Effectiveness of CASE Ultra Expert System in Evaluating Adverse Effects of Drugs.

Purpose of this pilot study is to test the QSAR expert system CASE Ultra for adverse effect prediction of drugs. 870 drugs from the SIDER adverse effect dataset were tested using CASE Ultra for carcinogenicity, genetic, liver, cardiac, renal and reproductive toxicity. 47 drugs that were withdrawn from market since the 1950s were also evaluated for potential risks using CASE Ultra and compared them with the actual reasons for which the drugs were recalled.

Optimizing predictive performance of CASE Ultra expert system models using the applicability domains of individual toxicity alerts.

Fragment based expert system models of toxicological end points are primarily comprised of a set of substructures that are statistically related to the toxic property in question. These special substructures are often referred to as toxicity alerts, toxicophores, or biophores. They are the main building blocks/classifying units of the model, and it is important to define the chemical structural space within which the alerts are expected to produce reliable predictions.

Benchmark performance of MultiCASE Inc. software in Ames mutagenicity set.

The predictive performances of MC4PC were evaluated using its learning machine functionality. Its superior characteristics are demonstrated in this following up study using the newly published Ames mutagenicity benchmark set.

Identification of structure-activity relationships for adverse effects of pharmaceuticals in humans: Part B. Use of (Q)SAR systems for early detection of drug-induced hepatobiliary and urinary tract toxicities.

This report describes the development of quantitative structure-activity relationship (QSAR) models for predicting rare drug-induced liver and urinary tract injury in humans based upon a database of post-marketing adverse effects (AEs) linked to approximately 1600 chemical structures. The models are based upon estimated population exposure using AE proportional reporting ratios. Models were constructed for 5 types of liver injury (liver enzyme disorders, cytotoxic injury, cholestasis and jaundice, bile duct disorders, gall bladder disorders) and 6 types of urinary tract injury (acute renal disorders, nephropathies, bladder disorders, kidney function tests, blood in urine, urolithiases).

A structural analysis of the differential cytotoxicity of chemicals in the NCI-60 cancer cell lines.

The primary functions of cancer chemotherapeutic agents are not only to inhibit the growth or kill the cancer cells, but to do so without eliciting unreasonable cytotoxic effects on the healthy cells and to withstand the ability of the cancer cells to develop resistance against it. This has unfortunately been proven so far to be a very difficult objective. In this perspective, the ability of small molecules (anti-tumor agents) to 'see' different cell types differently can be a key attribute.