Abstract
The explosion of data sources, accompanied by the evolution of technology and analytical techniques, has created considerable challenges and opportunities for drug development and healthcare resource utilization. We present a systematic overview these phenomena, and suggest measures to be taken for effective integration of the new developments in the traditional medical research paradigm and health policy decision making. Special attention is paid to pertinent issues in emerging areas, including rare disease drug development, personalized medicine, Comparative Effectiveness Research, and privacy and confidentiality concerns.
Highlights
The rapid increase in the quantity, diversity and accessibility of digitized patient data has presented unprecedented challenges and opportunities for drug development, regulatory reviews, and healthcare utilization and decision making (Mayer-Schonberger and Cukier 2014; Roski et al 2014)
We provide a high-level overview of the challenges and opportunities of Big Data vis-a-vis drug development, with emphasis on the potential for transforming the current paradigm of clinical research and regulatory review, advancing personalized medicine, and protection of the privacy of study participants
Despite the considerable advances made in Big data analytics, there are still pertinent methodological issues that limit the potential use of the so-called machine learning tools in evidence-based medicine
Summary
The rapid increase in the quantity, diversity and accessibility of digitized patient data has presented unprecedented challenges and opportunities for drug development, regulatory reviews, and healthcare utilization and decision making (Mayer-Schonberger and Cukier 2014; Roski et al 2014). The accompanying developments in methodological procedures and data visualization can help to improve operational efficiency in the execution of trials, and to tackle complex analytical issues that cannot readily be dealt with using traditional approaches The potential of these developments to contribute to efforts to reduce costs and to accelerate the delivery of drugs to patients that need them is immeasurable (LaValle et al 2011). We provide a high-level overview of the challenges and opportunities of Big Data vis-a-vis drug development, with emphasis on the potential for transforming the current paradigm of clinical research and regulatory review, advancing personalized medicine, and protection of the privacy of study participants. In the rest of the paper we discuss some of the challenges in incorporating Big Data in clinical development and conclude with suggested recommendations for further work
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
