Estimation Of Individual Pharmacokinetic Parameters Research Articles

Impacts of age and BMI on vancomycin model choice in a Bayesian software: Lessons from a very large multi-site retrospective study.

Model-informed precision dosing (MIPD) optimizes drug doses based on pharmacokinetic (PK) model predictions, necessitating careful selection of models tailored to patient characteristics. This study evaluates the predictive performance of various vancomycin PK models across diverse age and BMI categories, drawing insights from a large multi-site database. Adults receiving vancomycin intravenous therapy at United States health systems between January 1, 2022, and December 31, 2023, were included. Patient demographics, vancomycin administration records, and therapeutic drug monitoring levels (TDMs) were collected from the InsightRX database. Age and body mass index (BMI)-based subgroups were formed to assess model performance, with predictions made iteratively. The optimal model for each age-BMI subgroup was chosen based on predefined criteria: models were filtered for mean percentage error (MPE) ≤ 20% and normalized root mean squared error (RMSE) < 8 mg/L, and then the most accurate among them was selected. A total of 384,876 treatment courses across 155 US health systems were analyzed, contributing 841,604 TDMs. Eleven models were compared, showing varying accuracy across age-BMI categories (41%-73%), with higher accuracy observed once TDMs were available for Bayesian estimates of individual PK parameters. Models performed more poorly in younger adults compared to older adults, and the optimal model differed depending on age-BMI categories and prediction methods. Notably, in the a priori period, the Colin model performed best in adults aged 18-64 years across most BMI categories; the Goti/Tong model performed best in the older, non-obese adults; and the Hughes model performed best in many of the obese categories. Our study identifies specific vancomycin PK models that demonstrate superior predictions across age-BMI categories in MIPD applications. Our findings underscore the importance of tailored model selection for vancomycin management, especially highlighting the need for improved models in younger adult patients. Further research into the clinical implications of model performance is warranted to enhance patient care outcomes.

Standardization and validation of a novel UPLC-MS/MS method to quantify first line anti-tuberculosis drugs in plasma and dried blood spots

Tuberculosis (TB) is a high-burden infectious disease with high prevalence and mortality rates. The first-line anti-TB drugs include isoniazid (INH), rifampicin (RMP), pyrazinamide (PZA), and ethambutol (EMB). At present, the standard method of blood sampling for therapeutic drug monitoring (TDM) analysis is venipuncture. Dried blood spots (DBS) are a minimally invasive method for collecting small quantities of whole blood from fingertips. The aim of the current study was to develop an ultrahigh-performance liquid chromatography technique coupled to tandem mass spectrometry (UPLC-MS/MS) for simultaneous quantification of the first-line anti-TB drugs in human plasma and DBS as a sampling alternative. The separation and detection conditions were optimized to quantify INH, RMP, PZA, and EMB in both matrices in an ACQUITY UPLC H Class system coupled to a XEVO TQD detector. Chromatographic separation was performed through an Acquity HSS T3 column (2.1 × 100 mm, 1.8 μm) with 0.1% formic acid in water and acetonitrile as the mobile phase. The total run time was 7 min for both methods, with retention time in plasma of 0.85, 1.22, 3.16, and 4.04 min and 0.74, 0.87, 0.97, and 4.16 min for EMB, INH, PZA, and RMP in DBS, respectively. The bioanalytical methods developed were proved selective, linear, precise, and accurate (inter- and intra-assay); the matrix effect was demonstrated to be within the established limits. Short- and long-term stability, freeze–thaw cycles for plasma, and short-term stability for DBS were established. A total of 15 patients with 46 ± 17 (mean ± SD) years old were included, and anti-TB drug concentrations were quantified on plasma and DBS as proof of concept. Based on RMP and INH plasma concentrations (Cp), and Bayesian estimation of individual pharmacokinetic parameters, a dose adjustment was necessary for 93% of patients. The slopes of the correlation lines between plasma and DBS concentrations of RMP, EMB, INH, and PZA were 0.5321, 0.8125, 0.5680, and 0.6791, respectively. Finally, significant correlations (p < 0.05) were observed between DBS and plasma concentrations for RMP (r2 = 0.6961), EMB (r2 = 0.4369), INH (r2 = 0.8675) and PZA (r2 = 0.7363). A simple, fast, and reliable UPLC-MS/MS method was developed to quantify first-line anti-TB drugs in plasma and DBS, which provides an easy sampling and storage to be applied as a new strategy for TDM in patients with TB.

