Accelerating life sciences research

At OpenAI, we believe that AI can meaningfully accelerate life science innovation. To test this belief, we collaborated with the Applied AI team at Retro Bio⁠(opens in a new window), a longevity biotech startup, to create and research the impact of GPT‑4b micro, a miniature version of GPT‑4o specialized for protein engineering.

We are excited to share that we’ve successfully leveraged GPT‑4b micro to design novel and significantly enhanced variants of the Yamanaka factors, a set of proteins which led to a Nobel Prize for their role in generating induced pluripotent stem cells (iPSCs) and rejuvenating cells. They have also been used to develop therapeutics to combat blindness⁠(opens in a new window), reverse diabetes⁠(opens in a new window), treat infertility⁠(opens in a new window), and address organ shortages⁠(opens in a new window). 

In vitro, these redesigned proteins achieved greater than a 50-fold higher expression of stem cell reprogramming markers than wild-type controls. They also demonstrated enhanced DNA damage repair capabilities, indicating higher rejuvenation potential compared to baseline. This finding, made in early 2025, has now been validated by replication across multiple donors, cell types, and delivery methods, with confirmation of full pluripotency and genomic stability in derived iPSC lines. To ensure the findings are discoverable and replicable to benefit the life sciences industry, we are now sharing insights into the research and development of GPT‑4b micro.

An experimental GPT model for protein engineering

AI-assisted reengineering of SOX2 and KLF4 to increase stem cell reprogramming efficiency

Combining the top RetroSOX and RetroKLF variants produced the largest gains. Across three independent experiments, fibroblasts showed a dramatic rise in both early (SSEA-4) and late (TRA-1-60, NANOG) markers, with late markers appearing several days sooner than under the wild-type OSKM cocktail (Figure 5).