A pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposure
Abstract Estimating early exposure of drugs used for the treatment of emergent conditions is challenging because blood sampling to measure concentrations is difficult. The objective of this work was to evaluate predictive performance of two early concentrations and prior pharmacokinetic (PK) informa...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-07-01
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| Series: | Clinical and Translational Science |
| Online Access: | https://doi.org/10.1111/cts.13004 |
| _version_ | 1818655415037067264 |
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| author | Abhishek G. Sathe Richard C. Brundage Vijay Ivaturi James C. Cloyd James M. Chamberlain Jordan J. Elm Robert Silbergleit Jaideep Kapur Lisa D. Coles |
| author_facet | Abhishek G. Sathe Richard C. Brundage Vijay Ivaturi James C. Cloyd James M. Chamberlain Jordan J. Elm Robert Silbergleit Jaideep Kapur Lisa D. Coles |
| author_sort | Abhishek G. Sathe |
| collection | DOAJ |
| description | Abstract Estimating early exposure of drugs used for the treatment of emergent conditions is challenging because blood sampling to measure concentrations is difficult. The objective of this work was to evaluate predictive performance of two early concentrations and prior pharmacokinetic (PK) information for estimating early exposure. The performance of a modeling approach was compared with a noncompartmental analysis (NCA). A simulation study was performed using literature‐based models for phenytoin (PHT), levetiracetam (LEV), and valproic acid (VPA). These models were used to simulate rich concentration‐time profiles from 0 to 2 h. Profiles without residual unexplained variability (RUV) were used to obtain the true partial area under the curve (pAUC) until 2 h after the start of drug infusion. From the profiles with the RUV, two concentrations per patient were randomly selected. These concentrations were analyzed under a population model to obtain individual population PK (PopPK) pAUCs. The NCA pAUCs were calculated using a linear trapezoidal rule. Percent prediction errors (PPEs) for the PopPK pAUCs and NCA pAUCs were calculated. A PPE within ±20% of the true value was considered a success and the number of successes was obtained for 100 simulated datasets. For PHT, LEV, and VPA, respectively, the median value of the success statistics obtained using the PopPK approach of 81%, 92%, and 88% were significantly higher than the 72%, 80%, and 67% using the NCA approach (p < 0.05; Mann–Whitney U test). This study provides a means by which early exposure can be estimated with good precision from two concentrations and a PopPK approach. It can be applied to other settings in which early exposures are of interest. |
| first_indexed | 2024-12-17T03:09:19Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 1752-8054 1752-8062 |
| language | English |
| last_indexed | 2024-12-17T03:09:19Z |
| publishDate | 2021-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Clinical and Translational Science |
| spelling | doaj.art-f8f4a9c3744f4a54a8df1d458a787d4f2022-12-21T22:05:53ZengWileyClinical and Translational Science1752-80541752-80622021-07-011441444145110.1111/cts.13004A pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposureAbhishek G. Sathe0Richard C. Brundage1Vijay Ivaturi2James C. Cloyd3James M. Chamberlain4Jordan J. Elm5Robert Silbergleit6Jaideep Kapur7Lisa D. Coles8Department of Experimental and Clinical Pharmacology College of Pharmacy Minneapolis Minnesota USADepartment of Experimental and Clinical Pharmacology College of Pharmacy Minneapolis Minnesota USACenter for Translational Medicine University of Maryland College Park Maryland USADepartment of Experimental and Clinical Pharmacology College of Pharmacy Minneapolis Minnesota USADivision of Emergency Medicine Children’s National Hospital Washington DC USADepartment of Public Health Science Medical University of South Carolina Charleston South Carolina USADepartment of Emergency Medicine University of Michigan Ann Arbor Michigan USADepartment of Neurology and Department of Neuroscience Brain Institute University of Virginia Charlottesville Virginia USADepartment of Experimental and Clinical Pharmacology College of Pharmacy Minneapolis Minnesota USAAbstract Estimating early exposure of drugs used for the treatment of emergent conditions is challenging because blood sampling to measure concentrations is difficult. The objective of this work was to evaluate predictive performance of two early concentrations and prior pharmacokinetic (PK) information for estimating early exposure. The performance of a modeling approach was compared with a noncompartmental analysis (NCA). A simulation study was performed using literature‐based models for phenytoin (PHT), levetiracetam (LEV), and valproic acid (VPA). These models were used to simulate rich concentration‐time profiles from 0 to 2 h. Profiles without residual unexplained variability (RUV) were used to obtain the true partial area under the curve (pAUC) until 2 h after the start of drug infusion. From the profiles with the RUV, two concentrations per patient were randomly selected. These concentrations were analyzed under a population model to obtain individual population PK (PopPK) pAUCs. The NCA pAUCs were calculated using a linear trapezoidal rule. Percent prediction errors (PPEs) for the PopPK pAUCs and NCA pAUCs were calculated. A PPE within ±20% of the true value was considered a success and the number of successes was obtained for 100 simulated datasets. For PHT, LEV, and VPA, respectively, the median value of the success statistics obtained using the PopPK approach of 81%, 92%, and 88% were significantly higher than the 72%, 80%, and 67% using the NCA approach (p < 0.05; Mann–Whitney U test). This study provides a means by which early exposure can be estimated with good precision from two concentrations and a PopPK approach. It can be applied to other settings in which early exposures are of interest.https://doi.org/10.1111/cts.13004 |
| spellingShingle | Abhishek G. Sathe Richard C. Brundage Vijay Ivaturi James C. Cloyd James M. Chamberlain Jordan J. Elm Robert Silbergleit Jaideep Kapur Lisa D. Coles A pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposure Clinical and Translational Science |
| title | A pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposure |
| title_full | A pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposure |
| title_fullStr | A pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposure |
| title_full_unstemmed | A pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposure |
| title_short | A pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposure |
| title_sort | pharmacokinetic simulation study to assess the performance of a sparse blood sampling approach to quantify early drug exposure |
| url | https://doi.org/10.1111/cts.13004 |
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