Population Pharmacokinetic and Pharmacodynamic Analysis of Polmacoxib in Healthy Volunteers and Patients With Osteoarthritis

PurposePolmacoxib, a new coxib dually inhibiting cyclooxygenase-2 and carbonic anhydrase I/II, was recently approved for osteoarthritis treatment in South Korea. This study explored the population pharmacokinetic and pharmacodynamic characteristics of polmacoxib. MethodsNonlinear mixed-effects modeling was performed using pooled pharmacokinetic data from a Phase I study in healthy individuals and pharmacokinetic properties and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) data from a Phase IIb study in patients with osteoarthritis. Pharmacodynamic models for WOMAC were sequentially fit using individual pharmacokinetic parameter estimates. FindingsPolmacoxib concentrations in whole blood were adequately described by the 2-compartment model, with mixed zero- and first-order absorption kinetics. Iron concentration was the significant covariate associated with clearance of polmacoxib. The relationship between the whole blood concentration of polmacoxib and WOMAC was best described by a 2-effect compartment model that consisted of central and peripheral compartments with the rate constant of 0.408 min−1 for distribution to the central effect compartment. A decrease in WOMAC was linked to the central effect site compartment concentration through an ordinary maximum effect model with an effect site concentration needed to achieve 50% of the maximum effect of 508 ng/mL. ImplicationsThe current model accurately characterized the pharmacokinetic and pharmacodynamic properties of polmacoxib and could provide a basis for individualized drug therapy.

Bayesian estimation of pharmacokinetic parameters: an important component to include in the teaching of clinical pharmacokinetics and therapeutic drug monitoring.

Bayesian estimation of pharmacokinetic parameters (PKP), as discussed in this review, provides a powerful approach towards the individualization of dosing regimens. The method was first described by Lewis Sheiner and colleagues and it is well suited in clinical environs where few blood fluid measures of drugs are available in the clinic. This makes it a valuable tool in the effective implementation of therapeutic drug monitoring. The principle behind the method is Bayes theorem, which incorporates elements of variability in a priori-known population estimates and variability in the pharmacokinetic parameters, and known errors intrinsic to the assay method used to estimate the blood fluid drug concentrations. This manuscript reviews the Bayesian method. The literature was scanned using Pubmed to provide background into the Bayesian method. An Add-in for Excel program was used to show the ability of the method to estimate PKP using sparse blood fluid concentration vs time data. Using a computer program, the method was able to find reasonable estimates of individual pharmacokinetic parameters, assessed by comparing the estimated data to the true PKP. Education of students in clinical pharmacokinetics is incomplete without some mention and instruction of the Bayesian forecasting method. For a complete understanding, a computer program is needed to demonstrate its utility.

Vancomycin volume of distribution estimation in adults with class III obesity

To compare methods of estimating vancomycin volume of distribution (V) in adults with class III obesity. A retrospective, multicenter pharmacokinetic analysis of adults treated with vancomycin and monitored through measurement of peak and trough concentrations was performed. Individual pharmacokinetic parameter estimates were obtained via maximum a posteriori Bayesian analysis. The relationship between V and body weight was assessed using linear regression. Mean bias and root-mean-square error (RMSE) were calculated to assess the precision of multiple methods of estimating V. Of 241 patients included in the study sample, 159 (66.0%) had a body mass index (BMI) of 40.0-49.9 kg/m2, and 82 (34.0%) had a BMI of ≥50.0 kg/m2. The median (5th, 95th percentile) weight of patients was 136 (103, 204) kg, and baseline characteristics were similar between BMI groups. The mean ± S.D. V was lower in patients with a BMI of 40.0-49.9 kg/m2 than in those with a BMI of ≥50.0 kg/m2 (72.4 ± 19.6 L versus 79.3 ± 20.6 L, p = 0.009); however, body size poorly predicted V in regression analyses (R2 < 0.20). A fixed estimate of V (75 L) and use of a weight-based value (0.52 L/kg by total body weight [TBW]) yielded similar bias and error in this population. Results of the largest analysis of vancomycin V in class III obesity to date indicated that use of a fixed V value (75 L) and use of a TBW-based estimate (0.52 L/kg) for estimation of vancomycin V in patients with a BMI of ≥40.0 kg/m2 have similar bias. Two postdistribution vancomycin concentrations are needed to accurately determine patient-specific pharmacokinetic parameters, estimate area under the curve, and improve the precision of vancomycin dosing in this patient population.

