Discovery and translation
Target biology, pathway context, disease mechanisms and evidence prioritisation.
AI-MIDD
Mechanistic model-informed drug development
IQANOVA combines mechanistic pharmacology, AI-enabled surrogates, SBML model engineering and regulatory-aware validation to accelerate drug-development decisions without sacrificing biological interpretability.
The AI-MIDD workflow
AI-MIDD is a structured workflow: define context of use, reconstruct or import the mechanistic core, curate literature and datasets, calibrate and validate, build surrogates where speed is needed, and publish auditable outputs.
- QSP/PBPK/PBBM model reconstruction
- SBML conversion and model-card generation
- Global sensitivity, identifiability and virtual population workflows
- Surrogate validation aligned with context of use
1Context of use
2Mechanistic core
3Calibration
4Validation
5ATLAS deployment
Where it applies
Clinical development
Dose/regimen exploration, endpoint mapping, biomarker trajectories and subgroup strategy.
Regulatory and payer evidence
Transparent model files, validation evidence, assumption tracking and reproducible reports.