Benevolent AI: Shaping the Future of Scientific Discovery

Hi there, could you tell us a little about Benevolent AI and your motivations as a company?

Despite the huge growth of knowledge, scientific discovery has not changed for 50 years.  It’s impossible for humans alone to process all the information potentially available to advance scientific research.  A new scientific paper is published every 30 seconds, there are 10,000 updates to PubMed every day.  Consequently, only a small fraction of globally generated scientific information can form ‘useable’ knowledge.  Specifically, in Pharma innovation has not changed (cost, time & risk – still applying 20th Century methods to 21st Century problems) and is not meeting the needs of patients – patients are unnecessarily waiting for new medicines.

BenevolentAI are applying its proprietary AI technology to change this problem by enabling the analysis of vast quantities of complex scientific information and creating usable knowledge that can be applied.

Benevolent AI - using Artificial Intelligence to re-imagine scientific discovery

What is Benevolent AI's mission?

We are using AI to dramatically accelerate scientific discovery, changing the way knowledge is created and how new insights are discovered.  Essentially we are creating previously impossible Eureka moments from the world’s mass of highly fragmented data.

Initially we are focussed on applying AI to create better medicines faster for patients.  The medium-term mission (which we have started to make progress on in 2017) is to diversify beyond human drug discovery to other scientific industries both in bioscience (e.g. animal health, nutraceuticals) and outside bioscience e.g. energy, materials science, agriculture etc.


Benevolent AI is geared towards scientific discovery, how important is artificial intelligence in aiding new scientific discoveries?

See above, but essentially it’s the only way scientific discovery can make significant exponential advances in the modern world. We combine the power of machine brains with expert human brains.  The two are inextricably linked – our approach to AI would not work without our own scientists applying their knowledge to the hypotheses our technology creates.


Are there any notable cases which Benevolent AI has been involved in?

We have validated 24 hypotheses in bioscience and are now entering clinical trials with some of them.  For example, look at the recent Economist article on our website - for ALS we have shown that our AI technology finds things other scientists can’t or didn’t think to look for.  We have also signed a major deal with a US pharma company for Alzheimer’s and are developing drugs from a J&J in-licence deal. (you can find further information on all of this on our website).


Who are your main users? Are they primarily research orientated or do you find entrepreneurs and start-ups also seeking to access Benevolent AI's capabilities?

We are not a platform play and are not selling software.  Our business model sees us either developing the new drugs we find ourselves (with clinical partners) or licencing our discoveries to larger pharmaceutical organisations to manufacture and market.


Where do you see Benevolent AI in the future, and what role do you see your company having both within the world of technology, but also specifically scientific research?

We aim to revolutionise the process of scientific research – in a way reinvent the scientific method for the 21st Century.  We are already a $BN valued company – partly because we have demonstrated our technology works in drug discovery but also because investors recognise that our technology is scalable across all areas of science, so expect to have a big impact in developing AI technology and on science as a whole.





Register to search the database

Find out more about our services

Read more news

Support our infographics and articles

Register with Company Connecting here

Click here for more News and Nutshells

Contact us at:

E-mail: sends e-mail)

Phone: 0845 643 5375

First published on Company Connecting November 2016

©Company Connecting

AIMachine LearningArtificial IntelligenceScienceResearchR&D