Patentability Risks Posed By AI In Drug Discovery

The drug development process is inefficient and expensive. Pharmaceutical companies generally spend 10 to 15 years to bring a drug to market¹ and can expect to spend anywhere from $1 billion to $2 billion over this timespan.² Drug development has become more expensive over time, with costs doubling every nine years.³

Artificial intelligence ("AI") can potentially address these inefficiencies by reducing costs, especially at the drug discovery and design stage. The drug discovery process may involve identifying a biological target responsible for the disease, identifying molecules that interact with this target, and developing lead molecules into preclinical testing. AI can potentially accelerate this process by sifting through large quantities of data to identify targets and then designing drugs that bind to such targets. For instance, Insilico Medicine used its target-identification and generative chemistry AI platforms to create a potential fibrosis drug