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Applied Clinical Trials
There are various estimates in the public domain that applying big data strategies could potentially generate up to $100 billion in value annually across the US healthcare systems.
There are various estimates in the public domain, including one by McKinsey¹, that applying big data strategies could potentially generate up to $100 billion in value annually across the US healthcare systems, specifically by optimizing innovation and improving the efficiency of research and clinical trials. A component of this “Big Data” is the data acquired during a clinical trial regardless of the phase (early or late phase). A very recent press release, that IBM’s Watson will help Mayo Clinic in identifying suitable patients for cancer trials, is indeed a strong indicator that the collaboration between doctors and technologists in pharmaceutical drug development has matured further.
With the advent of global CROs entering into the capital intensive sector of healthcare reimbursements, supporting pharmaceutical and biotech companies to formulate their reimbursement strategy, it is only a natural course of evolution for them to be more data-driven and focused, thereby creating value for the drug product they are developing as early as they could. However, while doing so, the CROs should recognize that a “Patient’s Journey” begins as early as during the early phase of drug development, and encompasses several data-centric efforts from patient data visualization through to data mining in order to create robust data. To that end, there are several tools, technology platforms, and initiatives that are currently being explored, including the FDA’s $116 million pilot program called the “Mini-Sentinel,” established in 2008, that automatically combs medical databases for signs of drug safety issues that were not detected before approval.
One such tool—among several others that I use frequently in my organization and have been fascinated with due to its sheer ease of use and value—is our own in-house data visualization tool. I have had the fortune to use this tool to learn more about our subjects and patients in early phase trials. This tool not only is user friendly (read doctor friendly as well) but also provides a quick and nearly a “real-time” glimpse into safety profiles, which in turn enables me to make evidence based decisions. Moreover, I am able to readily share this data and associated information with the sponsors who may then use that information accordingly to address the evolving safety or clinical trial design related issues.
Most importantly, it provides me an insight into evolving data, highlighting trends, emerging signals, outliers, unusual patterns, and deviations in a clinical trial that otherwise may not be available to me until the end of the trial, and, even then, in less clear tables and listings that is critical for reviewers at the regulatory agencies. This proactive gathering of information about the behavior of a drug in development has proved to be very valuable. Such time-sensitive safety data, on several occasions, have been discovered during routine use of this data visualization tool, helping my medical colleagues at sponsor companies in their decisions as well.
As medical doctors who are sworn by the Hippocratic Oath, we are always obligated to ensure the safety and welfare of patients participating in clinical trials. Thus, utilizing tools and technology towards achieving that obligation should be part and parcel of any clinical trial. However, the challenge my colleagues and I face is the shortcomings of several of these tools and technology platforms, besides tending to be a tad sophisticated for a medical doctor with limited technology knowledge.
Therefore, the tools and technology that doctors gravitate towards should attempt to fulfill the following criteria:
With drug recalls and safety being scrutinized more than ever before, we as an industry should embrace and encourage application of data visualization tools that enables doctors engaged in drug development, especially when “time is of the essence.” Since doctors have an integral and a valuable part to play in drug development, John F. Kennedy’ saying that “Man is still the most extraordinary computer of all,” is even more applicable in this environment. Therefore, doctors are critical to fulfill this void and serve as the conduit between data and drug development. Thus as doctors, we have an obligation to the millions of patients we directly and indirectly impact as a result of our decision making in espousing the application of tools and technology in drug development. This, I am sure, will result in better health outcomes there by decreasing the capital burden in our healthcare spending.
Uma Arumugam, MD, Director, Clinical Research & Development, Early Phase Services, ICON plc.
1. McKinsey Global Institute – Big Data: The next frontier for innovation, competition and productivity