Big Data Analytics: The Next Evolution In Drug Development

The drug development process is complex and financially risky. A recent study by The Tufts Center for the Study of Drug Development estimates the cost of developing a new drug at $2.6 billion and suggests that costs of drug development are rising with a compound annual growth rate of 8.5 percent. These rising costs are largely driven by increases in out-of-pocket costs, such as larger clinical trial sizes and higher failure rates for drugs required to demonstrate superiority. Even when considering the efficacy of the 10 highest-grossing approved drugs in the United States, the fact is that for every patient a drug does help, between three and 24 patients fail to show improvement after treatment. Clinicians are typically forced to address this variability in patient outcomes with a trial-and-error approach to intervention, increasing healthcare costs and adding a burden to the patient.

Drug Developers, Providers, And Patients Need A Better Option 

High-throughput technologies are ushering in the era of Big Data in drug development, allowing researchers to assay patients in terms of their genome, epigenome, proteome, metabolome, and microbiome. Precision medicine initiatives are being undertaken to tailor disease treatment by taking into account individual variability in molecular and cellular systems. A biomarker- and technology-driven approach to developing targeted therapies and patient selection strategies has the potential to increase success in the drug development process, decrease cost, and ultimately improve patient outcomes with directed intervention. Read More

S. Pandarinath, Pharmacist, Certified Pharmacovigilance Professional.