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Impact of nutritional factors on the pharmacokinetics of antipsychotics - a systematic review
Michael Schepp1, Melanie Engel1, Anna Hirschbeck1
1Department of Psychiatry, Psychotherapy and Psychosomatics of the University Augsburg, Bezirkskrankenhaus Augsburg, Medical Faculty, University of Augsburg, Augsburg, Germany.
Introduction:
Nutritional habits and specific dietary components can significantly alter the pharmacokinetics (PK) of antipsychotics, potentially leading in worst cases to therapeutic failure or increased toxicity. Despite its clinical importance, a comprehensive systematic overview of these interactions remains a gap in current psychiatric research. This systematic review aims to evaluate how food intake or specific nutrients influence the PK parameters of antipsychotic medications.
Methods:
A systematic search was conducted across Web of Science, PubMed, Cochrane Database, and Scopus. Out of 18,598 identified records, 48 studies were included for data extraction which focused on Cmax, Area under the curve (AUC), time to maximum concentration (tmax), and t1/2 under varying nutritional conditions (e.g., fasting vs. fed, caffeine, and vitamin D levels).
Results:
The analysis of the included studies reveals highly drug-specific effects. For several second-generation antipsychotics, food intake is critical for bioavailability; for instance, lurasidone and ziprasidone exposure AUC increases 2- to 3-fold when administered with a meal of at least 350-500 kcal. Conversely, amisulpride absorption is significantly reduced by food intake (e.g., ∼25% reduction in AUC). Furthermore, clozapine metabolism may be influenced by seasonal vitamin D variations and also caffeine intake, which may be mediated by affecting the metabolism of Cytochrome P450 enzymes.
Conclusions:
Nutritional factors are a significant source of PK variability in antipsychotic treatment. The results underscore the necessity of standardized administration guidelines (e.g., "take with food" for ziprasidone or "fasted" for amisulpride) to ensure predictable plasma levels and optimize therapeutic outcomes in clinical practice.
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