THANK YOU FOR SUBSCRIBING
Pharma Tech Outlook | Saturday, November 27, 2021
The majority of industry stakeholders anticipate that the use of artificial intelligence and advanced data analytics in clinical research will continue to grow in the coming years, with significant implications for the pace, efficiency, and cost of these projects.
FREMONT, CA: Access to patient medical records, combined with rapid improvements in data analytics techniques and technology, has transformed many facets of healthcare in recent years, from early-stage discovery and research to patient treatment. The use of modern technologies to expedite and accelerate clinical research is one of the most significant applications. Advanced technologies, such as artificial intelligence (AI), can handle many of the most challenging aspects of drug development, with significant benefits for pharmaceutical companies, investigators, patients, regulators, and payers. While clinical research methods and standards have gotten increasingly complex, slowing progress and driving up costs, organizations ranging from startups to large pharmaceutical giants recognize the potential to employ AI to improve trial efficiency, patient recruitment, and outcome targeting. Given that people are at the birth of AI technology, its position in clinical research can expand enormously in the following years.
Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.
The number of experimental medications in development has risen considerably in recent years on a global basis. Numerous breakthroughs in treating various serious diseases, including cancer and viral and autoimmune diseases, represent potentially historical developments. The fact that numerous medications are in clinical development, some of which target the same or comparable indications, creates new levels of rivalry for patients to participate in clinical research and commercialization plans.
Often, these development efforts employ the time-honored strategy of identifying and targeting cells with increased proliferative activity linked with illness. On the other hand, manufacturers have recently concentrated clinical research on the root cause of disease — the underlying biological mechanisms linked with disease initiation and progression – to give the best possible benefit. This transition has also necessitated the development of more sophisticated processes for patient screening and clinical study execution.
Many pharmaceutical companies are now aggressively pursuing the use of automated algorithms and complex prediction models to aid in the identification of new molecular targets. Additionally, these models forecast the likelihood that novel medications will move through regulatory evaluation and ultimately succeed commercially. In some circumstances, adopting
More in News