PK parameters (namely the area under the time-concentration curve [AUC] and the maximal concentration [ ]) are obtained by noncompartmental analysis (NCA), and the BE analysis is performed using the two one-sided test (TOST) method. For ophthalmic drugs, however, only one sample of aqueous humor, in one eye, per eye can be obtained in each patient, which precludes the traditional BE analysis. To circumvent this issue, the U.S. Food and Drug Administration (FDA) has proposed an approach coupling NCA with either parametric or nonparametric bootstrap (NCA bootstrap). The model-based TOST (MB-TOST) has previously been proposed and evaluated successfully for various settings of sparse PK BE studies. In this paper, we evaluate, via simulations, MB-TOST in the specific setting of single sample PK BE study and compare its performance to NCA bootstrap. We performed BE study simulations using a published PK model and parameter values and evaluated multiple scenarios, including study design (parallel or crossover), sampling times (5 or 10 spread across the dosing interval), and geometric mean ratio (of 0.8, 0.9, 1, and 1.25). Using the simulated structural PK model, MB-TOST performed similarly to NCA bootstrap for AUC. For , the latter tended to be conservative and less powerful. Our research suggests that MB-TOST may be considered as an alternative BE approach for single sample PK studies, provided that the PK model is correctly specified and the test drug has the same structural model as the reference drug.

Optimal dosing of enoxaparin in overweight and obese children.

Current enoxaparin dosing guidelines in children are based on total body weight. This is potentially inappropriate in obese children as it may overestimate the drug clearance. Current evidence suggests that obese children may require lower initial doses of enoxaparin, therefore the aim of this work was to characterise the pharmacokinetics of enoxaparin in obese children and to propose a more appropriate dosing regimen. Data from 196 unique encounters of 160 children who received enoxaparin treatment doses were analysed. Enoxaparin concentration was quantified using the chromogenic anti factor Xa (anti-Xa) assay. Patients provided a total of 552 anti-Xa samples. Existing published pharmacokinetic (PK) models were fitted and evaluated against our dataset using prediction-corrected visual predictive check plots (pcVPCs). A PK model was fitted using a nonlinear mixed-effects modelling approach. The fitted model was used to evaluate the current standard dosing and identify an optimal dosing regimen for obese children. Published models of enoxaparin pharmacokinetics in children did not capture the pharmacokinetics of enoxaparin in obese children as shown by pcVPCs. A one-compartment model with linear elimination best described the pharmacokinetics of enoxaparin. Allometrically scaled fat-free mass with an estimated exponent of 0.712 (CI 0.66-0.76) was the most influential covariate on clearance while linear fat-free mass was selected as the covariate on volume. Simulations from the model showed that fat-free mass-based dosing could achieve the target anti-Xa activity at steady state in 77.5% and 78.2% of obese and normal-weight children, respectively, compared to 65.2% and 75.5% for standard total body weight-based dosing. A population PK model that describes the time course of anti-Xa activity of enoxaparin was developed in a paediatric population. Based on this model, a unified dosing regimen was proposed that will potentially improve the success rate of target attainment in overweight/obese patients without the need for patient body size categorisation. Therefore, prospective validation of the proposed approach is warranted.

Pharmacokinetic Model Based on Stochastic Simulation and Estimation for Therapeutic Drug Monitoring of Tacrolimus in Korean Adult Transplant Recipients.

Tacrolimus shows high variability in inter- and intraindividual pharmacokinetics (PK); therefore, it is important to develop an appropriate model for accurate therapeutic drug monitoring (TDM) procedures. This study aimed to develop a pharmacokinetic model for tacrolimus that can be used for TDM procedures in Korean adult transplant recipients by integrating published models with acquired real-world TDM data and evaluating clinically meaningful covariates. Clinical data of 1829 trough blood samples from 269 subjects were merged with simulated data sets from published models and analyzed using a nonlinear mixed-effect model. The stochastic simulation and estimation (SSE) method was used to obtain the final parameter estimates. The final estimated values for apparent clearance, the volume of distribution, and absorption rate were 21.2 L/h, 510 L, and 3.1/h, respectively. The number of postoperative days, age, body weight, and type of transplant organs were the major clinical factors affecting tacrolimus PK. A tacrolimus PK model that can incorporate published PK models and newly collected data from the Korean population was developed using the SSE method. Despite the limitations in model development owing to the nature of TDM data, the SSE method was useful in retrieving complete information from the TDM data by integrating published PK models while maintaining the variability of the model.

