AIMC Topic: Drug Discovery
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Algebraic graph-assisted bidirectional transformers for molecular property prediction.
Nature communications
Jun 10, 2021
The ability of molecular property prediction is of great significance to drug discovery, human health, and environmental protection. Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Although s...
In silico prediction of drug-induced ototoxicity using machine learning and deep learning methods.
Chemical biology & drug design
Jun 7, 2021
Drug-induced ototoxicity has become a serious global problem, because of leading to deafness in hundreds of thousands of people every year. It always results from exposure to drugs or environmental chemicals that cause the impairment and degeneration...
Automated and enabling technologies for medicinal chemistry.
Progress in medicinal chemistry
Jun 7, 2021
Having always been driven by the need to get new treatments to patients as quickly as possible, drug discovery is a constantly evolving process. This chapter will review how medicinal chemistry was established, how it has changed over the years due t...
Translational precision medicine: an industry perspective.
Journal of translational medicine
Jun 5, 2021
In the era of precision medicine, digital technologies and artificial intelligence, drug discovery and development face unprecedented opportunities for product and business model innovation, fundamentally changing the traditional approach of how drug...
Artificial intelligence in early drug discovery enabling precision medicine.
Expert opinion on drug discovery
Jun 2, 2021
: 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
Jun 1, 2021
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...
The machine learning life cycle and the cloud: implications for drug discovery.
Expert opinion on drug discovery
May 31, 2021
: Artificial intelligence (AI) and machine learning (ML) are increasingly used in many aspects of drug discovery. Larger data sizes and methods such as Deep Neural Networks contribute to challenges in data management, the required software stack, and...
Current directions in combining simulation-based macromolecular modeling approaches with deep learning.
Expert opinion on drug discovery
May 31, 2021
: Structure-guided drug discovery relies on accurate computational methods for modeling macromolecules. Simulations provide means of predicting macromolecular folds, of discovering function from structure, and of designing macromolecules to serve as ...
Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence.
Frontiers in immunology
May 31, 2021
Schistosomiasis is a parasitic disease caused by trematode worms of the genus and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns ...
Converging global crises are forcing the rapid adoption of disruptive changes in drug discovery.
Drug discovery today
May 18, 2021
Spiralling research costs combined with urgent pressures from the Coronavirus 2019 (COVID-19) pandemic and the consequences of climate disruption are forcing changes in drug discovery. Increasing the predictive power of in vitro human assays and usin...
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