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Built for Budget-Constrained Oncology: How AI Trial Matching Delivers ROI Without the Risk

By Samantha Kilgallen

Clinical trials are critical to innovation in oncology - but for many cancer centers, trial matching remains slow, manual, and misaligned with today’s budget realities. 

Shrinking research funding and rising operational demands have made it clear: traditional models no longer work. Oncology service lines need a better way to connect patients with trials—without adding cost or complexity. 

This article explores what that solution looks like. But first, let’s establish why a new approach is required. 

Why Traditional Matching Falls Short 

The standard manual trial matching process is labor-intensive, time-consuming, and prone to human error. It requires coordinators, principal investigators (PIs), and researchers to understand the eligibility criteria of each clinical trial; search enormous patient databases for potential matches; analyze individual patients’ medical histories; and evaluate whether the match satisfies both patient needs and trial requirements.  

This not only takes hours of hard work but also faces several other challenges: 

  • Low confidence: Trial inclusion criteria are established with little insight into the trial’s feasibility, creating a high risk of costly failure. 
  • High miss rates: Fragmented systems and inconsistent documentation lead recruitment teams to miss eligible patients and struggle with under-enrollment. 
  • Change Management challenges: Staff is often overburdened with disparate systems, reducing the adoption of new technology 

Worse still, many organizations lack the resources required to overcome these problems. While solutions have been built to streamline these processes and enable more efficient matching, they generally require a large upfront investment, just when funding is being cut. 

And that is where Inspirata comes in. 

Smarter Matching, Built for Oncology 

Inspirata’s Trial Navigator goes beyond basic algorithms. We combine machine learning with decades of cancer registry experience to equip leaders like you with the following: 

  • AI-Powered Pre-Screening: Pulls real-time data from EHRs, biomarkers, and staging to automatically surface eligible trials. 
  • EHR-Embedded Workflows: Designed to function inside your existing systems—no toggling, no disruption. 
  • Flexible to Your Environment: Centralized or decentralized, academic or community—we integrate with your workflows, not the other way around. 
  • Machine Learning That Learns You: Trained on millions of registry records, our solution evolves with your data and decision patterns over time. 

These features combine to produce a smarter, faster, more equitable trial matching process: 

  • Accelerate Enrollment: Get patients to innovative therapies sooner. 
  • Improve Equity: Reach and engage more diverse and representative trial populations. 
  • Drive Operational Efficiency: Free your staff from administrative burden and refocus on care delivery. 

But perhaps most importantly, we have developed a unique payment model that allows every oncology leader to access the technology – even while budgets and funding shrink. 

Built for Budget-Conscious Cancer Centers 

Our performance-based pricing model is simple: you only pay for the solution if we drive increased trial accrual. It is designed for oncology leaders who need real ROI – and the results speak for themselves: 

  • Faster matching speeds 
  • No software licensing fees 

Ultimately, Inspirata is more than a vendor. We’re a partner who shares your goals—and your risks. Whether you’re trying to hit accrual targets, optimize registry output, or support trial diversity goals, we offer a strategic advantage—without locking you into heavy, upfront investments. 

You succeed; we succeed. It’s that simple. 

Want to Learn More About Our Pay-for-Performance Trial Matching AI? 

Request a Demo 

 

Tags: clinical trials, cancer research, trial matching