Accelerating Immunology Insights with AI-Driven Solutions
At ImmSilico, we help you unlock the full potential of high-dimensional, multi-modal immunological data through strategic applications of AI, machine learning, and advanced analytics. Our expert consultancy empowers research teams and industry partners to transform complex datasets—including scRNA-seq, spatial data, immune repertoires, cellular co-localisation and cross-talk, proteomics, epigenetics, and/or CyTOF—into meaningful biological discoveries.
We bridge the gap between immunology, advanced data science, and emerging experimental technologies, helping you select and implement the right computational approaches for your research questions. Our guidance enables you to develop scalable, interpretable pipelines that streamline data interpretation workflows, ensure rigorous analysis, and accelerate innovation in tissue immunity research.
In addition, our in silico modelling of immune protein–ligand interactions provides structural insights that guide the design of next-generation CAR T cells and therapeutic targets—reducing off-target risks and accelerating precision immunotherapy.
Specific Services We Offer
Advanced AI and integrative solutions of single cell and spatial data
How to align high-dimensional sparse data generated by different technologies, eg, scRNA, Visium (sequence-based) and/or Xenium(image-based)
Systematic data imputation
Advanced solutions to translate transcriptomics/epigenomics/spatial data into diagnosis, prognosis, treatment choice, pathogenesis and therapeutic discovery
Deep learning/graph-based methods for immune dynamics
AI-driven strategies for immune repertoire dynamics and disease association
Systematic investigation of immune repertoire architecture, dynamics and disease association.
Identifying antigen-specific or disease-specific TCRs/BCRs and their spatio-temporal dynamics, eg, blood to tissue trafficking or over the course of vaccination/disease
Cutting-edge strategies to deorphanise orphan TCRs
In silico inference of TCR:pMHC structures, investigating impact of mutations on structural dynamics of these immune complexes
In silico design of TCR, CAR-T cells and/or target antigens
In silico identification of T cell targets in cancer patients
In silico identification of self-antigen targets in autoimmune disease
Public data repositories, and open access analytical resources
Integration of and/or alignment of your data with atlas-level public data
Benchmarking and model performance strategies using known resources (e.g., ImmGen, Human Cell Atlas)
Advanced Visualisation & Interpretation
Advice on biologically meaningful dimension reduction strategies, latent space coding and decoding etc
Interpret spatial and subclonal tissue architecture
Support scientific storytelling around AI findings
Use Case and Track Record
• Developed predictive TCR clustering to infer antigen specificity in tumour-reactive CD8+ T cells
• Designed multi-modal AI analysis of CPI-bound vs CPI-free T cell niches using CosMx & CITE-seq
• Implemented spatial niche identification to map regeneration zones in colonic crypts from IBD tissue
Mark Your Data Intelligible — Before Making it Actionable
We help you design the right AI and analytical strategies to navigate the complexity of immunological data—its high dimensionality, sparsity, noise, and entangled technical and biological variation.
Our consulting ensures you ask the right questions, choose the right tools, and build the right team—so your data reveals insight, not confusion.
Contact Us: contact@immsilico.com