Jul 1
Artificial Intelligence (AI) is reasonably well established in discovery and preclinical research, with success in areas such as target identification and molecular modeling. However, in clinical development, adoption has been fragmented and challenging to embed across the lifecycle.
Read the full article by Rob DiCicco from Drug Discovery News here.
Related Blog Posts
Are Pragmatic Trials The Patient Recruitment Solution We’ve Been Looking For?
The age-old problem for clinical research has been the ability to recruit patients. Many clinical research professionals have tried to crack this nut, whether with technology or partnerships or both. Let’s not forget the height of DCTs during the pandemic, which served their purpose but appear to have lost luster in the last few years.…
How Pandemic-Era Ingenuity Fuels the Future of Clinical Trials
It’s hard to believe that just five years ago, the clinical research industry found itself scrambling to adapt overnight. The COVID-19 pandemic ground global health systems to a halt and forced us all to move faster and more collaboratively than ever before. Read the full article by Allison Cuff Shimooka from The Medicine Maker here.
Science is Moving—Clinical Trials Must Catch Up
Clinical research has never been more capable of reaching new frontiers. The science is here. The technology is here. But the approach to trial design and execution hasn’t kept pace. The clinical research ecosystem proceeds cautiously for good reasons—patient safety chief among them. But too often, we’re held back by fixed mindsets and outdated processes.…