Interaction checking with mechanistic depth
Drug-drug interactions cause 30% of all adverse drug events. A patient on 8 medications has 28 interaction pairs to evaluate. Skippy DDI checks all of them in one call — explains the CYP mechanism, scores panel risk, and returns verified alternatives.
Additive anticoagulation and antiplatelet effect. Concurrent use significantly increases GI and intracranial bleeding risk.
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Interaction checking and CYP pathway analysis — same API shape as production.
Additive anticoagulation and antiplatelet effect. Concurrent use significantly increases GI and intracranial bleeding risk.
Avoid concurrent use if possible. If clinically necessary, use lowest effective aspirin dose (≤81mg/day) with close INR monitoring and GI protection.
94% conf.Omeprazole reduces CYP2C9-mediated warfarin clearance, increasing warfarin plasma levels and INR.
Monitor INR closely when initiating or discontinuing omeprazole. Pantoprazole has lower CYP2C9 interaction potential if PPI is required.
82% conf.Omeprazole provides gastroprotective benefit against aspirin-induced GI irritation. Low clinical risk.
Favorable combination — PPI co-prescription reduces aspirin-related GI risk. No dose adjustment needed.
71% conf.Six endpoints. One API.
Interaction checking, pathway analysis, alternatives, drug profiles, panel risk, and PGx dosing — all callable from a single integration.
Evaluates all N×(N-1)/2 drug pairs in a single call. Returns severity, mechanism, CYP conflicts, confidence score, and recommendation for every pair — with panel risk score and risk hub identification.
Given a MAJOR interaction, returns ranked alternatives verified against the full medication panel. The replacement is checked for new conflicts before being recommended.
Per-drug enzyme role breakdown (substrate, inhibitor, inducer) with cross-drug conflict detection across CYP2D6, CYP2C9, CYP2C19, and CYP3A4.
Full drug profile: mechanism of action, CYP metabolism, target bioactivities from DrugCentral, contraindications, and indications.
Aggregate risk score for a medication panel (MAJOR×3 + MODERATE×2 + MINOR×1), with risk hub — the drug involved in the most interactions — and top enzyme identified.
CPIC-grounded dosing recommendations for drug + diplotype pairs. Pharmacogenomics meets interaction checking in the same API — when a co-medication also has a PGx implication.
Common dangerous pairs
Frequently co-prescribed combinations with established clinical interaction evidence.
Additive anticoagulation + antiplatelet effect — major GI and intracranial bleeding risk
CYP3A4 inhibition → simvastatin plasma levels elevated → myopathy and rhabdomyolysis risk
Serotonin syndrome — potentially fatal. Washout period required before switching
Lactic acidosis risk — hold metformin 48h before and after contrast administration
CYP2C9 inhibition by fluconazole markedly elevates warfarin levels — INR monitoring required
Modest CYP3A4 overlap — atorvastatin levels modestly increased. Low clinical risk at standard doses
Interaction pairs scale as N×(N-1)/2. A patient on 8 medications has 28 pairsto evaluate — manually, that means 28 separate lookups. At 12 drugs, it's 66. Skippy DDI evaluates the entire panel in a single call, returns a panel risk score, and identifies the risk hub — the drug involved in the most interactions.
Panel risk scoring
Every interaction pair carries a severity rating. Panel risk score = MAJOR×3 + MODERATE×2 + MINOR×1. The drug with the most interactions in the panel is flagged as the risk hub.
Contraindicated or strongly discouraged. Life-threatening outcome possible. Requires alternative selection or clinical escalation.
Use with caution and close monitoring. Dose adjustment, enhanced monitoring, or an alternative may be warranted.
Low clinical risk at standard doses. Document for awareness. Routine monitoring is typically sufficient.
CYP enzyme pathway analysis
DDI doesn't return severity flags — it returns the mechanism. CYP substrate, inhibitor, and inducer relationships for each drug in your panel, with conflict detection across enzymes.
Major substrate for ~25% of marketed drugs. PM phenotype increases toxicity risk with codeine and TCAs.
Narrow therapeutic index substrates dominate this enzyme. Inhibitors cause clinically significant INR changes.
Genetic variation and drug inhibition both affect this pathway — PGx overlap is highest here.
