The explosion of health–related data could transform clinical trials and drug development. But only if we learn how to make sense of the data first.
Humanity generates about 16.3 zettabytes (one trillion gigabytes) of data each year. By 2025, that figure could rise tenfold. For doctors, more data could lead to deeper insights on patient populations, which could lead to more effective clinical trials and streamlined drug development. This influx of data, while important for drug development, also poses some big challenges. To be valuable, data needs to be consistent, accurate and clear, but for most clinical teams drawing data from different sources and systems, these are rare commodities.
Today’s clinical trial systems urgently need an overhaul. Traditional siloed technologies for clinical development require patient information to be entered many times over the course of a clinical trial, often introducing inconsistency. A unified eClinical platform could eliminate the risk of data duplication and inconsistency during a patient’s participation in a clinical trial. This change could save time and improve trial safety and patient experience.
In November, leaders from the clinical technology and drug development industry gathered for a webcast hosted by Scientific American Custom Media, Nature and Oracle Health Sciences, with speakers from Pfizer, to explore the creation of a clinical system that is empowered by data, rather than encumbered by it.
Within healthcare, multiple streams of patient information — from electronic health record (EHR) data and genomics data, to information derived from mobile health (mHealth) applications and social media — are rapidly converging. Add information from connected devices, biosensors and digital surveys on dosing and compliance, and the data flow becomes so immense that assessing its value becomes its own priority.
During the webcast, 177 participants from a variety of research and pharmaceutical backgrounds were asked to identify the most valuable streams of data for clinical research: 45.2 percent said genetics data will be most valuable; 32.7 percent said EHR data; 14.9 percent said mHealth data; and 7.2 percent said social media data.
They were also asked which emerging technologies might have the greatest positive impact on clinical trials. The poll indicated that 38.3 percent predict that the integration of real-world data would have the most impact. That includes EHRs, patient-generated information, data gathered from mobile devices, and pretty much any other data collected under normal circumstances outside a randomized clinical trial. Thirty five percent identified artificial intelligence and machine learning as drivers of change; 15.3 percent pointed to cloud technology; and 11.5 percent selected the rise of mHealth data.
If genetics, EHR, and real-world data will be instructing the insights of the future, fragmented eClinical point solutions that don’t allow for easy integration of these data sources are a hindrance to collective wellbeing.
In the midst of this outpouring data, clinical development is facing intense pressure. The timeline for drug discovery has dwindled from three to six years to three to nine months, according to James Streeter, global vice president of product strategy for Oracle Health Sciences. With the cost to win marketing approval for a drug now about $2.6 billion, the tolerance for protracted discovery is low.
Across the clinical development ecosystem, the desire to use data for faster discovery is running headlong into the inefficiencies caused by fragmented systems, processes and departments. Instituting industry-wide standards for information collection is one way to help bridge the gap. So, too, could clearing up the clutter around fragmented processes, including complex configuration across multiple clinical systems, redundant entry of patient data into multiple systems, manual monitoring and cleaning of data, and compliance concerns.
The clinical trials process is also under pressure. Patients are demanding more personalization. Rather than the traditional approach of risk-based monitoring, the trials process could one day be driven by prescriptive analytics or monitoring based on recommendations from machine learning. This future also depends on refining data collection and making it available to the right people at the right time throughout the lifecycle of a clinical trial — enabling more informed doctor-patient-pharma relationships and better decision-making.
DATA, TECHNOLOGY, AND THE FUTURE OF CLINICAL TRIALS
Though the challenge of reconciling streams of data appears daunting, there are solutions. Technology exists for the use of real-world data acquisition and processing — it just needs to be implemented across the industry. Once it is, standardization will assist innovation and reduce the gaps around real-world data capabilities. The biggest impact will come from the changes introduced to the clinical trial process. Monitoring of data, management processes and medical coding will be significantly changed with real-world data efforts, which will require organizations to go through procedural changes that could have regulatory impacts as well.
Consumable and consistent data could also help bring drugs to market faster. And for data to be implemented on a global scale, it’s important that it be consistent. When companies look at drug development, they don’t think just about the U.S. or the U.K. or Europe. In the future, devices will collect real-world data routinely and globally, and the data will be comparably useful for evidence within trials themselves.
As technical processes improve, so too will patient engagement in clinical trials. The experience and the ease of participation in clinical studies are critical in retention and compliance for patients. Take greater participation a step further and envision all data sources aggregated in one place, coupled with artificial intelligence identifying patterns in advanced therapies that humans aren’t able to spot, and there’s a formula for future success.
This reality is quickly approaching. Today, clinical trials commonly include thousands of patients; once this number reaches the millions, the insights that can be gleaned are going to be that much more robust and that much more significant — leading to bigger returns.