Challenges of designing an AI platform for Drug Discovery w/ Marek Kultys

Biology is complicated. Our scientists work with large amounts of scientific data to better understand the relationship between biological entities.

Many of these pieces form a coherent picture about one segment of the biology in question, but often, scientists are presented with conflicting evidence. There are many gaps in the understanding of biology and many blanks remain to be filled. Understanding and filling these gaps is incredibly important for scientists to be able to select the right targets.  

At Benevolent we use various computational technologies and a range of standard and non-standard design patterns to help drug discoverers explore and select the best targets for validation. The role of our machine learning researchers, engineers and designers is to build this technology that helps our scientists break though this vastness of biological information to develop medicines for the patients that need them most.  

Marek, Lead Product Designer, gives a talk at World Usability Day Silesia 2019 in which explores the design process at BenevolentAI where he builds user facing tools that help our scientists discover and develop new medicines.

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