Responsible for ~50% of drug metabolism. Broad inhibitor/inducer landscape makes this the highest-traffic enzyme.
Simvastatin + clarithromycin leading to rhabdomyolysis. SSRI + MAOI causing serotonin syndrome. Warfarin + NSAID resulting in fatal GI bleeding.
These are well-documented, preventable events — not edge cases. They happen when clinicians lack the mechanism-level detail to act on an alert. Skippy DDI surfaces not just the severity, but the CYP pathway, the clinical effect, and a verified alternative — at the moment of prescribing.
“69% of drug-drug interaction alerts are overridden by clinicians. The system isn't failing to generate alerts — it's failing to generate actionable ones.”
Published literature on DDI alert override rates in EHR systems
Static databases flag everything. Skippy DDI explains the mechanism, scores the risk, and offers a next step — so clinicians can act on an alert rather than dismiss it. Finding the interaction is step one. Knowing what to prescribe instead is what prescribing workflows actually need.
Prescribers, pharmacists, and platform builders
FHIR-native, Joint Commission aligned
DDI findings are returned as FHIR R4 Observation resources with LOINC code 89378-2 (Drug-drug interaction check) and calibrated confidence extensions — ready for certified EHR integration.
ECE-calibrated confidence scores (ECE = 0.07, Gate 1 confirmed) meet FDA SaMD AI/ML guidance requirements. Every interaction check generates an immutable audit record for Joint Commission medication safety documentation. HIPAA-ready with BAA available.
Not a static lookup table.
Drug interaction databases return a severity flag from a static rule table. Skippy DDI returns a verified finding from evidence — with mechanism, confidence, source lineage, and alternatives already evaluated.
Returns the CYP enzyme involved, the type of conflict (inhibition, induction, substrate competition), and the clinical effect — not just MAJOR/MODERATE/MINOR.
N×(N-1)/2 pairs evaluated in a single API call with a panel risk score and risk hub identification. Designed for real prescribing complexity.
Recommended substitutes are checked against the full medication panel before being returned. The replacement won't create a new conflict.
Every interaction carries a calibrated confidence score from real evidence — not a binary flag. Contested findings are surfaced explicitly, not silently dropped.
Built for the prescribing workflow
DDI alerts that interrupt workflow get dismissed. DDI that surfaces at the right moment with actionable detail gets used.
Fires when a new medication order is placed — surfaces interactions before the order is signed.
Panel risk summary on the patient chart — high-risk flag before any new prescribing session begins.
Full interaction report during pharmacist order review — detailed mechanism and alternative recommendations.
Five authoritative databases.
Every interaction finding is traceable to its source database — not a proprietary black box. Confidence scores reflect actual evidence quantity and quality across all five sources.
Primary DDI database — curated interaction pairs with severity, mechanism, and clinical evidence. ~1.2M catalogued interaction pairs from peer-reviewed literature.
FDA Drug Label database — brand-name resolution, prescribing information, contraindications, and FDA-reviewed interaction warnings from 15,000+ drug labels.
University of New Mexico bioactivity database — IC50/Ki binding assay data for CYP enzyme inhibitor classification and target conflict analysis.
Drug-Gene Interaction Database — drug-gene associations used for shared molecular target analysis and novel interaction inference via gene pathway overlap.
Stanford Pharmacogenomics Knowledgebase — PGx variant-drug annotations with level-of-evidence grades for gene-drug interactions and CPIC dosing guidelines.
Other Skippy medical products
When a co-medication inhibits or induces the very enzyme your patient is already genetically sensitive to, DDI and PGx together surface it. CPIC-grounded dosing for 21,000+ gene-drug pairs.
Hard verification gate for any AI-generated medical claim. Calibrated confidence, source lineage, and an immutable audit record on every call.
Pre-submission CPT and ICD-10 verification with NCD/LCD evidence — catch denial risks before claims go out.
Clinical Decision Support · Not a Substitute for Clinical Judgment. Skippy DDI is an evidence-grounded clinical decision support tool. All interaction findings, severity ratings, and alternative recommendations are intended to support — not replace — the judgment of qualified prescribers and pharmacists. Recommendations should be evaluated in the context of the individual patient's clinical history, comorbidities, and therapeutic goals.
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We work with EHR vendors, PBMs, and medication safety teams. Let's talk about your drug interaction problem.