Partner with us

Meet our Founding Team

Vijay Singamsetti, PhD

Founder & Chief Executive

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Stacy Townsend, PhD

Chief of Operations

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Susmitha Shankar, PhD

Chief of Technology

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Akash Ranjan, PhD

Principal Translational Science Strategist

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Dr. Xavier Laucirica

Founding Strategic Advisor - Clinical and Partnerships

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Dr. Ravi Padmanabhan, MD

Senior Clinical Advisor - Infectious Diseases

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Dr. Sujana Samala, MD

Head of Computational Pathology

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Sridhar Iyengar

Principal AI Advisor

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Vineeth Kalluru

Chief of Product

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A scientific intelligence that sees, understands, and predicts the immune system

Our Approach

Multi-omics data captures patient-specific immune-tumor interactions, but complexity obscures actionable insights. We are applying mechanistic modeling and advanced AI for neoantigen processing, simulate tumor microenvironment dynamics, including immune cell infiltration, cytokine signaling, and exhaustion pathways. Our goal is to turn immune heterogeneity into precise, predictive clarity.

Our bet on AI

We believe that AI can unlock immune-tumor complexity at scale. We are betting on training AI models on Multi-omics data to predict Neoantigens grounded by biophysical principles that accurately forecast MHC binding, TCR recognition, and immunogenicity for vaccine/drug design. The trained AI models will lead us to creating world's first accurate and exhaustive digital-twins to simulate dynamic immune networks like antigen processing, T-cell trafficking, cytokine cascades, and tumor microenvironment evolution under thousands of therapy scenarios.

Our Principles

Core tenets guiding Rudhira's immune-centric platform

  • Mechanistic first: Grounded in biochemical and biophysical models of antigens
  • Multi-omics native: Designed from the ground up to ingest, harmonize, and interpret large scale omics and spatial data
  • Patient-specific: Every digital twin reflects individual immune-tumor heterogeneity, not population averages
  • Clinically actionable: Outputs are biomarkers, stratification scores, and decision rules ready for trial design and adaptive therapy

Therapeutics developers

Partner with us in co-designing neoantigen pipelines and digital twins for your vaccines.

Clinical teams

Talk to us about your patient-specific simulation needs, biomarkers and virtual trials

Academic research labs

Collaborate with us to analyze multi-omics data for immune modeling in oncology research.

Frequently Asked Questions

Find answers to common questions about Rudhira AI's immune digital twin technology for precision oncology.

What is an immune digital twin?

A patient-specific virtual model of the immune system and tumor microenvironment in oncology, built from multi-omics data to simulate antigen presentation, T-cell responses, and therapy outcomes in real time.

What type of oncology therapies can you simulate?

We model responses to various existing cancer therapies predicting efficacy, resistance mechanisms, and optimal dosing/sequencing.

What Data inputs does the platform require?

Oncology multi-omics (WGS, RNA-seq, proteomics, immunopeptidomics), tumor microenvironment profiling, clinical history, and longitudinal response data—processed into unified patient representations.

How long does it take to build a digital twin?

From raw oncology data upload to actionable insights: hours for single cancer patients, days for cohort analysis—enabling rapid iteration in trial design and adaptive cancer therapy.