When we think of artificial intelligence (AI) in healthcare, it’s relatively easy to conjure up images of research and development teams combing...
What is clinical data collection and how does it affect real-world patients?
Clinical data collection is a phrase that’s thrown about a lot on the Permea blog. We’re big fans of it, and are eager to explore the myriad ways in which this concept can improve both the clinical trial and research and development processes. But what exactly is clinical data collection, and how does it affect the lives of patients in the real world?
As you’re likely already aware, data collection itself is the process of gathering quantitative and qualitative information on specific topics, using a systematic approach to measure certain aspects of targeted variables. The results of this process are known as data, and can be used for an endless variety of different purposes – be that for marketing departments to better understand their customer, or for medical practitioners to recognise the prevalence of a disease in a certain geographic location or community.
When data collection pertains specifically to the clinical trial process, it’s referring to data that might have been gathered in order to support drug development. Data can be used throughout the clinical trial process to varying extents – but we’re still waiting for many healthcare organizations to recognize the potential it has, and the impact it could have on real-world patients and their treatment programs.
There are countless different ways through which data can be collected, such as scraping, patient-reported data, surveys and questionnaires, natural language processing, social listening – the list is extensive and continually growing. However, clinical data on their own aren’t of much use, and data analysts are needed at this stage to extract the valuable and actionable insights that can result in positive change.
For context, only a small number of clinical trials actually results in a drug coming to market. Each trial can cost upwards of $2 billion, with the development process lasting 10-15 years on average, involving countless individuals and huge amounts of time and effort. It’s understandably disheartening when such an enormous investment – both financially and time-wise – results in nothing coming to fruition. Research and development teams are forced to go back to the drawing board and start from scratch, potentially embarking on yet another expensive, time-consuming and unsuccessful trial.
This is where data analytics steps in. By cleaning, organizing, and analyzing these data, analysts are able to generate new information and, as a results, new insights which can be taken into consideration by the pharmaceutical company when creating a new product candidate. Taking this new information into account during the drug development process can make or break the company’s end product – something that should be taken seriously.
If a research and development team are presented with actionable insights that determine which medications or therapies customers will and will not respond well to, they can consider in more detail whether or not it is worth pursuing trials that have been predicted to fail. By harnessing the power of data analytics in the clinical trial process, analysts are able to determine which trials warrant further investigation and can therefore avoid investing time, money and efforts in those which won’t result in anything – except a large bill.
Whilst all this sounds well and good, it might not immediately be apparent how this positively affects patients in the real world. By taking advantage of the insights and benefits of data analytics, drug developers are able to reduce the cost of a clinical trial by eschewing those likely to be unsuccessful – resulting in a smaller amount of money that they’ll need to recoup at the end. In practical terms, this means a cheaper end product for the consumer, as their medication won’t need to reimburse the pharmaceutical company in question for nine failed drug trials.
The healthcare sector in on the verge of recognizing the potential of clinical data collection. As long as ethical standards and best practices are adhered to, the large-scale adoption of this concept is a golden ticket to improving outcomes for patients in the real world – the people who matter most.