Event Title: Symposium Artificial Intelligence for Science, Industry and Society
Event Host: OECD
Location: Mexico City
Date: October 20, 2019 – October 25, 2019
Presentation Title: AI Innovation in the Pharmaceutical Sector – Accelerating Research
Team Member: Daniel Faggella, Emerj Founder and CEO
Back in August 2018, Alan Paic, Senior Policy Analyst, Science and Technology Policies at OECD, reached out to us because the OECD was in the early phases of planning an event about the uses of AI for scientific discoveries and the impact of these discoveries on industries and societies.
Paic had seen some of our work across different sectors and asked if we could put together a breakdown of how AI is affecting research and development in the pharmaceutical industry.
Over the course of the coming year, there was a lot of planning and organizing as to who the speakers would be and how the event would play out. They asked me to keynote, and I agreed. It all came together at the National Autonomous University of Mexico.
It was an event full of mostly scientists and researchers who are applying AI or are interested in applying AI to further their field. In my keynote, I covered an overview of where AI is being used in pharma research and development, including:
- Data Collection: Digitizing paper documents to better search for the information inside it and use it for machine learning applications.
- Data Enrichment: Automatically tagging digital documents and entities within them with metadata to facilitate search and discovery of information within those documents.
- Search and Discovery: Finding entities within digital documents and text databases using natural language search queries.
In addition, the pharmaceutical sector also has some cultural advantages when it comes to AI adoption that other sectors, such as banking, sorely lack, including:
- Culture of Experimentation: Pharmaceutical companies are open to risking massive amounts of resources for uncertain results.
Below are the slides presented:
What we Learned
The scientific community is really pushing the boundaries of AI in research, including everything from machine learning in high energy physics to deep learning in chemistry. There were a variety of presentations on AI being used to model and understand the world.
It was interesting, as someone who normally spends time researching AI in industry, to see what’s happening on the cutting edge of science and see researchers exchange ideas in the hard sciences.
Leaders from national AI plans seem to be willing to come together about ideas on AI advantages, risks, and opportunities. There was a session on the third day of the event that involved a lot of high-profile folks who were talking about preparing for an AI future at a societal level. It was great to be able to see high-level discourse about AI’s impact be so freely exchanged.
It’s good to see countries care about humanity in general and really think about AI national plans that hopefully improve human wellbeing on the aggregate.
Header Image Credit: Enerixico