Computational Models for Human and Animal Hepatotoxicity with a Global Application Scope

Hepatic toxicity is a key concern
for novel pharmaceutical drugs
since it is difficult to anticipate in preclinical models, and it
can originate from pharmacologically unrelated drug effects, such
as pathway interference, metabolism, and drug accumulation. Because
liver toxicity still ranks among the top reasons for drug attrition,
the reliable prediction of adverse hepatic effects is a substantial
challenge in drug discovery and development. To this end, more effort
needs to be focused on the development of improved predictive in-vitro and in-silico approaches. Current
computational models often lack applicability to novel pharmaceutical
candidates, typically due to insufficient coverage of the chemical
space of interest, which is either imposed by size or diversity of
the training data. Hence, there is an urgent need for better computational
models to allow for the identification of safe drug candidates and
to support experimental design. In this context, a large data set
comprising 3712 compounds with liver related toxicity findings in
humans and animals was collected from various sources. The complex
pathology was clustered into 21 preclinical and human hepatotoxicity
endpoints, which were organized into three levels of detail. Support
vector machine models were trained for each endpoint, using optimized
descriptor sets from chemometrics software. The optimized global human
hepatotoxicity model has high sensitivity (68%) and excellent specificity
(95%) in an internal validation set of 221 compounds. Models for preclinical
endpoints performed similarly. To allow for reliable prediction of
“truly
external” novel compounds, all predictions are tagged with
confidence parameters. These parameters are derived from a statistical
analysis of the predictive probability densities. The whole approach
was validated for an external validation set of 269 proprietary compounds.
The models are fully integrated into our early safety in-silico workflow.