Population pharmacokinetic modelling of cyclosporine in paediatric kidney transplant patients using routine TDM data
Authors
Roganović, Maša
Cvetković, Mirjana
Gojković, Ivana
Spasojević, Brankica
Kostić, Mirjana

Miljković, Branislava

Vučićević, Katarina

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Introduction: Cyclosporine (CyA), an immunosuppressive agent, is mandatory part of post-transplantation therapy protocols. CyA shows large interindividual and intraindividual pharmacokinetic (PK) variability, has a narrow therapeutic range and several factors has already been identified as sources of variability. Proactive dosing strategies to achieve and maintain predefined CyA levels, via therapeutic drug monitoring (TDM), may prevent graft rejection and minimize serious side effects [1,2]. Data obtained during TDM can be used for describing PK model on both population and individual level while taking into account individual characteristics. Furthermore, that model could inform optimal CyA dosing via Bayesian-TDM approach.
Objectives: We aimed in developing CyA population PK model and address sources of PK variabilities in order to explain observable differences in the concentrations of the drug. In addition, the objective of the study is to assess the effect of PK on the respons...e to CyA therapy using modelling approach.
Methods: Data regarding dosage regimens, CyA blood concentrations, concomitant medications and laboratory findings of significance in kidney transplant paediatric patients were collected from their medical history. Drug concentration was measured in whole blood samples, and the samples were drawn before (Ctrough) and 2 hours after the morning dose (C2). Population pharmacokinetic analyses was performed using nonlinear mixed effects modelling software – NONMEM® (version 7.4) with first-order conditional estimation method with interaction (FOCE-I). NONMEM outputs were handled in R software (graphical diagnostics). We tried fitting one- and two-compartment to concentration-time data. Covariate model building was performed using stepwise covariate procedure (SCM). Covariates that were tested are age, weight (WT), serum creatinine levels (CR) haematocrit (HCT) (continuous covariates). Influence of categorical covariates was also examined – gender (GEND) and type of transplanted graft - live or cadaveric transplantation (TRANS). Model appropriateness has been performed using numerical and visual approaches.
Results: : In total, 58 patients aged 2-25 years (mean± sd: 12.46±0.78), mainly paediatrics (79.31% up to 18 years) were included in the analysis. We have analysed 496 concentrations obtained during up to one year post-transplant period. Mean values of C0 and C2 are 126.1±4.37 ng/ml and 825.8±20.32 ng/ml, respectively. One-compartment model with first order absorption best described the data. Typical values of clearance (CL), volume (V), and absorption rate constant (Ka) from covariate model were 14.2 L/h, 1.94 L/kg, 1.3 1/h, respectively. Tested PK parameter-covariate relations that caused the significant drop in objective function value are influence of WT, CR and HCT on CL, and WT on volume V. Interindividual variability (IIV) on CL and V, after inclusion of covariates was 22.6 % and 25.3% (in the base model the IIV was 33.5% and 36.5%, respectively). In the further analyses, population pharmacokinetic/pharmacodynamic (popPK/PD) will be developed.
Conclusions: The results regarding PK parameters are in accordance with a published study in a similar population (paediatric transplant patients) [3]. Knowing individual parameters values can help maximize the benefits of drug therapy and minimize side effects, which is a cornerstone of safe and effective therapy.
References:
[1] Midtvedt K. Therapeutic drug monitoring of cyclosporine. Transplant Proc. 2004;36(2 Suppl):430S-433S. doi:10.1016/j.transproceed.2004.01.025.
