Prediction of valproate serum concentrations in adult psychiatric patients using Bayesian model estimations with NPEM2 population pharmacokinetic parameters. 1999

E Puentes, and T Puzantian, and B L Lum
Department of Pharmacy, Veterans Affairs Palo Alto Health Care System, California, USA.

Valproate serum concentrations between 45 and 125 microg/mL are associated with the drug's efficacy in acute mania. Adaptive control dosing of valproate has not been fully studied in psychiatry. The objective of this study was to derive population pharmacokinetic (PK) parameters for valproate in healthy volunteers and to test the ability of these PK parameters to estimate concentrations in adult psychiatric patients using a Bayesian program. Population PK parameters for oral valproate were estimated from 18 PK studies in six healthy volunteers (1) using NPEM2. A Bayesian PK program using these population parameters was used to predict valproate concentration-time points in a second cohort of 21 adult psychiatry patients using 0, 1, or 2 prior concentrations. Estimated population parameters (mean +/- SD) were: Ka, 1.15+/-1.75/h; V, 0.14+/-0.042 L/Kg; and CL, 0.902+/-0.133 L/h. Bayesian valproate estimations using these parameters were negatively biased (underestimations) using zero prior concentration and unbiased using 1 or 2 prior concentrations. Mean error values (95% CI) in microg/mL for predictions using 0, 1, or 2 prior concentration-time points were -12.0 (-22.5, -1.5), -9.5 (-19.1, 0.1), and -2.5 (-11.1, 6.1), respectively, and mean absolute error values in microg/mL (95% CI) were 19.8 (12.6, 27.1), 16.3 (9.4, 23.3), and 10.1 (4.9, 15.2), respectively. Population parameters derived from healthy adult volunteers provided biased predictions of valproate concentrations in adult psychiatric patients. However, estimates using 1 or 2 valproate concentration time points predicted future concentrations that were precise and unbiased, given the wide therapeutic target range.

UI MeSH Term Description Entries
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D011159 Population Surveillance Ongoing scrutiny of a population (general population, study population, target population, etc.), generally using methods distinguished by their practicability, uniformity, and frequently their rapidity, rather than by complete accuracy. Surveillance, Population
D004305 Dose-Response Relationship, Drug The relationship between the dose of an administered drug and the response of the organism to the drug. Dose Response Relationship, Drug,Dose-Response Relationships, Drug,Drug Dose-Response Relationship,Drug Dose-Response Relationships,Relationship, Drug Dose-Response,Relationships, Drug Dose-Response
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000222 Adaptation, Physiological The non-genetic biological changes of an organism in response to challenges in its ENVIRONMENT. Adaptation, Physiologic,Adaptations, Physiologic,Adaptations, Physiological,Adaptive Plasticity,Phenotypic Plasticity,Physiological Adaptation,Physiologic Adaptation,Physiologic Adaptations,Physiological Adaptations,Plasticity, Adaptive,Plasticity, Phenotypic
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly
D000369 Aged, 80 and over Persons 80 years of age and older. Oldest Old
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D001714 Bipolar Disorder A major affective disorder marked by severe mood swings (manic or major depressive episodes) and a tendency to remission and recurrence. Affective Psychosis, Bipolar,Bipolar Disorder Type 1,Bipolar Disorder Type 2,Bipolar Mood Disorder,Depression, Bipolar,Manic Depression,Manic Disorder,Manic-Depressive Psychosis,Psychosis, Manic-Depressive,Type 1 Bipolar Disorder,Type 2 Bipolar Disorder,Psychoses, Manic-Depressive,Bipolar Affective Psychosis,Bipolar Depression,Bipolar Disorders,Bipolar Mood Disorders,Depression, Manic,Depressions, Manic,Disorder, Bipolar,Disorder, Bipolar Mood,Disorder, Manic,Manic Depressive Psychosis,Manic Disorders,Mood Disorder, Bipolar,Psychoses, Bipolar Affective,Psychoses, Manic Depressive,Psychosis, Bipolar Affective,Psychosis, Manic Depressive

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