Research Paper on AuditMed: A Single-File, Browser-Based Clinical Evidence Audit Platform Architecture, Current Capabilities, and Proposed Applications in Drug Informatics and Pharmacy Education

BackgroundClinical pharmacists, trainees, and educators increasingly rely on multi-database literature retrieval and structured evidence synthesis to answer drug-information questions and support therapeutic decisions. Commercial integrated platforms exist but remain inaccessible to many learners in community, rural, and international training contexts. ObjectiveThis paper describes the architecture and current capabilities of AuditMed -- a single-file, browser-based clinical evidence audit platform -- and reports the findings of an initial internal validation exercise in which the platforms one-click Clinical Inference workflow was applied to a pre-authored compendium of ten complex clinical cases (Cases 30-39) to produce synthetic data outputs which are simulated for the deterministic engine. MethodsAuditMed integrates nineteen free, publicly available clinical and biomedical APIs into a six-stage Search[->]Select[->]Parse[->]Analyze[->]Infer[->]Create pipeline and produces nine structured output formats. A complex clinical case compendium (10 pre-authored cases spanning multi-organ disease, oncology, immunology, and hematology) was processed through the one-click inference workflow. Each output was reviewed against the cases documented diagnoses, lab values, medications, and pharmacy-boards-level teaching points to identify correctly flagged findings, missed findings, and structural artifacts. ResultsAcross ten cases, the platform correctly surfaced six high-yield teaching points: a three-agent serotonin-syndrome combination (Case 30), dual hepatotoxicity (Case 31), an amiodarone-digoxin P-gp interaction (Case 34), voriconazole CPIC-A pharmacogenomics (Case 36), phenytoin HLA-B*15:02 screening (Case 38), and warfarin CYP2C9/VKORC1 dosing guidance (Case 39). Four structural problems recurred: (i) a 50-layer polyroot reasoning chain was identical across all cases regardless of clinical seed; (ii) an input-parsing error mapped patient age to body temperature, producing physiologically impossible fevers of 41{degrees}C to 70{degrees}C in six cases; (iii) the diagnosis field in Case 38 was corrupted by a medication-dosing instruction that propagated through the entire report; and (iv) the embedded drug-drug interaction matrix was sparse, missing clinically significant pairs including ciprofloxacin-warfarin, voriconazole-cyclosporine, amphotericin-aminoglycoside nephrotoxicity stacking, and prednisone-warfarin. DiscussionAuditMeds pharmacogenomic and selected drug-drug interaction modules produced clinically meaningful outputs when they fired, and the platforms explicit verification-step architecture is a structural strength. The recurrent failure modes -- a boilerplate polyroot chain, input parsing without sanity validation, and sparse DDI coverage -- are amenable to short, high-yield engineering fixes and do not require re-architecting the pipeline. Case-level clinical question framing also suffers from a relevance-ranking bias toward medications in list order rather than by clinical acuity. ConclusionAuditMed demonstrates proof-of-concept for a free, transparent, auditable multi-source evidence synthesis workflow suitable for pharmacy education and drug-informatics training. The internal validation exercise reported here identifies four specific, tractable engineering priorities whose resolution is required before the platform can be responsibly recommended beyond research and educational use. Formal external validation against retrieval and synthesis benchmarks remains planned.