The process of conducting clinical trials to evaluate medical interventions currently includes the collection of an abundance of raw data, which is then formatted into structured datasets for analysis and distribution.
Following clinical trials, researchers release a Clinical Study Report (CSR), including a small subset of findings from the trial. The findings are then published in medical journals and reports for other industry experts to consume, and distributed to the public via coverage in news outlets.
This process can take anywhere from months to years, depending on the trial and the process required for the treatment, drug, or procedure to be cleared by the appropriate governing bodies. Researchers take on a considerable time and resource commitment when starting a clinical trial, and results are by no means guaranteed. According to a study by the Biotechnology Innovation Organization, just 9.6% of drugs entering Phase I clinical testing end up reaching the market, while just 30.7% of those entering Phase II and 58.1% entering Phase III result in success (link).
A contributing factor to the low success rate of clinical trials is the limited ability for researchers to evaluate the progression and intermediate results of the trial during the midst of one of the three phases. Many trials are what are known as blind studies or double-blind studies. In a blind study, the subjects are not allowed to know whether they are in the control or treatment group. In a double-blind study, the researchers are also not allowed to know that information.
Additionally, throughout the lifecycle of a clinical trial, researchers collect data that includes personally identifiable information (PII), or highly sensitive patient data, like name, address, date of birth, health history, as well as other data types like X-rays and genomic sequences, depending on the trial.
For researchers, the combination of the inability to observe and compute on live data and the prevalence of sensitive, protected information make it incredibly difficult to run analyses and process data in real time, resulting in ultimately unsuccessful trials receiving more resources, time, and attention than would be efficient.
TripleBlind’s Private Data Sharing Solution allows pharmaceutical and other healthcare companies the ability to not only compliantly access this metadata during the course of the trial but also allows for early indication trial reporting, which has the potential to allow researchers to gauge how well a clinical trial is going without violating the rules for blind and double-blind studies.
TripleBlind is enabling efficiencies in clinical trials by equipping researchers with the tools they need to gather all of the important insights needed to predict how likely it will be that a given trial will result in a successful breakthrough drug, treatment, or vaccine, without revealing which participants are receiving treatment and which are not. Using this approach, researchers can compile insights into early indication trial reports which can be reviewed and shared without exposing information that would compromise the legitimacy of the trial. Access to early indication trial reporting will allow pharmaceutical companies to develop better drugs and test more efficiently. Some dead-end trials may be abandoned earlier, and resources may be allocated toward other promising approaches.
Using the tools provided by the Private Data Sharing Solution, clinical researchers can compute on data ranging in format from tabular to image and video for use in a wide range of analytics from statistical analyses to AI model training and inference. Our goal is to provide tools to all industries, including healthcare and life sciences, to accelerate innovations, reduce costs and procedural burden, and increase the level of protection on personal information. Enabling early indication reporting for clinical trials is just one prime example of the many ways we are helping organizations to modernize their data processes.
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