Clinical trials experts have their say

R&D experts weigh in on what the future holds

Each year, on 20th May, the global health community celebrates International Clinical Trials Day, the anniversary of James Lind’s famous scurvy experiment in 1747 on H.M.S. Salisbury. Lind’s discovery – that sufferers of the disease recovered faster if they included citrus fruits in their diet – is considered one of the earliest examples of a successful controlled clinical trial.

Today’s clinical studies are drastically different, benefiting from modern expertise, access to advanced technology and vast volumes of data. Yet, the overall objective is consistent with Lind’s study 275 years ago: getting innovative, tested, and safe treatments to those who need them most. It’s important that the pharmaceutical industry remembers these objectives and takes action to ensure that patients always come first, and new treatments can be brought to those who need it. The opinions on what action needs to be taken varies depending on what area of the industry you operate in, and R&D experts have a range of thoughts on how to make the clinical trial experience better for all involved.

Putting patients first means managing data effectively

One such expert is Richard Young, vice president Vault CDMS at Veeva Systems. “Although they’ve been around for a while now, the Covid pandemic saw the reported adoption of virtual clinical trials in pharma skyrocket” states Young. “This meant that regardless of their proximity to research sites, volunteers could still participate in clinical trials without the need for in-person contact. Since then, the pharmaceutical industry has continuously made an effort to implement technology than can help make trials more patient-centric, and ultimately a more comfortable experience.”

Although patient centricity and the ability to conduct studies globally have been great steps forward for clinical trials, Young believes it has covered up a somewhat inconvenient truth. “With decentralised trials, sponsors have no clear-cut way to aggregate and review the huge volume of patient data being gathered from disparate sources. This problem is not new – and it is inherent with decentralised trials that the same data for different patients will be collected in different ways.” Moving forward, he feels that aggregating data in a central clinical data management system (CDMS) will be “crucial to achieving the visibility and timeliness that we know contribute to more effective trials.”

In the coming years, Young hopes to see an ambitious standard adopted industry-wide when it comes to digital trials. “The wishes of the patient should always come first” he says, “and this needs to be taken into account at all levels when executing trials. As data collection becomes distributed, trial data should continue to be aggregated and harmonised on one central platform. This allows for study managers to effectively oversee and manage trials and allow for clinical studies to be incorporated seamlessly into everyday life.”

The role of automation in clinical trials

As trials become more intricate, the number of processes and manual tasks involved increases. With technological advancements, there is a huge opportunity for automation to empower scientists to work smarter and more efficiently. This leaves the repetitive, manual tasks of clinical trials such as pipetting into test tubes to robots and gives scientists in the lab a chance to focus on more strategic and analytical work.

Craig Johnson, diagnostics & genomics lead at Automata, believes that automating processes can have a significant impact on every stage of a clinical trial. “From the initial development of the trial, through to sample collection and analysis, automating processes can ensure a level of repeatability and traceability that empowers lab technicians to process and analyse much higher volumes of high value data samples, with far greater precision,” claims Johnson.

“Clinical trials are a critical part of drug discovery, and many organisations will be running over 10 different trials concurrently. When the stakes are so high, it becomes critical to reduce the risk of errors.” Johnson notes, however, that it is not uncommon for organisations to track progress and results of multiple trials on paper. “Paper tracking is incredibly susceptible to manual error, especially when tens or hundreds of samples are managed per hour, and a single mistake can be costly and slow down the development of much needed drugs and treatments. With the full traceability offered by automated systems, lab technicians gain increased visibility to every step of the process, enabling them to eliminate potential mistakes and work more efficiently.”

When it comes to hospital trials, Johnson has noticed that they have a particular challenge around scale, with huge volumes of samples coming in at speed and labs needing to be able to process them with efficiency and care. “One way to manage this is through dynamic scheduling. Using an automated workflow management system can manage multiple lab processes across numerous trials at the same time, even when samples are coming in thick and fast from the ward. Automation also has an important role to play in data collection.

Machine learning and AI analysis technology is increasingly being applied in lab spaces, and as a result, this large volume of quality data is a true differentiator in producing precise results that support drug discoveries. To obtain these data sets, end-to-end automation is essential, as it gives lab technicians the ability to work with higher volumes of data than before without the fear of human error or losing track of results.”

International Clinical Trials Day offers the pharmaceutical and R&D community a chance to remember the past, and appreciate just how far clinical trials have come in recent years. But rather than resting on its laurels, it’s important that the industry continues to strive for improvements in the trial process, looking at how we can continue to innovate and adapt to improve trial outcomes for all involved.

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