Ed Addison, Cloud Pharmaceuticals

Ed Addison

Ed Addison, is Chairman and CEO of Cloud Pharmaceuticals, a Research Triangle Park company from Duke University that applies AI to drug design and discovery, achieving unprecedented results. Cloud Pharmaceuticals has designed new drugs in development for cancer and other diseases. Ed is also Chairman of InferenSys, an AI machine learning company under wraps that applies a breakthrough machine learning method to big data, to launch in 2018. With over 30 years experience, Ed is on the advisory board and/or board of directors of a number of companies deploying exponential technologies in life sciences, mobile apps and artificial intelligence, including Global Source Group, VoucherCart, Drug Logic and Parallel Medical Testing.

 

With a technical background in Artificial Intelligence and Bio-IT, and a strong business development and capital raising background, Ed is an established serial entrepreneur of disruptive ventures. Ed started 6 companies, funded 4 of them and exited 3. He has twice been named "Entrepreneur of the Year". He has advised 7 venture capital funds and over 20 early stage ventures. His expertise is in launching new technology ventures and new technology products.

 

Ed is an adjunct professor of engineering management, entrepreneurship and MBA courses. He has previously taught Artificial Intelligence, Computer Science, Systems Engineering and/or Bioinformatics for several universities including NC State University, Stevens Institute of Technology and Johns Hopkins University. Ed holds a BSEE from Virginia Tech, two MS degrees (in Electrical and Biomedical Engineering) from Johns Hopkins, an MBA from Duke University, and an 'online' law degree. He did a sabbatical year at MIT in Artificial Intelligence in 1985.

Sessions

1:35 PM - 1:55 PM

Applying AI to Accelerate Drug Discovery & Design from Patient Data to Drug

A survey of methods that can be used to discover novel targets from patient data, validate those targets from literature mining and drug safety data, design novel leads for those targets and insure that the lead candidate has good drug like properties – all enhanced with a variety of AI methods to be presented.

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