P557 Utility of “trough levels” adalimumab determination in patients with inflammatory bowel disease. Estimation of individual pharmacokinetic parameters through population pharmacokinetic model

P557 Utility of “trough levels” adalimumab determination in patients with inflammatory bowel disease. Estimation of individual pharmacokinetic parameters through population pharmacokinetic model

Data Analysis Protocol for the Development and Evaluation of Population Pharmacokinetic Models for Incorporation Into the Web-Accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo).

BackgroundHemophilia is an inherited bleeding disorder caused by a deficiency in a specific clotting factor. This results in spontaneous bleeding episodes and eventual arthropathy. The mainstay of hemophilia treatment is prophylactic replacement of the missing factor, but an optimal regimen remains to be determined. Rather, individualized prophylaxis has been suggested to improve both patient safety and resource utilization. However, uptake of this approach has been hampered by the demanding sampling schedules and complex calculations required to obtain individual estimates of pharmacokinetic (PK) parameters. The use of population pharmacokinetics (PopPK) can alleviate this burden by reducing the number of plasma samples required for accurate estimation, but few tools incorporating this approach are readily available to clinicians.ObjectiveThe Web-accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo) project aims to bridge this gap by providing a Web-accessible service for the reliable estimation of individual PK parameters from only a few patient samples. This service is predicated on the development of validated brand-specific PopPK models.MethodsWe describe the data analysis plan for the development and evaluation of each PopPK model to be incorporated into the WAPPS-Hemo platform. The data sources and structure of the dataset are discussed first, followed by the procedures for handling both data below limit of quantification (BLQ) and absence of such BLQ data. Next, we outline the strategies for building the appropriate structural and covariate models, including the possible need for a process algorithm when PK behavior varies between subjects or significant covariates are not provided. Prior to use in a prospective manner, the models will undergo extensive evaluation using a variety of techniques such as diagnostic plots, bootstrap analysis and cross-validation. Finally, we describe the incorporation of a validated PopPK model into the Bayesian post hoc model to produce individualized estimates of PK parameters.ResultsDense PK data has been collected for more than 20 brands of factor concentrate from both industry-sponsored and investigator-driven studies. The model development process is underway for the majority of molecules, with refinement and validation to be completed in 2017. Further, the WAPPS-Hemo co-investigator network has contributed more than 300 PK assessments for use in model development and evaluation. This constitutes the largest repository of this type of PK data globally.ConclusionsThe WAPPS-Hemo service aims to eliminate barriers to the uptake of individualized PK-tailored hemophilia treatment. By incorporating this tool into routine practice, clinicians can implement a personalized dosing strategy without performing rigorous sampling or complex calculations. This service is centred on validated models developed according to the robust approach to PopPK modeling described herein.ClinicalTrialClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRIXJh55)

P302 Utility of “trough levels” determination and anti-infliximab antibodies in patients with inflammatory bowel disease. Estimation of individual pharmacokinetic parameters (PK) through population pharmacokinetic model

P302 Utility of “trough levels” determination and anti-infliximab antibodies in patients with inflammatory bowel disease. Estimation of individual pharmacokinetic parameters (PK) through population pharmacokinetic model G. Juan1,2 *, A. Alvarino3,4, L. Oltra4, N. Maroto4, N. Cano2, I. Ferrer2, J. Hinojosa2,4. 1Hospital de Manises, Farmacia Hospitalaria, Valencia, Spain, 2Hospital de Manises, Digestivo, Manises, Spain, 3Hospital de Manises, LABCO, Valencia, Spain, 4Hospital de Manises, Gastroenterology, Valencia, Spain

Development of software for data analysis by therapeutic drug monitoring of teicoplanin, a glycopeptide antibiotic

We developed a new software named TEICTDM based on the Bayesian estimation utilized in the therapeutic drug monitoring (TDM) of teicoplanin, a glycopeptide antibiotic, for the estimation of individual pharmacokinetic parameters. Therefore, it is necessary to input more than one plasma concentration(s) determined in individual patient. Individual pharmacokinetic parameters were calculated by a least squares methods, MULTI2 (BAYES). Two-compartment model was applied to determine individual pharmacokinetic parameters in male healthy volunteers in Japan, and the relationship between clearance of teicoplanin and creatinine clearance in adult patients with various degrees of renal impairment in Europe was used. A series of work from data input to graph drawing or printing of results could efficiently carried out with the best of use of this software, suggesting that this software is now available in clinical practice.

