[Image courtesy of iStock Photo]
Here, we provide reflections from several industry experts who attended the event.
1. An urgency to put patients first is gaining ground
“There were several topics at this year’s DPharm that truly resonated with attendees,” said Jane Myles, vice president of clinical trials innovation at Curebase, a decentralized clinical trial software platform and clinical service provider. “Malcolm Gladwell emphasized how urgency is the key to driving innovation within the industry,” Myles said. “And Henry Wei referenced a quote from Google: ‘If we focus on humans, all else will follow,’ in an effort to push for more patient centricity in clinical operations.”
Recent innovations have made it easier to recruit patients into clinical trials while also offering new opportunities to optimize quality, innovation and diversity. In addition, the growing popularity of decentralized and hybrid clinical trial designs makes it easier to design patient-friendly clinical trials.
2. Natural language process is helping to make sense of unstructured data
Sujay Jadhav
At DPharm, another central topic was the lack of structured, clean patient data to help inform clinical trials. “Yet, upwards of 80% of healthcare data is unstructured, including the text-based notes of electronic health records, which often reflects physician thinking, patient experiences, and even critical symptoms and diagnostic information,” said Sujay Jadhav, CEO of Verana Health, a healthcare technology and analytics company.
Such unstructured data provide a more holistic view of the patient journey and can help physicians make better decisions at the point of care. “Natural language processing is making it possible to bring meaning to unstructured data in a standardized and repeatable fashion, which is already helping to advance research and clinical decision-making,” Jadhav said. “For biotech and pharmaceutical companies, understanding this information at scale using natural language technologies to extract key data can accelerate the development of life-changing therapeutics.”
3. Digital biomarkers, AI and wearables are improving patient access
Jaydev Thakkar
Two innovation themes that stood out at DPharm 22 were leveraging digital health tech to improve patient access to clinical trials and the rising use of digital biomarkers with real-world data captured from continuous wearable sensors. Perhaps unsurprisingly, the event also highlighted the potential of artificial intelligence and machine learning in clinical trials.
“While attendees talked about the need for more clarity around evolving regulatory guidelines, there was a buzz about growing acceptance of technology innovations by regulators,” said Jaydev Thakkar, chief operating officer of Biofourmis. The company specializes in transforming patient care through personalized, predictive virtual care and digital therapeutics.
“Patient and site surveys shared by many speakers made it clear that it’s incumbent on sponsors and CROs to keep patient-facing digital tech easy to use and provide services such as tech support for patients and sites, logistics and remote analysis and monitoring of data,” Thakkar said. “Overall, we saw a shift from discussing potentially disruptive ideas to sharing lessons learned from implementing innovations and how to scale.”
This year, DPharm maintained the tradition of keeping the focus on patients. “Diversity and inclusion in clinical trials received a lot of attention,” Thakkar noted. Nevertheless, the theme “remains a challenge to be solved through a concerted effort by the entire industry.”
4. Clinical trials traditionally relying on subjective endpoints are becoming more objective
Dr. Jacob Donoghue
“DPharm’s discussions of ways to modernize clinical trials is particularly gratifying for those of us applying AI in healthcare,” said Dr. Jacob Donoghue, CEO and co-founder of Beacon Biosignals, which applies AI to EEG to unlock precision medicine for neurological and psychiatric disorders
“Neurology and psychiatry clinical trials have long suffered from insufficient data quality and volume due to their reliance on subjective endpoints, site-based studies, and a lack of tools for collecting large data sets,” Donoghue said. “But with the emergence of affordable hardware that easily enables remote brain monitoring and machine learning technology that can analyze massive amounts of EEG data, we can now better understand the brain and neurologic disorders.”
Beacon Biosignals aims to use computational diagnostics to extract more rigorous insights about specific patient populations. That effort will “enable the development of precision medicines for treating conditions such as epilepsy, major depressive disorder, and other brain diseases,” Donoghue said.
Filed Under: clinical trials, Drug Discovery
