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.

Keywords::

• big data
• clinical pharmacology
• personalized medicine
• systems medicine
• therapeutics

Financial & competing interests disclosure

Authors are supported in part by the National Institutes of Health grant CA170653 and Lombardi Cancer Center CCSG grant NIH-P30 CA51008. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Key issues

• Big data in medicine is quickly transitioning from the research sector to the public community space, thus driving new biomedical discoveries, reassessment of current healthcare policies and reshaping of clinical practice.

• Creating effective individualized healthcare programs can be achieved with the implementation of big data in systems and clinical medicine.

• We provide insight into the influence of big data, in the form of ‘-omics’ and electronic medical records, on clinical pharmacology, as well as the evolving computational tools and platforms used for analytics.

• The current perspective envisions not only the discovery of novel drug–gene signatures and gene networks through big data but also the refined characterization of pharmaceutical-induced toxicity.

• In conclusion, big data further enables systems and clinical pharmacological approaches at an integrative and holistic level that can be applied to an individual for patient-specific treatment and healthcare maintenance.