Development of new software (Ver. 2.0) based on the Bayesian estimation utilized in the therapeutic drug monitoring of teicoplanin, a glycopeptide antibiotic

We developed a new software (Ver. 2.0) based on the Bayesian estimation utilized in the therapeutic drug monitoring (TDM) of teicoplanin, a glycopeptide antibiotic, for the estimation of individual pharmacokinetic parameters. Individual pharmacokinetic parameters were calculated by a least squares methods, MULTI2 (BAYES), and a two-compartment model with population pharmacokinetic parameters in adult patients in Japan was adopted. The predicted teicoplanin concentrations in patients were similar to the observed concentrations, suggesting that the software predicts with acceptable precision. This new software is now available in clinical practice.

Progress in Strategies for Dosage Regimen Individualization

Several findings suggest that patient outcome would be improved with individualized doses. The aim of this paper is to describe major approaches, methods and underlying basic foundations implemented, in clinical practice, for dosage individualization. Also we propose a new method codified by kinetic nomograms as reliable alternative to traditional Bayesian methods. Clinical and simulation data were reported to evaluate performances of the proposed methods. Real examples of therapeutic drug monitoring were selected. Bayesian methods were used to individualize high-dose methotrexate rate infusion and amikacin dosage regimen, and kinetic nomograms to adjust sirolimus doses. 1) Using only few measurements, Bayesian method resulted in accurate estimates of individual pharmacokinetic parameters of high dose methotrexate infusion. Targeting a pre-defined end-of-infusion level, infusion rate was individualized according to the previously obtained pharmacokinetic parameters. 2) With the same reasoning, individual pharmacokinetic parameters of amikacin were obtained by Bayesian estimation using three individual samples. Subsequent dosage adjustment allowed achievement of therapeutic goals at steady state. 3) Without computing individual pharmacokinetic parameters, nor using pharmacokinetic software, kinetic nomograms steered individual sirolimus blood levels within its therapeutic window with only two samples and in the first week after starting treatment. This contribution relates traditional Bayesian methods developed in 80's but not yet fully integrated in clinical context because of their complexity. The contribution focuses on recent developments based on population approaches, rendering the dosage adjustment methodology a simple and quick bedside application.

Abstract 762: Therapeutic drug monitoring of Anthracyclines and Taxanes in chemotherapy of breast cancer patients

Abstract Background: Anthracyclines (A) and Taxanes (T) remain amongst the most active drugs in breast cancer chemotherapy. However, significant toxicities are associated when administered at full doses in a number of patients (pts), so careful dose adjustments should be made in order to optimize their clinical effectiveness. A and T have high inter- and intra-patient variability, and a correlation between exposure and efficacy and toxicity has been demonstrated. Therefore, therapeutic drug monitoring (TDM) of these drugs, based on the individual pharmacokinetic (PK) parameters could personalize doses in order to diminish its toxicity and/or to improve the clinical benefit. Methods: A total of 24 pts (92 cycles) were treated with either single drugs, or combinations of two of these agents, usually with four initial cycles of A and 4 subsequent cycles of T. The initial dose was calculated using body-surface algorithm. Pts were monitored since the first cycle and subsequent doses pharmacokinetically adjusted until the target plasma concentration was reached. Bayesian estimates of individual PK parameters were calculated using a population PK models previously published and used for PK-based dose adjustment. Results: The main results are shown in the following table: 43% of pts treated with A had the initial dose increased by an average of 22% without toxicities grade II, except one pt which developed mucositis grade II. For paclitaxel, initial dose was increased in 25% of patients by an average of 22% with only one case of grade 2 asthenia. However, docetaxel initial dose of 60-75 mg/m2 was more toxic than the other drugs evaluated. The doses were reduced by an average of 22% due to toxicities such as grade 3 neutropenia, grade 2 asthenia or grade 2 leucopenia. Conclusion: Standard dosing regimen of A and T in breast cancer pts could be optimized by TDM in order to achieve the target plasma concentration during the chemotherapy treatment and ensure that pts receive the right dose. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 762. doi:1538-7445.AM2012-762

