Big data: the next frontier for innovation in therapeutics and healthcare

Abstract

Advancements in genomics and personalized medicine not only effect healthcare delivery from patient and provider standpoints, but also reshape biomedical discovery. We are in the era of the “-omics”, wherein an individual’s genome, transcriptome, proteome and metabolome can be scrutinized to the finest resolution to paint a personalized biochemical fingerprint that enables tailored treatments, prognoses, risk factors, etc. Digitization of this information parlays into “big data” informatics-driven evidence-based medical practice. While individualized patient management is a key beneficiary of next-generation medical informatics, this data also harbors a wealth of novel therapeutic discoveries waiting to be uncovered. “Big data” informatics allows for networks-driven systems pharmacodynamics whereby drug information can be coupled to cellular- and organ-level physiology for determining whole-body outcomes. Patient “-omics” data can be integrated for ontology-based data-mining for the discovery of new biological associations and drug targets. Here we highlight the potential of “big data” informatics for clinical pharmacology.

Challenges and Opportunities of Big Data in Health Care: A Systematic Review

“…New knowledge can then be generated from high volumes of effective data, enabling reuse of the data [15,20,21,32,33]. Open-source technology increases accessibility to and transparency of the data [12,25,26,30,35]. Finally, data quality can be maintained using analytics to get rid of unnecessary information [27].…”

Creation of a Multicenter Pediatric Inpatient Data Repository Derived from Electronic Health Records

“…Electronic health record (EHR) systems hold great promise for pediatric clinical research. [1][2][3][4] Primarily designed to improve clinical care, EHRs store vast amounts of routinely generated patient and provider data. 5 Through dissemination and development of sophisticated clinical research informatics tools, it is increasingly feasible to reuse EHR data for research.…”

Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases

“…11 For instance, due to the practical limitations in designing and implementing randomized clinical trials (RCTs) to address many important clinical questions, the mining of retrospective EHR and other large-scale clinical outcomes data has been proposed as a supplement to RCTs in the generation of practice-guiding evidence. 12 A restructured clinical taxonomy—one which moves away from the current organ/symptom-based classification system in favor of molecular descriptions of disease—has also been identified as a critical step toward precision medicine.…”