A Study of Novel Exploratory Tools, Digital Technologies, and Central Nervous System Biomarkers to Characterize Unipolar Depression.

Autor:	Sverdlov O; Novartis Pharmaceuticals Corporation, East Hanover, NJ, United States., Curcic J; Novartis Institutes for Biomedical Research, Basel, Switzerland., Hannesdottir K; Novartis Institutes for Biomedical Research, Cambridge, MA, United States., Gou L; Novartis Pharmaceuticals Corporation, East Hanover, NJ, United States., De Luca V; Novartis Institutes for Biomedical Research, Basel, Switzerland., Ambrosetti F; Novartis Institutes for Biomedical Research, Basel, Switzerland., Zhang B; Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, Washington, DC, United States., Praestgaard J; Novartis Institutes for Biomedical Research, Cambridge, MA, United States., Vallejo V; Novartis Institutes for Biomedical Research, Basel, Switzerland., Dolman A; Novartis Institutes for Biomedical Research, Cambridge, MA, United States., Gomez-Mancilla B; Novartis Institutes for Biomedical Research, Basel, Switzerland., Biliouris K; Novartis Institutes for Biomedical Research, Cambridge, MA, United States., Deurinck M; Novartis Institutes for Biomedical Research, Basel, Switzerland., Cormack F; Cambridge Cognition, Cambridge, United Kingdom., Anderson JJ; Neurotrack Technologies, Inc., Redwood City, CA, United States., Bott NT; Department of Medicine, School of Medicine, Stanford University, Stanford, CA, United States., Peremen Z; ElMindA Ltd., Herzliya, Israel., Issachar G; ElMindA Ltd., Herzliya, Israel., Laufer O; ElMindA Ltd., Herzliya, Israel., Joachim D; Sonde Health, Inc., Boston, MA, United States., Jagesar RR; Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, Netherlands., Jongs N; Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, Netherlands., Kas MJ; Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, Netherlands., Zhuparris A; Centre for Human Drug Research, Leiden, Netherlands., Zuiker R; Centre for Human Drug Research, Leiden, Netherlands., Recourt K; Centre for Human Drug Research, Leiden, Netherlands., Zuilhof Z; Centre for Human Drug Research, Leiden, Netherlands., Cha JH; Novartis Institutes for Biomedical Research, Cambridge, MA, United States., Jacobs GE; Centre for Human Drug Research, Leiden, Netherlands.; Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands.
Jazyk:	angličtina
Zdroj:	Frontiers in psychiatry [Front Psychiatry] 2021 May 06; Vol. 12, pp. 640741. Date of Electronic Publication: 2021 May 06 (Print Publication: 2021).
DOI:	10.3389/fpsyt.2021.640741
Abstrakt:	Background: Digital technologies have the potential to provide objective and precise tools to detect depression-related symptoms. Deployment of digital technologies in clinical research can enable collection of large volumes of clinically relevant data that may not be captured using conventional psychometric questionnaires and patient-reported outcomes. Rigorous methodology studies to develop novel digital endpoints in depression are warranted. Objective: We conducted an exploratory, cross-sectional study to evaluate several digital technologies in subjects with major depressive disorder (MDD) and persistent depressive disorder (PDD), and healthy controls. The study aimed at assessing utility and accuracy of the digital technologies as potential diagnostic tools for unipolar depression, as well as correlating digital biomarkers to clinically validated psychometric questionnaires in depression. Methods: A cross-sectional, non-interventional study of 20 participants with unipolar depression (MDD and PDD/dysthymia) and 20 healthy controls was conducted at the Centre for Human Drug Research (CHDR), the Netherlands. Eligible participants attended three in-clinic visits (days 1, 7, and 14), at which they underwent a series of assessments, including conventional clinical psychometric questionnaires and digital technologies. Between the visits, there was at-home collection of data through mobile applications. In all, seven digital technologies were evaluated in this study. Three technologies were administered via mobile applications: an interactive tool for the self-assessment of mood, and a cognitive test; a passive behavioral monitor to assess social interactions and global mobility; and a platform to perform voice recordings and obtain vocal biomarkers. Four technologies were evaluated in the clinic: a neuropsychological test battery; an eye motor tracking system; a standard high-density electroencephalogram (EEG)-based technology to analyze the brain network activity during cognitive testing; and a task quantifying bias in emotion perception. Results: Our data analysis was organized by technology - to better understand individual features of various technologies. In many cases, we obtained simple, parsimonious models that have reasonably high diagnostic accuracy and potential to predict standard clinical outcome in depression. Conclusion: This study generated many useful insights for future methodology studies of digital technologies and proof-of-concept clinical trials in depression and possibly other indications. Competing Interests: OS, JC, KH, LG, VD, FA, JP, VV, AD, BG-M, KB, MD, and J-HC were employed by Novartis. FC was employed by Cambridge Cognition. JA was employed by Neurotrack Technologies, Inc. ZP, GI, and OL were employed by ElMindA, Ltd. DJ was employed by Sonde Health, Inc. AZ, RZ, KR, ZZ, and GJ were employed by CHDR. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2021 Sverdlov, Curcic, Hannesdottir, Gou, De Luca, Ambrosetti, Zhang, Praestgaard, Vallejo, Dolman, Gomez-Mancilla, Biliouris, Deurinck, Cormack, Anderson, Bott, Peremen, Issachar, Laufer, Joachim, Jagesar, Jongs, Kas, Zhuparris, Zuiker, Recourt, Zuilhof, Cha and Jacobs.)
Databáze:	MEDLINE
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