Modern biotech has the tools to edit genes and design drugs, yet thousands of rare diseases remain untreated. According to executives from Insilico Medicine and GenEditBio, the missing ingredient for years has been finding enough smart people to continue the work. AI, they say, is becoming the force multiplier that lets scientists take on problems the industry has long left untouched.
Speaking this week at Web Summit Qatar, Insilico’s CEO and founder Alex Aliper laid out his company’s aim to develop “pharmaceutical superintelligence.” Insilico recently launched its “MMAI Gym” that aims to train generalist large language models, like ChatGPT and Gemini, to perform as well as specialist models.
The goal is to build a multi-modal, multi-task model that, Aliper says, can solve many different drug discovery tasks simultaneously with superhuman accuracy.
“We really need this technology to increase the productivity of our pharmaceutical industry and tackle the shortage of labor and talent in that space, because there are still thousands of diseases without a cure, without any treatment options, and there are thousands of rare disorders which are neglected,” Aliper said in an interview with TechCrunch. “So we need more intelligent systems to tackle that problem.”
Insilico’s platform ingests biological, chemical and clinical data to generate hypotheses about disease targets and candidate molecules. By automating steps that once required legions of chemists and biologists, Insilico says it can sift through vast design spaces, nominate high-quality therapeutic candidates, and even repurpose existing drugs — all at dramatically reduced cost and time.
For example, the company recently used its AI models to identify whether existing drugs could be repurposed to treat ALS, a rare neurological disorder.
But the labor bottleneck doesn’t end at drug discovery. Even when AI can identify promising tar …