T-Max™ Immune Intelligence Platform
MBF Therapeutics (MBFT) is an animal health biotech company on a mission to build the world's leading AI-driven immune intelligence infrastructure for animal health. Founded on the belief that veterinary immunology has been chronically underserved by data, MBFT is pioneering a new category of biologics development — one where every vaccine study generates both clinical value and machine-learning-ready immune data at scale.
A fully integrated pipeline links early in vitro readouts directly to in vivo and eventual clinical performance.
Executive Summary
The Mission
The T-Max platform is engineered to generate mechanistic, multi-dimensional, outcome-linked immunological data required to train artificial intelligence and predictive biology models — not merely optimize for regulatory endpoints.
The Opportunity
The T-Max platform represents not an incremental improvement in veterinary vaccinology, but a foundational infrastructure investment in the future of AI-driven immunology. Every study is prospectively engineered to capture the full arc of immune activation — from innate sensing through adaptive priming to memory formation.
The data produced is structured, longitudinal, and purpose-built for training generalizable immunology foundation models.
The Data Gap in Animal Immunology
The global animal health industry generates vast vaccine efficacy data — yet remains profoundly data-poor in the way that matters most for the next era of biomedical science: mechanistic understanding structured for machine learning.
The consequence: a field rich in products but poor in predictive models. Vaccine development remains largely empirical — iterative, expensive, and slow. T-Max is being built to change that.
T-Max Technical Edge: The Four Pillars
Antigen Design
Full-length natural antigens are used to systematically map protective immunogenic regions. This approach dramatically reduces immune-escape risk compared to truncated or computationally predicted antigen designs used by competitors.
Immune Profiling
Deep T-cell and B-cell analysis provides the mechanistic insight necessary to train predictive AI models. We move beyond binary efficacy signals to understand the precise cellular choreography of successful immune protection.
CaptaVax™ Delivery
Optimized calcium phosphate nanoparticle delivery minimizes confounding variables, ensuring that the immune response measured is driven by the antigen — not the delivery vehicle — producing dramatically cleaner training data.
Data Ecosystem
A fully integrated pipeline links early in vitro readouts directly to in vivo and eventual clinical performance. Every data point is tagged with structured metadata, making the entire corpus immediately ML-ready.
MBFT's integrated biology-data-AI stack and compounding data moat position it to become a valuable creator of vaccines and essential intelligence required to develop the next generation of therapeutics.
Core Thesis: T-Max as an Immune Data Instrument
T-Max is founded on a principle that distinguishes it from every existing animal vaccine platform: its primary design objective is to produce understanding, not merely products.
Beyond Vaccination
Studies capture the complete immune activation timeline — not just efficacy endpoints — from innate sensing to memory formation.
Mechanistic Depth
Each experiment yields multi-dimensional immune profiles spanning innate signatures, T-cell subsets, TCR/BCR repertoires, cytokine cascades, and outcome-linked biomarkers.
AI-Ready by Design
Data is structured and longitudinal, linked across pathogen, species, dose, route, and timepoint — the precise architecture required to train generalizable immunology foundation models.
The AI Learning Architecture
T-Max generates the right data, in the right structure, to train AI models capable of predicting how animals respond to infectious agents. Each study feeds a self-reinforcing learning loop.
This feedback architecture is self-reinforcing: each generation of T-Max studies produces smarter models, which design more targeted experiments, which generate higher-quality training data. Over time, the platform accumulates an increasingly powerful and proprietary immunological intelligence asset.
Foundation Model Capabilities
T-Max data is designed to support foundation-model–style AI — models that learn generalizable rules of immune biology and can be fine-tuned for specific pathogens, species, or clinical questions.
Vaccine Response Prediction
Predict magnitude, quality, and durability of immune responses to novel candidates prior to expensive in vivo studies.
Correlates of Protection
Identify specific immune signatures — innate, cellular, or humoral — that predict protection across pathogens and species.
Cross-Variant Coverage Modeling
Learn the rules of cross-reactivity and predict coverage against emerging variants or strains.
Disease Progression Forecasting
Model how immune dynamics evolve post-infection to predict disease severity, shedding, and transmission risk.
