A PRIORI PREDICTIVE METHODS OF ASSESSING HEALTH EFFECTS OF CHEICALS IN THE ENVIRONMENT
M.J. Kland · University of North Texas Digital Library (University of North Texas) · 1977
Passage of the Toxic Substances Control Act (TSCA) last year emphasized the urgent need for the formulation of viable criteria and interim standards limiting the exposure of increasingly large segments of the U.S. population to environmental chemical toxicants. Unfortunately, current methods of developing these standards are both time-consuming and costly. The resulting need for a priori predictive techniques to assess the inherent potential of chemicals, such as the halocarbons found in chlorinated waters, for inducing adverse biological effects, has led to the use of a number of analytical methods designed primarily for screening large numbers of chemical compounds before they impose unacceptable environmental hazards, frequently of crisis proportions. Four of the techniques best adapted to dealing with the multifactorial environmental problems of chemical health effects will be briefly described: (1) quantitative structure/activity relationships (QSAR); (2) factor analysis (FA); (3) pattern recognition/artificial intelligence (PR/AI); and (4) molecular connectivity (MC). While it is clear that none provides easy answers, it would appear that the more recent areas of PR and MC both merit more intensive investigation as predictive tools. In particular, the relative simplicity of the MC approach and the possibility of substantially reducing the empirical component are attractive incentives for pursuing further work in this area.