Immunai Opens Free Single-Cell Sequencing Program for Academic Labs
Immunai, a New York–based company specializing in AI-driven immune system mapping, has announced a program offering academic researchers free access to its single-cell immune profiling platform, covering transcriptomic, surface proteomic, and TCR sequencing for studies of up to 1,000 human samples. The initiative is aimed at groups studying cancer, autoimmunity, and immunotherapy, as well as other immune-related areas, and is intended to offset reduced access to research infrastructure caused by tightening federal funding.
The initiative, called the Grand Collaboration Initiative for Single-Cell Immune Profiling, provides free sequencing for 100 to 1,000 patient samples, including peripheral blood mononuclear cells (PBMC) or tissue. Researchers will receive multi-omic data through CITE-seq, covering about 1,500 genes per cell and more than 80 surface proteins, along with TCR sequencing. Data will be returned with quality control and annotations for independent analysis and publication. Selected datasets will also be incorporated into Immunai’s AMICA immune atlas.
Image credit: Immunai’s platform
The program builds on Immunai’s integrated end-to-end immune profiling platform, which combines single-cell multiomics with computational and functional validation. The pipeline starts with generating high-resolution data from blood and tumor samples, capturing whole transcriptomes, surface proteomes, and immune receptor repertoires. This information is augmented with AMICA, Immunai’s proprietary atlas that reportedly incorporates more than 300,000 patient samples, spanning 500 diseases and 80 immune cell types
Immunai has recently expanded AMICA through collaborations, including its April 2025 partnership with the Parker Institute for Cancer Immunotherapy (PICI). That effort is building what the groups describe as the world’s largest patient-centric single-cell dataset for real-world immunotherapy.
Analysis across these datasets is performed through the company’s ImmunoDynamics Engine (IDE), a machine learning framework that links immune features to treatment responses and clinical outcomes. The IDE is designed to prioritize trial arms or patient subgroups, validate therapeutic hypotheses with mechanistic insight, identify patient stratification biomarkers, add confidence to preclinical efficacy and safety evaluation, and highlight immune targets with therapeutic potential.
Insights derived computationally are tested through functional genomics to confirm their biological relevance. Results are returned in an interpretable format that includes underlying data, with the stated aim of supporting clinical and translational decision-making.
Eligibility is limited to non-commercial human studies with relevant clinical metadata and regulatory approvals for data sharing. Proposals are due by October 1, 2025, with sample processing scheduled to begin later in 2025 and continue into early 2026.
Applications will be reviewed by a panel that includes Stanley R. Frankel (Columbia University), Mikael Dolsten (formerly Pfizer), Ansuman Satpathy (Stanford University), and Adeeb Rahman (Immunai CTO).
Topics: AI & Digital
