February 27-28, 2019
San Francisco

The 2nd AI-PI: Drug Discovery 2019 Summit returns to San Francisco, February 27 – 28, 2019. Key decision makers from pharma, biotech drug developers and technology companies will meet not to only discuss but share real world technical insight and data driven applications of AI and Machine Learning in Drug Development.

At this critical time when AI and Machine Learning technologies promise to revolutionize traditional pharmaceutical practices, gain a competitive advantage by joining the solution led meeting and capitalize on the benefits of AI technologies by:

Exploring real world case studies from the likes of Genentech, Berg & Amgen and discovering how AI & Machine Learning are being implemented in pharma and biotech today.
Gaining clarity on how to best structure datasets to maximize the impact AI and Machine Learning can have on your early drug development processes.
Understanding how AI and Machine Learning can be utilized for drug repositioning and repurposing purposes.
Debating how to best integrate AI talent into your R&D processes to streamline your drug discovery pipeline.
Finding out how Machine Learning can optimize molecule design to fast track drug candidate prediction.



Kim Branson
Head of AI (ECDi)


Brandon Allgood


Slava Akmae
Senior Vice President,
Chief Analytics Officer


Sandor Szalma
Global Head of Computational Biology


Ji Ma
Principal Scientist


Marcin von Grotthuss
Senior Computational
The Broad Institute

What 2018 Attendees Had to Say:

"The information I got was beyond expectation. The case sharing was informative and enlightening. The speakers’ cases answered questions that I had before the meeting and inspired me to explore AI in my own work. The Summit also provides adequate time for networking and discussion, which allowed me to exchange ideas and explore future collaboration opportunities."
Sammy Cui, Senior Research Associate, Unilever

"This conference was very helpful in clarifying challenges and opportunities in this space as it related to our existing and potential future partners. It also had very knowledgeable and enjoyable people to meet." 
Ari Allyn-Feuer, University of Michigan Medical School


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