Opinion versus evidence for the need to move away from animal testing

Abstract

toxicology, animal models are as much misleading as they are helpful. Half of the results are wrong (Ioannidis, 2005) -we only don't know which half… But the statement "half are wrong" is probably rather optimistic. Evidence versus opinion in toxicologyI am a strong advocate of evidence-based approaches, not least because I was one of the initiators of Evidence-based Toxicology (EBT) and the respective Collaboration and hold the first IntroductionFor the 10 th anniversary of Food for Thought … in ALTEX, it seemed appropriate to summarize what we have learned on this journey with respect to the core subject of this journal: the need for alternatives to animal experimentation. The series has mostly focused on toxicology, but here the aspects that apply also to drug development and basic research shall be considered.Sure, we need animal models -when we want to study animals. For example, we have to test drugs for animals in animals. However, when studying human physiology, pharmacology and Food for Thought ... Opinion Versus Evidence for the Need to Move Away from Animal Testing Thomas HartungJohns Hopkins University, Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA, and University of Konstanz, CAAT-Europe, Konstanz, Germany SummaryScience is based on facts and their discourse. Willingly or unwillingly, facts are mixed with opinion, i.e., views or judgments formed, not necessarily based on fact or knowledge. This is often necessary, where we have controversial facts or no definitive evidence yet, because we need to take decisions or have to prioritize. Evidence-based approaches aim at identifying the facts and their quality objectively and transparently; they are now increasingly embraced in toxicology, especially by employing systematic reviews, meta-analyses, quality scoring, risk-of-bias tools, etc. These are core to Evidence-based Toxicology. Such approaches aim at minimizing opinion, the "eminence-based" part of science. Animal experiments are the basis of a lot of our textbook knowledge in the life sciences, have helped to develop desperately needed therapies, and have made this world a safer place. However, they represent only one of the many possible approaches to accomplish all these things. Like all approaches, they come with shortcomings, and their true contribution is often overrated. This article aims to summarize their limitations and challenges beside the ethical and economical concerns (i.e., costs and duration as well as costs following wrong decisions in product development): they include reproducibility, inadequate reporting, statistical under-powering, lack of inter-species predictivity, lack of reflection of human diversity and of real-life exposure. Each and every one of these increasingly discussed aspects of animal experiments can be amended, but this would require enormous additional resources. Together, they prompt a need to engineer a new paradigm to ensure the safety of patients and consumers, new products and therapies.

Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility

“…It is possible that these models obtain stronger results than single animal tests in cases where they can leverage reliable data on analogs or off-target hazards of the predicted compound. Shortcomings in animal testing have been discussed earlier ( Basketter et al , 2012 ; Hartung, 2008 , 2013 ); a recent publication of ours ( Smirnova et al , 2018 ) summarizes this for the systemic endpoints though the balance between opinion and evidence is difficult in the absence of systematic reviews ( Hartung, 2017a ). For the acute and topical hazards addressed here, some analyses available are in line with our earlier findings ( Luechtefeld et al , 2016c , d ) and those reported here: The variability of the LLNA was pointed out by Urbisch et al (2015) : By retesting 22 LLNA performance standards in the standard LLNA protocol, a reproducibility of only 77% was found ( Kolle et al , 2011 ).…”

3S - Systematic, systemic, and systems biology and toxicology

“…The shortcomings of the current paradigm have been discussed earlier (Hartung, 2008a, 2013; Basketter et al, 2012; Paparella et al, 2013, 2017); some studies that cast doubt as to their performance are summarized in Table 1, using the more factual references, though the balance between opinion and evidence is difficult in the absence of systematic reviews (Hartung, 2017b). However, they stress the need for the strategic development of a new approach (Busquet and Hartung, 2017), especially for the systemic toxicities.…”

Brazil Moves Toward the Replacement of Animal Experimentation

“…It is widely acknowledged that animal experimentation has, in the past, been a great ally for humanity in the advancement of science, especially in the life sciences. 8 However, animal-based research models have been widely criticised for many reasons, and some scientists believe that, with the advancement of science, such models will no longer be the first choice for various biological assays and investigations. 8,9 Experiments based on animal models are unsustainable for various reasons.…”

“…8 However, animal-based research models have been widely criticised for many reasons, and some scientists believe that, with the advancement of science, such models will no longer be the first choice for various biological assays and investigations. 8,9 Experiments based on animal models are unsustainable for various reasons. These include cost and time requirements, animal welfare considerations, technical questions related to the low predictive capacity and poor reproducibility of in vivo studies and the extent of technical-scientific progress made in recent decades.…”