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Pharma Tech Outlook | Thursday, February 24, 2022
Pharma companies can benefit from the use of AI and machine learning at every stage of the drug discovery and development process.
Fremont, CA: When it comes to embracing digital health technology, the pharmaceutical industry has been hesitant to adopt and deploy AI and machine learning tactics, which has made broad-scale digital transformation challenging for pharmaceutical organizations. Drug discovery and development have a lot of potentials, but it depends on pharmaceutical organizations' capacity to integrate cutting-edge health technology into their everyday strategy.
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To speed up both the discovery and production of new drugs, artificial intelligence (AI) and machine learning can be employed at every stage of the process.
Phase1- AI in drug discovery
In the drug development process, reviewing and interpreting existing material is followed by testing how candidate medicines interact with their targets. According to the Insider Intelligence research AI in Drug Discovery and Development, AI might reduce drug discovery expenses by as much as 70 percent for corporations.
Phase 2- AI in preclinical development
In the preclinical research phase of drug discovery, potential therapeutic targets are evaluated using animal models. Utilizing AI during this phase could facilitate trials and allow researchers to more accurately forecast how a drug might interact with an animal model.
Phase 3- AI in clinical trials
After completing the preclinical development phase and obtaining FDA approval, researchers begin testing the medicine on human subjects. Overall, this is a four-step procedure that is typically regarded as the longest and most expensive part of the drug production trip. AI can enhance participant monitoring during clinical trials by collecting a more extensive data set quickly and by tailoring the trial experience to increase participant retention.
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