Use of therapeutic drug monitoring of cancer chemotherapy to modify initial per-protocol doses.

e13015 Background: Therapeutic drug monitoring (TDM) is not routinely used for chemotherapy agents. Nonetheless, TDM has the potential to improve the clinical benefit of chemotherapy agents due to their narrow therapeutic index and highly variable pharmacokinetics. The main objective of this study was to evaluate the dose modifications on the standard dosing regimen based on the individual pharmacokinetic (PK) parameters of six antineoplasic drugs (oxaliplatin, cisplatin, doxorubicin, irinotecan, paclitaxel, and 5-fluorouracil). Methods: A total of 187 patients (pts) (764 cycles), treated with either drug tested, were monitored and doses in second or subsequent cycles were pharmacokinetically adjusted until the patients reached the target plasma concentration. Bayesian estimates of individual PK parameters were calculated using a population PK model previously published and were used for pharmacokinetic-based dose adaptation. Patient's toxicities were assessed before each cycle using the National Cancer Institute Common Toxicity Criteria. Results: The main results are shown in the Table. In one out of four patients, the dose was increased an average of 12% without increasing the toxicity. In one out of four patients, the dose was decreased an average 16% due to toxicity caused by the complexity of the therapeutic program but not due to previous dose increases. These results evidence TDM might benefit one out of two oncology patients. Conclusions: Half of the patients evaluated did not achieve the target plasma concentration during the first cycle of chemotherapy. TDM of anticancer drugs is a tool to optimize cancer treatment and ensure that patients receive the right dose. Drug N (pts/cycles) Dose maintenance(% pts) Dose increase (% pts) Dose decrease (% pts) Avg dose increase (%) Avg dose decrease (%) Oxaliplatin 13/51 77 — 23 — 22 Cisplatin 17/62 35 47 18 14 15 Doxorubicin 21/67 52 19 29 13 13 Irinotecan 39/165 31 46 23 13 18 Paclitaxel 46/182 61 4 35 10 12 5-fluorouracil 51/237 37 51 12 12 15 Total 187/764 49 28 23 12 16 No significant financial relationships to disclose.

Population pharmacokinetics of amodiaquine and desethylamodiaquine in pediatric patients with uncomplicated falciparum malaria

The study aimed to characterize the population pharmacokinetics of amodiaquine (AQ) and its major metabolite N-desethylamodiaquine (N-DEAQ), and to assess the correlation between exposure to N-DEAQ and treatment outcome. Blood samples from children in two studies in Zanzibar and one in Papua New Guinea were included in the pharmacokinetic analysis (n = 86). The children had been treated with AQ in combination with artesunate or sulphadoxine-pyrimethamine. The population pharmacokinetics of AQ and N-DEAQ were modeled using the non-linear mixed effects approach as implemented in NONMEM. Bayesian post-hoc estimates of individual pharmacokinetic parameters were used to generate individual profiles of N-DEAQ exposure. The correlation between N-DEAQ exposure and effect was studied in 212 patients and modeled with logistic regression in NONMEM. The pharmacokinetics of AQ and N-DEAQ were best described by two parallel two-compartment models with a central and a peripheral compartment for each compound. The systemic exposure to AQ was low in comparison to N-DEAQ. The t(1/2 lambda) of N-DEAQ ranged from 3 days to 12 days. There was a statistically significant, yet weak, association between N-DEAQ concentration on day 7 and treatment outcome. The age-based dosing schedule currently recommended in Zanzibar appeared to result in inadequate exposure to N-DEAQ in many patients.

A Limited Sampling Strategy for Estimating Individual Pharmacokinetic Parameters of Coagulation Factor VIII in Patients With Hemophilia A

