External Evaluation of Risperidone Population Pharmacokinetic Models Using Opportunistic Pediatric Data
Risperidone is approved to treat schizophrenia in adolescents and autistic disorder and bipolar mania in children and adolescents. It is also used off-label in younger children for various psychiatric disorders. Several population pharmacokinetic models of risperidone and 9-OH-risperidone have been...
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| Format: | Article |
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Frontiers Media S.A.
2022-03-01
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| Series: | Frontiers in Pharmacology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2022.817276/full |
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| author | Eleni Karatza Samit Ganguly Samit Ganguly Chi D. Hornik William J. Muller Amira Al-Uzri Laura James Stephen J. Balevic Daniel Gonzalez |
| author_facet | Eleni Karatza Samit Ganguly Samit Ganguly Chi D. Hornik William J. Muller Amira Al-Uzri Laura James Stephen J. Balevic Daniel Gonzalez |
| author_sort | Eleni Karatza |
| collection | DOAJ |
| description | Risperidone is approved to treat schizophrenia in adolescents and autistic disorder and bipolar mania in children and adolescents. It is also used off-label in younger children for various psychiatric disorders. Several population pharmacokinetic models of risperidone and 9-OH-risperidone have been published. The objectives of this study were to assess whether opportunistically collected pediatric data can be used to evaluate risperidone population pharmacokinetic models externally and to identify a robust model for precision dosing in children. A total of 103 concentrations of risperidone and 112 concentrations of 9-OH-risperidone, collected from 62 pediatric patients (0.16–16.8 years of age), were used in the present study. The predictive performance of five published population pharmacokinetic models (four joint parent-metabolite models and one parent only) was assessed for accuracy and precision of the predictions using statistical criteria, goodness of fit plots, prediction-corrected visual predictive checks (pcVPCs), and normalized prediction distribution errors (NPDEs). The tested models produced similarly precise predictions (Root Mean Square Error [RMSE]) ranging from 0.021 to 0.027 nmol/ml for risperidone and 0.053–0.065 nmol/ml for 9-OH-risperidone). However, one of the models (a one-compartment mixture model with clearance estimated for three subpopulations) developed with a rich dataset presented fewer biases (Mean Percent Error [MPE, %] of 1.0% vs. 101.4, 146.9, 260.4, and 292.4%) for risperidone. In contrast, a model developed with fewer data and a more similar population to the one used for the external evaluation presented fewer biases for 9-OH-risperidone (MPE: 17% vs. 69.9, 47.8, and 82.9%). None of the models evaluated seemed to be generalizable to the population used in this analysis. All the models had a modest predictive performance, potentially suggesting that sources of inter-individual variability were not entirely captured and that opportunistic data from a highly heterogeneous population are likely not the most appropriate data to evaluate risperidone models externally. |
| first_indexed | 2024-12-12T21:26:56Z |
| format | Article |
| id | doaj.art-1e401b42d0c7455caf1a8461cdd9224a |
| institution | Directory Open Access Journal |
| issn | 1663-9812 |
| language | English |
| last_indexed | 2024-12-12T21:26:56Z |
| publishDate | 2022-03-01 |
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| series | Frontiers in Pharmacology |
| spelling | doaj.art-1e401b42d0c7455caf1a8461cdd9224a2022-12-22T00:11:26ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122022-03-011310.3389/fphar.2022.817276817276External Evaluation of Risperidone Population Pharmacokinetic Models Using Opportunistic Pediatric DataEleni Karatza0Samit Ganguly1Samit Ganguly2Chi D. Hornik3William J. Muller4Amira Al-Uzri5Laura James6Stephen J. Balevic7Daniel Gonzalez8Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United StatesDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United StatesRegeneron Pharmaceuticals, Inc., Tarrytown, NY, United StatesDuke Clinical Research Institute, Durham, NC, United StatesAnn and Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, United StatesOregon Health and Science University, Portland, OR, United StatesArkansas Children’s Hospital Research Institute and the University of Arkansas for Medical Sciences, Little Rock, AR, United StatesDuke Clinical Research Institute, Durham, NC, United StatesDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United StatesRisperidone is approved to treat schizophrenia in adolescents and autistic disorder and bipolar mania in children and adolescents. It is also used off-label in younger children for various psychiatric disorders. Several population pharmacokinetic models of risperidone and 9-OH-risperidone have been published. The objectives of this study were to assess whether opportunistically collected pediatric data can be used to evaluate risperidone population pharmacokinetic models externally and to identify a robust model for precision dosing in children. A total of 103 concentrations of risperidone and 112 concentrations of 9-OH-risperidone, collected from 62 pediatric patients (0.16–16.8 years of age), were used in the present study. The predictive performance of five published population pharmacokinetic models (four joint parent-metabolite models and one parent only) was assessed for accuracy and precision of the predictions using statistical criteria, goodness of fit plots, prediction-corrected visual predictive checks (pcVPCs), and normalized prediction distribution errors (NPDEs). The tested models produced similarly precise predictions (Root Mean Square Error [RMSE]) ranging from 0.021 to 0.027 nmol/ml for risperidone and 0.053–0.065 nmol/ml for 9-OH-risperidone). However, one of the models (a one-compartment mixture model with clearance estimated for three subpopulations) developed with a rich dataset presented fewer biases (Mean Percent Error [MPE, %] of 1.0% vs. 101.4, 146.9, 260.4, and 292.4%) for risperidone. In contrast, a model developed with fewer data and a more similar population to the one used for the external evaluation presented fewer biases for 9-OH-risperidone (MPE: 17% vs. 69.9, 47.8, and 82.9%). None of the models evaluated seemed to be generalizable to the population used in this analysis. All the models had a modest predictive performance, potentially suggesting that sources of inter-individual variability were not entirely captured and that opportunistic data from a highly heterogeneous population are likely not the most appropriate data to evaluate risperidone models externally.https://www.frontiersin.org/articles/10.3389/fphar.2022.817276/fullrisperidonepediatricspharmacokineticsprecision dosingpopulation modeling |
| spellingShingle | Eleni Karatza Samit Ganguly Samit Ganguly Chi D. Hornik William J. Muller Amira Al-Uzri Laura James Stephen J. Balevic Daniel Gonzalez External Evaluation of Risperidone Population Pharmacokinetic Models Using Opportunistic Pediatric Data Frontiers in Pharmacology risperidone pediatrics pharmacokinetics precision dosing population modeling |
| title | External Evaluation of Risperidone Population Pharmacokinetic Models Using Opportunistic Pediatric Data |
| title_full | External Evaluation of Risperidone Population Pharmacokinetic Models Using Opportunistic Pediatric Data |
| title_fullStr | External Evaluation of Risperidone Population Pharmacokinetic Models Using Opportunistic Pediatric Data |
| title_full_unstemmed | External Evaluation of Risperidone Population Pharmacokinetic Models Using Opportunistic Pediatric Data |
| title_short | External Evaluation of Risperidone Population Pharmacokinetic Models Using Opportunistic Pediatric Data |
| title_sort | external evaluation of risperidone population pharmacokinetic models using opportunistic pediatric data |
| topic | risperidone pediatrics pharmacokinetics precision dosing population modeling |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2022.817276/full |
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