Pharmacokinetics of apixaban in patients with end stage renal disease on hemodialysis and atrial fibrillation: results from the RENAL-AF trial

Abstract Background/Introduction Apixaban use is increasing for stroke prevention in patients with atrial fibrillation (AF) and end stage renal disease (ESRD) on hemodialysis. There is uncertainty as to the optimal dose in this population in part related to the limited available pharmacokinetic (PK) data. Purpose We comprehensively evaluated the PK of apixaban collected over 1 month of apixaban dosing in 63 patients with AF and ESRD on hemodialysis. Methods Patients with AF and ESRD on hemodialysis were randomized to warfarin versus apixaban within the RENAL-AF trial with 5 mg BID dosing, except for 2.5 mg BID in those age ≥80 years or weight ≤60 kg. The 5 mg BID dose could be reduced to 2.5mg BID for minor bleeding. Day 1 PK data was collected on all patients pre- and post-hemodialysis. Day 3 and 1 month pre- and post-hemodialysis PK samples were collected in 49 patients. The timing of apixaban dosing and hemodialysis relative to PK samples was recorded. Dosing history, hemodialysis, and PK samples were chronologically integrated with patient specific data such as body size, age, race and gender. This dataset was combined with the ARISTOTLE dataset, and the published PK model from ARISTOTLE describing exposures in the AF population was updated to incorporate an additional clearance term for hemodialysis. The model estimated apixaban exposures (AUC) in RENAL-AF were compared to ARISTOLTE AUC values. Results There were 285 PK concentrations collected among 63 patients in the RENAL-AF trial. Patients had median age 69 years with 41% women (N=26) and a median weight of 84 kg (49, 157). The median AUCs for patients with ESRD on hemodialysis were 5,452 and 2,990 for patients treated with 5mg BID and 2.5mg BID doses, respectively. The median AUCs for patients treated with 5mg BID from ARISTOTLE increased from 2,802 for patients with class 1 CKD to 5,863 for class 4 CKD, while they increased from 2,392 for class 1 CKD to 2,881 for class 4 CKD in patients treated with 2.5mg BID. The median AUC for patients with ESRD on hemodialysis were within 50% of the exposure of patients from ARISTOTLE for all classes of CKD for the 2.5mg BID dose and for classes 2, 3A, 3B, and 4 CKD for the 5mg BID dose (Figure). Conclusions The steady state apixaban exposure data in patients with AF and ESRD on hemodialysis were modestly higher but consistent with the results of non-ESRD patients from ARISTOTLE, using 5 mg BID unless patients had age ≥80 years or weight ≤60 kg. Additional clinical outcomes data on the use of apixaban in patients with AF and ESRD on hemodialysis are needed. Funding Acknowledgement Type of funding source: Private grant(s) and/or Sponsorship. Main funding source(s): Investigator sponsored grant from Bristol-Myers Squibb and Pfizer

Optimizing clonidine dosage for sedation in mechanically ventilated children: A pharmacokinetic simulation study.