Therapeutic drug monitoring of factor VIII is well established in the treatment of patients with hemophilia attributable to important interindividual variability. The individual initial factor VIII dosage is usually calculated according to individual pharmacokinetic parameters obtained after a dose test administered before the surgery, using at least five-concentration data. The authors proposed a limited sampling strategy to estimate individual pharmacokinetic parameters from one- or two-concentration data in patients with hemophilia A before surgery. The mean population pharmacokinetic parameters and the interindividual variability (CV) were obtained from a group of 33 patients according to a two-compartment model using NONMEM. Eighteen additional patients were used to estimate the predictive performances of the population parameters and to evaluate the limited sampling strategies. Population parameters were clearance 2.6 mL/h per kilogram (CV 45.4%), initial volume of distribution 2.8 L (CV 21.1%). From two sampling times (0.5 and 6 hours or 0.5 and 8 hours after the end of infusion), the estimation of pharmacokinetic parameters was precise and not biased. Until now, in the hemophilic center of Lyon, the factor VIII dosage before surgery was based on the determination of the clearance, estimated from five- to nine-concentration data and on the target concentration (infusion rate = clearance x target). Ruffo et al proposed a limited sampling strategy (two-stage method) to estimate pharmacokinetic parameters from two concentration measurements drawn 3 and 9 hours after the dose. No information was given on the bias and precision of the estimation. This paper reports a one-stage method for a population pharmacokinetic study of factor VIII. The Bayesian estimation of individual pharmacokinetic parameters based on only two sampling times (0.5 and 6 hours or 0.5 and 8 hours after the end of infusion) is useful to define the best factor VIII dosage in hemophilic patients before surgery.

Real-time Dose Adjustment of Cyclophosphamide in a Preparative Regimen for Hematopoietic Cell Transplant: A Bayesian Pharmacokinetic Approach

Dose-related toxicity of cyclophosphamide may be reduced and therapeutic efficacy may be improved by pharmacokinetic sampling and dose adjustment to achieve a target area under the curve (AUC) for two of its metabolites, hydroxycyclophosphamide (HCY) and carboxyethylphosphoramide mustard (CEPM). To facilitate real-time dose adjustment, we developed open-source code within the statistical software R that incorporates individual data into a population pharmacokinetic model. Dosage prediction performance was compared to that obtained with nonlinear mixed-effects modeling using NONMEM in 20 cancer patients receiving cyclophosphamide. Bayesian estimation of individual pharmacokinetic parameters was accomplished from limited (i.e., five samples over 0-16 hours) sampling of plasma HCY and CEPM after the initial cyclophosphamide dose. Conditional on individual pharmacokinetics, simulations of the AUC of both HCY and CEPM were provided for a range of second doses (i.e., 0-100 mg/kg cyclophosphamide). The results compared favorably with NONMEM and returned accurate predictions for AUCs of HCY and CEPM with comparable mean absolute prediction error and root mean square prediction error. With our method, the mean absolute prediction error and root mean square prediction error of AUC CEPM were 11.0% and 12.8% and AUC HCY were 31.7% and 44.8%, respectively. We developed dose adjustment software that potentially can be used to adjust cyclophosphamide dosing in a clinical setting, thus expanding the opportunity for pharmacokinetic individualization of cyclophosphamide. The software is simple to use (requiring no programming experience), reads individual patient data directly from an Excel spreadsheet, and runs in less than 5 minutes on a desktop PC.

Therapeutic Drug Monitoring for Dose Individualization of Cisplatin in Testicular Cancer Patients Based Upon Total Platinum Measurement in Plasma

Cisplatin (CDDP) is an anticancer agent widely used in testicular cancer, for which pharmacokinetic (PK)/pharmacodynamic relationships have usually been based upon measurement of its unbound fraction in plasma. Because it has been shown that free CDDP clearance can be related to patient's body surface area (BSA), dosage is mostly adjusted a priori using only this single parameter, with mixed results for accurately predicting CDDP exposure and reducing toxicities. In contrast, the authors present here an original, 5-day continuous infusion schedule, coupled to a daily Bayesian adaptive dosing with feedback strategy, based upon the rapid assay of total, rather than free, CDDP in plasma. Nineteen patients (66 therapeutic courses) were treated with platinum-based combinational therapy. Plasma samples were analyzed to allow real-time Bayesian estimation of individual PK parameters with subsequent prospective dose adjustment in order to reach a target Cmax (Cend) of 1.95 mg/L of total platinum. Performance of the Bayesian dosing method was evaluated by comparing target Cmax with achieved Cmax. The mean+/-SD Cmax achieved was 1.93+/-0.16 mg/L. No statistically significant difference was observed between experimental and target values (P>0.05, t test), and Cend achievement was done with an overall 6.6% precision, a performance to be compared with the initial 54% interpatient variability observed in CDDP clearance. A nonlinear mixed effect model population PK analysis was subsequently performed to identify retrospectively the covariates associated with PK parameters of total CDDP. It showed a good correlation (r=0.84, P=0.004) between total platinum clearance and therapeutic course number. A weaker correlation (r=0.59) was found between BSA and total CDDP clearance and, importantly, no additional relationship was established with BSA when successive therapeutic courses, and not only the first one, were considered. This highlights the critical importance of total drug accumulation on CDDP pharmacokinetics when several infusions are to be administered in a row and, therefore, the need for real-time dose individualization that takes into account the course number, rather than BSA. Finally, doses of CDDP administered during each course were significantly higher (+20%, P<0.01) than the ones classically normalized with BSA, thus leading to an overall greater drug exposure in the patients. It is noteworthy that despite these markedly higher doses, little severe toxicity was reported, and all of the patients presented in this study were still alive and disease free after a follow-up of up to 15 years.

