Indication prioritization
Compare how a mechanism may behave across disease contexts and identify the assumptions driving the difference.
For pharma and biotech
See how a drug program may behave in the connected immune system
ImmuNovus uses mechanistic immune models and AI-assisted simulation to explore targets, compounds, indications, biomarkers, and responder hypotheses before the next costly stage of development.
Research behind the approach
Explore original studies in immune-system modeling, therapeutic target identification, and multiscale simulation, alongside the published methods that support this work.
Make the next experiment more informative
Drug-development evidence is often fragmented across assays, models, and populations. ImmuNovus brings explicit immune mechanisms into the decision, helping teams compare hypotheses, expose assumptions, and prioritize what to validate next.
Decision modules
Target and mechanism assessment
Trace downstream immune consequences and examine where a proposed intervention may alter the system.
Biomarker and responder hypotheses
Explore mechanistic explanations for heterogeneous response and prioritize measurable signals for validation.
Compound or combination comparison
Compare plausible system-level effects under defined assumptions before committing to the next study.
Outputs are research decision support and hypotheses for validation. They are not a clinical diagnosis, an autonomous program selection, or a replacement for experimental evidence.
How it works
01
Define the decision
Start with the program question, comparison, decision point, and available evidence.
02
Configure the context
Represent relevant disease biology, intervention assumptions, measurements, and population context.
03
Run mechanistic simulations
Use AI-assisted tools to explore scenarios while retaining traceable model logic and inputs.
04
Inspect the rationale
See which mechanisms and assumptions drive each result, including uncertainty and alternative explanations.
05
Prioritize validation
Translate the result into the next experiment, biomarker analysis, or evidence request.
Mechanistic intelligence, accelerated by AI
Statistical and generative methods can surface patterns and speed analysis. ImmuNovus adds an executable biological layer: immune mechanisms are represented explicitly, simulated under defined assumptions, and available for inspection. AI helps users work with the models; it does not replace the mechanistic rationale.
Designed to complement existing data, modeling, and drug-development workflows.
An inspectable modeling layer, expanding across scales
The operational modeling layer represents immune pathways and interactions as executable biology. Teams configure a question, run simulations, and inspect which mechanisms and assumptions drive a result.
Connections across molecular, cellular, and system scales are designed to expand as the model and evidence base grow. Published CD4+ T-cell research has demonstrated multiscale integration. ImmuNovus is extending this approach across additional immune cell types and disease contexts.