Computer-aided drug discovery has been around for decades, although the past few years
have seen a tectonic shift towards embracing computational technologies in both academia …

Disease modeling and target identification are the most crucial initial steps in drug
discovery, and influence the probability of success at every step of drug development …

The drug discovery process involves designing compounds to selectively interact with their
targets. The majority of therapeutic targets for low molecular weight (small molecule) drugs …

Over the past few years, the adoption of machine learning (ML) techniques has rapidly
expanded across many fields of research including formulation science. At the same time …

Health digital twins (HDTs) are virtual representations of real individuals that can be used to
simulate human physiology, disease, and drug effects. HDTs can be used to improve drug …

For a new molecular entity (NME) to become a drug, it is not only essential to have the right
biological activity also be safe and efficient, but it is also required to have a favorable …

The characterization of ligand binding modes is a crucial step in the drug discovery process
and is especially important in campaigns arising from phenotypic screening, where the …

Artificial intelligence (AI) is a transformative technology that is capturing popular imagination
and can revolutionize biomedicine. AI and machine learning (ML) algorithms have the …

High-fidelity in vitro tumor models are important for preclinical drug discovery processes.
Currently, the most commonly used model for in vitro drug testing remains the two …

Background: Cancer is a chronic, heterogeneous illness that progresses through a spectrum
of devastating clinical manifestations and remains the 2nd leading contributor to global …