Review Articles

2017  |  Vol: 3(2)  |  Issue: 2(March-April)
Novel insights of toxicological evaluation of herbal medicine: Human based toxicological assays

Yasara de Mel1, Sashini Perera1, Pamoda Bashini Ratnaweera2, Chanika Dilumi Jayasinghe*1

1Department of Zoology, The Open University of Sri Lanka, Nawala, Nugegoda, Sri Lanka.

2Department of Science and Technology, Uva Wellassa University, Badulla, Sri Lanka

*Corresponding Author    

Chanika D. Jayasinghe

Department of Zoology

The Open University of Sri Lanka, Nawala, Nugegoda

Telephone +94112881446, 94772806425 


Herbal medicine is still the mainstay of about 80% of the world population for their primary healthcare. Recently, herbal medicine is being accepted as a promising therapeutic modality against many chronic diseases where western medicine perceived to be less successful. Clearly, majority of herbal remedies are considered as safe for consumption, however, there are concerns about their safety. Hence, toxicological evaluation is imperative to reduce the risk associated with herbal products and to confirm their safety and effectiveness. To date, research with experimental animals is considered as a gold standard in toxicology testing, nonetheless, in vivo animal tests are constrained by time, ethical considerations, experimental cost and lack of sufficient congruence between the animal and human physiologies. With the advent of science and technology several novel human-based toxicological models have been introduced. The current review briefly describes the human based toxicity assays introduced as alternatives to in vivo assays, under the categories of cell-based cytotoxicity assays, organ cultures and bioengineered organs on chips, molecular biological models (toxicogenomics and next generation sequencing) and in silico models. Particularly, the promises, limitations and prospects of these assays with respect to herbal drug toxicity are discussed herein.

Keywords: Herbal medicine, toxicity, cytotoxicity, organs on chip, toxicogenomics, next generation sequencing, In silico

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