scholarly journals Predictive performance of parent-metabolite population pharmacokinetic models of (S)-ketamine in healthy volunteers

2021 ◽  
Author(s):  
M. E. Otto ◽  
K. R. Bergmann ◽  
G. Jacobs ◽  
Michiel J. van Esdonk
Keyword(s):  
Clinical Trials ◽  
Healthy Volunteers ◽  
Predictive Performance ◽  
Individual Variability ◽  
Population Pharmacokinetic ◽  
Prediction Errors ◽  
Population Demographics ◽  
Solid Foundation ◽  
Study Designs ◽  
Circulatory Dynamics

Abstract Purpose The recent repurposing of ketamine as treatment for pain and depression has increased the need for accurate population pharmacokinetic (PK) models to inform the design of new clinical trials. Therefore, the objectives of this study were to externally validate available PK models on (S)-(nor)ketamine concentrations with in-house data and to improve the best performing model when necessary. Methods Based on predefined criteria, five models were selected from literature. Data of two previously performed clinical trials on (S)-ketamine administration in healthy volunteers were available for validation. The predictive performances of the selected models were compared through visual predictive checks (VPCs) and calculation of the (root) mean (square) prediction errors (ME and RMSE). The available data was used to adapt the best performing model through alterations to the model structure and re-estimation of inter-individual variability (IIV). Results The model developed by Fanta et al. (Eur J Clin Pharmacol 71:441–447, 2015) performed best at predicting the (S)-ketamine concentration over time, but failed to capture the (S)-norketamine Cmax correctly. Other models with similar population demographics and study designs had estimated relatively small distribution volumes of (S)-ketamine and thus overpredicted concentrations after start of infusion, most likely due to the influence of circulatory dynamics and sampling methodology. Model predictions were improved through a reduction in complexity of the (S)-(nor)ketamine model and re-estimation of IIV. Conclusion The modified model resulted in accurate predictions of both (S)-ketamine and (S)-norketamine and thereby provides a solid foundation for future simulation studies of (S)-(nor)ketamine PK in healthy volunteers after (S)-ketamine infusion.

Population Pharmacokinetic Modeling of BeneFIX in Pediatric and Adult Patients with Hemophilia B Demonstrates Weight as An Important Factor Contributing to Inter-Patient PK Variability.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1218-1218 ◽  
Author(s):  
Chandrasekhar Udata ◽  
Sharon Sullivan ◽  
Patrick Kelly ◽  
David A. Roth ◽  
Xu Meng
Keyword(s):  
Clinical Trials ◽  
Body Weight ◽  
Individual Variability ◽  
Factor Ix ◽  
Adult Patients ◽  
Hemophilia B ◽  
Peripheral Compartment ◽  
Population Pharmacokinetic ◽  
Population Pharmacokinetic Modeling ◽  
First Time

Abstract Clinical trials in patients with hemophilia B have demonstrated considerable inter-patient variability in the pharmacokinetics (PK) of Factor IX (FIX) replacement therapy, including the recovery, an important PK parameter from which individualized clinical dosing decisions are calculated. In clinical trials of plasma-derived and recombinant factor IX replacement therapies, the age of the patient has been demonstrated to affect recovery (younger patients have lower recovery values than older patients), however the specific contribution of age, as well as additional covariates such as body weight and race to PK variability has not been systematically evaluated. We analyzed an extensive database of BeneFIX PK data collected from 8 separate clinical trials conducted over 13 years. A systematic approach involving population PK modeling and simulation was utilized for the first time to estimate the effects of individual-specific covariate factors on PK of BeneFIX in the pooled population that included pediatric and adult patients. A total of 4025 plasma FIX activity PK data sets collected from 191 patients, aged 0 to 69 years were used for the analysis. There were 111 children (£15 years) including 53 infants <2 years, and 80 adults (>15 years) in the pooled data. The majority (84%) of patients were Caucasian. The remaining patients were African American (7%), Hispanic (4%), Asian/Japanese (3%), and other ethnicity (3%). The data were analyzed using nonlinear mixed-effects modeling with the NONMEM software system. Age, weight, and race were examined as covariates for the ability to explain inter-individual variability in the BeneFIX PK. The PK in pediatric and adult patients was described by a two-compartment model with first-order elimination and a zero-order input using the following parameters: clearance (CL), volume of central compartment (V1), volume of peripheral compartment (V2) and inter-compartmental clearance (Q). Population predicted BeneFIX PK parameters, standardized to a 70 kg patient, were 7.46 (standard error; 0.20) mL/hr/kg, 131 (4.4) mL/kg, 71.5 (2.1) mL/kg and 12.1 (1.1) mL/h/kg, for CL, V1, V2 and Q, respectively. The final model was able to simulate data in close agreement with the actual study observations. Variability (%CV) in BeneFIX PK was explained most significantly by allometrically scaled body weight (Figure 1a), while age and race had no discernible effects on BeneFIX PK in the population studied. Observed recovery values were slightly lower in children (£15 years) compared with those in adults (>15 years) since the initial volume of distribution (V1), normalized to body weight, was slightly higher in children than in adults, while the variability in the observed recovery values was comparable between children and adults (Figure 1b). In conclusion, the present analysis, for the first time, systematically describes and quantifies the sources of age-dependent variability of factor IX PK, using BeneFIX data, and provides a better understanding of the importance of body weight in the disposition of BeneFIX. This confirms existing weight-based dosing recommendations and further supports consideration of dosing adjustments that are individualized based on the patient’s body weight in the context of the achieving the desired clinical response, such as recovery. This also may be important in pediatric patients during growth periods associated with significant weight change. Figure 1a. Clearance versus Body weight Figure 1a. Clearance versus Body weight Figure 1b. Recovery versus Body weight Figure 1b. Recovery versus Body weight

