Clinical Trials aren’t Digital enough. 5 Possible reasons.
Clinical Trials are said to date back some 300 years. In the 1940s, randomized trials caused large leaps, but the movement has been incremental after that. Today the cost pressure from the pharma companies, transfers to the CROs. However, the extent of automation isn’t enough, and Digital hasn’t managed to get enough of a claw hold in the value chain to make a discernible difference. The tech giants and consulting companies continue to push without too much success at a holistic level.
Patient recruitment and retention continue to be a challenge, and on the other hand processing and maintain the Trial Master File is barely digital. Heaps of data is generated during the trial, but not enough gets done with it from reading layers of data to recognizing potential adverse reaction markers in advance. If you are part of the Clinical Trial effort for a drug in any shape or form, you know this. If you are a drug consumer, then you are paying for the removable inefficiencies.
Having done work in this area, we believe the hindrances to Digital arrive in different phases of potential Transformation – during Concept and Planning, Implementation and largely in overall Change Management.
PoCs and Pilot Fascination:
All advisors suggest, and the enterprises prefer to wet their feet a bit by doing a Proof of Concept, and / or a pilot. Enough PoCs of mobile based applications, wearable devices, other IoT and automation are available in the market. However, the technology needs to get proven yet again because “our company is slightly different and we need to see…”. Many organizations fail to break out of this phase, and progress towards scale and larger integrations, or even prioritize through the larger plan.
Unreliable data, and lack of validity:
Data science, data scientists need to play a much larger role in the overall trial process. Instead of helping assimilate data and closing the databases as a process step, they need to be able show patterns, indicate corelated data sets. It is as important to corelate how data is captured (from patients), as it is to ensure validity of measurement (From the smart and connected devices) to determine the outcomes of the study.
Insufficient empowerment of Project Managers and Investigators
It is important to use available data to do more. Large amount of cost of the overall trial germinates from legal cases. At the end of the line the investigator is responsible for patient safety and it is important to empower her to prevent adverse reactions and fatalities.
Trials, and Project Managers need to feel the need to do more in terms of understanding layers of patient data (based on drug administration), correlating them and utilizing even machine learning algorithms to predictively prevent adverse reactions.
Low long-term patient engagement
Today, the drop-out rates of patients is sub optimal running around 50% for longer studies. The drop out causes a drop in the data stream which could be further used. But, the problem is that patients often start with less than required engagement or just get disengaged over a period of time. Wearable technology, smart devices and personalized digital platforms can surely help to keep patients engaged and get them to complete the study.
Human resistance to new technology, and larger change
One of the largest, if not the largest problem is that of managing change in the Project Team or the CRO. I remember the obtuse resistance brought about by doctors monitoring cardiac data (ECG reports, and other data) to let the data pass through simple AI algorithms to see patterns, and automate the mundane work done by analysts. There needs to be an overall mindset change and understanding that technology can read through reams of data that is impossible for a human mind to comprehend. As a natural reaction, stakeholders prefer to resist transformational change, and prefer small steps to reduce risk and perceived uncertainty.
Get on the Digital bandwagon and see how it significantly improves your clinical trials. Visit the 3nayan web site or write to us.
#healthcare #machinelearning #ai #digitaltransformation #clinicaltrial #patientengagement #clinicalstudies #iqvia #covance #parexel #icon #ppd #syneos
About The Author