A Population Pharmacokinetic/Pharmacodynamic Analysis of Regadenoson, an Adenosine A2A-Receptor Agonist, in Healthy Male Volunteers

The aims of this study were to investigate the safety, tolerability, pharmacokinetics and pharmacodynamics of regadenoson (CVT-3146) in healthy, male volunteers. Thirty-six healthy, male volunteers aged 18-50 years were included in this randomised, double-blind, crossover, placebo-controlled study to evaluate single intravenous bolus doses of regadenoson that ranged from 0.1 to 30.0 micro g/kg. Subjects received one dose of regadenoson or placebo on successive days while supine, then the same dose of regadenoson or placebo on successive days while standing. As part of the safety evaluation, vital signs and adverse events were monitored and recorded throughout the course of the study in all subjects. Up to 20 plasma samples were collected for regadenoson concentration determination within the 24 hours after each supine dosage. All urine was collected during the 24-hour time period post-dose and an aliquot was used for the determination of the regadenoson concentration. Heart rate and blood pressure were recorded at many of the same timepoints that the samples for the pharmacokinetic analysis were taken. A non linear mixed-effect modelling approach, using the software NONMEM, was utilised in modelling the plasma and urine concentration-time profiles and temporal changes in heart rate after regadenoson administration in the supine position. The influences of several covariates, including bodyweight, body mass index and age, on pharmacokinetic model parameters were investigated. Adverse events were more prevalent at regadenoson doses above 3 micro g/kg, and the increase in the occurrence of adverse events was dose-related. Most of the adverse events were related to vasodilation and an increase in heart rate and were generally of mild to moderate severity. Based on the severity and frequency of adverse events, the maximum tolerated doses of regadenoson were deemed to be 10 micro g/kg in the standing position and 20 micro g/kg in the supine position. The pharmacokinetics of regadenoson were successfully described by a three-compartment model with linear clearance. Following intravenous bolus dose administration, regadenoson was rapidly distributed throughout the body, followed by relatively slower elimination (terminal elimination half-life of approximately 2 hours). The clearance was estimated to be 37.8 L/h, with renal excretion accounting for approximately 58% of the total elimination. The volume of distribution of the central compartment and the volume of distribution at steady state were estimated to be 11.5L and 78.7L, respectively. Individual pharmacokinetic parameter estimates were fixed in the pharmacodynamic model, where changes in heart rate were related to plasma drug concentrations using a Michaelis-Menten model. The maximum heart rate increase (Emax) and plasma regadenoson concentration causing a 50% increase in the maximum heart rate (EC50) were estimated to be 76 beats per minute and 12.3 ng/mL, respectively. None of the tested covariates was found to be correlated with any of the pharmacokinetic model parameters. The pharmacokinetics and the effects of regadenoson on heart rate were successfully described using pharmacokinetic/pharmacodynamic modelling. The lack of a correlation between the model estimates and various baseline patient demographics supports unit-based dose administration of regadenoson.

