Perez-Castello, I(1); Mangas-Sanjuan, V(2); González-GarcÃa, I.(2,3); Gonzalez-Alvarez, I(2); Marco-Garbayo, JL(1); Troconiz, I(4); Bermejo, M (2).
(1) Hospital of Gandia; (2) Pharmacokinetics and Pharmaceutical Technology Area, Miguel Hernandez University; (3) Pharmacokinetics and Pharmaceutical Technology Department, University of Valencia; (4) Pharmacometrics and Systems Pharmacology. University of Navarra.
Introduction: Lithium is an antidepressant used as primary treatment for the prevention of episode recurrences in bipolar disorder, acute treatment of mania and to a lesser extent depression. Due to its relatively narrow therapeutic range and high inter-individual (IIV) and residual (RSV) variability, routine therapeutic drug monitoring (TDM) of lithium is therefore necessary to ensure dosing schedules with satisfactory result and without severe side effects and toxicity.
Methods: 96 psychiatric patients were enrolled in this. Lithium carbonate was administrated to all patients at different dose levels (200, 300, 400, 600 and 800 mg) and administration intervals (8, 12 and 24 h). Different demographic, biochemical and anthropometric covariates were selected. Patients received several treatment cycles and one plasma concentration measurement for each patient was obtained always before starting next cycle (pre-dose) at steady state. Experimental data were fitted using non-linear mixed-effects modelling implemented in NONMEM 7.2. Different approaches were implemented in order to capture the concentration profiles observed: (1) addition of IIV on CL, (2) use of Prior information and (3) IOV on bioavailability dose fraction (F1). Model selection was based on the lowest and significant OFV and goodness-of-fit (GOF) plots. Covariate analysis was performed manually, adding the covariates into the final base model. Final model evaluation was carried out using prediction corrected-visual predictive check (pc-VPC) (n=1000) and Bootstrap (n=1000) analysis.
Results: Plasma observations were described using a two-compartment model. Creatinine clearance (CrCl) was selected as significant covariate on typical clearance parameter with a power relationship. Individual concentration-time course profiles from selected individuals were represented.
Conclusions: The addition of inter-occasion variability on the bioavailability dose fraction (F1) allowed for a better characterization of the individual profiles and to assess drug compliance. Nearly half of the F1 estimated (46%) were different from 1±10%, representing that patients did not meet the prescribed dose regimen along all monitored cycles. The final model was able to characterize the number of individuals/observations out of the therapeutic interval with more precision compared to the other approaches proposed.
Reference: PAGE 24 () Abstr 3384 [www.page-meeting.org/?abstract=3384]
Poster: Drug/Disease modeling - Absorption & PBPK