Levodopa in Parkinson’s Disease: A Review of Population Pharmacokinetics/Pharmacodynamics Analysis
2017
Background : Parkinson’s disease is the second most common neurodegenerative disorder after Alzheimer’s disease. Although levodopa remains the single effective agent in the management of Parkinson’s disease, the accurate determination of this optimal dosage is complicated by marked between-subject and between-occasion variability in this population. This review presents a synthesis of the population pharmacokinetic and pharmacodynamic models of levodopa described in Parkinson’s disease. Methods: A literature search was conducted from the PubMed database, from their inception through April 2016, using the following terms: levodopa, pharmacokinetic(s), pharmacodynamic(s) population, model(ling) and nonlinear mixed effect. Articles were excluded if they were not pertinent. References of all selected articles were also evaluated. Results : A total of 12 articles were finally retained. The following covariates were selected as interindividual variability factors: body weight, age, sex, creatinine clearance and levodopa dose. The clinical response versus effect site concentration relationship was described with different sigmoidal E max models. Different pharmacodynamic effects were described: UPDRS, Tapping, Dyskinesia, CURSΣ and treatment response scale. Discussion: This review allows us to realize interpretation of a patient’s clinical picture and confirmed the appropriateness of the pharmacokinetic-pharmacodynamic modeling for levodopa. External evaluation of previous published models should be also continued to evaluate these previous studies. New pharmacokinetic and/or pharmacodynamic population modelling studies could be consider to improve future models and decrease variability, to better understand the evolution of patients with Parkinson’s disease treated by levodopa. This article is open to POST-PUBLICATION REVIEW . Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.
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