[2] Kang JS, Lee MH. Overview of therapeutic drug monitoring. Korean J Intern Med. 2009;24(1):1-10. doi:10.3904/kjim.2009.24.1.1
[3] Fanta S, Jönsson S, Backman JT, Karlsson MO, Hoppu K. Developmental pharmacokinetics of ciclosporin-a population pharmacokinetic study in paediatric renal transplant candidates. Br J Clin Pharmacol. 2007;64(6):772-84. doi: 10.1111/j.1365-2125.2007.03003.x
Source:
Page. Abstracts of the Annual Meeting of the Population Approach Group in Europe, 2021Note:
- PAGE 29 (2021)
- Poster: Drug/Disease Modelling - Paediatrics
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PharmacyTY - CONF AU - Roganović, Maša AU - Cvetković, Mirjana AU - Gojković, Ivana AU - Spasojević, Brankica AU - Kostić, Mirjana AU - Miljković, Branislava AU - Vučićević, Katarina PY - 2021 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4819 AB - Introduction: Cyclosporine (CyA), an immunosuppressive agent, is mandatory part of post-transplantation therapy protocols. CyA shows large interindividual and intraindividual pharmacokinetic (PK) variability, has a narrow therapeutic range and several factors has already been identified as sources of variability. Proactive dosing strategies to achieve and maintain predefined CyA levels, via therapeutic drug monitoring (TDM), may prevent graft rejection and minimize serious side effects [1,2]. Data obtained during TDM can be used for describing PK model on both population and individual level while taking into account individual characteristics. Furthermore, that model could inform optimal CyA dosing via Bayesian-TDM approach. Objectives: We aimed in developing CyA population PK model and address sources of PK variabilities in order to explain observable differences in the concentrations of the drug. In addition, the objective of the study is to assess the effect of PK on the response to CyA therapy using modelling approach. Methods: Data regarding dosage regimens, CyA blood concentrations, concomitant medications and laboratory findings of significance in kidney transplant paediatric patients were collected from their medical history. Drug concentration was measured in whole blood samples, and the samples were drawn before (Ctrough) and 2 hours after the morning dose (C2). Population pharmacokinetic analyses was performed using nonlinear mixed effects modelling software – NONMEM® (version 7.4) with first-order conditional estimation method with interaction (FOCE-I). NONMEM outputs were handled in R software (graphical diagnostics). We tried fitting one- and two-compartment to concentration-time data. Covariate model building was performed using stepwise covariate procedure (SCM). Covariates that were tested are age, weight (WT), serum creatinine levels (CR) haematocrit (HCT) (continuous covariates). Influence of categorical covariates was also examined – gender (GEND) and type of transplanted graft - live or cadaveric transplantation (TRANS). Model appropriateness has been performed using numerical and visual approaches. Results: : In total, 58 patients aged 2-25 years (mean± sd: 12.46±0.78), mainly paediatrics (79.31% up to 18 years) were included in the analysis. We have analysed 496 concentrations obtained during up to one year post-transplant period. Mean values of C0 and C2 are 126.1±4.37 ng/ml and 825.8±20.32 ng/ml, respectively. One-compartment model with first order absorption best described the data. Typical values of clearance (CL), volume (V), and absorption rate constant (Ka) from covariate model were 14.2 L/h, 1.94 L/kg, 1.3 1/h, respectively. Tested PK parameter-covariate relations that caused the significant drop in objective function value are influence of WT, CR and HCT on CL, and WT on volume V. Interindividual variability (IIV) on CL and V, after inclusion of covariates was 22.6 % and 25.3% (in the base model the IIV was 33.5% and 36.5%, respectively). In the further analyses, population pharmacokinetic/pharmacodynamic (popPK/PD) will be developed. Conclusions: The results regarding PK parameters are in accordance with a published study in a similar population (paediatric transplant patients) [3]. Knowing individual parameters values can help maximize the benefits of drug therapy and minimize side effects, which is a cornerstone of safe and effective therapy. References: [1] Midtvedt K. Therapeutic drug monitoring of cyclosporine. Transplant Proc. 2004;36(2 Suppl):430S-433S. doi:10.1016/j.transproceed.2004.01.025. [2] Kang JS, Lee MH. Overview of therapeutic drug monitoring. Korean J Intern Med. 2009;24(1):1-10. doi:10.3904/kjim.2009.24.1.1 [3] Fanta S, Jönsson S, Backman JT, Karlsson MO, Hoppu K. Developmental pharmacokinetics of ciclosporin-a population pharmacokinetic study in paediatric renal transplant candidates. Br J Clin Pharmacol. 2007;64(6):772-84. doi: 10.1111/j.1365-2125.2007.03003.x C3 - Page. Abstracts of the Annual Meeting of the Population Approach Group in Europe T1 - Population pharmacokinetic modelling of cyclosporine in paediatric kidney transplant patients using routine TDM data UR - https://hdl.handle.net/21.15107/rcub_farfar_4819 ER -