scholarly journals Melatonin in Cancer Treatment: Current Knowledge and Future Opportunities

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2506
Author(s):  
Wamidh H. Talib ◽  
Ahmad Riyad Alsayed ◽  
Alaa Abuawad ◽  
Safa Daoud ◽  
Asma Ismail Mahmod
Keyword(s):  
Clinical Trials ◽  
Current Knowledge ◽  
Biological Activities ◽  
Experimental Studies ◽  
Therapeutic Effects ◽  
Cell Proliferation Inhibition ◽  
Different Types ◽  
Solid Foundation

Melatonin is a pleotropic molecule with numerous biological activities. Epidemiological and experimental studies have documented that melatonin could inhibit different types of cancer in vitro and in vivo. Results showed the involvement of melatonin in different anticancer mechanisms including apoptosis induction, cell proliferation inhibition, reduction in tumor growth and metastases, reduction in the side effects associated with chemotherapy and radiotherapy, decreasing drug resistance in cancer therapy, and augmentation of the therapeutic effects of conventional anticancer therapies. Clinical trials revealed that melatonin is an effective adjuvant drug to all conventional therapies. This review summarized melatonin biosynthesis, availability from natural sources, metabolism, bioavailability, anticancer mechanisms of melatonin, its use in clinical trials, and pharmaceutical formulation. Studies discussed in this review will provide a solid foundation for researchers and physicians to design and develop new therapies to treat and prevent cancer using melatonin.

POPULATION PHARMACOKINETICS AND DOSING OPTIMIZATION OF TEICOPLANIN IN CHILDREN WITH MALIGNANT HAEMATOLOGICAL DISEASE

2015 ◽  
Vol 101 (1) ◽  
pp. e1.41-e1
Author(s):  
Wei Zhao ◽  
Daolun Zhang ◽  
Thomas Storme ◽  
André Baruchel ◽  
Xavier Declèves ◽  
...  
Keyword(s):  
Population Pharmacokinetics ◽  
Haematological Malignancy ◽  
External Validation ◽  
Predictive Performance ◽  
Paediatric Population ◽  
Pharmacokinetic Parameters ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
High Risk Population ◽  
Dosing Regimen

BackgroundChildren with haematological malignancy represent an identified subgroup of the paediatric population with specific pharmacokinetic parameters. In these patients, inadequate empirical antibacterial therapy may result in infection-related morbidity and increased mortality, making optimization of the dosing regimen essential. As paediatric data are limited, our aim was to evaluate the population pharmacokinetics of teicoplanin in order to define the appropriate dosing regimen in this high-risk population.MethodsThe current dose of teicoplanin was evaluated in children with haematological malignancy. Population pharmacokinetics of teicoplanin was analysed using NONMEM software. The dosing regimen was optimised based on the final model.ResultsEighty-five children (age range: 0.5 to 16.9 years) were included. Therapeutic drug monitoring and opportunistic samples (n=143) were available for analysis. With the current recommended dose of 10 mg/kg/day, 41 children (48%) had sub-therapeutic steady-state trough concentrations (Css,min<10 mg/liter). A two-compartment pharmacokinetic model with first-order elimination was developed. Systematic covariate analysis identified that bodyweight (size) and creatinine clearance significantly influenced teicoplanin clearance. The model was validated internally. Its predictive performance was further confirmed in an external validation. In order to reach the target AUC of 750 mg·h/L, 18 mg/kg was required for infants, 14 mg/kg for children and 12 mg/kg for adolescents. A patient-tailored dose regimen was further developed and reduced variability in AUC and Css,min values compared to the mg/kg-basis dose, making the modelling approach an important tool for dosing individualization.ConclusionsThis first population pharmacokinetic study of teicoplanin in children with haematological malignancy provided evidence-based support to individualize teicoplanin therapy in this vulnerable population.

