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Latest in lab automation
In this article Drug Target Review's Izzy Wood highlights three of the latest findings using lab automation techniques and technologies that aid scientists.
List view / Grid view
Artificial Intelligence
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AI tools aid the discovery of super tight-binding antibodies
An AI strategy developed by US scientists could accelerate the development of new antibody drugs.
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Artificial intelligence: a great crash of hype into reality
Technology is infamous for falling into a hype cycle, with its peaks and valleys of exaggerated expectations and disillusionment — AI-driven drug discovery is no exception. In this article, Aaron Daugherty, Vice President Discovery at Aria Pharmaceuticals, highlights how the industry can use AI to transform research.
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New database maps proteins that could predict cancer
Swedish researchers unveiled a new cancer protein profile database compiled from artificial intelligence and machine learning.
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Scientists identify a biomarker that predicts CAR T-cell therapy efficacy
Combining AI with cutting-edge flow cytometry and massive sequencing technologies, researchers describe CAR T cell characteristics that determine their therapeutic capacity for the first time.
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Harnessing AI technology for IVF embryo selection
A US study used an AI algorithm to determine chromosomal numbers in IVF embryos.
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AI can detect an early sign of osteoarthritis from an x-ray image
Finnish researchers have developed AI based neural network to detect an early knee osteoarthritis from x-ray images, that can save the patient from unnecessary examinations, treatments and even knee joint replacement surgery.
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Artificial intelligence-aided screening could boost speed of new drug discovery
Using a natural language-inspired technique, researchers at the University of Central Florida, US, developed an interpretable and generalisable drug target interaction model that achieves 97 percent accuracy in identifying drug candidates for a broad variety of target proteins. Here, Dr Ozlem Ozmen Garibay and Aida Tayebi, who worked on the…
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How many drug discovery breakthroughs have we missed?
Today’s drug screening methods use one or two types of data. However, disease biology is not replicable by simple screening models because diseases are complex and heterogenous. However, advanced screening methods that process dozens of data sources at one time have uncovered novel hits that have been overlooked across the…
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New machine learning model could encode words to kill cancer cells
US researchers, using new machine learning techniques have developed a virtual molecular library of “words” that encode commands to kill cancer cells.
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Drug Target Review Screening ebook 2022
In this ebook are articles on how artificial intelligence can be used to identify drug candidates, data-lead screening models and autonomous strategies for molecular discovery.
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ebook: A data-driven approach to preclinical drug discovery
This ebook details Euretos’ approach to predicting novel gene-disease associations including a case study on Multiple Sclerosis GWAS and drug targets.
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Drug Target Review – Issue 4 2022
A new Drug Target Review issue is now ready to download! This issue features articles which explore how artificial intelligence can enhance screening and ways to find new hits through simultaneous orthogonal screens. Also included are articles on CRISPR, immuno-oncology and RSV vaccines.
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ebook: Microscopy for neuroscience research
Imaging the structure and function of the nervous system at a cellular level – challenges and considerations.
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The future of drug development: AI tailors artificial DNA
Swedish researchers have designed synthetic DNA that controls a cells’ protein production using AI.
