AIMC Topic: Drug Design

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Flexibility in Drug Product Development: A Perspective.

Molecular pharmaceutics
The process of bringing a drug to market involves innumerable decisions to refine a concept into a final product. The final product goes through extensive research and development to meet the target product profile and to obtain a product that is man...

An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19.

BioMed research international
The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health concerns around the world. The lack of approved drugs or vaccines continues to be a challenge and further necessitates the discovery of new therapeutic ...

Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery.

Molecular diversity
The accumulation of massive data in the plethora of Cheminformatics databases has made the role of big data and artificial intelligence (AI) indispensable in drug design. This has necessitated the development of newer algorithms and architectures to ...

Assigning confidence to molecular property prediction.

Expert opinion on drug discovery
: Computational modeling has rapidly advanced over the last decades. Recently, machine learning has emerged as a powerful and cost-effective strategy to learn from existing datasets and perform predictions on unseen molecules. Accordingly, the explos...

Prediction of African Swine Fever Virus Inhibitors by Molecular Docking-Driven Machine Learning Models.

Molecules (Basel, Switzerland)
African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic conseque...

Combining generative artificial intelligence and on-chip synthesis for de novo drug design.

Science advances
Automating the molecular design-make-test-analyze cycle accelerates hit and lead finding for drug discovery. Using deep learning for molecular design and a microfluidics platform for on-chip chemical synthesis, liver X receptor (LXR) agonists were ge...

Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review.

Molecular diversity
Artificial intelligence (AI) renders cutting-edge applications in diverse sectors of society. Due to substantial progress in high-performance computing, the development of superior algorithms, and the accumulation of huge biological and chemical data...

Machine learning models for classification tasks related to drug safety.

Molecular diversity
In this review, we outline the current trends in the field of machine learning-driven classification studies related to ADME (absorption, distribution, metabolism and excretion) and toxicity endpoints from the past six years (2015-2021). The study fo...

Artificial intelligence in early drug discovery enabling precision medicine.

Expert opinion on drug discovery
: Precision medicine is the concept of treating diseases based on environmental factors, lifestyles, and molecular profiles of patients. This approach has been found to increase success rates of clinical trials and accelerate drug approvals. However,...

De novo molecular design and generative models.

Drug discovery today
Molecular design strategies are integral to therapeutic progress in drug discovery. Computational approaches for de novo molecular design have been developed over the past three decades and, recently, thanks in part to advances in machine learning (M...