An expert system for prediction of chemical toxicity
Drug Information Journal
By: James P. Hickey, Andrew J. Aldridge IV, Dora R. Passino-Reader, and Anthony M. Frank
Links
- More information: Publisher Index Page (via DOI)
- Download citation as: RIS | Dublin Core
Abstract
The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry
Suggested Citation
Hickey, J.P., Aldridge, A.J., Passino-Reader, D.R., Frank, A.M., 1992, An expert system for prediction of chemical toxicity: Drug Information Journal, v. 26, no. 4, p. 487-495, https://doi.org/10.1177/009286159202600405.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | An expert system for prediction of chemical toxicity |
| Series title | Drug Information Journal |
| DOI | 10.1177/009286159202600405 |
| Volume | 26 |
| Issue | 4 |
| Publication Date | August 28, 2016 |
| Year Published | 1992 |
| Language | English |
| Publisher | SAGE Publications |
| Publisher location | Thousand Oaks, CA |
| Contributing office(s) | Great Lakes Science Center |
| Description | 7 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Drug Information Journal |
| First page | 487 |
| Last page | 495 |