Flagship hopes biotechs will flock to Mirai’s algorithm-based platform to enhance their genetic meds

Amid the genetic medicines arms race, Flagship Pioneering is unveiling a new company to help biotechs fine-tune the precision of their therapies.

The venture creation firm has loaded up Mirai Bio with an initial commitment of $50 million, funds Mirai will use to advance a platform designed to “enhance and accelerate genetic medicine development across a wide range of therapeutic areas and modalities," according to a Sept. 26 release.

Mirai’s platform harnesses algorithms not only to ensure its biotech partners’ gene therapies are delivered to a specific tissue and cell type but also to optimize the cargo of the therapies in question. Further, the platform could help accelerate the journey through key manufacturing steps and the transition into the clinic. 

Mirai is “pioneering the first open end-to-end platform for the biotech industry to enable the co-creation of fully optimized genetic medicines," according to Flagship.

“We are in the age of information molecules, yet enormous technological challenges in the delivery, cargo design, and manufacturing of these molecules have hindered the speedy and full realization of their potential,” Hari Pujar, Ph.D., founding president of Mirai and operating partner at Flagship, said in a Sept. 26 release.

“We created Mirai to solve these key limitations through AI trained on high quantities of quality in vivo data,” Pujar added. “By applying machine intelligence to the design of every atom within the medicine and opening this platform to the entire industry, we will have vast collective data points rolling through our optimization loops, allowing a greater innovation advantage to benefit each partner on the Mirai platform.”

Flagship first set up Mirai back in 2021. Travis Wilson, executive chair at Mirai and growth partner at Flagship Pioneering, explained in the release that the bioplatform company is designed to solve the challenge “every new company with a payload idea faces” when they come to turn their theory into reality.

“Leveraging learnings from semiconductors as a centralized resource model that fueled the rapid advancement of tech, we’ve developed a solution that’s been hiding in plain sight: an open platform to unlock genetic medicine development,” Wilson explained.