Clonidine is in widespread off-label use as a sedative in mechanically ventilated children, despite limited evidence of efficacy. A variety of dosage regimens have been utilized in clinical practice and in research studies. Within these studies, clonidine has inconsistently shown useful sedation properties. One of the reasons attributed to the inconsistent signs of efficacy is suboptimal clonidine dosing. This study aims to propose a target plasma concentration and simulate clonidine pharmacokinetics (PK) in a cohort of mechanically ventilated children to evaluate the adequacy of clonidine dosage regimens used in clinical practice and research studies. A literature search was undertaken to identify a clonidinepharmaockinetic-pharmacodynamics (PKPD)model, from which a target concentration for sedation was defined. Using a previously published PK model, the projected plasma concentrations of 692 mechanically ventilated children (demographics taken from a recent study) were generated. Doses from recently published clinical studies were investigated. Adequacy of each regimen to attain therapeutic clonidine plasma concentrations was assessed. A target plasma concentration of above 2µg/L was proposed. Nine dosage regimens (four intravenous boluses, four intravenous infusions, and one nasogastric route boluses) were evaluated ranging from 1µg/kg eight hourly intravenous boluses to a regimen up to 3µg/kg/hr continuous intravenous infusion. Regimens with a loading dose of 2µg/kg followed by variable continuous infusion of up to 2µg/kg/hr titrated according to sedation score appear most suitable. Doses should be halved in neonates. The variety of dosage regimens in the previous studies of clonidine along with difficulties in the conduct of interventional studies may have contributed to the lack of efficacy data to support its use. Simulations of clonidine plasma concentrations based on known population pharmacokinetic parameters suggest a loading dose followed by higher than current practice maintenance dose infusion is required to achieve adequate steady-state concentrations early in treatment. Further PKPD studies will aid in the determination of the optimal clonidine dosage regimen.

Pulmonary Pharmacokinetics of Colistin following Administration of Dry Powder Aerosols in Rats.

Colistin has been administered via nebulization for the treatment of respiratory tract infections. Recently, dry powder inhalation (DPI) has attracted increasing attention. The current study aimed to investigate the pharmacokinetics (PK) of colistin in epithelial lining fluid (ELF) and plasma following DPI and intravenous (i.v.) administration in healthy Sprague-Dawley rats. Rats were given colistin as DPI intratracheally (0.66 and 1.32 mg base/kg of body weight) or i.v. injection (0.66 mg base/kg). Histopathological examination of lung tissue was performed at 24 h. Colistin concentrations in both ELF and plasma were quantified, and a population PK model was developed and compared to a previously published PK model of nebulized colistin in rats. A two-compartment structural model was developed to describe the PK of colistin in both ELF and plasma following pulmonary or i.v. administration. The model-estimated clearance from the central plasma compartment was 0.271 liter/h/kg (standard error [SE] = 2.51%). The transfer of colistin from the ELF compartment to the plasma compartment was best described by a first-order rate constant (clearance of colistin from the ELF compartment to the plasma compartment = 4.03 × 10-4 liter/h/kg, SE = 15%). DPI appeared to have a higher rate of absorption (time to the maximum concentration in plasma after administration of colistin by DPI, ≤10 min) than nebulization (time to the maximum concentration in plasma after administration of colistin by nebulization, 20 to 30 min), but the systemic bioavailabilities by the two routes of administration were similar (∼46.5%, SE = 8.43%). Histopathological examination revealed no significant differences in inflammation in lung tissues between the two treatments. Our findings suggest that colistin DPI is a promising alternative to nebulization considering the similar PK and safety profiles of the two forms of administration. The PK and histopathological information obtained is critical for the development of optimal aerosolized colistin regimens with activity against lung infections caused by Gram-negative bacteria.

