Artificial intelligence is revolutionizing the pharmaceutical space by unearthing novel methods to address some of the toughest diseases. The leader of this revolution is Dr. Alex Zhavoronkov, the CEO and co-founder of Insilco Medicine. Through AI, his team has designed a novel molecule to treat idiopathic pulmonary fibrosis, a rare lung disease without any known cause or cure.
This drug, still awaiting regulatory approval, has shown promising results in preliminary clinical trials, offering hope to patients affected by IPF. The molecule’s discovery exemplifies the growing influence of AI in medicine, particularly in drug development.
A New Era in Drug Discovery
Traditionally, the discovery and bringing of a drug to market is something time consuming and capital intensive, involving 10-15 years and costing more than $2 billion. But what’s worse, 90% of drugs entering clinical trials do not end up succeeding in them. AI is going to reshape this course by reducing time as well as cost and failure rates during drug discovery.
The two major steps in AI-based drug discovery are the identification of therapeutic targets and the design of molecules to interact with those targets. For example, Insilco Medicine uses generative AI, a type of technology that is used in developing tools such as ChatGPT, to suggest and iterate molecular designs. This means the laborious and expensive manual synthesis of hundreds of molecules is eliminated, greatly speeding up drug development.
Generative AI and Its Impact
Since 2014, Insilco Medicine has already raised more than $425 million and is using AI through its entire pipeline in drug discovery. Its AI doesn’t only help identify potential therapeutic targets but also evaluates the likelihood of success in clinical trials.
In developing IPF treatment, the AI machine established that there was an entirely novel protein, TNIK, which would be the primary modulator of the disease. Using this knowledge, it synthesized a novel small-molecule inhibitor to target TNIK, preparing and screening merely 79 of these versus 500 that other industry average for four years or less for development that took a total of only 18 months.
The AI System Pioneers Expanding Horizons in AI-Driven Medicine
Insilco Medicine has six molecules currently in clinical trials, and four have recently been cleared to begin testing. Other than these, the company is advancing nearly 30 more promising compounds. These were all generated “from scratch” using AI.
Other companies, such as Recursion Pharmaceuticals, are pushing boundaries in their own way. Recursion has utilized automated experiments and AI-trained tools to find unknown relationships between molecules and diseases within large datasets. Its proprietary supercomputer, Biohive 2, enables rapid data processing and accelerates drug discovery efforts. Already in clinical trials for lymphoma and solid tumors is one of the molecules designed by AI from Recursion that specifically targets certain genes that drive cancer.
Role of AI in Revolutionizing Drug Discovery
Challenges and Future Outlook
Despite all this, there’s still the problem of scarce quality data for AI-driven drug discovery and is prone to introducing biases. The company Recursion addresses this problem by producing enormous datasets from automated experiments that are guaranteed to be a good base for learning AI models.
As AI really goes about changing the face of healthcare, experts say, it needs to deliver. That means that drugs which are discovered with AI need to work reliably through clinical trials, doing better than everything else, say experts. This partnership promises a new breakthrough era in the discovery of medicinal medicines as this field matures further.
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