Finding the right clinical profile — for research, commercial intelligence, or access strategy — has always been a manual, slow, error-prone process. iHealth changes that with a clinical search platform that reads what traditional systems ignore: the free text of medical records.
With +5 million lives in a longitudinal database and NLP trained for Brazilian medical Portuguese, we locate clinical profiles with surgical precision — by diagnosis, treatment line, comorbidities, biomarkers, and dozens of variables extracted from unstructured clinical text.
Electronic health record systems structure only a small fraction of what is clinically recorded. Coded diagnoses, prescribed medications, test results — all of that exists in structured fields. But what truly defines a patient's clinical profile lies elsewhere: in physician progress notes, nursing notes, reports, and clinical observations.
That's the data conventional systems can't read. And it's exactly where the richest information for research, access, and commercial intelligence resides.
iHealth reads that text. It extracts the relevant clinical variables through NLP in medical Portuguese and makes them searchable in a platform that combines clinical precision with operational speed.
Locate patients through complex combinations of clinical criteria — primary and secondary diagnosis, disease stage, current and prior treatment line, medications in use, comorbidities, biomarkers, test results, and clinical variables extracted by NLP from free text. Clinically validated results documented with traceability for use in regulatory studies.
Mapping of the patient population treated with a specific medication — by region, demographic profile, progression pattern, and clinical outcomes. Identification of diagnosis gaps, therapeutic-line switching opportunities, and market potential by indication. Real-world data to support commercial and market-access strategies.
Identification of eligible candidates for clinical trials based on the protocol's inclusion and exclusion criteria — with automatic extraction of clinical variables via NLP. A qualified candidate list, with auditable documentation for use in screening and regulatory submission.
Detailed characterization of the identified population — prevalence by region, demographic distribution, current treatment pattern, most frequent comorbidities, clinical outcomes, and average time between milestones of the clinical journey. Real-world data that supports market access analyses, HEOR, and launch planning.
Beyond finding the profile, iHealth tracks the clinical evolution of identified patients over time — monitoring outcomes, treatment changes, hospitalizations, and adverse events in the longitudinal database. Ideal for comparative effectiveness studies, disease burden, and patient journey analyses with real-world data.
iHealth owns its data infrastructure. We don't broker data from other sources — we generate, structure, and maintain our own longitudinal clinical database, with full control over quality, traceability, and regulatory compliance.
Our NLP engine isn't a generic tool adapted to Portuguese. It was built from the ground up for the vocabulary, abbreviations, and narrative structures of Brazilian medical Portuguese — with clinical precision validated by specialists.
40+ hospitals across all 5 regions of Brazil — not just São Paulo and Rio. That means real epidemiological representativeness of the Brazilian population, with geographic, demographic, and treatment-pattern diversity.
LGPD-first architecture with anonymization at the source, irreversible hashing, complete lineage, and documented legal bases. Outputs ready for regulatory submission to CONITEC, ANVISA, FDA, and EMA.
We have the database. We have the methodology. And we have the hospital partners to support your project — from design to results.
