The Silicon Review
“Unlocking the power of scientific data to make more effective drugs for the people that need them.”
When many of us hear the term "artificial intelligence" (AI), we imagine robots doing our jobs, rendering people obsolete. And, since AI-driven computers are programmed to make decisions with little human intervention, some wonder if machines will soon make the difficult decisions we now entrust to our doctors.
Rather than robotics, AI in health care mainly refers to doctors and hospitals accessing large data sets of potentially life-saving information, which includes treatment methods and their outcomes, survival rates, and speed of care gathered across millions of patients, geographical locations, and innumerable and sometimes interconnected health conditions. New computing power can detect and analyze large and small trends from the data and even make predictions through machine learning that's designed to identify potential health outcomes.
One such firm which is using scientific innovations and technologies in the healthcare sector to bring about a potential change in this sector is BenevolentAI.
BenevolentAI is the global leader in the development and application of artificial intelligence ("AI") for scientific innovation. The firm aims to accelerate the journey from inventive ideas to medicines for patients by developing AI to generate new treatments for some of the world's 8,000 untreated diseases.
The team of technologists, AI researchers, and scientists build and apply AI to the entire drug discovery and development process. The technology unlocks unknown factors by creating new ideas based on facts to provide a different understanding of the disease, which leads to inventive steps and real insights that drive the development of new medicines and treatments.
The central vision of the firm is, reimagining drug discovery to bring more effective medicines to every patient using AI.
UNLOCKING THE POWER OF SCIENTIFIC DATA
BenevolentAI integrates AI technologies at every step of the drug discovery process: from early discovery to late-stage clinical development. The platform of computational and experimental techniques and methods draws on vast quantities of mined and inferred biomedical data. It is built and used by our world-class scientists, researchers, and technologists, working side-by-side, to improve and accelerate every step of the drug discovery process. The company's strength comes from this integrated, end-to-end approach, combined with a relentless pursuit of scientific and technological excellence.
Perfect machine learning opportunity
BenevolentAI has spent the last five years developing a knowledge pipeline that pulls data from various structured and unstructured biomedical data sources and curates and standardizes this knowledge via a data fabric. This data is fed into our proprietary knowledge graph, which extracts and contextualizes the relevant information. The knowledge graph is made up of a vast number of contextualized, machine curated relationships between diseases, genes, drugs, and with over 20 types of biomedical entities.
Human biology is one of the most complex information systems, and any variations of the underlying biological processes can cause symptoms and diseases to occur. To do this, the firm brings together experts across ML, engineering, biology, bioinformatics, and chemistry together for each of our research programs.
To do this, the firm uses machine learning and data science to guide the entire process of target identification. Relation inference AI models help us predict potential non-obvious disease targets that may be overlooked by scientists.
Design By leveraging advanced AI, their EvoChem product is continuously learning from this vast chemical space and generating drug-like molecules with desirable properties that can be synthesized 'on-demand.' EvoChem designs de novo compounds based on multiparametric optimizations with a scoring function that factors in all the features we are seeking to optimize for that molecule. The compound ideas are ranked and the best candidates are selected directly for synthesis, while others serve to inspire chemists to explore the chemical space further.
At BenevolentAI, they apply machine learning models to identify patient groups by the molecular signature of their disease and design, allowing us to run faster clinical trials. This precision medicine guided approach allows the firm to identify patient subtypes more likely to respond to drugs, further increasing the probability of success in the clinic. This approach has benefits for existing medicines too: it can be used to elucidate the mechanism of action, identify new patient responders, improve diagnosis, and, more precisely, target treatment.
The Marvel behind the glorious metamorphosis of BenevolentAI
Joanna Shields serves as the Chief Executive Officer of BenevolentAI. She is a tech industry veteran with over 25 years' experience building and scaling global companies, including Facebook, Bebo, Aol, Google, Real Networks, and Efi. Before joining BenevolentAI, she served in the UK Government as Under Secretary of State and Minister for Internet Safety & Security, Digital Economy Adviser and Chair and CEO of TechCity UK. Joanna is passionate about creating responsible technology that benefits humanity. She is a leading advocate for children's rights and safety online and founder of the We Protect Global Alliance.