There’s a data revolution on the horizon.
As leading contract research organisations (CROs) continue to benefit from technological innovations, they will further advance the field of drug development and the way we recruit patients for clinical trials. Key to this revolution is the burgeoning use of big data, which, in simple terms, refers to the extraordinarily large volume of data collected across the clinical trial process.
These vast data come from a number of sources, including biomarkers, genomic sequencing, electronic health record, claims data, patient registries, payer records, pharmaceutical research, wearables, medical devices and clinical trial data, among others. Pharmaceutical and biotech companies can harness this information for the purpose of improving clinical trial design, patient recruitment, site selection and overall decision-making.
In this blog, Tom O’Leary, Chief Information Officer at ICON, reveals how big data can be leveraged to solve key challenges in recruitment and drug development. Specifically, he will focus on the following:
- Addressing issues surrounding the quality of data
- Using big data to recruit patients
- Employing data technologies to engage patients and improve health outcomes
- Reducing clinical trial dropout rates through the use of big data
- Making big data available for analysis sooner to reduce costs
- Understanding big data’s role in the future of healthcare
Addressing issues surrounding the quality of data
The magnitude of data that needs to be captured in healthcare is beyond comprehension. Imaging data, genomics, proteomics, medical records, the list is endless. With this information overload comes the issue of data quality. As more data are collected, costs increase exponentially. Two solutions that are quickly improving data quality include:
- Cloud-based data, where information is stored on the internet through a cloud computing provider who manages and operates data storage as a service
- Internet of Things (IoT), which consists of a system of interrelated, internet-connected objects that are able to collect and transfer data over a wireless network without human intervention
However, it must be pointed out that while cloud-based storage and the IoT are expected to improve the quality of data in the future, they will not be able to do so retroactively. Regardless, technological advances are making it possible for us to capture data on patients as they go about their daily lives. For instance, wearables and medical devices can tell us how many steps a patient has taken, their heart rate and the amount of rest they need. Moving forward, the idea is that we will be able to access this type of data and use that information to better understand patients’ conditions.
Using big data as a recruitment tool
The days of broad-spectrum antibiotic drugs and beta blocker cardiovascular therapies are long gone. Now, we’re looking at a very niche market, consisting of cohorts of patients who are going to receive benefits from very specific therapies.
As these targeted therapies continue to expand, big data is expected to increase in value, especially with regard to recruitment. The traditional recruiting approach was to reach out to a network of physicians, explaining that you have a clinical development program in a specific therapeutic area, and then asking whether they have patients who would benefit from this particular drug. A physician may start out highlighting five to 10 patients. However, when shown the inclusion/exclusion criteria, the Physician may only be able to enroll one or two patients.
Today, researchers are looking to heatmap the world to find where there are concentrations of patients suffering from specific conditions or diseases with the help of electronic health and medical record data. After all, there is little point in trying to recruit patients in areas where a disease is not prevalent.
Employing data collection technology to engage specific patient groups and improve health outcomes
With the development of data collection technology, we have the opportunity to go directly to the patient with specific diseases and conditions, and explain that we have therapies and drugs that are targeted to cure or improve the patient’s quality of life. The ultimate goal here is to engage patients early on regarding their medical care.
In fact, all the evidence indicates that patients who are actively engaged in clinical trials achieve better health outcomes. Typically, they more fully understand their condition and how to manage it. More importantly, when the therapies work, they become the direct recipients of their benefits.
Reducing clinical trial dropout rates
The dropout rate for clinical trials has been a major issue for quite some time. One main factor is that the trial, itself, may not be effective for the patient. Finding the right patient for the right trial is half the battle. As previously mentioned, the use of big data can help ensure patients are matched with the right trial to fit their needs.
Secondly, trust and communication with the patient are imperative in the context of a clinical trial. This starts by keeping the patient informed throughout the process, which can now be achieved through the use of technology. Historically patient details we captured and entered into a database without necessarily considering the criticality of patient engagement in the clinical trial process. However, the data revolution is signaling the end of those days.
Making big data available for analysis sooner to reduce costs
Currently, a lot of money is wasted on not identifying the right patients at the start of a trial. Moreover, the time it takes to recruit a patient is a long, arduous process. Making big data available for analysis sooner can take years of clinical trial timelines by allowing us to select the right patients from the start, which, in turn, can lower overall trial costs and reduce the time it takes to get drugs developed.
Understanding big data’s role in the future of healthcare
The skills to leverage and analyse big data are going to be built on a workforce of hungry and technologically competent individuals. This process is going to take time to generate the appropriate foundation to build up big data to its full potential. However, almost every metric signals that this will happen much quicker than previously anticipated.
There is no doubt that big data represents the future of healthcare. The CROs that embrace the data revolution will be the ones that thrive in the digital era.
For additional information on big data and the clinical trial process, read PharmaBoardroom’s exclusive interview with Tom O’Leary, CIO at ICON.