Chan Zuckerberg Initiative Launches AI Model to Decode Cellular Behavior

On July 10, 2025, the Chan Zuckerberg Initiative (CZI) announced the launch of its latest artificial intelligence model, GREmLN (Gene Regulatory Embedding-based Large Neural model), designed to enhance researchers' understanding of cellular behavior by focusing on the intricate networks that govern how cells operate. This significant advancement aims to facilitate the resolution of complex biological issues such as cancer by providing insights into the molecular interactions within cells.

The GREmLN model represents a crucial milestone in CZI’s ongoing efforts to develop a series of AI biomodels that can predict and elucidate cellular functions across various biological systems, ultimately aiding in the prevention, management, and treatment of diseases. "Our model provides an approach, grounded in biology, to leverage AI for deriving new insights into health and disease," stated Andrea Califano, President of the Chan Zuckerberg Biohub New York and Clyde and Helen Wu Professor of Chemical and Systems Biology at Columbia University Vagelos College of Physicians and Surgeons. He emphasized that GREmLN is designed to reshape AI to align with biological realities rather than forcing biology to conform to AI paradigms.

Unlike traditional AI approaches, GREmLN prioritizes the "molecular logic" that orchestrates gene interactions, akin to conversations occurring within a cell. This innovative methodology enables scientists to monitor critical alterations that may signal the onset of diseases, thereby highlighting potential targets for new therapies. GREmLN has been trained on over 11 million data points sourced from CZI's CellxGene, a platform utilized by thousands of researchers to expedite discoveries by examining and contrasting individual cell data across various tissues, including the brain, lung, kidney, and blood.

The implications of GREmLN extend beyond mere research applications; it is poised to address pivotal biological and medical inquiries. For instance, the model could facilitate the early detection of cellular transformations indicative of cancer or neurodegenerative conditions before they become irreversible. "Understanding cellular behavior means understanding the network of conversations happening inside every cell," remarked Theofanis Karaletsos, Senior Director of AI at CZI. He noted that GREmLN captures cellular complexity in unprecedented ways, marking a significant advancement toward simulating and predicting cellular behavior.

As GREmLN evolves, its potential applications could range from thwarting cancer cells' ability to evade therapeutic interventions to minimizing inflammation-induced damage to neural cells. Furthermore, the model may enable researchers to anticipate cellular responses to new pharmaceuticals, thereby enhancing the likelihood of success in clinical trials. Ultimately, GREmLN signifies a new era of AI tools tailored to deepen scientists' comprehension of life's intricate logic.

This model joins a suite of biomodels developed by CZI, including TranscriptFormer, the pioneering generative AI model that integrates datasets across different species to aid researchers in exploring cellular functions on a broader scale. Both models are integral components of CZI’s virtual cell platform, which is designed to be open and accessible to the global scientific community, thereby fostering collaborative advancements in biomedical research, disease diagnosis, and therapeutic development. The Chan Zuckerberg Initiative's commitment to innovative research continues to pave the way for breakthroughs in understanding and treating complex diseases, aligning with its overarching mission to promote human health and well-being.

In conclusion, the introduction of GREmLN underscores the transformative potential of artificial intelligence in the life sciences, promising to enhance the precision and efficacy of future medical treatments and research endeavors.