• Elena Fioravanzo

A Review of In Silico Tools as Alternatives to Animal Testing: Principles, Resources and Application


If you are just starting with computational toxicology, or if you wish an update the available tools, I suggest you to read this paper, a review of in silico tools as alternative to animal testing: (Q)SAR, rea-across, PBK and others. It was published just few weeks ago and the authors are well known experts: Judith C. Madden, Steven J. Enoch, Alicia Paini, Mark T.D. Cronin.


Free to download: https://journals.sagepub.com/doi/full/10.1177/0261192920965977


Abstract

Across the spectrum of industrial sectors, including pharmaceuticals, chemicals, personal care products, food additives and their associated regulatory agencies, there is a need to develop robust and reliable methods to reduce or replace animal testing. It is generally recognised that no single alternative method will be able to provide a one-to-one replacement for assays based on more complex toxicological endpoints. Hence, information from a combination of techniques is required. A greater understanding of the time and concentration-dependent mechanisms, underlying the interactions between chemicals and biological systems, and the sequence of events that can lead to apical effects, will help to move forward the science of reducing and replacing animal experiments. In silico modelling, in vitro assays, high-throughput screening, organ-on-a-chip technology, omics and mathematical biology, can provide complementary information to develop a complete picture of the potential response of an organism to a chemical stressor. Adverse outcome pathways (AOPs) and systems biology frameworks enable relevant information from diverse sources to be logically integrated. While individual researchers do not need to be experts across all disciplines, it is useful to have a fundamental understanding of what other areas of science have to offer, and how knowledge can be integrated with other disciplines. The purpose of this review is to provide those who are unfamiliar with predictive in silico tools, with a fundamental understanding of the underlying theory. Current applications, software, barriers to acceptance, new developments and the use of integrated approaches are all discussed, with additional resources being signposted for each of the topics.


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