AIMC Topic: Drug Development
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Harnessing artificial intelligence for the next generation of 3D printed medicines.
Advanced drug delivery reviews
May 18, 2021
Artificial intelligence (AI) is redefining how we exist in the world. In almost every sector of society, AI is performing tasks with super-human speed and intellect; from the prediction of stock market trends to driverless vehicles, diagnosis of dise...
Application of Machine Learning in Translational Medicine: Current Status and Future Opportunities.
The AAPS journal
May 18, 2021
The exponential increase in our ability to harness multi-dimensional biological and clinical data from experimental to real-world settings has transformed pharmaceutical research and development in recent years, with increasing applications of artifi...
Big Techs and startups in pharmaceutical R&D - A 2020 perspective on artificial intelligence.
Drug discovery today
May 7, 2021
We investigated what kind of artificial intelligence (AI) technologies are utilized in pharmaceutical research and development (R&D) and which sources of AI-related competencies can be leveraged by pharmaceutical companies. First, we found that machi...
Utilizing Artificial Intelligence to Manage COVID-19 Scientific Evidence Torrent with Risklick AI: A Critical Tool for Pharmacology and Therapy Development.
Pharmacology
Apr 28, 2021
INTRODUCTION: The SARS-CoV-2 pandemic has led to one of the most critical and boundless waves of publications in the history of modern science. The necessity to find and pursue relevant information and quantify its quality is broadly acknowledged. Mo...
AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders.
BMC bioinformatics
Apr 20, 2021
BACKGROUND: Drug-target interaction (DTI) plays a vital role in drug discovery. Identifying drug-target interactions related to wet-lab experiments are costly, laborious, and time-consuming. Therefore, computational methods to predict drug-target int...
Artificial intelligence to deep learning: machine intelligence approach for drug discovery.
Molecular diversity
Apr 12, 2021
Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design a...
GanDTI: A multi-task neural network for drug-target interaction prediction.
Computational biology and chemistry
Mar 18, 2021
Drug discovery processes require drug-target interaction (DTI) prediction by virtual screenings with high accuracy. Compared with traditional methods, the deep learning method requires less time and domain expertise, while achieving higher accuracy. ...
DTI-SNNFRA: Drug-target interaction prediction by shared nearest neighbors and fuzzy-rough approximation.
PloS one
Feb 19, 2021
In-silico prediction of repurposable drugs is an effective drug discovery strategy that supplements de-nevo drug discovery from scratch. Reduced development time, less cost and absence of severe side effects are significant advantages of using drug r...
Driving success in personalized medicine through AI-enabled computational modeling.
Drug discovery today
Feb 17, 2021
The development of successful drugs is expensive and time-consuming because of high clinical attrition rates. This is caused partially by the rupture seen in the translatability of the drug from the bench to the clinic in the context of personalized ...
Artificial intelligence, machine learning, and drug repurposing in cancer.
Expert opinion on drug discovery
Feb 12, 2021
: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposin...
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