Reconciling evidence-based medicine and precision medicine in the era of big data: challenges and opportunities.

Daniel Lew,Jacques S Beckmann

doi:10.1186/s13073-016-0388-7

Abstract

This era of groundbreaking scientific developments in high-resolution, high-throughput technologies is allowing the cost-effective collection and analysis of huge, disparate datasets on individual health. Proper data mining and translation of the vast datasets into clinically actionable knowledge will require the application of clinical bioinformatics. These developments have triggered multiple national initiatives in precision medicine—a data-driven approach centering on the individual. However, clinical implementation of precision medicine poses numerous challenges. Foremost, precision medicine needs to be contrasted with the powerful and widely used practice of evidence-based medicine, which is informed by meta-analyses or group-centered studies from which mean recommendations are derived. This “one size fits all” approach can provide inadequate solutions for outliers. Such outliers, which are far from an oddity as all of us fall into this category for some traits, can be better managed using precision medicine. Here, we argue that it is necessary and possible to bridge between precision medicine and evidence-based medicine. This will require worldwide and responsible data sharing, as well as regularly updated training programs. We also discuss the challenges and opportunities for achieving clinical utility in precision medicine. We project that, through collection, analyses and sharing of standardized medically relevant data globally, evidence-based precision medicine will shift progressively from therapy to prevention, thus leading eventually to improved, clinician-to-patient communication, citizen-centered healthcare and sustained well-being.

Highlights

Since the writings of the Greek physician and philosopher Galen in around 150–200 AD, healthcare has been largely influenced by organ-based anatomy
Interpretation, and exploitation of this wealth of data, embodied in activities regrouped under the term “clinical bioinformatics”, are likely to provide unprecedented opportunities for integrative approaches, allowing a shift from the traditional organ-based paradigm to a more allinclusive and systemic assessment of health and disease, and the practice of systems medicine [21,22,23]
It is not unlikely that, in a couple of years, we will see, akin to what happened in the fields of radiology and imaging, the increasing importance of the medical specialty of clinical bioinformatics. This evolution might require a profound reshaping of medical curricula to train highly specialized experts, responsible for the interpretation of the ever-increasing amount and complexity of data, for modeling disease and for issuing reports that will serve as decision support for clinical staff

Summary

Introduction

Since the writings of the Greek physician and philosopher Galen in around 150–200 AD, healthcare has been largely influenced by organ-based anatomy. Precision medicine seeks to move away from symptom-based taxonomies towards the development of individualized care, to be achieved through the molecular characterization of individuals in a multi-layered patient-centered system, with customized medical interventions, taking into account a myriad of factors (such as the patient’s genome, environment, and lifestyle) that can influence development of disease or treatment response and thereby improve health (modified from [101]).

Results

Conclusion