Clinical Trial Optimisation In The Digital Era: A Brief Guide
The hundreds of clinical trials undertaken were central to the unprecedented haste in resolving the global COVID crisis. Any new drug or medical procedure can’t be of widespread use without testing its efficacy and potential side effects. In this case, researchers understood the risks of any delay in the testing, as it meant more infections and more time for the virus to mutate.
As the crisis more or less eases, valuable lessons are helping the world prepare for the next one. One example involves streamlining future clinical trials using digital technology, culminating in the rise of the ‘digital’ clinical trials. This site allows you to understand the role of metadata in optimising clinical trials. Moreover, here’s a brief guide to assist you in this tech-heavy era and its implications moving forward.
Elements Of Digitising Trials
Before going in-depth, it’s essential to know how clinical trials work. New drugs, including COVID vaccines, undergo four phases of clinical trials before being ready for consumption.
- Phase I – testing for safety via an open-label design; sample size can include up to 100 healthy volunteers (HVs) and patients.
- Phase II – testing for efficacy (plus further testing for safety) often via a randomized, controlled trial (RCT); sample size can include hundreds, primarily patients.
- Phase III – testing for effectiveness (not to be confused with efficacy) through an RCT; sample size can be up to 3,000, primarily patients.
- Phase IV – testing for long-term effects through an open-label design; sample size is typically up to 1,000 and restricted to patients.
On the other hand, medical devices like implants undergo only two stages: feasibility (also called pilot) and pivotal. Sample sizes range from 10 to 50 HVs and patients for pilot trials and between 100 and 300 patients for pivotal ones.
Recruiting participants, collecting trial data, and analysing said trial data lay the groundwork for digitising such tests. The opportunity to streamline the process and reduce costs exists because of decades of technological progress, from state-of-the-art instruments to social media.
One example of digital clinical trial optimisation involves standardised metadata. By enabling ample access to clinical trial data and monitoring it in real-time, researchers and other involved parties can keep closer tabs on developments of new drugs and medical devices. With this level of availability, medical breakthroughs can enter the public market faster.
Game Changers
Technological advances coincide with the rise in registered clinical trials. As of this writing, the total number of archived tests in ClinicalTrials.gov is over 400,000, with the majority being tests done outside the U.S. To put that into perspective, it only had a little over 1,000 archived tests at the time of its founding in 2000.
There’s no doubt that clinical trials in the digital era will be significantly different from those in decades past. Industry experts believe that the following trends will be more predominant in the coming years.
- Decentralised Clinical Trial (DCT)
By employing technologies such as telehealth and mobile apps, DCTs can perform their functions without the need for subjects to be physically present. It becomes a win-win situation when considering that people don’t have to make the trip to the venue of the clinical trial, a boon for those with serious conditions.
However, experts also iterate that decentralised designs won’t render conventional ones obsolete. They believe that hybrid clinical trials will carry the best of both worlds: tech for less complicated issues and clinical visits for more severe ones.
- Blockchain Technology
The current model of clinical trials suffers from issues ranging from unintentional bias to patient data security. The likes of DCTs may help mitigate such negatives, but they need the right technology to make it so. Blockchain may hold the key.
Blockchain in clinical trials will work the same way as in the financial sector: distributed ledgers across a decentralised network. Experts say that clinical trial data stored in such databases will be less prone to tampering and allow researchers to look at records in years past. Everyone will have the same level of access to pertinent information.
The Dilemma Of Patient Trust
Despite these steady strides, experts believe that the lack of patient trust will remain an obstacle in improving clinical trial designs. Many people have faith in their doctors, but they also worry about their data being shared with private companies. In one instance, this fear led to the closure of an information-sharing program by the National Health Service after just three years.
The healthcare sector faces the responsibility of proving to the public that it’ll use the data for medical advances. The technology available to healthcare providers today will provide a tremendous opportunity to increase patient engagement.
Conclusion
Whether to prepare for the next pandemic or any other reason, optimising the current model of clinical trials is necessary. Harnessing the latest technology and fostering patient confidence are crucial steps toward better treatment.