Literature DB >> 23518859

Leveraging biodiversity knowledge for potential phyto-therapeutic applications.

Vivekanand Sharma1, Indra Neil Sarkar.   

Abstract

OBJECTIVE: To identify and highlight the feasibility, challenges, and advantages of providing a cross-domain pipeline that can link relevant biodiversity information for phyto-therapeutic assessment.
MATERIALS AND METHODS: A public repository of clinical trials information (ClinicalTrials.gov) was explored to determine the state of plant-based interventions under investigation.
RESULTS: The results showed that ≈ 15% of drug interventions in ClinicalTrials.gov were potentially plant related, with about 60% of them clustered within 10 taxonomic families. Further analysis of these plant-based interventions identified ≈ 3.7% of associated plant species as endangered as determined from the International Union for the Conservation of Nature Red List. DISCUSSION: The diversity of the plant kingdom has provided human civilization with life-sustaining food and medicine for centuries. There has been renewed interest in the investigation of botanicals as sources of new drugs, building on traditional knowledge about plant-based medicines. However, data about the plant-based biodiversity potential for therapeutics (eg, based on genetic or chemical information) are generally scattered across a range of sources and isolated from contemporary pharmacological resources. This study explored the potential to bridge biodiversity and biomedical knowledge sources.
CONCLUSIONS: The findings from this feasibility study suggest that there is an opportunity for developing plant-based drugs and further highlight taxonomic relationships between plants that may be rich sources for bioprospecting.

Entities:  

Keywords:  biodiversity informatics; bioprospecting; clinical trials; medicinal plants

Mesh:

Year:  2013        PMID: 23518859      PMCID: PMC3721164          DOI: 10.1136/amiajnl-2012-001445

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


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