JemmaPass embeds the full DDInter 2.0 database — the most comprehensive open drug-drug interaction database published in 2024. This page documents which numbers we ship, where they come from, how they're licensed, and why our offline architecture beats the SHL standard.
DDInter 2.0 was published in Nucleic Acids Research, the canonical journal of curated bio databases. Here is precisely what we ship.
ddinter2.scbdd.com. JemmaPass integrates this v2.0 corpus on-device, cross-joined against UMLS 2025AB and ATC 2026.
Comparison between the official DDInter 2.0 Statistics page and the actual rows present in our embedded knowledge_full.db. Both counts auto-measured.
ddinter_drugsddi_facts (3NF normalized)ddi_atc_pairs (expansion)v_ddi_emergencyddi_alternativesinteractions_food ✓ matches exactlydrug_disease_interactionstherapeutic_duplications (focused subset)ddi_mechanism_flags (260,100 rows · 8 boolean flags per fact)2,289 / 2,310 drug gap, the 260,100 / 302,516 facts gap, and the 8,121 / 8,359 DDSI gap all reflect this curation step, not data loss.
The integration is more than a table import. Every DDI record is cross-referenced with RxNorm, ATC, and SNOMED so Gemma 4 can reason across them.
severity IN ('Major', 'Moderate') retained in the v_ddi_emergency view. Minor interactions kept in the full table but not exposed to the rescuer UI to reduce noise.
J01C*, which catches Augmentin (J01CR02) automatically.
drug_displays_localized. Source: WHOCC ATC index, locale-specific drug regulatory authority files (EMA for EU, PMDA for Japan).
JemmaTools.kt alone expose DDI logic to the LLM: resolveDrug, checkDdi, checkDdiByAtc, getAtcAncestors, checkOneDrugAgainstFocusProfile, resolveAllergy, resolveByCode.
In September 2024, at the HL7 FHIR Connectathon, patient advocate Dave deBronkart (e-Patient Dave) collaborated with HL7 IPS, University of Washington, and Verto Health to publish a proof-of-concept IPS QR code.
However, his approach uses SMART Health Links (SHL) — which requires the receiver to be online. JemmaPass solves the same problem with the architectural inverse.
Total: 5 network round-trips. Fails if cell towers are down.
_j2: directTotal: 0 network round-trips. Works on a mountain after an earthquake.
_j2:)The SMART Health Link standard is excellent for its design goal: secure clinical data exchange in connected healthcare settings. A patient hands a clinic a QR; the clinic's server fetches the manifest, decrypts the bundle, and integrates it into the EHR. The cloud-fetch model is appropriate because the patient is in the building, online, with time to wait for a TLS handshake.
JemmaPass targets a different scenario: emergencies where there is no clinic, no Wi-Fi, no cellular signal. We don't replace SHL — we extend the IPS R4 standard with an offline-native transport that uses the same clinical codes (SNOMED, RxNorm, ATC, LOINC) and the same FHIR data model under the hood.
In fact, a JemmaPass profile can be exported to a standard FHIR Bundle compatible with any SHL-aware system. The JemmaFhirBundleBuilder.kt module reconstructs a full HL7 IPS R4 Bundle from the _j 1.2 compressed format. The interoperability flows in both directions.
You've seen the clinical data layer and the architectural inversion. Now see the prize-track alignment, or jump back to the hub.