If you’ve been following this blog for a while, you’ll likely have noticed that we often refer to the potential of data analytics and data-driven technology to streamline the drug development process and improve the everyday lives of countless patients. Whilst this all sounds well and good, it might be a little unclear how exactly this will work in reality – something we’ll unpack in this post.
November 22, 2021
How is data-driven technology changing the landscape of patient care?
Firstly, the existing drug development process is long, expensive, and requires huge amounts of effort on the part of research and development teams. Exciting new medications don’t appear overnight, and there’s often a decade in between the concept of a new treatment and it actually coming to market. Throw millions upon millions of dollars into the mix, and you’re looking at a risky investment, from both a financial and time-based perspective.
Essentially, this results in a costly medication or treatment for the person who matters most – the patient. As nine out of ten clinical trials fail to pass the second phase, the 10% of successful product candidates shoulder the burden of reimbursing the pharmaceutical company, which can often enter into territory of tens of billions of dollars. Ultimately, this cost shows up as a heftier price tag on new drugs, often placing an undue burden on those who have no alternative but to buy this medication.
This is where data steps in. By harnessing the power of predictive analytics, pharmaceutical companies can streamline their efforts and are able to avoid the expensive and time-consuming trials that are likely to end in failure. By only focusing on the trials that are predicted to be successful, data analytics is helping to wipe billions of dollars off the final bill for a particular treatment – which, as you’ve probably already guessed, leaves a little extra in the patient’s wallet.
However, cutting drug trial expenses and medication costs isn’t the only way data-driven technology is changing the landscape of patient care. Pharmaceutical companies are gradually starting to recognise the downsides of one-size-fits-all blockbuster treatments, and are adopting a more compassionate, patient-centric approach to healthcare. More and more time is being dedicated to finding out what patients really need, want, and expect from their medication or therapy – and that’s resulting in a more considered and careful way of viewing the healthcare sector.
Patients aren’t a homogenous hivemind with the exact same responses, thoughts and preferences when it comes to treatment: they’re individuals, and should be seen as such. Whilst developing a new drug for each person is obviously unrealistic, there are myriad ways in which research and development teams can adopt a more thoughtful outlook and take patient opinions into account when devising a new product candidate.
By engaging with social listening methods and natural language processing, data analysts are able to ethically and responsibly hear what patients have to say about their treatment. If, for example, a large number of patients complain about a specific side effect they experienced when using a certain drug, research and development teams can take this into account. We’re entering an exciting new phase of drug development, and considering the patient above all is key in ensuring a more accurate, compassionate and effective approach to tackling a variety of conditions.