Combining Private Enterprise
with Academic Excellence
The Toxicology Research Laboratory, a GLP operated, AAA LAC lntl. accredited facility, is an independent contract research organization (CRO) located within the University of Illinois at Chicago (UlC). The Laboratory has conducted many preclinical toxicology programs on potential therapeutic agents and other chemicals. Entities such as the National Cancer Institute, the World Health Organization, the U.S. Army Medical Research and Development Command, and several biotechnology, pharmaceutical, and agricultural companies utilize the expertise and commitment of the interdisciplinary Toxicology Research Laboratory team
The 100,000 sf animal facility is supported by four ACLAM-certified clinical veterinarians. A strong Quality Assurance Unit (QAU) oversees strict compliance with Good Laboratory Practices (GLPs). The Archives, which is maintained by the QAU, is dedicated to the storage of raw data, files, specimens and final reports, and is secured from all unauthorized personnel.
The Toxicology Research Laboratory has significant experience in utilizing rodents, dogs, rabbits, and non-human primates in preclinical safety assessment programs. These include acute, subchronic, and chronic toxicity studies; reproductive and developmental toxicity studies; neurobehavioral toxicity studies; and pharmacokinetics, metabolism, and disposition studies. Expertise in neuro-phamacology and cardiovascular pharmacology testing is also available on-site.
The Toxicology Research Laboratory is fully computerized, and uses the LABCAT online data collection system for the capture of in-life, clinical pathology, organ weight, and histopathology data. This data collection system includes built-in statistical programs, which allows for immediate analysis of data (ANOVA, Dunnett's Test, Duncan's Multiple Range Procedure, Regression Analysis, etc). Additional statistical programs such as BMDP, SPSS, SAS, etc., are available in-house and utilized by our biostatisticians in the analysis of complex data sets.