ArticleJournal of psychopharmacology (Oxford, England)2026
A one-compartment model provides benchmark Lithium dose prediction.
Article in Journal of psychopharmacology (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Correlation Analysis of Blood Lithium Metabolism Kinetics and Concentration-to-Dose Ratio in Patients With Hypertension and Manic Episodes.Human psychopharmacology · 2026Article
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6 authors.
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Abstract
backgroundLithium is an effective treatment for recurrent affective disorders, but it has a narrow therapeutic window and requires regular serum concentration monitoring, especially during periods of dose titration. Numerous attempts have been made to develop dose prediction methods to facilitate initiation and swift achievement of effective levels, but these typically lack sufficient accuracy and can be challenging to implement in practice.
aimsDevelop a pharmacokinetic model of lithium to enable accurate dose prediction which is adaptable for clinical practice.
methodsThe calculator was developed from a one-compartment model, which assumes that lithium distributes into total body water and requires only simple body measurements (age, sex, height and weight) as input variables. Its performance was compared to six commonly cited dose prediction methods in patients with bipolar disorder taking lithium, using two independent research samples from the United Kingdom (
resultsOur one-compartment model performed better than the previous models, accurately predicting the required lithium dose within one 200 mg lithium carbonate tablet. The mean prediction error was 10 mg (SD = 148 mg) in this sample of euthymic subjects taking stable doses of lithium sampled at steady state.
conclusionsThis model sets a new benchmark for lithium dose prediction accuracy and requires only simple body measurements. Further validation work in larger, diverse samples and future developments, such as the ability of the model to back-calculate levels from samples taken outside the recommended 12-hour window, may support its translation and use in practice.
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