According to Victoria DiBiaso, global head of clinical operations strategy and collaboration at Sanofi, “When it comes to improving trials, you have to look at protocol optimization. For us, that is where it all begins.
These best practices can help sponsors and CROs work together seamlessly to prevent and alleviate protocol deviations in their clinical studies keeping development on time and within budget.
Efforts to improve the provider selection/qualification process have improved in recent years, and with the help of digitized, centralized data, additional advancements are on the horizon.
According to Anne White, Lilly’s VP of next generation development and project management, for the past two years the company has steadily worked toward finding a way to get its medicines to patients faster.
“The key to fully understanding the safety and efficacy of new medical and device therapies is developing clinical trial databases that adequately reflect the diversity of the U.S. population.”
“A partnering deal with a bigger pharma company would certainly help us through [the Phase 3] process,” explains Jeff Davidson, CEO of Keystone Nano, a company that develops nanoparticles that target solid tumors by going after cancer cells and leaving the normal cells intact.
In 2017, real-world evidence (RWE) became the topic everyone wanted to discuss. Several executives I have spoken to recently believe it will continue to grow in importance as we move into 2018 and beyond. But why the sudden interest in RWE?
It is widely known that women, as well as elderly and minority populations, have long been underrepresented in clinical trials for drugs and biologics. A new study found a similar pattern when it comes to evaluating medical devices.
“The Korean pharmaceutical industry has been accelerating investments in open innovation and focusing on R&D for entry into overseas markets,” says Deborah Chee, president, Korean National Enterprise for Clinical Trials.
According to speakers at an FDA workshop, natural language processing (NLP) can be a useful way to extract meaningful information from unstructured data, such as text and tables from electronic health records (EHRs), journals, and social media, but it isn’t ready for full-scale use.