Knowledge-based battery design of short-term tests based on dose information.

A construction of batteries of short-term tests (STTs) is described which is based on a classification of 73 chemicals in regard to their carcinogenicity. The 73 chemicals were studied within the U.S. National Toxicology Program (Ashby and Tennant, 1988). The batteries are validated using the classification of 35 additional chemicals. They are defined by logically structured combinations of rules. The single rules are defined by the z-scores of the logarithmic values of the limiting doses obtained from the 4 in vitro STTs used in the study by Ashby and Tennant. The limiting dose is defined as the lowest effective dose or the highest ineffective dose (Waters et al., 1987). The batteries are constructed by minimizing the number of disagreements with the classification by Ashby and Tennant. Compared with the results obtained from single STTs, 2 batteries of 3 STTs have higher concordances with the carcinogenicity data, namely 70% for the NTP data and 74-77% for the independent test data. In addition, a theoretical result shows that the proposed battery design, for a large enough learning set of chemicals, leads to results which are replicated with high probability on a large enough validation set. Based on the first results obtained with a limited number of chemicals it is concluded that the knowledge-based battery design is worth further development.