Aripiprazole, a novel antipsychotic drug, is metabolized by CYP3A4 and CYP2D6 forming mainly its active metabolite dehydroaripiprazole. In this study, aripiprazole and dehydroaripiprazole serum levels of psychiatric patients were measured and related to dose, comedication, and clinical effects including therapeutic and side effects. Patients were treated with mean doses of 20 +/- 8 mg/day of aripiprazole (median 15 mg, range 7.5-60 mg). Serum levels correlated significantly with the dose (r = 0.419; P < 0.01), with a mean value of aripiprazole of 214 +/- 140 ng/ml. Mean concentrations of the active metabolite dehydroaripiprazole amounted to 40% of the parent compound. Comedication with CYP3A4 and CYP2D6 inducers or inhibitors changed serum levels up to 51%. Improvement was best in patients with a serum level between 150 and 300 ng/ml. No or only mild side effects were detected in patients, with aripiprazole plasma concentrations between 110 and 249 ng/ml. A total of 32% of the patients who received no other antipsychotic drug besides aripiprazole reported side effects; tension being the most frequent one. Since serum levels of aripiprazole and dehydroaripiprazole were highly variable between individuals, and distinct ranges were associated with good therapeutic response and minimal side effects, it seems likely that therapeutic drug monitoring can be helpful to improve the antipsychotic drug therapy.

BackgroundTreatment algorithms are considered as key to improve outcomes by enhancing the quality of care. This is the first randomized controlled study to evaluate the clinical effect of algorithm-guided treatment in inpatients with major depressive disorder.MethodsInpatients, aged 18 to 70 years with major depressive disorder from 10 German psychiatric departments were randomized to 5 different treatment arms (from 2000 to 2005), 3 of which were standardized stepwise drug treatment algorithms (ALGO). The fourth arm proposed medications and provided less specific recommendations based on a computerized documentation and expert system (CDES), the fifth arm received treatment as usual (TAU). ALGO included 3 different second-step strategies: lithium augmentation (ALGO LA), antidepressant dose-escalation (ALGO DE), and switch to a different antidepressant (ALGO SW). Time to remission (21-item Hamilton Depression Rating Scale ≤9) was the primary outcome.ResultsTime to remission was significantly shorter for ALGO DE (n=91) compared with both TAU (n=84) (HR=1.67; P=.014) and CDES (n=79) (HR=1.59; P=.031) and ALGO SW (n=89) compared with both TAU (HR=1.64; P=.018) and CDES (HR=1.56; P=.038). For both ALGO LA (n=86) and ALGO DE, fewer antidepressant medications were needed to achieve remission than for CDES or TAU (P<.001). Remission rates at discharge differed across groups; ALGO DE had the highest (89.2%) and TAU the lowest rates (66.2%).ConclusionsA highly structured algorithm-guided treatment is associated with shorter times and fewer medication changes to achieve remission with depressed inpatients than treatment as usual or computerized medication choice guidance.