Literature DB >> 25068930

An analysis of the use of animal models in predicting human toxicology and drug safety.

Jarrod Bailey1, Michelle Thew1, Michael Balls2.   

Abstract

Animal use continues to be central to preclinical drug development, in spite of a lack of its demonstrable validity. The current nadir of new drug approvals and the drying-up of pipelines may be a direct consequence of this. To estimate the evidential weight given by animal data to the probability that a new drug may be toxic to humans, we have calculated Likelihood Ratios (LRs) for an extensive data set of 2,366 drugs, for which both animal and human data are available, including tissue-level effects and MedDRA Level 1-4 biomedical observations. This was done for three preclinical species (rat, mouse and rabbit), to augment our previously-published analysis of canine data. In common with our dog analysis, the resulting LRs show: a) that the absence of toxicity in the animal provides little or virtually no evidential weight that adverse drug reactions (ADRs) will also be absent in humans; and b) that, while the presence of toxicity in these species can add considerable evidential weight for human risk, the LRs are extremely inconsistent, varying by over two orders of magnitude for different classes of compounds and their effects. Therefore, our results for these additional preclinical species have important implications for their use in predicting human toxicity, and suggest that alternative methods are urgently required. 2014 FRAME.

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Year:  2014        PMID: 25068930     DOI: 10.1177/026119291404200306

Source DB:  PubMed          Journal:  Altern Lab Anim        ISSN: 0261-1929            Impact factor:   1.303


  19 in total

1.  Retrospective mining of toxicology data to discover multispecies and chemical class effects: Anemia as a case study.

Authors:  Richard S Judson; Matthew T Martin; Grace Patlewicz; Charles E Wood
Journal:  Regul Toxicol Pharmacol       Date:  2017-02-24       Impact factor: 3.271

2.  Importance of Systematic Reviews and Meta-analyses of Animal Studies: Challenges for Animal-to-Human Translation.

Authors:  Zahra Bahadoran; Parvin Mirmiran; Khosrow Kashfi; Asghar Ghasemi
Journal:  J Am Assoc Lab Anim Sci       Date:  2020-07-29       Impact factor: 1.232

Review 3.  Convergence of human pluripotent stem cell, organoid, and genome editing technologies.

Authors:  Lin Wang; Zhaohui Ye; Yoon-Young Jang
Journal:  Exp Biol Med (Maywood)       Date:  2021-01-19

4.  The multifactorial role of the 3Rs in shifting the harm-benefit analysis in animal models of disease.

Authors:  Melanie L Graham; Mark J Prescott
Journal:  Eur J Pharmacol       Date:  2015-03-28       Impact factor: 4.432

5.  Advances in neuroscience imply that harmful experiments in dogs are unethical.

Authors:  Jarrod Bailey; Shiranee Pereira
Journal:  J Med Ethics       Date:  2017-07-24       Impact factor: 2.903

6.  Hepatotoxicity of Antimycotics Used for Invasive Fungal Infections: In Vitro Results.

Authors:  Sandra Doß; Heike Potschka; Fanny Doß; Steffen Mitzner; Martin Sauer
Journal:  Biomed Res Int       Date:  2017-04-04       Impact factor: 3.411

7.  Safety Profile Based on Concordance of Nonclinical Toxicity and Clinical Adverse Drug Reactions for Blood Cancer Drugs Approved in Japan.

Authors:  Sachie Kubota; Kazuyuki Saito; Shunsuke Ono; Yasuo Kodama
Journal:  Drugs R D       Date:  2017-03

8.  Necessary, but Not Sufficient. The Benefit Concept in the Project Evaluation of Animal Research in the Context of Directive 2010/63/EU.

Authors:  Matthias Eggel; Herwig Grimm
Journal:  Animals (Basel)       Date:  2018-02-28       Impact factor: 2.752

9.  QSAR models of human data can enrich or replace LLNA testing for human skin sensitization.

Authors:  Vinicius M Alves; Stephen J Capuzzi; Eugene Muratov; Rodolpho C Braga; Thomas Thornton; Denis Fourches; Judy Strickland; Nicole Kleinstreuer; Carolina H Andrade; Alexander Tropsha
Journal:  Green Chem       Date:  2016-10-06       Impact factor: 10.182

Review 10.  Understanding biomaterial-tissue interface quality: combined in vitro evaluation.

Authors:  Michael Gasik
Journal:  Sci Technol Adv Mater       Date:  2017-07-31       Impact factor: 8.090

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