@conference{ author = "Roganović, Maša and Cvetković, Mirjana and Gojković, Ivana and Spasojević, Brankica and Kostić, Mirjana and Miljković, Branislava and Vučićević, Katarina", year = "2021", abstract = "Introduction: Cyclosporine (CyA), an immunosuppressive agent, is mandatory part of post-transplantation therapy protocols. CyA shows large interindividual and intraindividual pharmacokinetic (PK) variability, has a narrow therapeutic range and several factors has already been identified as sources of variability. Proactive dosing strategies to achieve and maintain predefined CyA levels, via therapeutic drug monitoring (TDM), may prevent graft rejection and minimize serious side effects [1,2]. Data obtained during TDM can be used for describing PK model on both population and individual level while taking into account individual characteristics. Furthermore, that model could inform optimal CyA dosing via Bayesian-TDM approach. Objectives: We aimed in developing CyA population PK model and address sources of PK variabilities in order to explain observable differences in the concentrations of the drug. In addition, the objective of the study is to assess the effect of PK on the response to CyA therapy using modelling approach. Methods: Data regarding dosage regimens, CyA blood concentrations, concomitant medications and laboratory findings of significance in kidney transplant paediatric patients were collected from their medical history. Drug concentration was measured in whole blood samples, and the samples were drawn before (Ctrough) and 2 hours after the morning dose (C2). Population pharmacokinetic analyses was performed using nonlinear mixed effects modelling software – NONMEM® (version 7.4) with first-order conditional estimation method with interaction (FOCE-I). NONMEM outputs were handled in R software (graphical diagnostics). We tried fitting one- and two-compartment to concentration-time data. Covariate model building was performed using stepwise covariate procedure (SCM). Covariates that were tested are age, weight (WT), serum creatinine levels (CR) haematocrit (HCT) (continuous covariates). Influence of categorical covariates was also examined – gender (GEND) and type of transplanted graft - live or cadaveric transplantation (TRANS). Model appropriateness has been performed using numerical and visual approaches. Results: : In total, 58 patients aged 2-25 years (mean± sd: 12.46±0.78), mainly paediatrics (79.31% up to 18 years) were included in the analysis. We have analysed 496 concentrations obtained during up to one year post-transplant period. Mean values of C0 and C2 are 126.1±4.37 ng/ml and 825.8±20.32 ng/ml, respectively. One-compartment model with first order absorption best described the data. Typical values of clearance (CL), volume (V), and absorption rate constant (Ka) from covariate model were 14.2 L/h, 1.94 L/kg, 1.3 1/h, respectively. Tested PK parameter-covariate relations that caused the significant drop in objective function value are influence of WT, CR and HCT on CL, and WT on volume V. Interindividual variability (IIV) on CL and V, after inclusion of covariates was 22.6 % and 25.3% (in the base model the IIV was 33.5% and 36.5%, respectively). In the further analyses, population pharmacokinetic/pharmacodynamic (popPK/PD) will be developed. Conclusions: The results regarding PK parameters are in accordance with a published study in a similar population (paediatric transplant patients) [3]. Knowing individual parameters values can help maximize the benefits of drug therapy and minimize side effects, which is a cornerstone of safe and effective therapy. References: [1] Midtvedt K. Therapeutic drug monitoring of cyclosporine. Transplant Proc. 2004;36(2 Suppl):430S-433S. doi:10.1016/j.transproceed.2004.01.025. [2] Kang JS, Lee MH. Overview of therapeutic drug monitoring. Korean J Intern Med. 2009;24(1):1-10. doi:10.3904/kjim.2009.24.1.1 [3] Fanta S, Jönsson S, Backman JT, Karlsson MO, Hoppu K. Developmental pharmacokinetics of ciclosporin-a population pharmacokinetic study in paediatric renal transplant candidates. Br J Clin Pharmacol. 2007;64(6):772-84. doi: 10.1111/j.1365-2125.2007.03003.x", journal = "Page. Abstracts of the Annual Meeting of the Population Approach Group in Europe", title = "Population pharmacokinetic modelling of cyclosporine in paediatric kidney transplant patients using routine TDM data", url = "https://hdl.handle.net/21.15107/rcub_farfar_4819" }
Roganović, M., Cvetković, M., Gojković, I., Spasojević, B., Kostić, M., Miljković, B.,& Vučićević, K.. (2021). Population pharmacokinetic modelling of cyclosporine in paediatric kidney transplant patients using routine TDM data. in Page. Abstracts of the Annual Meeting of the Population Approach Group in Europe. https://hdl.handle.net/21.15107/rcub_farfar_4819
Roganović M, Cvetković M, Gojković I, Spasojević B, Kostić M, Miljković B, Vučićević K. Population pharmacokinetic modelling of cyclosporine in paediatric kidney transplant patients using routine TDM data. in Page. Abstracts of the Annual Meeting of the Population Approach Group in Europe. 2021;. https://hdl.handle.net/21.15107/rcub_farfar_4819 .
Roganović, Maša, Cvetković, Mirjana, Gojković, Ivana, Spasojević, Brankica, Kostić, Mirjana, Miljković, Branislava, Vučićević, Katarina, "Population pharmacokinetic modelling of cyclosporine in paediatric kidney transplant patients using routine TDM data" in Page. Abstracts of the Annual Meeting of the Population Approach Group in Europe (2021), https://hdl.handle.net/21.15107/rcub_farfar_4819 .