Browse by author
Lookup NU author(s): Dr Oisín KavanaghORCiD, Dr David CousinsORCiD, Dr Victoria Wing
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).Background: Lithium 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. Aims: Develop a pharmacokinetic model of lithium to enable accurate dose prediction which is adaptable for clinical practice. Methods: The 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 (n = 40) and Germany (n = 18). Results: Our 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. Conclusions: This 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.
Author(s): Kavanagh ON, Asprey E, Edelmann KA, Ritter P, Cousins DA, Wing VC
Publication type: Article
Publication status: Published
Journal: Journal of Psychopharmacology
Year: 2025
Pages: epub ahead of print
Online publication date: 29/10/2025
Acceptance date: 02/04/2018
Date deposited: 10/11/2025
ISSN (print): 0269-8811
ISSN (electronic): 1461-7285
Publisher: Sage Publications Ltd.
URL: https://doi.org/10.1177/02698811251378508
DOI: 10.1177/02698811251378508
Altmetrics provided by Altmetric
