Modern biotech has the tools to cure thousands of rare diseases, but not enough scientists to do the work. That's changing fast as AI-powered automation transforms drug discovery and gene editing from labor-intensive research into scalable platforms. Speaking at Web Summit Qatar this week, executives from Insilico Medicine and GenEditBio revealed how their AI systems are filling talent gaps that have left rare disorders untreated for decades, potentially unlocking personalized therapies for millions of patients.
Insilico Medicine just unveiled what its CEO Alex Aliper calls "pharmaceutical superintelligence" - and the timing couldn't be more critical. Thousands of rare diseases still have zero treatment options, not because science lacks the capability, but because the industry lacks enough trained researchers to tackle them all. At Web Summit Qatar this week, Aliper laid out how AI is becoming the force multiplier that lets small teams punch above their weight.
The company recently launched its MMAI Gym platform, designed to train generalist large language models like ChatGPT and Gemini to perform as well as specialist models built for drug discovery. Insilico's goal is a multi-modal, multi-task AI that can solve different drug discovery challenges simultaneously with what Aliper describes as 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," Aliper told TechCrunch in an interview.
The 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 and nominate high-quality therapeutic candidates at dramatically reduced cost and time. The company recently deployed its AI models to identify whether existing drugs could be repurposed to treat ALS, a rare neurological disorder that affects roughly 5,000 people in the U.S. annually.