Development of a population pharmacokinetic model for carbamazepine based on sparse therapeutic monitoring data from pediatric patients with epilepsy

Population models can be important extensions of therapeutic drug monitoring (TDM), as they allow estimation of individual pharmacokinetic parameters based on a small number of measured drug concentrations. This study used a Bayesian approach to explore the utility of routinely collected and sparse TDM data (1 sample per patient) for carbamazepine (CBZ) monotherapy in developing a population pharmacokinetic (PPK) model for CBZ in pediatric patients that would allow prediction of CBZ concentrations for both immediate- and controlled-release formulations. Patient and TDM data were obtained from a pediatric neurology outpatient database. Data were analyzed using an iterative 2-stage Bayesian algorithm and a nonparametric adaptive grid algorithm. Models were compared by final log likelihood, mean error (ME) as a measure of bias, and root mean squared error (RMSE) as a measure of precision. Fifty-seven entries with data on CBZ monotherapy were identified from the database and used in the analysis (36 from males, 21 from females; mean [SD] age, 9.1 [4.4] years [range, 2-21 years]). Preliminary models estimating clearance (Cl) or the elimination rate constant (K(el)) gave good prediction of serum concentrations compared with measured serum concentrations, but estimates of Cl and K(el) were highly correlated with estimates of volume of distribution (V(d)). Different covariate models were then tested. The selected model had zero-order input and had age and body weight as covariates. Cl (L/h) was calculated as K(el) . V(d), where K(el) = [K(i) - (K(s) . age)] and V(d) = [V(i) + (V(s) . body weight)]. Median parameter estimates were V(i) (intercept) = 11.5 L (fixed); V(s) (slope) = 0.3957 L/kg (range, 0.01200-1.5730); K(i) (intercept) = 0.173 h(-1) (fixed); and K(s) (slope) = 0.004487 h(-1) . y(-1) (range, 0.0001800-0.02969). The fit was good for estimates of steady-state serum concentrations based on prior values (population median estimates) (R = 0.468; R(2) = 0.219) but was even better for predictions based on individual Bayesian posterior values (R(2) = 0.991), with little bias (ME = -0.079) and good precision (RMSE = 0.055). Based on the findings of this study, sparse TDM data can be used for PPK modeling of CBZ clearance in children with epilepsy, and these models can be used to predict Cl at steady state in pediatric patients. However, to estimate additional pharmacokinetic model parameters (eg, the absorption rate constant and V(d)), it would be necessary to combine sparse TDM data with additional well-timed samples. This would allow development of more informative PPK models that could be used as part of Bayesian dose-individualization strategies.

Population Pharmacokinetics of Efavirenz in an Unselected Cohort of HIV-1-Infected Individuals

The aim of this study was to characterise the population pharmacokinetics of efavirenz in a representative patient population and to identify patient characteristics influencing the pharmacokinetics of efavirenz, with the ultimate goal of further developing techniques that can be applied to optimise therapeutic drug monitoring of antiretroviral agents. Ambulatory HIV-1-infected patients using an efavirenz-containing regimen were included. During regular visits, blood samples were collected for efavirenz plasma concentrations and clinical chemistry parameters. Concentrations of efavirenz were quantitatively assessed by a validated high-performance liquid chromatographic with ultraviolet detection method. Using nonlinear mixed-effect modelling (NONMEM), the pharmacokinetics of efavirenz were described. Disposition of efavirenz was described by a two-compartment model and absorption was modelled using a chain of three transition compartments. Apparent clearance (CL/F), volume of distribution after oral administration (V(d)/F), intercompartmental clearance, the peripheral volume of distribution and the intercompartmental transition rate constant (k(tr)) were estimated. Furthermore, interindividual, interoccasion and residual variability were estimated. The influence of patient characteristics on the pharmacokinetic parameters of efavirenz was explored. From 172 patients, 40 full pharmacokinetic curves and 315 efavirenz plasma concentrations at a single timepoint were available, resulting in a database of 1009 efavirenz plasma concentrations. CL/F, V(d)/F, and k(tr) were 11.7 L/h (4.3% relative standard error [RSE]), 189L (14.6% RSE) and 3.07 h(-1) (11.2% RSE), respectively. Residual variability in the model was composed of 0.14 mg/L additive error and 8.85% proportional error. Asian race and baseline total bilirubin (TBR) increased the relative bioavailability of efavirenz by 56% and 57%, respectively. No significant covariates were found for CL/F or V(d)/F. The pharmacokinetic parameters of efavirenz were adequately described with the developed population pharmacokinetic model. Asian race and baseline TBR were found to be significantly correlated with the bioavailability of efavirenz. The described model will be an essential tool in further optimisation of efavirenz-containing antiretroviral therapy, e.g. by the use of Bayesian estimation of individual pharmacokinetic parameters.