RxSage answers one critical question for every patient encounter: "Is it safe to prescribe this drug?" — powered by 7 evidence sources, deterministic risk guardrails, and GPT-4o clinical reasoning.
Hypertensive crisis risk. Standard local anesthetic becomes dangerous without a flag.
Compounded bleeding risk. Ibuprofen post-extraction can trigger serious hemorrhage.
MRONJ risk is non-obvious. Years-old prescriptions still elevate jaw osteonecrosis probability.
Clean profile, no flags. RxSage confirms safe — dentist proceeds with confidence.
Dentists prescribe local anesthetics, antibiotics, analgesics, and sedation agents — often to patients on complex medication regimens. A single missed drug interaction can escalate into a medical emergency mid-procedure.
Existing drug reference tools aren't built for dental workflows. They're generic, slow, and require manual chart review. RxSage is purpose-built: one API call surfaces every clinically relevant risk before the chair tips back.
For dental software companies, this is a differentiation opportunity. Practices that can't get this kind of safety check through your platform will look elsewhere.
Every API request passes through a deterministic, multi-layer pipeline before GPT-4o ever reasons about the case.
Brand names resolve to generics (Tylenol → acetaminophen, Coumadin → warfarin). Dosage noise stripped automatically.
Supabase exact-match cache returns instantly — no tokens burned. In-memory L1 cache skips all external calls for recently seen drug combos.
Six sources run in parallel — no single source of truth. Everything cross-referenced before GPT-4o sees it.
Patient factors set a hard risk floor in code — GPT-4o cannot lower it. Elderly + CKD + NSAID always returns high, no exceptions.
Evidence scored on a 7-tier trust scale (case report → RCT → systematic review → FDA label). Conflicts auto-resolve to the higher-trust source.
GPT-4o answers 7 dental workflow questions — anesthetic safety, antibiotic safety, analgesic safety, sedation safety, oral manifestations, and procedure context. Every claim must trace to verified evidence. A grounding check flags any interaction GPT-4o mentions that isn't in the source data.
Select a clinical scenario or build a custom patient profile and run the analysis.
Select a scenario or configure a
patient profile and run the analysis.
FDA labels, adverse event reports, and peer-reviewed literature — cross-referenced on every query. All free public APIs, no licensing risk.
154 drugs mapped to pharmacological classes. 39 class-pair interaction rules. 16 drug-condition rules. Instant, no network call.
Tier 6 — CuratedLabel warnings, contraindications, and interactions. Real-world co-prescription data from FAERS adverse events.
Tier 7 — FDA LabelStructured FDA drug labels in SPL XML from NLM. Interactions extracted by LOINC code.
Tier 7 — FDA LabelPairwise drug interaction literature via E-utilities. Covers both drug–drug pairs and drug–procedure pairs (e.g., bisphosphonate + extraction → MRONJ literature).
Tier 3–5 — LiteratureATC classification and CYP enzyme data for metabolic pathway conflicts.
Tier 5 — Curated DBInteraction and precaution sections from NLM drug pages.
Tier 4 — NLMYour UI surfaces only what each moment needs — from a glanceable mid-procedure flag to a full audit trail for documentation.
Rendered in under 100ms by your UI. Everything needed at a glance during a live procedure.
For the pre-procedure review. Interaction breakdowns, procedure modifications, and workflow sections.
Full clinical explanation, source attribution, evidence quality metadata, and referral guidance.
POST a patient profile and candidate drug. Get back a validated, schema-compliant clinical analysis. Works with any stack.
# One-time setup — get your API key at rxsage.com import requests response = requests.post( "https://api.rxsage.com/v1/analyze", headers={"X-API-Key": "your_api_key_here"}, json={ "patient": { "age": 67, "sex": "male", "conditions": ["atrial fibrillation", "hypertension"], "medications": ["warfarin", "lisinopril"], "allergies": ["penicillin"], }, "candidate_drug": "ibuprofen 600mg", "procedure": "molar extraction", } ) result = response.json() print(result["tier1"]["proceed_flag"]) # → "do_not_proceed" print(result["tier1"]["risk_level"]) # → "high"
SHA-256 hashed keys stored in Supabase. Rate limits: 10/min, 100/hr, 500/day per key.
Two-layer caching means repeat drug lookups return in milliseconds. Cache hits are rate-limit exempt.
Every response is validated against strict Pydantic models before returning. No malformed JSON ever reaches your UI.
Every critical safety decision is enforced deterministically in code. GPT-4o is a reasoner, not a gatekeeper.
Patient factors like age >65, renal impairment, polypharmacy, and pregnancy set a minimum risk level in code — independent of GPT-4o's output. If the model returns "medium" but the floor is "high", it gets overridden. This logic is auditable and testable.
After GPT-4o responds, a grounding check scans every claimed interaction against the verified evidence set. Claims that aren't traceable to a source are flagged with a grounding warning — so your users always know when the model is reaching beyond confirmed data.
When sources disagree, the ranker defaults to the higher-trust source. FDA labels beat observational data. Conflict logic is surfaced in the Tier 3 response.
Every analysis is logged: key ID, risk level, latency, cache status, and fallback usage. Full audit trail for every clinical decision — ready for regulatory review.
Book a 30-minute technical walkthrough with the RxSage team. We'll cover integration, pricing, and answer any clinical or engineering questions.
Used by dental software teams in the US · HIPAA-conscious architecture · Free sandbox keys available