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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한정신약물학회 Clinical Psychopharmacology and Neuroscience Clinical Psychopharmacology and Neuroscience 제19권 제4호
- 발행연도
- 2021.11
- 수록면
- 577 - 588 (12page)
- DOI
- 10.9758/cpn.2021.19.4.577
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초록· 키워드
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A growing body of evidence now proposes that machine learning and deep learning techniques can serve as a vital foundation for the pharmacogenomics of antidepressant treatments in patients with major depressive disorder (MDD).
In this review, we focus on the latest developments for pharmacogenomics research using machine learning and deep learning approaches together with neuroimaging and multi-omics data. First, we review relevant pharmacogenomics studies that leverage numerous machine learning and deep learning techniques to determine treatment prediction and potential biomarkers for antidepressant treatments in MDD. In addition, we depict some neuroimaging pharmacogenomics studies that utilize various machine learning approaches to predict antidepressant treatment outcomes in MDD based on the integration of research on pharmacogenomics and neuroimaging. Moreover, we summarize the limitations in regard to the past pharmacogenomics studies of antidepressant treatments in MDD. Finally, we outline a discussion of challenges and directions for future research. In light of latest advancements in neuroimaging and multi-omics, various genomic variants and biomarkers associated with antidepressant treatments in MDD are being identified in pharmacogenomics research by employing machine learning and deep learning algorithms.
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참고문헌 (79)
참고문헌 신청
Lin E / 2020 / Precision psychiatry applications with pharmacogenomics : artificial intelligence and machine learning approaches / Int J Mol Sci 21:969
Klein ME / 2017 / Clinical implementation of pharmacogenomics for personalized precision medicine : barriers and solutions / J Pharm Sci 106:2368~2379
Torres EB / 2016 / Toward precision psychiatry : statistical platform for the personalized characterization of natural behaviors / Front Neurol 7:8
Amare AT / 2017 / Pharmacogenomics in the treatment of mood disorders : strategies and opportunities for personalized psychiatry / EPMA J 8:211~227
Lin E / 2016 / Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy / Prog Neuropsychopharmacol Biol Psychiatry 64:334~340
Klein ME / 2017 / Clinical implementation of pharmacogenomics for personalized precision medicine : barriers and solutions / J Pharm Sci 106:2368~2379
Torres EB / 2016 / Toward precision psychiatry : statistical platform for the personalized characterization of natural behaviors / Front Neurol 7:8
Amare AT / 2017 / Pharmacogenomics in the treatment of mood disorders : strategies and opportunities for personalized psychiatry / EPMA J 8:211~227
Lin E / 2016 / Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy / Prog Neuropsychopharmacol Biol Psychiatry 64:334~340
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