Recently, using artificial intelligence (AI) in drug discovery has received much attention
since it significantly shortens the time and cost of develo** new drugs. Deep learning (DL) …

Conventional wet laboratory testing, validations, and synthetic procedures are costly and
time-consuming for drug discovery. Advancements in artificial intelligence (AI) techniques …

High rates of failure, exorbitant costs, and the sluggish pace of new drug discovery and
development have led to a growing interest in repurposing “old” drugs to treat both common …

Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …

Lanthanide-doped upconversion nanoparticles (UCNPs) have aroused extraordinary
interest due to the unique physical and chemical properties. Combining UCNPs with other …

The COVID-19 pandemic has highlighted the need to quickly and reliably prioritize clinically
approved compounds for their potential effectiveness for severe acute respiratory syndrome …

Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs
and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an …

A few commonly used non-antibiotic drugs have recently been associated with changes in
gut microbiome composition, but the extent of this phenomenon is unknown. Here, we …

Given the high attrition rates, substantial costs and slow pace of new drug discovery and
development, repurposing of'old'drugs to treat both common and rare diseases is …