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      Limitations of Animal Studies for Predicting Toxicity in Clinical Trials : Is it Time to Rethink Our Current Approach?

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          Summary

          Animal testing is used in pharmaceutical and industrial research to predict human toxicity, and yet analysis suggests that animal models are poor predictors of drug safety in humans. The cost of animal research is high—in dollars, delays in drug approval, and in the loss of potentially beneficial drugs for human use. Human subjects have been harmed in the clinical testing of drugs that were deemed safe by animal studies. Increasingly, investigators are questioning the scientific merit of animal research. This review discusses issues in using animals to predict human toxicity in pharmaceutical development. Part 1 focuses on scientific concerns over the validity of animal research. Part 2 will discuss alternatives to animal research and their validation and use in production of human pharmaceuticals.

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          Diagnostic tests 4: likelihood ratios.

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            Are animal models predictive for humans?

            It is one of the central aims of the philosophy of science to elucidate the meanings of scientific terms and also to think critically about their application. The focus of this essay is the scientific term predict and whether there is credible evidence that animal models, especially in toxicology and pathophysiology, can be used to predict human outcomes. Whether animals can be used to predict human response to drugs and other chemicals is apparently a contentious issue. However, when one empirically analyzes animal models using scientific tools they fall far short of being able to predict human responses. This is not surprising considering what we have learned from fields such evolutionary and developmental biology, gene regulation and expression, epigenetics, complexity theory, and comparative genomics.
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              Refining clinical diagnosis with likelihood ratios.

              Likelihood ratios can refine clinical diagnosis on the basis of signs and symptoms; however, they are underused for patients' care. A likelihood ratio is the percentage of ill people with a given test result divided by the percentage of well individuals with the same result. Ideally, abnormal test results should be much more typical in ill individuals than in those who are well (high likelihood ratio) and normal test results should be most frequent in well people than in sick people (low likelihood ratio). Likelihood ratios near unity have little effect on decision-making; by contrast, high or low ratios can greatly shift the clinician's estimate of the probability of disease. Likelihood ratios can be calculated not only for dichotomous (positive or negative) tests but also for tests with multiple levels of results, such as creatine kinase or ventilation-perfusion scans. When combined with an accurate clinical diagnosis, likelihood ratios from ancillary tests improve diagnostic accuracy in a synergistic manner.
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                Author and article information

                Contributors
                Journal
                JACC Basic Transl Sci
                JACC Basic Transl Sci
                JACC: Basic to Translational Science
                Elsevier
                2452-302X
                25 November 2019
                November 2019
                25 November 2019
                : 4
                : 7
                : 845-854
                Affiliations
                [1]Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington
                Author notes
                [] Address for correspondence: Dr. Gail A. Van Norman, Department of Anesthesiology and Pain Medicine, University of Washington, 2141 8th Avenue West, Seattle, Washington 98119. gvn@ 123456uw.edu
                Article
                S2452-302X(19)30316-X
                10.1016/j.jacbts.2019.10.008
                6978558
                31998852
                96775563-ef00-4101-be65-1aeb8d1259e1
                © 2019 The Author

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 14 October 2019
                : 14 October 2019
                Categories
                TRANSLATIONAL PERSPECTIVE

                animal research,drug development,toxicity,translational research,fda, u.s. food and drug administration,lr, likelihood ratio,nlr, negative likelihood ratio,npv, negative predictive value,plr, positive likelihood ratio,ppv, positive predictive value

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