Designing and characterizing first Iranian study evaluating serum levels of lithium in patients for population pharmacokinetics (FIRELOLIPOP): baseline and first report

Sci Rep. 2025 May 3;15(1):15514. doi: 10.1038/s41598-025-99698-y.

ABSTRACT

Bipolar disorder (BD) is a chronic psychiatric illness characterized by recurrent manic and depressive episodes, leading to significant impairment. Lithium remains a key treatment for BD, particularly in relapse prevention. However, its narrow therapeutic range and inter-individual pharmacokinetic variability necessitate careful dosing. This study aims to establish a suitable platform to investigate the pharmacokinetics of lithium in hospitalized patients with BD in Mashhad, Iran, to optimize therapeutic use and minimize toxicity. This cross-sectional study was conducted at Ibn Sina Hospital, Mashhad, between 2016 and 2022. Hospitalized patients diagnosed with BD and receiving lithium therapy were included. Clinical, demographic, and laboratory data were collected, including lithium serum levels, renal function parameters, and co-administered medications. Advanced data pre-processing techniques were applied to ensure accuracy and facilitate future pharmacokinetic modeling. A total of 701 patients (53.1% male, mean age: 38.0 SD: ± 12.2 years) with 795 hospitalization episodes were analyzed. The mean lithium serum concentration was 0.65 ± 0.30 mEq/L. Thyroid disorders (5.9%) and diabetes (5.6%) were the most common comorbidities. The mean duration of hospitalization during lithium treatment was 21.7 ± 10.8 days. Sodium valproate was the most frequently co-prescribed medication (n = 553), followed by lorazepam (n = 468) and risperidone (n = 458). Lithium dosing showed considerable variability, emphasizing the need for individualized therapeutic strategies. This study provides valuable insights into lithium pharmacokinetics in Iranian BD patients. The findings highlight the necessity of personalized dosing approaches to enhance efficacy and reduce adverse effects. Future research should incorporate pharmacokinetic modeling and machine learning to refine lithium therapy.

PMID:40319121 | DOI:10.1038/s41598-025-99698-y