“A world in which no disease goes untreated.”
|Founded: Nov 2013 in London, United Kingdom
Category: Artificial Intelligence/Big Data
Primary office: London, UK
Core technical team: London, UK
Amount raised: USD $292 million (3 rounds)
- Precision Medicine: Uses Machine Learning to identify right treatment for patients
- Molecular Design: Empowers chemists to evaluate millions of drug molecules and design improved drug molecules in fewer cycles
- Partnership offers: Open source online interface for developers and research scientists to build applications and contribute to data assets
- Knowledge Platform: Provides articles and publications about research work in renowned journals
- Target Identification: Applies machine learning models to validate highest quality and hypothesis for new drug targets
- Alliances with pharmaceutical companies for consolidating research
- Diversity Analysis Tool; Open Source Programme to promote contribution and partnership
- Subscription Newsletters and Blog for keeping partners informed
- High level of technical expertise in underlying technologies, machine learning, artificial intelligence, data analytics, genomics and bioinformatics
- Experts in Precision Medicine
- Partnership with Top Pharmaceutical Partners e.g AstraZeneca
Distinct AI Features
- Neural Networks
Benevolent AI use the predictive power of AI algorithm to design new molecules; extracting new hypothesis based on a knowledge graph composed of over a billion relationships between genes, targets, diseases, proteins and drugs. Integrates AI into every step of drug discovery from early discovery to late stage clinical development. The AI model is built on vast quantities of mined and inferred biomedical data. The data is then fed into proprietary knowledge graph, which extracts and contextualizes relevant information. The knowledge graph is made up of a machine curated relationships between genes, diseases, drugs and over twenty types of biomedical entities. Relation inference AI models aids to predict potential non-obvious disease targets overlooked by scientists.
The machine learning models are used to identify patient groups by the molecular signature of design thus facilitating faster clinical trials. This precision medicine approach allows company to identify patient subtypes more likely to respond to drugs, hence, increase success probability in clinic.
Rate of return on customer’s investment to make AI work
- More money, time and effort is spent on building framework that will support research and advanced technology
- Less effort is required except for upgrades in technology
- Gene Sequences
- Drug Architecture
- Chemogenomics data
- Benevolent AI are using quantum-inspired approaches, often in combination with machine learning, and aim to achieve quicker and more-accurate drug discovery.
- Proprietary AI Drug Discovery Platform (e.g., baricitinib) for Covid-19.
- Cross Functional Expertise Team inclusive of biologists, chemists, engineers, informaticians and data scientists
- Drug discovery and development facility for clinical testing
- Partnership with top pharmaceutical companies and global research institutes
- Open Source Programme to improve data diversity
- User-friendly platform to attract contributors
- Active R&D drug programs for intelligent drug discovery
- Publishes research in distinguished scientific journals and world-renowned conferences
- Adoption of AI and machine learning technology to reduce timelines for drug discovery and improve the agility of the research process
- Acquisition of research lab to expand research space and capabilities
- Increase partnership network
- Raise funds
- Grow highly skilled and diversify workforce
- Focus resources on the fastest growing areas of businesses
- Black, R. 2018. BenevolentAI Buys Into Huge Research Lab to Expand Drug Discovery Operation. https://www.idigitalhealth.com/news/benevolentai-purchases-huge-research-lab-to-expand-its-drug-discovery-operation. InsideDigitalHealth.
- Butcher, M. 2019. BenevolentAI starts AI collaboration with AstraZeneca to accelerate drug discovery. https://techcrunch.com/2019/05/01/benevolentai-starts-ai-collaboration-with-astrazeneca-to-accelerate-drug-discovery/.TechCrunch.
- Cheung, K. C. 2020. Why Biotech and Big Pharma are Counting on AI. https://algorithmxlab.com/blog/biotech-big-pharma-counting-ai/. Algorithm – XLAB.
- Crunchbase 2020. Benevolent AI Funding Rounds. https://www.crunchbase.com/organization/benevolent-ai/company_financials.
- Golden. 2020. Benevolent AI. https://golden.com/wiki/BenevolentAI-R9DGJA8#:~:text=Ken%20Mulvany%2C%20Brent%20Gutekunst%2C%20Ivan,Cambridge%2C%20Belgium%20and%20New%20York.
- Growjo. 2020. BenevolentAI Competitors, Revenue and Alternatives. https://growjo.com/company/BenevolentAI#:~:text=Estimated%20Revenue%20%26%20Financials,venture%20funding%20in%20April%202018.&text=BenevolentAI’s%20total%20funding%20is%20%24207.7M.
- Langione. M, et.al. 2019. Will Quantum Computing Transform Biopharma R&D? https://www.bcg.com/en-ca/publications/2019/quantum-computing-transform-biopharma-research-development. BCG.
- Oranges, R. 2019. This AI unicorn is disrupting the pharma industry in a big way. https://www.wired.co.uk/article/benevolent-ai-london-unicorn-pharma-startup#:~:text=Benevolent%20AI%20can%20also%20use,%2C%20diseases%2C%20proteins%20and%20drugs. WIRED.
- Patyal, S. 2018. BenevolentAI: Revolutionizing drug discovery using Artificial Intelligence. https://digital.hbs.edu/platform-digit/submission/benevolentai-revolutionizing-drug-discovery-using-artificial-intelligence/. HBS Digital Innovation and Transformation.
- Taylor, M. 2020. How BenevolentAI bounced back from a $1 billion loss. https://www.wired.co.uk/article/benevolent-ai-winning-startup#:~:text=In%20reality%2C%20the%20%241%20billion,number%20of%20undisclosed%20American%20investors. WIRED.
- The Silicon Review. 2019. BenevolentAI– Expediting the journey from data to medicine using Artificial Intelligence (AI) technologies. https://thesiliconreview.com/magazine/profile/benevolentai-expediting-the-journey-from-data-to-medicine-using-artificial-intelligence-ai-technologies
- Damilola Balogun