Estimating uptake of phthalate ester metabolites into the human nail plate using pharmacokinetic modelling

There is a lack of knowledge regarding uptake of phthalate esters (PEs) and other chemicals into the human nail plate and thus, clarity concerning the suitability of human nails as a valid alternative matrix for monitoring long-term exposure. In particular, the relative importance of internal uptake of phthalate metabolites (from e.g. blood) compared to external uptake pathways is unknown. This study provides first insights into the partitioning of phthalate-metabolites between blood and nail using pharmacokinetic (PK) modelling and biomonitoring data from a Norwegian cohort. A previously published PK model (Lorber PK model) was used in combination with measured urine data to predict serum concentrations of DEHP and DnBP/DiBP metabolites at steady state. Then, partitioning between blood and nail was assessed assuming equilibrium conditions and treating the nail plate as a tissue, assuming a fixed lipid and water content. Although calculated as a worst-case scenario at equilibrium, the predicted nail concentrations of metabolites were lower than the biomonitoring data by factors of 44 to 1300 depending on the metabolite. It is therefore concluded that internal uptake of phthalate metabolites from blood into nail is a negligible pathway and does not explain the observed nail concentrations. Instead, external uptake pathways are more likely to dominate, possibly through deposition of phthalates onto the skin/nail and subsequent metabolism. Modelling gaseous diffusive uptake of PEs from air to nail revealed that this pathway is unlikely to be important. Experimental quantification of internal and external uptake pathways of phthalates and their metabolites into the human nail plate is needed to verify these modelling results. However, based on this model, human nails are not a good indicator of internal human exposure for the phthalate esters studied.

Excel-Based Tool for Pharmacokinetically Guided Dose Adjustment of Paclitaxel.

Neutropenia is a frequent and severe adverse event in patients receiving paclitaxel chemotherapy. The time above a paclitaxel threshold concentration of 0.05 μmol/L (Tc > 0.05 μmol/L) is a strong predictor for paclitaxel-associated neutropenia and has been proposed as a target pharmacokinetic (PK) parameter for paclitaxel therapeutic drug monitoring and dose adaptation. Up to now, individual Tc > 0.05 μmol/L values are estimated based on a published PK model of paclitaxel by using the software NONMEM. Because many clinicians are not familiar with the use of NONMEM, an Excel-based dosing tool was developed to allow calculation of paclitaxel Tc > 0.05 μmol/L and give clinicians an easy-to-use tool. Population PK parameters of paclitaxel were taken from a published PK model. An Alglib VBA code was implemented in Excel 2007 to compute differential equations for the paclitaxel PK model. Maximum a posteriori Bayesian estimates of the PK parameters were determined with the Excel Solver using individual drug concentrations. Concentrations from 250 patients were simulated receiving 1 cycle of paclitaxel chemotherapy. Predictions of paclitaxel Tc > 0.05 μmol/L as calculated by the Excel tool were compared with NONMEM, whereby maximum a posteriori Bayesian estimates were obtained using the POSTHOC function. There was a good concordance and comparable predictive performance between Excel and NONMEM regarding predicted paclitaxel plasma concentrations and Tc > 0.05 μmol/L values. Tc > 0.05 μmol/L had a maximum bias of 3% and an error on precision of <12%. The median relative deviation of the estimated Tc > 0.05 μmol/L values between both programs was 1%. The Excel-based tool can estimate the time above a paclitaxel threshold concentration of 0.05 μmol/L with acceptable accuracy and precision. The presented Excel tool allows reliable calculation of paclitaxel Tc > 0.05 μmol/L and thus allows target concentration intervention to improve the benefit-risk ratio of the drug. The easy use facilitates therapeutic drug monitoring in clinical routine.

Integrated semi‐physiological pharmacokinetic model for both sunitinib and its active metabolite SU12662

