Posted on April 5th, 2019 by Chris Cheadle PhD in Pharma R&D
Partnerships between different sectors, companies, organizations and stakeholders are responsible for some of the greatest innovations happening in the life sciences today. By sharing resources and information while learning from each other, collaborators are discovering amazing new ways to address pressing research problems.
At ConTech 2018, one such partnership took center stage in a presentation on identifying new knowledge by applying AI and machine learning, featuring Elsevier’s Dr. Umesh Nandal and Dr. Gordon Broderick, Director of the Center for Clinical Systems Biology at the Rochester General Hospital. Dr. Nandal, a senior machine learning & NLP scientist, began the talk by detailing some of the pain points that researchers have to deal with, such as:
- Sorting through an ever-increasing body of scientific literature (2.7 million new peer-reviewed articles published every year!)
- Not missing anything relevant amongst this deluge of information
- Gaining important insights in a shorter period of time
Experts like Dr. Nandal want to use technology to help today’s researchers tackle these challenges, and there is a dedicated AI Lab at Elsevier that is leveraging machine learning and artificial intelligence to do so. Dr. Nandal and his colleagues are working at extracting unstructured information from literature and patents, much of which is “hidden” in tables, images and video. They have been using Elsevier’s Entellect platform to connect the information that is being extracted.
As Dr. Nandal explained in the presentation, he and his team cannot do their work alone. They collaborate with researchers like Dr. Gordon Broderick (who Umesh affectionately calls “Dr. G”) to better understand needs, workflows and questions that need to be answered.
“We have to come back to them again and again. ‘Did I solve your problem correctly?’ Then we need to solve their next problem,” he explained.
“We’ve been fortunate to work in close collaboration with Elsevier,” said Dr. Broderick, who discussed how text-mining tools from Elsevier have helped in the creation of disease models that his hospital-based research group uses in its drug repurposing efforts. Dr. Broderick leads a high-performance computing effort in modeling the molecular dynamics of intracellular life. These models give insights that could lead to better diagnoses and guide the design of effective treatments for complex medical conditions that defy conventional approaches. In this virtual biology environment, he collaborates with researchers around the world to tackle some of the most elusive and complex illnesses that affect the function of the hormone, immune, and nervous systems.
Check out the video of the full 20-minute presentation to learn more about how these ground-breaking models work and to hear some of the success stories that have resulted.
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