The AI Respiratory Research Intelligence agent — airway to alveolus to outcome.
A scientific research agent (not a chatbot, not a diagnostic tool) that discovers, connects, analyses, challenges and synthesises respiratory-medicine knowledge from authorized literature, databases, datasets and enterprise tools — to help you understand what is known, what is unknown, what may be true, what has failed and what to test next.
Twelve deeply-connected knowledge domains spanning the research lifecycle.
Asthma, COPD, idiopathic pulmonary fibrosis, cystic fibrosis, pulmonary hypertension, ILD, bronchiectasis and acute lung injury/ARDS across severity and phenotype.
Airway epithelium & goblet cells, alveolar biology, mucus & cilia, smooth muscle, fibroblast activation, surfactant, the pulmonary vasculature and lung immune cells.
Type-2 vs non-T2 inflammation, eosinophils, ILC2s, IL-4/5/13, TSLP, neutrophilic pathways and fibrosis signalling — mechanism → biomarker → target → therapy → outcome.
Genomics (GWAS, CFTR & rare variants), single-cell & spatial lung atlases, sputum/BAL proteomics, the airway microbiome and exhaled-breath metabolomics — connected across scales.
Human-genetic, functional and multi-omics evidence for respiratory targets — with tractability, lung delivery, safety and prior failures clearly separated.
Small molecules, biologics, RNA & gene therapy — plus the inhaled-delivery science: aerosol deposition, device–formulation fit and local vs systemic exposure.
FeNO, blood/sputum eosinophils, spirometry (FEV1), imaging, and phenotype/endotype biomarkers that stratify patients — with validation and clinical-utility context.
Design, population, endpoints (exacerbation rate, FEV1, FVC decline), biomarkers, comparators, results and adverse events — surfacing failed hypotheses and design opportunities.
Inhalers & nebulizers, adherence & inhaler technique, safety signals, and real-world effectiveness — distinguishing a signal from confirmed causality.
Exacerbation & decline modelling, survival analysis, cluster/endotype analysis, causal inference and multi-omics integration on authorized respiratory datasets.
Reasons across Disease ↔ Gene ↔ Cell ↔ Mediator ↔ Pathway ↔ Biomarker ↔ Target ↔ Drug ↔ Device ↔ Trial ↔ Outcome, with every claim traceable to primary sources.
Finds conflicting findings, non-T2 mechanism gaps, missing biomarkers and poorly-validated targets — then frames testable hypotheses and experiments.
Surface novel, testable research directions and drug-repurposing leads across the whole ecosystem — not a single paper.
Integrate literature, omics, trials and real-world data into one traceable evidence graph so hidden connections become visible.
A built-in scientific critic tests for confounding, batch effects, power, publication bias, replication and prior failures.
Research questions, proposals, protocols, SAPs, reviews and manuscript scaffolds — never fabricating data, patients, stats or citations.
Statements are tagged so you always know their standing — and confidence is stated, never inflated. Citations, DOIs, PMIDs, dataset and trial IDs are drawn from primary sources; if a source can't be verified it says so. Respiratory Genius is a research-intelligence system, not a substitute for a physician — it does not diagnose or treat individuals.
We use cookies to run Anxya Health and improve your experience. Choose how we may use them. Read our Cookie Policy, Privacy Policy and Terms.