Artificial intelligence in clinical research

Abstract

<p>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%.</p>

Optimizing clinical research procedures in public health emergencies

“…Diversity and evolution in AI technology have led to a wide range of potential applications in clinical research. Natural language processing (NLP), the ability of programmed computers to analyze written and spoken word, in addition to machine learning, which looks at algorithms that assist in predictive decision making without explicit programming, can hasten the patient recruitment process by identifying suitable patients through analysis of electronic medical records 39–41 . When applied to electronic health records and databases, modeling through NLP and machine learning can potentially identify new biomarkers worth assessing in a more formal context 41 .…”

Recent Trends of AI in Pharmaceutical Industries: A Review

“…All things considered, DeepCure's emphasis on small-molecule medicines is a great asset to the pharmaceutical sector and may shorten the time and expense associated with drug research and development. The company's creative strategy and inventive use of technology bode well for the future of the field and its capacity to enhance patient outcomes [35,36].…”

Automation in pharmaceutical sector by implementation of artificial intelligence platform: a way forward

“…Natural language processing (NLP), the ability of programmed computers to analyze written and spoken word, in addition to machine learning, which looks at algorithms that assist in predictive decision making without explicit programming, can accelerate the patient enrolment process by recognizing appropriate patients through analysis of electronic medical records. 26,32,33 Application of electronic health records and databases, modeling through NLP and machine learning can potentially identify new biomarkers worth assessing in a more formal context. 26 In clinical trial conduct where digitalization is being implemented include consent processes, patient adherence, and scheduling through wearable monitoring, medication logging, and virtualization of staff-patient interactions including consultations, study updates, and patient coaching to minimize attrition.…”

“…Hence, it is in such setting that AI has extensive role to enhance efficiency and the speed of drug development even produce advanced technology for developing and prolonging patient lives with safety. 1,3,4 Healthcare practice will be digitalized and regionalized which will have improved connectivity, accessibility, and convenience for future medical consultation. 5 It is essential to recognize innovative technologies that offer the automation of tedious tasks for revolution in pharmaceutical sector.…”