Lead Investigator: Amit Etkin, Alto Neuroscience, Inc.
Title of Proposal Research: Clinical and demographic predictors of antidepressant treatment in patients with major depressive disorder with agomelatine versus vortioxetine
Vivli Data Request: 7539
Funding Source: Employee salaries at Alto Neuroscience, Inc. are supported by internal Alto funds
Potential Conflicts of Interest: Amit Etkin, Nicholas Cooper, Adam Savitz, Li Shen, and Anna Thomas are full-time employees of Alto Neuroscience-work being proposed is part of the job responsibilities for Alto. Alto is supporting this project. Amit Etkin owns equity in Mindstrong Health and Akili Interactive for unrelated work. Adam Savitz owns stock in Johnson&Johnson and was a full time employee of J&J (Janssen Research & Development) until July 2021. No conflict with this project. J&J has no involvement in the project.
Summary of the Proposed Research:
While there are multiple antidepressants presently on the market, most make use of very similar mechanisms related to regulation of serotonin or norepinephrine levels. Two notable exceptions are agomelatine (which stimulates melatonin receptors, thereby resynchronizing circadian rhythms, and blocks the serotonin 5-HT2C receptor, which increases dopamine release) and vortioxetine (which increases availability of serotonin in synapses, but also a binds to a number of serotonin receptors). However, little is known about whether clinical or demographic variables differentially predict treatment outcome. Information gained on this question would further our understanding of the impact and relevance of non-traditional antidepressant mechanisms of action, may help select patients who may optimally respond to one treatment or the other, or guide the development of future novel medicines. We will address this question using a variety of statistical analyses of clinical and demographic data from a study of vortioxetine versus agomelatine in patients with depression. The specific dataset chosen to address this question is large, such that we can discover and then separately replicate relationships between clinical/demographic variables and treatment outcome. Our statistical methods will be ones common to clinical trial research, as well as those more closely related to simple forms of machine learning. Given the broad relevance of the proposed analyses, meaningful impact is expected for the general population of depressed patients (22M in the US alone), as well as patients with anxiety or trauma-related disorders in which antidepressant treatment is also a mainstay (10M’s in the US). Indeed, at present it is estimated that one in eight in the US is on an antidepressant at any given time, thus illustrating both the breadth and need for a precision approach such as that described herein.
A Randomised, Double-blind, Parallel-group, Active-controlled, Flexible Dose Study Evaluating the Effects of [Vortioxetine] Lu AA21004 Versus Agomelatine in Adult Patients Suffering From Major Depressive Disorder With Inadequate Response to Antidepressant Treatment
Data Contributor: Lundbeck
Study ID: NCT01488071
Sponsor ID: 14178A