has been used and considered as a first-line therapy for acute and maintenance
treatment of mania in bipolar disorder despite the presence of other
mood-stabilizers. Lithium has narrow therapeutic index and patients may
experience poor response and/or toxicities that are both dose and concentration
dependent. Therefore, estimation lithium pharmacokinetics parameters and the
appropriate dose to achieve the desired level are necessary to optimize lithium
therapy for all patients. Thus, the objective of this study is to determine the population pharmacokinetics
of tacrolimus in Saudi bipolar
patients and to identify factors that explain variability.
Method: A retrospective chart
review was performed at King Saud University Medical City on bipolar patients
who received oral lithium. The average and standard deviation for age,
weight, serum creatinine, total daily dose of lithium, and trough levels in our
patient population were analyzed. The
population pharmacokinetic models were developed using Monolix 4.4. After the appropriate base model was
established, five covariates were tested, specifically age, gender, weight,
serum creatinine, and creatinine
clearance. For covariate testing, we started by plotting the individual
pharmacokinetic parameters vs. covariates to screen for potentially significant
correlations. Then, we performed a stepwise regression analysis to test the
significant covariates identified in step 1 using the log-likelihood ratio
Results: The analysis included a total of 170 lithium
plasma concentrations from 31 (77% female) patients with a mean (±SD) age of 36.3 ± 10.5 years and body weight of 82.7 ± 14.8 kg.
The patients received a lithium total daily dose (TDD) of 750 ± 260 mg/day,
which resulted in trough concentration of 0.73 ± 0.26 mmol/L. The mean
creatinine clearance (Clcr) for the subjects was 119.2 ± 32.8 ml/min. The data
were adequately described by two compartment open model with linear absorption
and elimination. Due to single point sparse data, not all parameters and their
inter-individual variability could be determined. Thus, lithium clearance (CL)
and its inter-individual variability were determined while other
pharmacokinetic parameters were fixed using available literature information. Average
parameter estimates for lithium CL, volume of the central compartment (V1), volume of the
peripheral compartment (V2), and intercompartmental
clearance (Q) were 1.15 L/h, 22.1 L (fixed), 3.35 L (fixed), and 0.44 L/h
(fixed), respectively. The inter-individual variability (coefficients of
variation) in CL was 42%. The
most significant covariate on lithium CL was found to be creatinine clearance.
The population CL of lithium in the final model was expressed as CL =
1.15 × (Clcr/119.2)0.117.
The population pharmacokinetic model of lithium in Saudi bipolar patients was
established and significant covariate on the lithium model was identified. This
model showed the significant inter-individual variability between subjects. In
addition, our findings showed that creatinine clearance is the most significant covariate on lithium CL.
These findings offering basis for rational
individualization of lithium dosing regimens. Further studies are required to
understand the factors that may influence the pharmacokinetics of lithium and
may assist in drug dosage decisions.