The Key To A Precision Medicine Future: AI Plus Human Ingenuity

Artificial intelligence (AI) is being used to find new promising targets and design new molecules to treat diseases. It is also being applied in the optimisation of the clinical trial process – analysing data to predict outcomes to help prevent timely and costly late-stage failures, and producing health digital twins to speed up trials, and precision public health. It’s very possible to imagine a data-driven, streamlined, precision medicine future merging the best of human and machine intelligence to manage our individual health in ways we never previously imagined.

- Dr Alex Aliper

Artificial intelligence (AI) is accelerating precision medicine, giving us the ability to analyse complex data sets and find patterns that can tell us how genes are linked to diseases, and how diseases are linked to biological processes. AI can process reams of existing scientific data and uncover new biomarkers for disease, new targets for therapeutics, and even design new drug-like molecules to treat disease. And we’re still in the early stages of what this technology can do.

Generative Adversarial Networks (GANs) – machine learning models that create new images, video, and text from existing data – were first proposed in 2014 by a young scientist named Ian Goodfellow, currently with DeepMind. He and other scientists discovered that technology can be utilised to generate new images based on specific generation conditions. Now, this technology has exploded, bringing with it breakthroughs that have lately dominated headlines – from Microsoft’s new Copilot for Office, to Bing’s AI chatbot, to image- and art-generating tools like DALL-E and Midjourney.

Generative AI is an amazing tool that is quickly evolving to transform the way we create, work, and discover. What is often misunderstood, however, is the essential role that humans play in advancing these technologies. That’s particularly true in AI drug discovery, where we are working with diverse and complex datasets and an untold number of potential interactions and biological responses. Back in 2016, Insilico Medicine’s founder and CEO, Alex Zhavoronkov, PhD, was one of a few pioneers to realise the potential of generative AI in drug discovery. He published the first peer-reviewed paper in the emerging field of “generative chemistry” on applying GANs to generate novel small molecules against cancer.