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Pharma Tech Outlook | Wednesday, February 22, 2023
AI-based technologies have substantially impacted the drug discovery industry.
FREMONT, CA: Marketing, customer satisfaction, and employee retention are just some of the applications of artificial intelligence. It transforms drug discovery and development in medicine, biotechnology, and pharmacology. A study found that discovering and developing a drug costs an average of
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dollar 1.3 billion and takes 12 to 15 years. Therefore, it should be familiar that AI-powered technologies have gained much traction in the drug discovery industry. Almost 40 percent of the drug discovery and development pipeline uses artificial intelligence each year, according to a paper in Nature.
Major trends include the following.
More efficiency in biology modeling and drug target discovery: Genes, proteins, receptors, enzymes, and other biological targets are usually the starting points for drug development. A cell's behavior or function can be influenced by proteins, making them the most common drug targets. To date, traditional drug discovery efforts have involved selecting specific proteins with pockets capable of being modified by promising drug-like molecules (which then serve as ligands).
There are computational challenges associated with this process. Organizations now use AI to correlate and match large amounts of data, leading to more efficient drug target identification and discovery. AI-powered healthcare enterprises focused their resources on building advanced modeling tools that identify and validate new targets and model biology.
Improved protein structure prediction: Predicting protein structure is important for drug discovery because it provides insight into how the protein functions and, thus, can be controlled, modified, and affected.
A computational biology research report noted that predicting protein structures remains a challenge. Over 200 million protein structures belonging to animals, plants, bacteria, fungi, and other organisms were predicted and publicly shared in July, reducing what would typically take years to mere seconds.
Another aspect of drug design that received attention recently was the virtual screening of existing databases. Identifying specific peculiarities in large databases and finding similarities define artificial intelligence features. In partnership with AI platforms, pharmaceutical giants have invested millions of dollars in virtually screening trillions of synthesized compounds through this technology.
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