scholarly journals Healthy Volunteers’ Perceptions of the Benefits of Their Participation in Phase I Clinical Trials

2018 ◽  
Vol 13 (5) ◽  
pp. 494-510 ◽  
Author(s):  
Jill A. Fisher ◽  
Lisa McManus ◽  
Megan M. Wood ◽  
Marci D. Cottingham ◽  
Julianne M. Kalbaugh ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Phase I ◽  
Healthy Volunteers ◽  
Employment Status ◽  
Qualitative Interviews ◽  
Trial Participation ◽  
Phase I Trials ◽  
Phase I Clinical Trials ◽  
Financial Compensation ◽  
Trial History

Other than the financial motivations for enrolling in Phase I trials, research on how healthy volunteers perceive the benefits of their trial participation is scant. Using qualitative interviews conducted with 178 U.S. healthy volunteers enrolled in Phase I trials, we investigated how participants described the benefits of their study involvement, including, but not limited to, the financial compensation, and we analyzed how these perceptions varied based on participants’ sociodemographic characteristics and clinical trial history. We found that participants detailed economic, societal, and noneconomic personal benefits. We also found differences in participants’ perceived benefits based on gender, age, ethnicity, educational attainment, employment status, and number of clinical trials completed. Our study indicates that many healthy volunteers believe they gain more than just the financial compensation when they accept the risks of Phase I participation.

scholarly journals Population Pharmacokinetic Analysis of Vancomycin Using Serum Cystatin C as a Marker of Renal Function

2009 ◽  
Vol 54 (2) ◽  
pp. 778-782 ◽  
Author(s):  
Akihiro Tanaka ◽  
Tetsuya Aiba ◽  
Takashi Otsuka ◽  
Katsuya Suemaru ◽  
Tatsuya Nishimiya ◽  
...  
Keyword(s):  
Renal Function ◽  
Cystatin C ◽  
Predictive Performance ◽  
Pharmacokinetic Analysis ◽  
Pharmacokinetic Parameters ◽  
Population Pharmacokinetic ◽  
Serum Cystatin C ◽  
Serum Cystatin ◽  
New Model ◽  
The Mean

ABSTRACT We determined the population pharmacokinetics of vancomycin (VAN) using the glomerular filtration rate (GFR) estimated from the serum cystatin C concentration. We examined the predictive performance of the trough serum VAN concentration for determination of the initial dose by using a new model for the analysis of the population pharmacokinetic parameters. Data for 86 patients were used to estimate the values of the population pharmacokinetic parameters. Analysis with a nonlinear mixed-effects modeling program was done by using a one-compartment model. Data for 78 patients were used to evaluate the predictive performance of the new model for the analysis of population pharmacokinetic parameters. The estimated GFR values determined by using Hoek's formula correlated linearly with VAN clearance (VAN clearance [ml/min] = 0.825 × GFR). The mean volume of distribution was 0.864 (liters/kg). The interindividual variability of VAN clearance was 19.8%. The accuracy of the prediction determined by use of the new model was statistically better than that determined by use of the Japanese nomogram-based model because the 95% confidence interval (−3.45 to −1.38) of the difference in each value of the mean absolute error (−2.41) did not include 0. Use of the serum cystatin C concentration as a marker of renal function for prediction of serum VAN concentrations may be useful.

scholarly journals External validation of the predictive performance of population pharmacokinetic models for phenobarbital in pediatric patients

2020 ◽  
Author(s):  
Sunae Ryu ◽  
Woo Jin Jung ◽  
Zheng Jiao ◽  
Jung Woo Chae ◽  
Hwi-yeol Yun
Keyword(s):  
External Validation ◽  
Predictive Performance ◽  
Validation Dataset ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Models ◽  
Bayesian Forecasting ◽  
Predictive Capability ◽  
Young Infants ◽  
Simulation Based

