Pharmaceutical and medical device makers spend over $130bn each year collecting and analyzing new data, mostly through clinical trials. It costs over $1.8bn to bring a new drug to market, and over $4bn when factoring in the cost of failures. By more efficiently understanding and analyzing this data, new drugs can reach patients quicker, safer, and at a lower cost.
In this presentation, Eran will discuss how ETL pipelines can be built using the Apache and other open source projects to improve clinical trial development. We will examine how the system is built, the challenges we faced and how we are able to reduce cost, accelerate execution time, and improve results. We will also demonstrate how reliable resource allocation, scalable data ingestion adapters, on-demand and fault tolerant job deployments, and monitoring benefit clinical trial decision-making and execution.