Artificial intelligence in clinical research

Veerabhadra Sanekal Nayak, Mohammed Saleem Khan, Bharat Kumar Shukla, Pranjal R. Chaturvedi


Envision dedicating fifteen years to a critical interest and emptying staggering amount of funds into it, at the same time confronting a disappointment rate of 95 percent. That is the crippling reality for pharmaceutical organizations, which toss billions of dollars consistently toward medications that possible won't work – and after that do a reversal to the planning phase and do it once more. Today's medications go to the business sector after an extensive, very costly process of drug development. It takes anywhere in the range of 10 to 15 years, here and there significantly more, to convey a medication from introductory revelation to the hands of patients – and that voyage can cost billions up to 12 billion, to be correct. That is just a lot to spend, and excessively yearn for patients to hold up. Patients can hardly wait 15 years for a lifesaving drug, we require another productive focused on medication revelation and improvement process. Artificial Intelligence, can significantly reduce the time included, and also cut the expenses by more than half. This is made conceivable through a totally distinctive way to deal with medication revelation. With the present technique, for each 100 medications that achieve first stage clinical trials, only one goes ahead to wind up a genuine treatment. That is stand out percent, it's an unsustainable model, particularly when there are ailments, for example, pancreatic malignancy which has a normal five-year survival rate of 6%.


Artificial intelligence, Clinical trials, Information technology, Risk based monitoring, Drug development, Risk mitigation

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