To advance science without compromising trial efficiency, we must prioritise simpler user journeys and connected data.
Clinical trials are constantly pushing the boundaries of innovation. Over the past few years, there’s been an explosion of advancements, such as the widespread use of biomarkers in precision medicine, exemplified by initiatives such as Genomics England’s 100,000 Genomes Project, that supports patients with rare diseases and cancer,[1] alongside the increasing integration of real-world and digital device insights.[2]
A large-scale analysis of protocols and other data sources from over 16,000 trials highlighted a trend toward increasing complexity in clinical trials across all the indications evaluated.[3] Complex science often undermines operational efficiency. Over the past seven years, the average number of amendments per protocol increased by 60 per cent. At the same time, the typical time to implement an amendment has almost tripled.[4]
Even making minor changes to a gene therapy trial, such as increasing the number of participants, can significantly impact a study’s success by driving costs up sharply. Overhyped technologies (like decentralised clinical trial solutions) have often fallen short of expectations, leading to lower operational efficiency rather than sought-after improvements.
To avoid a tug-of-war between scientific rigour and operational efficiency, we must focus on the user and data journeys of sites, patients, and sponsors. Simpler everyday experiences with the use of connected data are the foundation to delivering the trials we need rather than what the technology allows.
Helping sites remove the hurdles
Sites have been voicing their concerns for years about the growing technology burden. Common pain points include navigating over 15 portals per study, organising password changes every six to eight weeks, and accommodating each sponsor’s unique definitions, standards, and database setups. Not only do disconnected tools take site staff away from patient care and absorb their time in training, but they also undermine data quality by forcing repeated data entry. Viviënne van de Walle, medical director and founder of PT&R, likens the site experience to being stuck “in a really bad escape room”.
Thankfully, we are turning a corner on delivering better site support. An aspiration of fewer systems will reduce the site admin burden with positive knock-on effects on both patient recruitment and engagement. A better patient experience would then widen access to life-enhancing treatments, particularly in rare diseases. Reflecting on her experiences and needs as a rare disease patient, Helen Shaw, co-founder of the virtual site VCTC, observes: “I see how hard it is to take part in a clinical trial. But patients do want that opportunity to be offered something that they wouldn’t get in their standard care, whether additional MRIs or new medicines.”
Tailoring to individual site needs
Simplifying at a time when science is becoming more complex can feel counterintuitive. But when sites and sponsors shed the legacy systems holding them back, they can finally determine what processes they need to run the trials they want.
Sponsors and CROs (Clinical Research Organisations) are increasingly focused on alleviating a site’s concerns when introducing new systems, even when those systems are ultimately designed to simplify processes. This involves being aligned on shared objectives and working together closely.
All sites are unique, bringing varying levels of technological experience. A ‘one-size-fits-all’ style of interaction is one of the most commonly cited challenges that sites face in their partnerships with sponsors.[5] One clinical trial management software leader notes the impact of this mindset on sites: “Every site can have a different starting point or place of comfort when it comes to implementing technology. The ideal is to remove some of the administrative burden, but sites can have mixed feelings about new technology.”
They add: “Simplifying is a big win. It shows that we’re moving to a mindset of fixing problems instead of just adding more functionality.”
Smart automation relies on connecting data
With cell and gene therapies accounting for a bigger share of the drug development pipeline,[6] we can expect an evolving research profile: more studies with relatively small patient populations and rolling regulatory approvals, leading (hopefully) to compressed timelines. Yet, paradoxically, even a study of 30-40 patients can still ingest and generate huge volumes of relevant data (e.g. DNA-related, molecular information) because each person is treated as an individual rather than a study average. This data is then used to develop highly personalised and effective treatments.
As we transition into a non-EDC-centric world, we need more flexible data management so sponsors can drive science forward while delivering complex studies efficiently. Rather than a one-size-fits-all approach, systems and technology must be able to support the majority of protocols with enough flexibility for niche trial requirements.
Artificial intelligence (AI) and machine learning (ML) will play an important role in transforming raw data, so it is clean and usable. Andy Cooper (CEO of CluePoints, a risk tracking and analytics provider) observes that machine learning is already taking the noise out of edit checks, for example.
AI and ML are not yet ready to solve all our data challenges. But in the meantime, automation can generate value at multiple points during clinical data management. Commenting on its impact within their organisation, a senior data science leader at a top global healthcare company says: “The growing number and complexity of trials means we should be working at scale, not just in production and facilities but also in our clinical setup. These functions have to be able to work together, and to scale.”
Once all study data is connected, advances in clinical trial efficiency become feasible. For instance, automation is one of the four main pillars that this healthcare company is optimising for growth. Its data science leader explains the importance of another pillar — a strong data foundation — to their team’s success: “It’s common for data infrastructure setup to be horribly patchworked. You can’t introduce meaningful end-to-end automation on poor data and without seamless processes. We need to get rid of the patchwork.”
Balancing complexity and trial efficiency
Now is the time to challenge outdated practices, including excessive data collecting, cleaning, and querying. Too much time, money, and effort is spent today on the latest technology that generates excess data – all in the name of “innovation”. A pragmatic, value-focused approach is needed to innovate sustainably. Regulators are already heading in the right direction by encouraging a risk-based approach to trial design, focusing on the data and processes that ensure trial quality.[7]
Our goal is to unify data with the right processes and skilled employees, enabling clinical teams to concentrate on the science while data management systematically uncovers patterns within and across studies. The benefits of a centralised approach go beyond operational efficiency and, over time, could change the economics of clinical trials. By bringing medical, investigators, and site coordinators onto a single, connected platform, we can streamline patient recruitment, and address emerging challenges in drug development more effectively.
It’s time to end the conflict between scientific rigour and trial efficiency. By prioritising simpler everyday experiences for sites, clean connected data, and a pragmatic approach to innovation, we will advance science together.
By Manny Vasquez, Interim Lead, Clinical Data Strategy
References
[1] Genomics England, 100,000 Genomes Project. https://www.genomicsengland.co.uk/initiatives/100000-genomes-project
[2] Diabetes Research Institute, ‘The Expanding Role of Real-World Evidence Trials In Health Care Decision Making’, J. Diabetes Sci. Technol.
[3] Boston Consulting Group, ‘Clinical Trials are Becoming More Complex: A Machine Learning Analysis of Data from over 16,000 Trials’, Scientific Reports
[4] Tufts University Center for the Study of Drug Development, ‘New Benchmarks on Protocol Amendment Practices, Trends and their Impact on Clinical Trial Performance’, Therapeutic Innovation and Regulatory Science
[5] Tufts CSDD, Comprehensive Summary of Site Engagement Literature, https://csdd.tufts.edu/white-papers
[6] Pink Sheet, ‘Orphans Account For More Than A Third Of EU New Drug Approvals In 2022’
[7] European Medicines Agency, ICH guideline E8 (R1) on general considerations for clinical studies