Journal
PHARMACEUTICAL RESEARCH
Volume 34, Issue 4, Pages 681-686Publisher
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s11095-016-2069-z
Keywords
alternative models; experimental animals; in silico modelling; mammals; toxicology
Funding
- Sao Paulo Research Foundation (FAPESP, Brazil) [2011/15984-0, 2013/25080-7]
- National Council for Scientific and Technological Development (CNPq, Brazil) [310522/2015-3]
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Mammalian models have served as a basis for R&D over the past decades. Nevertheless, these models are expensive, laborious, may yield results that cannot always be translated into the human in vivo situation and, more recently, have reverberated great social and ethical dilemmas. Hence, the prospect of changes in the global scientific scenario and the Three Rs principle (Reduction, Replacement and Refinement) have encouraged the development of alternative methods to the use of mammals. Despite the efforts, suitable alternative tests are not available in all areas of biomedical research, as regulatory acceptance requires time, prior validation and robust financial and scientific investment. In this perspective, we aim to shed light on the concepts, challenges and perspectives for implementation of innovative alternative animal and non-animal methods in scientific research. The applicability and meaningfulness of invertebrate animal models, in silico analysis and reverse pharmacology are discussed, among other aspects of relevance in today's scenario. Overall, the use of alternative models, including Artemia salina (brine shrimp), Caenorhabditis elegans (roundworm), Danio rerio (zebra fish), Drosophila melanogaster (fruit fly), Galleria mellonella (greater waxmoth) and in silico modelling, increased 909% from 1990 to 2015, as compared to 154% of conventional mammals in the same period. Thus, technological and scientific advancements in the fields of toxicology and drug development seem to have diminished the need for mammalian models. Today, however, mammals still remain critically indispensable to provide - in most cases -reliable data subsidizing and validating translation into the clinical setting.
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