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We do it because
it matters
Jerome Pesenti, BenevolentTech CEO, BenevolentAI
WHAT’S the problem?
Despite the huge growth of knowledge
the process of scientific discovery HAS
NOT CHANGED FOR 50 YEARS
...
ABOUT BenevolentAI
A British technology Company applying AI to
accelerate and enhance scientific discovery
15/03/2017 3
Fo...
BenevolentAI Corporate Structure
15/03/2017 4
Applying proprietary AI
technology in bioscience
Refining and developing the...
HOW we are different
15/03/2017 5
Platform Vendors (e.g. Watson)
• Scientific discovery is one of many use cases
• Focus o...
OUR traction and technology validation
24 validated hypothesis in clinical and pre clinical development in 6 months
$800m ...
Our AI enabled drug discovery workflow
15/03/2017 7
1. Initial
Research
2. Hypothesis
Generation
3. Hypothesis
Validation
...
KNOW WHAT YOU KNOW – in order to put the
pieces together but first we need to know what
the pieces are!
BREAKING SILOS - m...
Our methodology and the skills it requires
15/03/2017 Private and Confidential 9
Codify drug
development
Implement
discove...
WE ARE RECRUITING!
• 40 AI researchers in London and NYC.
• 10 software engineers in London.
15/03/2017 10
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BenevolentTech - Harnessing the power of AI to accelerate global scientific discovery

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Jérôme Pesenti, CEO, BenevolentTech - the technology arm of BenevolentAI - presenting at Project Juno's second Machine Intelligence Showcase.

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BenevolentTech - Harnessing the power of AI to accelerate global scientific discovery

  1. 1. We do it because it matters Jerome Pesenti, BenevolentTech CEO, BenevolentAI
  2. 2. WHAT’S the problem? Despite the huge growth of knowledge the process of scientific discovery HAS NOT CHANGED FOR 50 YEARS In the modern world it’s IMPOSSIBLE for humans alone to process all the complex information available to ensure continued significant advances in scientific discovery Without technology’s help science based industries will REGRESS 15/03/2017 2
  3. 3. ABOUT BenevolentAI A British technology Company applying AI to accelerate and enhance scientific discovery 15/03/2017 3 Founded in 2013 – post successful exit of Proximagen Group plc $BN company with strong balance sheet ($87m raised to date) 70+ team of world class scientists and technologists (40+ doctorates/advanced degrees) Technology enabling previously impossible tasks in bioscience Across the road from here
  4. 4. BenevolentAI Corporate Structure 15/03/2017 4 Applying proprietary AI technology in bioscience Refining and developing the AI technology
  5. 5. HOW we are different 15/03/2017 5 Platform Vendors (e.g. Watson) • Scientific discovery is one of many use cases • Focus on bottom of the stack rather than solving use case end-to-end • Technology developed in a vacuum without direct access to scientists • Ecosystem strategy with horizontal technology that has limited understanding of domain knowledge • No user feedback loop, developed in isolation • Sell software BenevolentAI • Sole focus on a specific discovery use case: end to end drug discovery and development • Direct and constant access to the science team • Laser-targeted to the needs of the drug discovery scientists • Understands very precisely domain & language that can extract and represent existing knowledge • Uses domain knowledge to make predictions • Improves and learns quickly based on user feedback, building unique differentiation • Applying software to develop own drugs
  6. 6. OUR traction and technology validation 24 validated hypothesis in clinical and pre clinical development in 6 months $800m signed out-licence agreements 300granted patents (portfolio) covering large series of compounds MULTIPLE repurposing opportunities being pursued in clinic (J&J in-licence) 1st Phase IIb clinical study in 2017 15/03/2017 6
  7. 7. Our AI enabled drug discovery workflow 15/03/2017 7 1. Initial Research 2. Hypothesis Generation 3. Hypothesis Validation 4. Programme Initialisation Drugs Targets Diseases Novel associations Rapid in silico validation Biological testing Private and Confidential
  8. 8. KNOW WHAT YOU KNOW – in order to put the pieces together but first we need to know what the pieces are! BREAKING SILOS - most biological knowledge is locked away in scientific publications/patents/ reports. Each individual scientist only knows a small subset of this. SUM OF THE PARTS - by automating the extraction of biological knowledge, we can enable our scientists to base their work on all biological knowledge rather than a small slice and find connections they would otherwise have missed. 15/03/2017 8 MACHINE LEARNING AND NLP - need to use and develop state-of-the-art NLP and machine learning algorithms. UNIQUE ALGORITHMS - making predictions requires using unique deep learning algorithms that leverage information across multiple data sets, both structured and unstructured. UNIQUE TOOLS - partnership with drug scientists requires uniquely designed tools and the efficient collection and processing of feedback. BIO-RELEVANT - deep learning algorithms need to be adapted to bio-chemical structures and processes. The BenevolentAI tech challenges Private and Confidential
  9. 9. Our methodology and the skills it requires 15/03/2017 Private and Confidential 9 Codify drug development Implement discovery product Optimize discovery steps Track usage measure performance • Drug Discovery • UX Design • Product Mngt • Software Engr • ML, NLP, DL • Bio/Chem Informatics • Data Science Collect feedback • Machine Learning • UX Design
  10. 10. WE ARE RECRUITING! • 40 AI researchers in London and NYC. • 10 software engineers in London. 15/03/2017 10

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