Aim: Several studies have reported population pharmacokinetic models for phenobarbital (PB), but the predictive performance of these models has not been well documented. This study aims to do external validation of the predictive performance in published pharmacokinetic models. Methods: Therapeutic drug monitoring data collected in neonates and young infants treated with PB for seizure control, was used for external validation. A literature review was conducted through PubMed to identify population pharmacokinetic models. Prediction- and simulation-based diagnostics, and Bayesian forecasting were performed for external validation. The incorporation of size or maturity functions into the published models was also tested for prediction improvement. Results: A total of 79 serum concentrations from 28 subjects were included in the external validation dataset. Seven population pharmacokinetic studies of PB were selected for evaluation. The model by Voller et al. [27] showed the best performance concerning prediction-based evaluation. In simulation-based analyses, the normalized prediction distribution error of two models (those of Shellhaas et al. [24] and Marsot et al. [25]) obeyed a normal distribution. Bayesian forecasting with more than one observation improved predictive capability. Incorporation of both allometric size scaling and maturation function generally enhanced the predictive performance, but with marked improvement for the adult pharmacokinetic model. Conclusion: The predictive performance of published pharmacokinetic models of PB was diverse, and validation may be necessary to extrapolate to different clinical settings. Our findings suggest that Bayesian forecasting improves the predictive capability of individual concentrations for pediatrics.

scholarly journals Incorporating Nonlinear Kinetics to Improve the Predictive Performance of Population Pharmacokinetic Models for Ciclosporin in Adult Renal Transplant Recipients: A Comparison of Modelling Strategies

2020 ◽  
Author(s):  
Jun-Jun Mao ◽  
Zheng Jiao ◽  
Xiao-Yan Qiu ◽  
Ming Zhang ◽  
Ming-Kang Zhong
Keyword(s):  
Renal Transplant ◽  
Predictive Performance ◽  
Population Pharmacokinetic ◽  
List Type ◽  
Renal Transplant Recipients ◽  
Transplant Recipients ◽  
Inhibitory Effects ◽  
Nonlinear Kinetics ◽  
Nonlinear Properties ◽  
Modelling Strategies

AbstractAimCiclosporin (CsA) has been shown to follow nonlinear pharmacokinetics in renal transplant recipients who received Neoral-based triple immunosuppressive therapy. Some of these nonlinear properties have not been fully considered in population pharmacokinetic (popPK) analysis. Therefore, the aim of this study was to determine the potential influence of nonlinearity and the functional forms of covariates on model predictability.MethodsA total of 2969 CsA whole-blood measurements, including 1328 pre-dose and 1641 2-h post-dose concentrations, were collected from 173 patients who underwent their first renal transplantation. Four popPK models based on different modelling strategies were developed to investigate the discrepancy between empirical and theory-based, linear and nonlinear compartmental kinetic models and empirical formulae on model predictability. Prediction-based and simulation-based diagnostics (prediction-corrected visual predictive checks) were performed to determine the stability and predictive performance of these four models.ResultsModel predictability improved when nonlinearity was considered. The theory-based nonlinear model which incorporated nonlinear property based on known theoretical relationships performed better than the other two compartmental models. The nonlinear Michaelis-Menten model showed a remarkable improvement in predictive performance over that of the other three compartmental models. The saturated binding of CsA to erythrocytes, and auto-inhibition that arose from the inhibitory effects of CsA on CYP3A4/P-gp and CsA-prednisolone drug interaction may have contributed to the nonlinearity.ConclusionsIncorporating nonlinear properties are likely to be a promising approach for improving CsA model predictability. However, CsA nonlinear kinetics resources need further investigation. Until then, Michaelis-Menten empirical model can be used for CsA dose adjustments.What is already known about this subjectCsA in renal transplant recipients receiving Neoral-based triple immunosuppressive therapy followed nonlinear pharmacokinetics.Nonlinearity is rarely incorporated into CsA population pharmacokinetic (popPK) modelling processes.What this study addsFour popPK models based on different modelling strategies were developed to investigate the discrepancy between empirical and theory-based compartmental kinetic models and empirical formulae, as well as the effect of nonlinearity on CsA model predictability.Based on the four models, incorporating nonlinear properties is likely to be a promising approach for improving CsA model predictability.Saturated distribution into red blood cells, and auto-inhibition that arose from the inhibitory effects of CsA on CYP3A4/P-gp and CsA-prednisolone drug interaction may be the main sources of CsA PK nonlinearity.Principal Investigator statementThe authors confirm that the Principal Investigator for this paper is Zheng Jiao and that he had direct clinical responsibility for patients.

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