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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Pharmacol. | doi: 10.3389/fphar.2019.01215

Computational Analysis of Therapeutic Neuroadaptation to Chronic Antidepressant in a Model of the Monoaminergic Neurotransmitter and Stress Hormone Systems

 Mariam B. Camacho1, Warut D. Vijitbenjaronk1 and  Thomas J. Anastasio1*
  • 1University of Illinois at Urbana-Champaign, United States

The clinical practice of selective serotonin reuptake inhibitor (SSRI) augmentation relies heavily on trial-and-error. Unfortunately, the drug combinations prescribed today fail to provide relief for many depressed patients. In order to identify potentially more effective treatments, we developed a computational model of the monoaminergic neurotransmitter and stress-steroid systems that neuroadapts to chronic administration of combinations of antidepressant drugs and hormones by adjusting the strengths of its transmitter-system components (TSCs). We used the model to screen 60 chronically administered drug/hormone pairs and triples, and identified as potentially therapeutic those combinations that raised the monoamines (serotonin, norepinephrine, and dopamine) but lowered cortisol following neuroadaptation in the model. We also evaluated the contributions of individual and pairs of TSCs to therapeutic neuroadaptation with chronic SSRI using sensitivity, correlation, and linear temporal-logic analyses. All three approaches revealed that therapeutic neuroadaptation to chronic SSRI is an overdetermined process that depends on multiple TSCs, providing a potential explanation for the clinical finding that no single antidepressant regimen alleviates depressive symptoms in all patients.

Keywords: Depression, monoamine, cortisol, stress, SSRI augmentation, Polypharmacy, combination therapy, multidrug therapy, Overdetermined system, Neural Network, Systems Biology

Received: 08 Feb 2019; Accepted: 23 Sep 2019.

Copyright: © 2019 Camacho, Vijitbenjaronk and Anastasio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Thomas J. Anastasio, University of Illinois at Urbana-Champaign, Champaign, United States,