Autoimmunity and risk assessment.
Author(s) -
M I Luster,
Petia P. Simeonova,
Randle M. Gallucci,
Jodi Matheson
Publication year - 1999
Publication title -
environmental health perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.257
H-Index - 282
eISSN - 1552-9924
pISSN - 0091-6765
DOI - 10.1289/ehp.99107s5679
Subject(s) - risk assessment , autoimmunity , risk analysis (engineering) , disease , medicine , computational biology , biology , computer science , pathology , computer security
Among the issues dealing with identifying potential adverse immunologic effects (i.e., suppression, hypersensitivity, or autoimmunity) associated with xenobiotic exposure, general agreement exists among the regulatory and pharmaceutical communities that predictive tests for autoimmunity are in most need of development in order to improve risk assessment. The estimation of risk (i.e., the probability of a deleterious effect resulting from exposure) involves both the qualitative evaluation of whether a hazard exists and the quantitative evaluation for determining an acceptable level of exposure in humans. Unless adequate human data are available, which is uncommon, this is based on animal studies. Although animal models exist to study autoimmune processes, these models do not readily lend themselves to interpretation in the risk assessment process due, for the most part, to the complexity of autoimmune disease(s), as they are multifactorial and exhibit genetic heterogeneity in humans. To improve the risk assessment process, researchers must develop and validate animal models that not only incorporate mechanistic information into the assessment process but also allow for consideration of potent genetic, physiologic, and environmental influences.
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