Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care

• Published in: Critical care clinics Vol. 39; no. 4; pp. 627 - 646
• Main Authors: Sanchez-Pinto, Lazaro N., Bhavani, Sivasubramanium V., Atreya, Mihir R., Sinha, Pratik
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-10-2023
• Subjects: Acute respiratory distress syndrome; Biomarkers; Critical Care; Data Science; Ecosystem; Electronic health records; Humans; Machine learning; Precision Medicine; Sepsis; Technology; Acute respiratory distress syndrome; Precision medicine; Machine learning; Critical care; Biomarkers; Sepsis; Electronic health records
• ISSN: 0749-0704; 1557-8232; 1557-8232
• DOI: 10.1016/j.ccc.2023.03.002

Precision medicine aims to identify treatments that are most likely to result in favorable outcomes for subgroups of patients with similar clinical and biological characteristics. The gaps for the development and implementation of precision medicine strategies in the critical care setting are many, but the advent of data science and multi-omics approaches, combined with the rich data ecosystem in the intensive care unit, offer unprecedented opportunities to realize the promise of precision critical care. In this article, the authors review the data-driven and technology-based approaches being leveraged to discover and implement precision medicine strategies in the critical care setting.