Zhavoronkov, A. (2018) Artificial Intelligence for Drug Discovery, Biomarker Development, and Generation of Novel Chemistry. Molecular Pharmaceutics, 15, 4311-4313.
https://doi.org/10.1021/acs.molpharmaceut.8b00930

has been cited by the following article:

• TITLE: Traditional Uses and Big Data Approaches: A Semi-Systematic Review on the Refoundation of Tropical Ethnopharmacology and Pharmacognosy under WHO Frameworks

  AUTHORS: Nabèrè Ouattara, Samson Guenne, Alphonsine Ramdé-Tiendrébéogo, Nâg-Tiéro Roland Meda

  KEYWORDS: Ethnopharmacology, Medicinal Plants, Traditional Knowledge, Pharmacognosy, WHO, Big Data

  JOURNAL NAME: Journal of Biosciences and Medicines, Vol.14 No.8, August 31, 2026

  ABSTRACT: Background: Ethnopharmacology plays a central role in the discovery and validation of medicinal plants and their molecular compounds, particularly in tropical regions where biodiversity and traditional knowledge are highly concentrated. Aim: This semi-systematic review aims to examine how ethnopharmacology and pharmacognosy are being reshaped under WHO frameworks and data-driven approaches. Methods: A PRISMA-informed semi-systematic review of peer-reviewed literature was conducted across major scientific databases and WHO sources. Results: Our research included one hundred and sixteen studies, revealing partial convergence between traditional uses and pharmacognostic validation, alongside significant methodological heterogeneity. Conclusion: Integrative and ethically grounded frameworks are required to ensure scientific rigor, cultural legitimacy, and sustainability in tropical ethnopharmacology.