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Pharma Tech Outlook | Wednesday, September 15, 2021
AI and machine learning can be beneficial at all stages of the drug discovery process.
Fremont, CA: The pharmaceutical industry has been quite slow to adopt digital health technology, and pharmaceutical companies as a whole have taken a long time to implement AI and machine learning strategies, complicating large-scale digital transformation. There is an abundance of opportunity for drug discovery and development, but it is contingent on companies' ability to integrate advanced health technology into their everyday strategies. AI and machine learning can offer several benefits at all stages of the drug discovery process.
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AI and ML in the drug development process
AI in drug discovery
The drug discovery process begins with the reading and analysis of pre-existing literature and continues with the testing of potential drugs' interactions with targets. According to Insider Intelligence's AI in Drug Discovery and Development report, AI could help companies save up to 70 percent on drug discovery costs.
AI in preclinical development
Preclinical development is the stage of drug discovery in which potential drug targets are evaluated using animal models. Using AI during this phase could help trials run more smoothly and enable researchers to predict how a drug will interact with the animal model more accurately and quickly.
AI in clinical trials
After passing the preclinical development stage and receiving FDA approval, researchers begin testing the drug on human subjects. This is a four-phase process in total and is frequently regarded as the most time-consuming and expensive stage of the drug manufacturing process.
AI can aid in participant monitoring during clinical trials by rapidly generating a larger set of data and improving participant retention through the personalization of the trial experience.
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