Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care - 11/09/23

Doi : 10.1016/j.ccc.2023.03.002

Lazaro N. Sanchez-Pinto, MD ^a,^b,^⁎ , Sivasubramanium V. Bhavani, MD ^c, Mihir R. Atreya, MD, MPH ^d, Pratik Sinha, MD, PhD ^e,^f
^a Department of Pediatrics, Northwestern University Feinberg School of Medicine, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA
^b Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA
^c Department of Medicine, Emory University, 100 Woodruff Circle, Atlanta, GA 30322, USA
^d Division of Critical Care Medicine, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Avenue, Cincinnati, OH 45229, USA
^e Division of Clinical and Translational Research, Department of Anesthesia, Washington University School of Medicine, 1 Barnes Jewish Hospital Plaza, St. Louis, MO 63110, USA
^f Division of Critical Care, Department of Anesthesia, Washington University School of Medicine, 1 Barnes Jewish Hospital Plaza, St. Louis, MO 63110, USA

^∗Corresponding author. Division of Critical Care Medicine, Ann & Robert H. Lurie Children’s Hospital of Chicago, 225 East Chicago Avenue, Bx73, Chicago, IL 60611.Division of Critical Care MedicineAnn & Robert H. Lurie Children’s Hospital of Chicago225 East Chicago Avenue, Bx73ChicagoIL60611

Résumé

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.

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Keywords : Critical care, Precision medicine, Acute respiratory distress syndrome, Sepsis, Machine learning, Electronic health records, Biomarkers

Plan

Key points

Introduction

Uncovering relevant disease phenotypes from observational data

Secondary Use of Clinical Data

Clinical Trajectories

Physiologic Data

Biomarkers and Multiomics

Implementing precision medicine strategies in the critical care setting

Designing Next-Generation Clinical Trials Leveraging the Electronic Health Record

Using Machine Learning to Predict Patient Phenotypes

Integrated Approaches for the Use of Real-Time Multiomics and Endotyping

Challenges and opportunities of data science approaches to advance precision medicine in critical care

Leveraging Real-World Data

Building Collaborative Networks

Summary

Clinics care points

Conflicts of interest

	Author contributions: all authors: concept, design, drafting of article, and final approval of the version to be published.
	Funding: none for this article. Dr L.N. Sanchez-Pinto, S.V. Bhavani, and P. Sinha received funding from the NIH.

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Vol 39 - N° 4

P. 627-646 - octobre 2023 Retour au numéro

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Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care - 11/09/23

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