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The pharmacopeia used by physicians and lay people in medieval Europe haslargely been dismissed as placebo or superstition. While we now recognise thatsome of the materia medica used by medieval physicians could have had usefulbiological properties, research in this area is limited by the labour-intensiveprocess of searching and interpreting historical medical texts. Here, wedemonstrate the potential power of turning medieval medical texts intocontextualised electronic databases amenable to exploration by algorithm. Weuse established methodologies from network science to reveal statisticallysignificant patterns in ingredient selection and usage in a key text, thefifteenth-century Lylye of Medicynes, focusing on remedies to treat symptoms ofmicrobial infection. We discuss the potential that these patterns reflectrational medical decisions. In providing a worked example of data-driventextual analysis, we demonstrate the potential of this approach to encourageinterdisciplinary collaboration and to shine a new light on theethnopharmacology of historical medical texts.

Datamining a medieval medical text reveals patterns in ingredient choice  that reflect biological activity against the causative agents of specified  infections