Powering Question-Driven Problem Solving to Improve the Chances of Finding New Medicines
A Talk by Samiul Hasan (Scientific Lead, Data and Computational Sciences Solutions, GSK)
About this Talk
Making true “molecule”-“mechanism”-“observation” relationship connections is a time consuming, iterative and laborious process. In addition, it is very easy to miss critical information that affects key decisions or helps make plausible scientific connections.
The current practice for deciphering such relationships frequently involves subject matter experts (SMEs) requesting resource from resource-constrained data science departments to refine and redo highly similar ad hoc searches. The result of this is impairment of both the pace and quality of scientific reviews.
In this presentation, I show how semantic integration can be made to ultimately become part of an integrated learning framework for more informed scientific decision making. I will take the audience through our pilot journey and highlight practical learnings that should inform subsequent endeavours.
About The Speakers
Scientific Lead, Data and Computational Sciences Solutions, GSK
Samiul Hasan is the Scientific Lead in the Data and Computational Sciences Solutions team at GSK. Samiul’s passion is in using computational techniques including semantic technologies to enhance scientific decision making and increase the chances of getting better treatments to patients more quickly.