Woo Yul Lee (1,2), Yun Seob Jung (1,2), Dong Woo Chae (1,2), Kyungsoo Park (1,2)
(1) Department of Pharmacology, Yonsei University College of Medicine, Seoul, Korea (2) Brain Korea 21 Plus Project for Medical Science, Yonsei University, Seoul, Korea
Introduction: We believe only few population pharmacodynamic models have been developed regarding clinical effects of an antidepressant. Moreover, in real clinical settings, it is prevalent to use antidepressants in multiple categories as combination regimen to improve depressive symptoms rather than a single category regimen. In this respect, it is essential to estimate the effects of drugs prescribed for depression including antidepressants, antipsychotics, mood stabilizers and anxiolytics from different category and quantify expected beneficial effects when used as a combination therapy.
Objectives:
– Develop a pharmacodynamic model of frequently used antidepressants
Methods: MADRS (Montgomery Asberg Depression Rating Scales) were used for the measurement of drug effect on depression [1] and our data were collected retrospectively using Electric Medical Record in Yonsei university hospital from January 2005 to August 2017. Patients who were hospitalized for depression, major depressive disorder and depressive disorder as main diagnosis were included in our data. The total number of subjects and measurements used for analysis were 129 and 353, respectively. MADRS score was measured at the time of admission and few days later for follow up score after treatment. The number of MADRS score measured in each individual ranged from 1 to 8. Classes of drugs of interest were SSRI, antipsychotics, benzodiazepines, tetracyclic antidepressants, mood stabilizers and buspirone. Each was administered on daily basis until the day of discharge, so we could assumed all had reached steady state concentration at the time of follow up measure of MADRS score even though there were no concentration records. Data exploration and model building process was carried out using R ver 3.3.3 and NONMEM ver 7.3.
Results: Mixed weibull model was chosen for the basic structural model [2]. Based on the structural model, Effects of antidepressants on the MADRS score were 0.031 (SSRIs), 0.016 (antipsychotics), 0.0215 (benzodiazepines), 0.047 (tetracyclic antidepressant), 0.0513 (buspirone) and fixed to be 0 which was less than 0.001 (mood stabilizers). Buspirone showed the largest effect on MADRS score improvement. Estimated baseline score for MADRS score was 28.6, and hill coefficient that explains the curvilinearity of descending MADRS score was 0.37. . The inter-individual variabilities (CV%) were 29.72% (SSRI), 31.47% (antipsychotics), 30.65% (benzodiazepines), 32.89% (tetracyclic antidepressant), 14.02% (baseline MADRS score). We fixed CVs for other parameters to be 0 due to high eta shrinkage and statistically insignificant value. Relative standard errors (RSEs) in parameters ranged between 46% and 62% for the effect of drugs and those in other parameters were less than 34%.
Conclusions: We started to quantify the effect of each drug in combination regimen. The model will further be developed with potential covariates, and inter-occasional variabilities so we can predict and suggest optimized antidepressant combination therapy in patient with depressive symptoms.
References:
[1] Thomas J. Carmody, A. John Rush, Ira Bernstein, Diane Warden, Stephen Brannan, Daniel Burnham, et al. The Montgomery Äsberg and the Hamilton ratings of depression: A comparison of measures. European Neuropsychopharmacology (2006) 16, 601-611.
[2] Venkatesh Pilla Reddy, Magdalena Kozielska, Martin Johnson, An Vermeulen, Rik de Greef, Jing Liu, et al. Structural Models Describing Placebo Treatment Effects in Schizophrenia and Other Neuropsychiatrie Disorders. ClinPharmacokinet2011:50(7) 429-460.
Reference: PAGE 27 (2018) Abstr 8573 [www.page-meeting.org/?abstract=8573]
Poster: Drug/Disease Modelling - CNS