Abstract Machine learning (ML) promises to tackle the grand challenges in chemistry and
speed up the generation, improvement and/or ordering of research hypotheses. Despite the …

By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the
host-pathogen evolutionary arms race. As pathogens evolve tactics for evading antibiotics …

Developments in computational omics technologies have provided new means to access
the hidden diversity of natural products, unearthing new potential for drug discovery. In …

Drug discovery is a cost and time-intensive process that is often assisted by computational
methods, such as virtual screening, to speed up and guide the design of new compounds …

With the rise of machine learning (ML), humans are no longer the only ones capable of
learning and contributing to an organization's stock of knowledge. We study how …

Chemical toxicity evaluations for drugs, consumer products, and environmental chemicals
have a critical impact on human health. Traditional animal models to evaluate chemical …

The use and production of chemical compounds are subjected to strong legislative pressure.
Chemical toxicity and adverse effects derived from exposure to chemicals are key regulatory …

The discovery of molecular structures with desired properties for applications in drug
discovery, crop protection, or chemical biology is among the most impactful scientific …

Early toxicity assessment plays a vital role in the drug discovery process on account of its
significant influence on the attrition rate of candidates. Recently, constant upgrading of …

Academic and pharmaceutical industry research are both key for progresses in the field of
molecular machine learning. Despite common open research questions and long-term …