Predicting the Risk of Phospholipidosis with in Silico Models and an Image-Based in Vitro Screen

The
drug-induced accumulation of phospholipids in lysosomes of various
tissues is predominantly observed in regular repeat dose studies,
often after prolonged exposure, and further investigated in mechanistic
studies prior to candidate nomination. The finding can cause delays
in the discovery process inflicting high costs to the affected projects.
This article presents an in vitro imaging-based method for early detection
of phospholipidosis liability and a hybrid approach for early detection
and risk mitigation of phospolipidosis utilizing the in vitro readout
with in silico model prediction. A set of reference compounds with
phospolipidosis annotation was used as an external validation set
yielding accuracies between 77.6% and 85.3% for various in vitro and
in silico models, respectively. By means of a small set of chemically
diverse known drugs with in vivo phospholipidosis annotation, the
advantages of combining different prediction methods to reach an overall
improved phospholipidosis prediction will be discussed.