Species Transfer Learning
Apply immunological rules learned in one animal species to accelerate learning in another.
Antigen Optimization
Use AI-derived insights to rationally select and optimize antigens for maximum immunogenicity and protection breadth.
T Max Universal Platform: Natural Antigen Identification & Vaccine Development
🔬 IN VITRO TRACK
DNA Plasmid Constructs
Engineer targeted gene sequences for pathogen antigens
Produce Individual Proteins
Isolate and replicate specific protein targets
Challenge Disease-Experienced Cells/Tissues
Screen proteins against naturally primed cells/tissues to identify candidate antigens
Formulate Vaccine Candidate(s)
Combine with CaPNP nanoparticles + adjuvant for delivery optimization
🧬 IN VIVO TRACK
Vaccinate Naïve Host
Routes: IN, ID, Eye, IM - Mucosal or Systemic
Models: pig, mouse, chicken, cow, human
Safety / Challenge Studies
- Clinical signs
- Pathogen loads
- Innate responses
- Cytokine responses
- T cell & B cell responses
- Neutralizing antibody
- Pathology
Advanced Multi-Plasmid Vaccine Testing
Experimental multi-plasmid vaccine candidates evaluated for efficacy and safety
Strategic Significance
T-Max is being built at the precise moment when three structural forces — in AI, animal health, and global biosecurity — are converging to create a window of opportunity that did not exist five years ago.
Maturation of AI for Biology
Foundation models have proven they can extract generalizable biological rules from well-structured data — predicting protein function, immune behavior, and drug response with remarkable accuracy. The bottleneck is no longer algorithmic: it is the absence of structured, high-dimensional biological datasets produced under GCLP at the scale these models require.
Unmet Need in Animal Immunology
Animal health is among the most economically consequential sectors in biomedical science — yet it remains one of the most data-impoverished. No structured, longitudinal immunological dataset exists at scale across species. This gap is not a gap in effort; it is a gap in infrastructure, and it is the core bottleneck preventing rational, predictive vaccine development.
Zoonotic Risk & Food Security
Seventy-five percent of emerging infectious diseases originate in animals. As global demand for animal protein expands and spillover risk intensifies, the field's dependence on reactive, empirical approaches to vaccine development is no longer tenable. Predictive, data-driven tools are moving from competitive advantage to operational necessity.
MBFT Leadership & Advisors
MBFT Leadership
Thomas Tillett
CoFounder & CEO, MBFT; leads business strategy & capital raising.
Lorraine H. Keller, PhD
CoFounder & CSO, MBFT: leads scientific strategy and R&D management.
Ron Cravens, MS, DVM
CMO leads Clinical and Marketing strategy.
Scientific Advisory Board
Raymond R (Bob) Rowland, PhD
University of Illinois School of Veterinary Medicine
David Hurley, PhD
UNC Medicine; Expert in T-cell immunobiology
Terry Coffey, PhD
Retired CSO Smithfield Foods
Board of Directors
Thomas Tillett
CoFounder & CEO, MBFT; leads business strategy & capital raising.
Chris Cashman
Retired CEO Marinus Pharmaceuticals; pharma strategy. Chairman of the Board.
Joe Connor DVM, MS
Adjunct Professor, University of Illinois College of Veterinary Medicine: inducted into the PIC Hall of Fame and the Swine Web Hall of Fame.
Dhiren Thaker, PhD
Former Dean, UNC Eshelman School of Pharmacy.
Aris Persidis, PhD
CEO Biovista; Pioneer of AI-driven drug repositioning.
Anthony Green, PhD
Board observer, CSO at Ben Franklin Technology Partners.
Conclusion:
Immune Intelligence for the Age of AI
"MBF Therapeutics is building the immune intelligence infrastructure for animal health in the age of AI."
The T-Max platform is a fundamentally new kind of biological instrument — designed to produce vaccines, and produce understanding by capturing the full arc of immune activation, linking every measurement to meaningful clinical outcomes. T-Max is building the data architecture for immunology foundation models capable of transforming how vaccines are designed, how disease risk is predicted, and how animal health is managed globally.
MBF Therapeutics