Aiming the achievement of efficient drug development, which costs several hundreds of million dollars per compound, we propose a novel alternative toxicity test towards the screening of safe medicines with high extrapolation efficiency to humans, reducing the development cost and time.
S4: Systems Toxicology Developments supported by Big Data and Artificial Intelligence
Hazard identification for poorly characterized chemicals has long been a challenge. Given the huge number of chemicals for testing, it is impractical to apply in vivo and in vitro assays to all chemicals. Modern in silico methods for analyzing potential effects induced by chemical exposures provide an efficient and economical way for chemical hazard identification.
Toxicity studies in the 21st -century require the development of novel methodologies which augment existing techniques by the application of in silico modeling and simulation, machine learning and large-scale data analytics connected in custom pipelines through integrated platforms.