We present a python library to train more generalizable drug-target affinity prediction models.
We present a novel training framework to improve the generalizability of drug-target affinity prediction models.
We exploit the chemical language in SMILES and aminoacid sequences to predict drug-target affinity and present state-of-the-art level affinity prediction models.