Big Data Provides Pathway to Precision Medicine
Description of Track
Speaker Atul Butte, MD,Ph.D.
Director, UCSF Institute for Computational Health Sciences
The remarkable ascent of Big Data for example from biomedical imaging, next generation sequencing and adjacent technologies that deliver a multiplicity of heterogeneous data has been a tremendous boon for basic biomedical research and for precision medicine. However, this has transferred the bottleneck from data generation to analysis and meaningful interpretation. This is challenging academia and industry to create infrastructure and capabilities that can translate the data tsunami into actionable knowledge for researchers, drug developers and clinicians. In this Session, the speakers will address their efforts to meet this challenge.
Notes-Data Driven Healthcare
With the arrival of molecular medicine and genomics trillions of points of molecular, clinical and epidemiological data will be available to be “mined” by innovative computational tools from researchers and hospitals worldwide. Much of the data as well as clinical samples is already available from NIH/UCSF organizations such as ImmPort.org.
Entrepreneurial companies have already been created and funded utilizing existing public data, gene expression arrays and clinical samples. The cost of clinical studies for new products can be drastically reduced because of available data from previous studies. Think of how Amazon collects data on consumer purchases and on-line searches to drive their retail marketing.
The objectives of “Precision Medicine”can be reviewed at the UCSF Institute for Computational Health Sciences WEB site to build computational infrastructure linking electronic health records to accelerate discovery and better care.
In 2015 a Precision Medicine Initiative received $215M in funding by the government.