To round off our series, ‘Four things we learnt from CTO Southern California 2020’ we’re tal...
To round off our series, ‘Four things we learnt from CTO Southern California 2020’ we’re talking about data. Is too much data in clinical trials a problem?
But before we get started, have you read parts 1-3? Click the links to read our thoughts on the importance of finding relevant patient populations; how to decide which CRO to use; and when to hire a Patient Advocacy team.
These topics were not only critical debates at CTO’s conference earlier this month, but they are also the issues shaping the future of the Life Sciences industry. So, even if you didn’t attend CTO in San Diego, we would love to hear your thoughts! Leave a comment, or get in touch with one of the team here.
Data collection in clinical trials is a labour-intensive and costly process. The average clinical trial generates up to 3,000,000 data points from baseline characteristics to primary & secondary outcome measures and adverse effects. After being collected, each of these data points is processed, quality monitored and then transformed into analysable data sets. Yet, on average, only 18% of the data is reported on - inefficient, to say the least.
These figures demonstrate the urgent need to overhaul clinical trial systems and processes, but what is the solution?
To be valuable clinical trial data needs to be consistent and accurate. However, outdated methods for data collection are still common practice across the industry. From relying on a patients’ memory to determine medication adherence, to manually entering patient information into multiple systems, archaic methods leave data collection vulnerable to inconsistencies that could tank a trial.
Many of our clients are seeking to modernise their trials, using new technology to improve data collection from mobile app development to IoT for remote monitoring and machine learning for EHR processing. There is no doubt that technology has made data easier to collect and share, and goes a long way to streamline the clunky clinical trial process.
However, as highlighted at CTO, although technology can improve these processes, do we need this volume of data? The consensus was we should be consolidating the information collected in clinical trials rather than focusing on the introduction of new technology.
The purpose of a clinical trial is to produce an outcome, so you need to collect data that provides a definitive result. However, in many trials, unnecessary (‘nice to know’) data is collected. Having such a vast amount of information is overwhelming, counterproductive and can be misleading; making it challenging to decide the next steps for the trial.
The desperate need for a more rigorous approach was discussed at CTO; each data point should be carefully evaluated, to ensure only the metrics that are relevant to the study are collected. Obviously, trialists should be diligently and adhere to any rules or parameters set by regulatory authorities, but to disrupt current processes the whole industry needs to adapt. The professionals we met at CTO were sceptical this could be achieved without regulatory changes.
Data collection is part of a broader conversation about the need for clinical trials to become more streamlined and efficient, not only to aid researchers but also to better serve patients (a theme that runs throughout our 4 part series).
So, what does the future hold? A clinical system that is empowered by data, rather than burdened by it, we hope.
Enjoyed our series about CTO? If you want to discuss any of the issues further get in touch!
