Pink flamingos, blue icebergs and disruptive innovations in clinical trials
doi:10.1038/nindia.2015.167 Published online 15 December 2015
The clinical trials scenario in India could benefit from a technology leapfrog that heralds disruptive innovations such as wearable devices and the Internet of Things for efficient management of clinical data, according to data management experts attending a conference in Mumbai.
Clinical data management professionals debating new innovations at the second Society for Clinical Data Management (SCDM) conference last week (11-12 December 2015) strongly advocated embracing these new technologies to make the drug development process leaner, efficient, faster and economic.
Richard Young from Global Consulting Partners, Medidata Solutions said India has the opportunity to leapfrog using such innovations given that the country has a large number of patients and is not tied to a legacy of clinical trials system. China has recently conducted the first study assisted by wearable devices for a neutraceutical company. However, compliance and data security are issues in trials of wearable devices that need to be taken care of, he added.
“Earlier, you only had to answer two questions in clinical data trials – does it hurt, and does it work? Today there is a third question, can we save a life, reduce the disease burden, and improve quality of life?” Young said. While the industry was hesitant to adopt technologies, patients have been driving their use. Data management, therefore, could become more patient-centric in future with wearable devices and real time data becoming key to clinical trials.
New technologies transform the research and development process, accelerating drug discovery, said Appalla Venkataprabhakar of clinical research organisation Quintiles. The use of wearables assumes significance in the era of risk based management (RBM), according to Nimita Limaye of Tata Consultancy Services.
One must keep an eye on the 'pink flamingo' or inevitable surprises and existing models of data collection need to change, said Abby Abraham of clinical analytics solutions company Algorics. Comparing data collection to a rowing boat full of people doing their own things not necessarily in consonance, he said these processes need more streamlined approaches. RBM needs to be integral to clinical data management and there are enough examples to show why. Ganapathy Vijayasena of Icon Clinical Research pointed out that in patient-centric monitoring there was a need to check data minutely. The trick was to ask the right questions.
RBM offers an error rate four times lower than other practices, alongside 30% reduction in source data verification. RBM, therefore, is clearly an improvement over traditional review methods, said Jagadeesh Rudraswamymath of Quintiles. The Internet of Things (IOT) can be used effectively for clinical trials. For instance, one can track if a patient has taken medicines using an ingestible pill which emits signals to a patch on the body that in turn signals a CDM system, said Nilofar Nomani of Chiltern International.
Even as RBM and IOT were emerging trends, there is a concern over reporting adverse events. Carlton Dsouza of Quintiles said mechanisms to report adverse events were inadequate and there was an industry trend to withhold importance of safety information. Worse still, there was delayed reporting in case of death. He suggested that the time to report adverse events should be reduced from 24 hours to 12 hours and robust reporting made mandatory in post marketing trials.
Too much data could also be a problem. Demetrios Zambas of pharma group Novartis said RBM uptake has been slow because “it has made common sense too expensive”. Trials need smart data enough to demonstrate safety, he said. Like in icebergs, which crowd out all other light and allow only the blue to be seen, he said data managers must "bring out the blue" by fine tuning the data that is needed.
Regulators too are keen on RBM, said Steve Wilson of the US Food and Drug Administration in a webcast. For wearable devices, he said, the resultant data should be valid and reliable to meet all regulatory requirements.