Article révisé par les pairs
Résumé : We present an open-source web application addressing inappropriate self-medication with over-the-counter (OTC) analgesics through evidence-based, personalized benefit-risk assessments. Self-medication often relies on personal opinions rather than professional guidance, increasing risks of adverse drug reactions and leading to preventable burden on patients and healthcare systems. Our software implements a weighted decision-support algorithm based on clinical guidelines for the widely used OTC analgesics paracetamol (acetaminophen), ibuprofen, naproxen, and aspirin (acetylsalicylic acid). It analyzes user-specific symptoms, comorbidities, co-medications, and demographics using a three-tier scoring system to generate personalized recommendations. The algorithm runs client-side, ensuring data privacy while enhancing recommendations with patient-specific explanations and scientific references that make pharmacological evidence accessible to patients. Publicly available at www.medicationguide.org, this open-source software represents a replicable framework for personalized medication guidance that has the potential to transform medication selection across diverse healthcare contexts.

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