Trial acceleration has been a topic of conversation for the pharmaceutical sector for years and as technology advances, it is becoming even more of a reality. The time that artificial intelligence (AI) can save sponsors and sites makes it easier than ever to reduce trial timelines; however, the technology will only work well if foundations are strong.
AI is being used to help with site selection, data management and more in the early stages of protocol planning, but cannot replace the basics that should be in place to ensure trials run smoothly. This means that issues need to be addressed which impact parties in the very early stages, and this may not be something that technology alone can resolve.
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Issues such as communication channels, training, delayed start-up and contract negotiations cause study delays before a site even enrols its first patient, so resolving these pain points is needed to accelerate this process and reduce time to first-patient-dosed.
Poor relationships are a key pain point
While Jimmy Bechtel, chief site success officer for the Society for Clinical Research Sites (SCRS), believes that AI can support in many areas – including recruitment and retention, budgets and contracts and protocol complexity – he cautions that delays will persist if relationship issues between sites and sponsors or contract research organisations (CROs) remain unsolved.
Bechtel, who is speaking at the 2026 Summit for Clinical Operations Executives (SCOPE) conference taking place in Orlando, Florida, from 2-5 February, believes that first and foremost, sponsors and CROs should be more collaborative and communicative with sites to resolve pain points that will continue to slow down trials if not properly addressed.
“Sites and sponsors or CROs need effective relationship management practices, open and transparent communication and knowing the appropriate channels to identify who to contact about things,” says Bechtel. “Obviously, that’s a two-way street and the sites have their part to play in that as well. When we do that, we see effective and efficient clinical trial execution.”
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By GlobalDataThis can be as simple as ensuring there is someone available in the same or a similar time zone, so sites are not forced to wait a full day for a response, says Anusha Shetty, senior director of strategy at Veeva Systems.
Areas of delay include start-up and training, which Bechtel says can be a huge area of inefficiency for sites.
Training specifically is a problem, with sites frequently being asked to conduct training multiple times, even though it remains valid from a previous study. This adds to timelines as it delays enrolment while site staff repeat tasks. Shetty agrees that sites are often asked to conduct redundant training, which could also include training they do not require as part of their roles in the trial.
This is something that needs to be rectified on the sponsor and vendor level to try and avoid providing unnecessary burden to investigators. Shetty highlights that one solution could be providing a central database which shows conducted trainings, which can be fed into all studies to avoid duplication.
Another major cause of delay is budgets and contracts. Shetty says there is currently no good way of reusing previously negotiated or agreed-upon language, meaning sites and sponsors end up starting from scratch with contracts for every study.
Bechtel says that not only this, but the back-and-forth negotiations between sites and sponsors are a significant bottleneck for all parties, citing how more effective communication could help solve this, as well as an understanding of expectations on both sides.
“Having to go back and forth is inefficient or ineffective in a negotiation process, so it’s going to delay that process even more,” he explains.
“If a site is going to ask for things that are not included in that original budget, it really has to do its due diligence to provide the sponsors and CROs the appropriate data and justification behind why that’s important and why that’s part of the successful execution of that clinical trial.”
AI must be properly implemented
Technology should not be implemented just because it exists, but because it can assist, adds Shetty. “Technology can certainly help if it’s done in the right way. It can suggest sites, assist with monitoring, prepare documents, find holes in the data, and identify poor-performing sites. Technology can do these things much faster than people, so it can assist here with trial acceleration. If we can automate some of those things, make them more efficient, I think we can get to that acceleration, and not only within study startup, but even beyond.”
However, AI is a game changer when it comes to reducing workload in administrative tasks.
“AI and advanced data across the entire continuum of the clinical trial can assist very early on in identifying sites and designing protocols,” says Dr Jared Saul, CMO of Commercial Healthcare and Life Sciences at Amazon Web Services.
“There’s a massive amount of value hidden in data about previous trials, real-world data, data from the early research phase and even historical trials. If you can get the right insights from that, it really helps inform the protocol,” he explains.
After all, time is money, notes Saul, but it will take time to see how investment into AI will compound to add value.
“Trials cost millions of dollars, especially as you get to Phase III. I think we’re going to start to hear more and more concrete examples of drugs that are brought to market, where we can look back at the tools. Even with the state of technology we have today, we’ve been able to reduce the cost of the trial by 15% or 20%. That comes when we are living in a world where 2% or 5% acceleration or cost reduction is quite significant.”
Collaboration is key
The prevailing sentiment is clear: collaboration at every stage is essential for all parties to align on expectations and accelerate studies. Early collaboration, Saul explains, is a potential solution to this.
“For sponsors, working with the providers earlier on is a good thing; it helps de-risk it. Rather than design a protocol on paper and on your computer, and then go do the trial, having a collaborative approach is really appealing on both ends of it,” he adds.
While Becthel concludes: “Without effective relationship management, the rest of it is going to be really challenging, so that’s really foundational. I can see a world where technology enables that a little bit more effectively if leveraged well and with purpose. It is a bit chicken and egg, but the focus needs to be on effective relationships, and if technology is a solution there, that is great.”
