Dr. Alex Zhavoronkov of Insilico Medicine is at the forefront of using artificial intelligence (AI) to uncover useful molecules for treating diseases. Over a video call, he showcases a small, green, diamond-shaped pill developed by his company to treat idiopathic pulmonary fibrosis (IPF), a rare progressive lung disease with no known cause or cure.
While the drug has yet to receive approval, early clinical trials have shown it to be promising. Insilico Medicine represents a new wave of innovation where AI plays a critical role in drug discovery, a process traditionally dominated by medicinal chemists. Smaller AI-driven biotech companies, alongside larger pharmaceutical firms, are employing AI to make drug discovery faster and more cost-effective.
Alphabet, Google’s parent company, has also entered this space with its UK-based AI drug discovery company, Isomorphic Labs, launched in late 2021. Using AI in drug discovery could significantly reduce the time and cost it takes to bring a new drug to market, which currently averages 10 to 15 years and costs over $2 billion. AI has the potential to transform this process, making it more efficient and increasing the likelihood of success.
Charlotte Deane, a professor of structural bioinformatics at Oxford University, notes that we are at the beginning of understanding how impactful AI could be.
AI-driven drug discovery transformation
Companies like Insilico Medicine are leading this transformation.
Founded in 2014 and with over $425 million in funding, Insilico uses AI at multiple steps in drug discovery. This includes identifying therapeutic targets at the molecular level and designing drugs to correct these targets using generative AI. Insilico’s AI-driven approach has already resulted in the development of six molecules currently in clinical trials, including the one for IPF.
Recursion Pharmaceuticals is another key player, leveraging what it claims is the fastest supercomputer owned by a pharmaceutical company to generate and analyze massive amounts of molecular data. This approach helped them develop a molecule now in early-stage clinical trials for treating lymphoma and solid tumors. Despite these advancements, the biggest challenge remains the lack of data from which AI can learn, potentially introducing biases in the process.
Recursion attempts to mitigate this by generating its own data through automated experiments. Ultimately, the goal for companies like Insilico Medicine and Recursion is to demonstrate that AI-discovered molecules can successfully navigate through clinical trials and prove to be more effective than traditional methods. As Recursion’s CEO Chris Gibson notes, the world’s perception will shift once AI demonstrates a higher probability of success in drug development.
When that milestone is achieved, it will be clear that AI is the future of drug discovery.
Rashan is a seasoned technology journalist and visionary leader serving as the Editor-in-Chief of DevX.com, a leading online publication focused on software development, programming languages, and emerging technologies. With his deep expertise in the tech industry and her passion for empowering developers, Rashan has transformed DevX.com into a vibrant hub of knowledge and innovation. Reach out to Rashan at [email protected]
