A case study of the Ancientbiotics collaboration

Erin Connelly, Christina Lee, Jessica Furner-Pardoe, Charo del Genio, Freya Harrison

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
54 Downloads (Pure)

Abstract

Interdisciplinary collaboration is regarded as a desirable way of researching and, in some instances, even a requirement for academic teams and funding proposals. This paper explores the possibilities, but also the problems, of collaboration between different disciplines through a case study of the Ancientbiotics team. This team explores the potential of natural products contained in historical medical recipes. The search for clinically useful natural products in unusual places, such as historical medical practices, is a well-established endeavor in the scientific disciplines. The Ancientbiotics collaboration, largely based across UK institutions, takes this path a step forward in combining modern scientific knowledge of natural products with expertise from humanities to identify ingredient combinations. After 7 years of practice, the research has produced a variety of outcomes. This perspective will explore how the team worked within an interdisciplinary framework to advance investigation and application of historical medical recipes.
Original languageEnglish
Article number100632
Number of pages8
JournalPatterns
Volume3
Issue number12
Early online date9 Dec 2022
DOIs
Publication statusPublished - 9 Dec 2022

Bibliographical note

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited..

Keywords

  • AMR
  • DSML3: Development/pre-production: Data science output has been rolled out/validated across multiple domains/problems
  • collaboration
  • datamining
  • ethnopharmacology
  • history of medicine
  • interdisciplinary
  • medieval studies
  • network analysis

ASJC Scopus subject areas

  • Decision Sciences(all)

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