By Allison Proffitt 

February 12, 2025 | At the Venture, Innovation and Partnering forum at last week’s SCOPE Summit in Orlando, Shane Senior, the Managing Director and Owner of Crosstree Capital Partners, delivered a bit of an ultimatum: evolve or die! While the decentralized trial revolution never quite materialized, the AI revolution underway in clinical trials is poised for more dramatic change than ever in the next five years.  

The Changing Landscape of Deal-Making in the Clinical Trials Market 

The initial excitement around decentralized trials following the COVID-19 pandemic, has not delivered widespread disruption. “I think we are moving into the next generation of clinical trials,” Senior said. “I want to be cautions when I say that, because I was on the bandwagon of decentralized clinical trials. I thought with COVID coming in, that was going to be the first time we saw true disruption in the industry. That’s kind of shot to the moon and come back down very quickly,” he quipped. Nevertheless, Senior now expects a seismic shift toward smart clinical trials, driven by data and advanced technology.  

He highlighted several examples of disruptive companies along the clinical trial process that he expects to change how trials work. In trial design and feasibility, TriNetX and BEK Health are using real-world data to optimize trial protocols and identify suitable patient populations within health systems. Platforms like Deep6 AI and XCures are leveraging unstructured data from electronic medical records (EMRs) and other healthcare systems to refine patient recruitment and eligibility. Companies like OpenClinica or Protocol First can pull EMR data directly into the EDC database with objective endpoints, he said.  

New digital biomarkers and other objective endpoints will be a big transition in the market, he predicted. WCG, for example, recently announced a new biomarker using voice inflection to measure depression. He also included ActiGraph’s wearable devices and their recent acquisition of Biofourmis. “There’s going to be a profound shift in the industry where you will be able to use half the patients to power your study and get a better signal,” he said.  

In the data management and interoperability steps, Senior highlighted tools from MaxisIT, Saama, and eClinical Solutions that will automate data with AI to enable truly adaptive trials and risk-based monitoring in ways that are much more cost efficient. 

Medical writing is another area of significant impact, Senior said. He shared about a recent Narrativa pilot where the AI-generated submission paperwork was more accurate than the manually prepared documents. “Imagine being able to start the medical writing process before the clinical trial is over, and what you can do to further power your study!” Senior said. “I think we’re going to see profound impacts in terms of assisting clinicians and biostatisticians around this.”  

Finally, for the pharmacovigiliance and drug safety steps, Senior mentioned the work of Vitrana. He predicted that over the next five to ten years, automation will significantly cut down on pharmacovigilance monitoring. For example, currently, the cost of case processing and pharmacovigilance—monitoring adverse events related to drugs—sits at about $50 per record. Senior pointed out that much of this work is outsourced to India, where human workers manually input data into databases. However, he argued that automation will revolutionize this process, making it possible to process cases at a fraction of the current cost—potentially as low as $20 per record. The potential for cost savings is substantial—companies adopting AI-driven solutions could lower their costs by 15% while also improving speed and quality. 

Tech-Enabled Growing Pains 

Despite the clear advantages of AI-driven automation, Senior acknowledged that the transition to a more technology-centric approach will not be without its challenges. There are significant risks and hassle to transitioning away from traditional processes, especially in a regulated industry like pharmaceuticals. CROs and pharmaceutical companies are often hesitant to adopt new technologies, fearing the unknowns and potential disruptions that come with such a shift. Additionally, investors are typically focused on either services or technology, often overlooking the potential of hybrid models that combine both. 

But Senior believes that early adopters who embrace these innovations will be able to capitalize on the market’s shifting dynamics. He emphasized that AI is not a future trend—it is happening right now.  

He pointed to a specific example where a CRO adopted AI technology and won a $150 million global pharmacovigilance program with a top pharmaceutical company. The AI-enabled CRO was able to deliver the service at a price far lower than its competitors, who still relied on outdated methods and manual labor.  

“That’s one $150 million study that AI has won,” he said. “Those studies are global programs that are generally three to five years, and as each one of those big programs, especially, come up, the AI adopters are going to win those studies. So how long is it going to take before this impacts the market—five year? Every single one of these studies will be up [for bidding] in five years, and every single one of them will be won by AI-enabled technology.”  

Successful companies won’t build their own model, he notes. Citing DeepSeq as an example, he says the technology development is moving too fast. But there’s a huge opportunity for combining technology, services, and the application-managed services to interface with databases.  

It’s unavoidable, Senior said. “The early adopters are going to eat this market alive.”