Clinical Trials: A Form of Insanity?
Albert Einstein is credited for saying “insanity is doing the same thing over and over again and expecting different results.” That sentiment pretty much summarizes how much the highly regulated world of recruitment in clinical trials has changed in the past 20 years. (And this also might be the closest any of us gets to being Einstein.)
To be fair, most of the healthcare industry hasn’t kept pace with the new possibilities of technology. This is why anomalies like One Medical stand out so brightly – they’ve managed to grow into a tech-forward healthcare businesses in an industry that is largely not.
The past 20 years has seen the addition of electronic data capture (EDC) through devices, risk-based monitoring and – more recently – flexible clinical trials such as decentralized trials. There is some change happening by implementing these new technologies, but we’re not changing the underlying processes themselves.
Although it may be easiest to not change and keep running clinical trials the same way, the cost is also incredibly expensive. Just think about how many clinical trials fail due to not recruiting enough patients or operational inefficiencies. We already know the system is broken.
Even today the metrics around clinical trials haven’t improved. Several years ago, Tufts Center for the Study of Drug Development found that 11% of clinical trials fail to recruit one patient. And 37% of sites selected for clinical trials under-enroll the patients needed. Given that the cost of running a clinical trial is often in the millions, failed clinical trials are costing institutions major portions of their research budget. How can organizations afford not to make a change when they are spending so much on failing studies? Change is in their best interest.
One change that we have seen? Protocols are becoming more and more complicated and it’s not a trend that’s likely to change. With precision medicine and genomics, there is an even greater need to narrow the inclusion and exclusion criteria for patients in clinical trials. This method promises exciting findings, but it also will make it even more complex to find patients using traditional resources.
The days of sifting through paper records or staring at EMRs are increasingly coming to an end. It’s time to let technology do the heavy lifting and find patients for you.
And that’s where we come into the picture and simplify your life. Our purpose-built software uses natural language processing (NLP), a form of artificial intelligence, to read both unstructured and structured medical data. It’s truly a new world for clinical trials – it means our software breezes through unstructured data such as PDFs, images and doctors’ notes as well as structured EMR data to find the right patients for clinical trials in real time. This also means a reduction in clinical burden and reallocating those precious hours to working with patients or more valuable tasks.
We’re addressing the issue on both the pharma and the healthcare organization sides to ensure we’re making a comprehensive impact.
It’s time to break the cycle of insanity in clinical trials. Reach out to us if you’d like to learn more about how we’re creating a new category of solutions.
Author
Jason Attanucci, VP and General Manager, Life Sciences
jason.attanucci@deep6.ai