Previously published pharmacokinetic (PK) models for sunitinib and its active metabolite SU12662 were based on a limited dataset or lacked important elements such as correlations between sunitinib and its metabolite. The current study aimed to develop an improved PK model that circumvented these limitations and to prove the utility of the PK model in treatment optimization in clinical practice. One thousand two hundred and five plasma samples from 70 cancer patients were collected from three PK studies with sunitinib and SU12662. A semi-physiological PK model for sunitinib and SU12662 was developed incorporating pre-systemic metabolism using non-linear mixed effects modelling (nonmem). Allometric scaling based on body weight was applied. The final model was used for simulation of the PK of different treatment regimens. Sunitinib and SU12662 PK were best described by a one and two compartment model, respectively. Introduction of pre-systemic formation of SU12662 strongly improved model fit, compared with solely systemic metabolism. The clearance of sunitinib and SU12662 was estimated at 35.7 (relative standard error (RSE) 5.7%) l h(-1) and 17.1 (RSE 7.4%) l h(-1), respectively for 70 kg patients. Correlation coefficients were estimated between inter-individual variability of both clearances, both volumes of distribution and between clearance and volume of distribution of SU12662 as 0.53, 0.48 and 0.45, respectively. Simulation of the PK model predicted correctly the ratio of patients who did not reach proposed PK targets for efficacy. A semi-physiological PK model for sunitinib and SU12662 in cancer patients was presented including pre-systemic metabolism. The model was superior to previous PK models in many aspects.

Concentration–effect relationships with perampanel in patients with pharmacoresistant partial‐onset seizures

Although there is a general paucity of published pharmacokinetic (PK) data for new antiepileptic drugs (AEDs), PK analyses of pooled data from clinical studies of perampanel have recently been presented. We present PK/pharmacodynamic (PD) analyses of pooled data from phase III studies of perampanel describing efficacy and safety as a function of exposure, in order to determine whether a predictable concentration-effect relationship exists for perampanel efficacy and/or adverse events (AEs). The effects of concomitant enzyme-inducing AEDs (EIAEDs) and non-enzyme-inducing AEDs on the exposure, efficacy, and safety of perampanel are also considered. Three multicenter, randomized, double-blind, placebo-controlled phase III studies investigated the efficacy and safety of perampanel 2-12 mg in patients with uncontrolled partial-onset seizures despite prior therapy with two or more AEDs. From baseline onward, patients also received ongoing treatment with stable doses of one to three approved concomitant AEDs. AEs were monitored throughout the studies. Changes from baseline in seizure frequency and 50% responder rates were evaluated. Exposure to perampanel was predicted based on the actual (last) dose using a previously established PK model. A population PK/PD model for the relationship between perampanel exposure and seizure frequency was estimated using nonlinear mixed-effect modeling with first-order conditional estimation, whereas logistic analyses for responder rate and AEs were performed using SAS analysis software. The PK/PD population included 1,109 patients. Seizure frequency decreased linearly as predicted perampanel average steady-state plasma concentrations increased. Concomitant EIAEDs (carbamazepine, oxcarbazepine, and phenytoin) reduced exposure to perampanel but had no effect on the slope of the PD model-predicted relationship between exposure and reduction in seizure frequency. The probability of patients achieving a response was predicted to increase as perampanel average plasma concentration at steady state increased. No demographic, AED, region, or study covariate had any effect on the probability of achieving a positive treatment response to perampanel or on the slope of the exposure-response curve. Across the phase III studies, there were reports of dizziness (32.9%), somnolence (21.7%), fatigue (13.9%), irritability (12.3%), gait disturbance (9.1%), weight increase (6.1%), dysarthria (4.5%), and euphoric mood (0.5%); the model-predicted probability of these AEs increased significantly at higher exposure to perampanel (all p < 0.001). There was no effect of demographic variables or region on the probability of experiencing any of the AEs analyzed. PK and PD analyses have played a pivotal role in the clinical development of perampanel as an adjunctive treatment for pharmacoresistant partial-onset seizures. Phase III data suggest that a significant relationship exists between increases in perampanel plasma concentration (i.e., systemic exposure) and reductions in seizure frequency. In addition, increases in perampanel plasma concentration may potentially be associated with increases in AE rates. The model-predicted concentration-safety profile of perampanel does not appear to be affected by patient age, gender, or ethnicity. Although concomitant EIAEDs may influence perampanel PK, they do not appear to alter the relationship between perampanel plasma concentration and seizure frequency. Understanding these relationships between perampanel plasma concentration and clinical response will be valuable in utilizing this novel AED.