Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic
knowledge and provides expedited solutions to complex challenges. Remarkable …

Steady progress over four decades toward understanding the pathogenesis and clinical
consequences of hepatic fibrosis has led to the expectation of effective antifibrotic drugs, yet …

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

Molecular proximity orchestrates biological function, and blocking existing proximities is an
established therapeutic strategy. By contrast, strengthening or creating neoproximity with …

The COVID-19 pandemic has emphasized the need for novel drug discovery process.
However, the journey from conceptualizing a drug to its eventual implementation in clinical …

This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

Computer-aided drug design (CADD) is an emerging field that has drawn a lot of interest
because of its potential to expedite and lower the cost of the drug development process …

Parkinson's disease (PD) is characterized by the loss of neuronal cells, which leads to
synaptic dysfunction and cognitive defects. Despite the advancements in treatment …

Recent research on artificial intelligence indicates that machine learning algorithms can
auto-generate novel drug-like molecules. Generative models have revolutionized de novo …

We study the problem of generating diverse candidates in the context of Multi-Objective
Optimization. In many applications of machine learning such as drug discovery and material …