Day One - 06 July 2021

9:00 am - 9:45 am EST Dotmatics Platform & Adventures in AI

Dan Ormsby - Senior Consultant, Dotmatics

Dotmatics is an industry leading cloud-based scientific R&D data management platform. An ambition of Dotmatics is to make all the research data available via querying and reporting. In building the querying and reporting features we have also built the perfect springboard for adventures into AI.

This talk will cover the current crop of practical AI/ML prototypes available in the Dotmatics platform and some early plans to automate AI/ML techniques over all the data our customers store in our platform. We will cover the use of WebAssembly for edge computing/client side deployment of models and some interesting observations of the benefits of the new AWS x2gd instance types for accessing larger (2 billion+) sets of purchasable compounds. 



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Dan Ormsby

Senior Consultant
Dotmatics


                                                                                           



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Haydn Boehm

Head of Commercial Marketing, Digital Lab Productivity Solutions
Merck Life Science

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Dr Annette Hellbach

Director, Head of Science Enablement Tools
Merck Life Science

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Dr Emma Gardener

Technical Application Scientist
Merck Group

  • To accelerate scientific discovery, our industry must re-imagine laboratories as smart and automated data centers to generate clean, machine actionable, and reproducible data rapidly as compared to today’s artisan (and mostly manual) research approaches.
  • Cloud access to smart connected laboratories is no longer a reality waiting to happen. This newer breed of laboratories is ushering in new knowledge driven by data, computation, artificial intelligence, automation, and high-throughput robotics with the goal of fundamentally advancing the life sciences
  • Learn how the University of Wisconsin remotely leveraged and integrated the Strateos automated robotic cloud lab, and created a fully automated robotic discovery process driven by artificial intelligence that designs and screens for millions of protein sequences in a reproducible and iterative manner, making the long process of protein engineering much faster and more reliable.


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Philip Romero

Ph.D., Assistant Professor
UW-Madison

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Jacob Rapp

Graduate Student
UW-Madison

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Ben Miles Ph.D.

Head of Product
Strateos