Every clinical trial starts with a protocol—a sprawling document, often 300 pages or more, spelling out procedures, visit schedules, and measurements down to the minute. Then comes the translation problem.
Research sites receive these protocols as PDFs. Teams spend weeks, sometimes longer, converting dense regulatory text into calendars, billing grids, checklists—the practical tools they need to actually run a study. Drug sponsors, meanwhile, watch this same manual process repeat at every site they work with. When protocol amendments arrive, and they always do, everyone starts over.
Concordare Trials, a New York startup that incorporated just last summer, believes it has engineered a way out of this cycle. The company is launching a platform that uses artificial intelligence to digest clinical protocols in any format and spit out standardized digital files. From those files, the system auto-generates the operational documents sites need. What typically consumes weeks, Concordare claims, happens in minutes.
Whether the industry is ready to trust AI with such foundational work—and whether Concordare's proprietary format can gain traction in a standards-driven field—remains an open question.
A File Format With Ambitions
At the heart of Concordare's platform sits something the company calls CPTM: Clinical Protocol Trial Model. Think of it as a universal translator for trial protocols.
The process starts simple enough. Upload a protocol—Word draft, final PDF, doesn't matter—into Concordare's web application. The AI engine parses the text and converts it into a structured, machine-readable CPTM file. That digital protocol becomes, in the company's words, "a single source of truth."
The CPTM file aligns with CDISC naming conventions, the lingua franca of clinical data systems. From there, automation kicks in: the platform generates patient visit calendars, treatment checklists, informed consent templates, billing grids populated with CPT code intelligence, study trackers, contracts. Sites can theoretically connect this protocol logic to electronic data capture systems, clinical trial management software, electronic trial master files, payment platforms.
Concordare's roadmap includes native connectors for major eClinical systems and electronic health records. For now, the company relies on API and file-based exchanges—a pragmatic starting point, perhaps, but one that may complicate the "plug and play" promise.
The Speed Promise
Speed sells in clinical research. Study startup timelines have long been a pain point, with sites waiting months to receive finalized documents and sponsors hemorrhaging money during delays.
Concordare's website states that site preparation time can drop from weeks to minutes. In LinkedIn posts, the company has suggested its work with Rutgers Health and New Jersey Medical School could "accelerate study start-up by 6–8 weeks." Those are significant claims in an industry where every day of delay costs thousands, sometimes millions.
The pitch extends beyond speed to consistency. According to Concordare's F6S profile, roughly 13 percent of protocol deviations stem from misinterpretation or manual conversion errors—coordinators reading the same document differently, creating slightly different visit schedules, missing billing codes. A standardized digital protocol, interpreted once by AI and deployed universally, should theoretically eliminate those inconsistencies.
On the compliance front, Concordare says it's building toward 21 CFR Part 11 readiness with versioned protocol files, audit trails, and role-based access controls. The platform doesn't store protected health information, which simplifies some regulatory concerns but doesn't eliminate all of them.
Early Deployments, Quiet Partnerships
Concordare's public profile mentions deployment at Rutgers, though details remain thin. Neither Rutgers nor the startup has issued a formal press release, and inquiries to both organizations went unanswered. LinkedIn posts from Concordare reference a partnership with Rutgers Health focused on digitizing protocols and trimming startup timelines, but specifics—study types, volume, measurable outcomes—haven't surfaced publicly.
The company also lists a collaboration with Allegheny Health Network, facilitated through Innovation Works' AlphaLab accelerator in Pittsburgh. That partnership reportedly centers on embedding digital protocols into real-world site workflows. Concordare has been hiring in Pittsburgh, a signal the company intends to maintain a presence beyond its New York headquarters at 122 East 42nd Street.
The startup is part of the 2026 NYU Entrepreneurs Challenge cohort in the digital tech venture track. The team includes CEO Zach Sawaged, who brings experience as a clinical research coordinator—useful context for someone building tools for sites. Advisors Jeffrey Clement and David Epstein round out the leadership, and the company recently brought on Nathan Maher as founding engineer and tech lead.
For a team that appears to number fewer than 10 people, Concordare is making considerable noise.
Timing, Standards, and a Crowded Field
Concordare's launch coincides with genuine momentum around protocol digitization. For years, the concept lingered in pilot purgatory. Now regulatory bodies are finally aligning.
Last December, the International Council for Harmonisation finalized ICH M11, a guideline for structured clinical protocols. In June 2025, CDISC released version 4.0 of its Unified Study Definitions Model (USDM), the standard underpinning digital protocol exchange. TransCelerate BioPharma, an industry consortium of major sponsors, has been pushing what it calls Digital Data Flow—a shift from document-centric to data-centric trial design. In an October 2025 update, TransCelerate noted growing regulatory readiness and ecosystem adoption, pointing out that the average lag from protocol approval to study startup still runs around four months. Much of that delay traces back to manual document preparation.
Concordare is hardly alone in sensing an opportunity. Faro Health offers an AI platform for study design and protocol authoring. Nurocor's clinical platform centers on USDM-based digital protocols and claims 50 percent acceleration. Risklick Protocol AI focuses on end-to-end protocol design aligned with M11 and USDM. Novo Nordisk released OpenStudyBuilder, an open-source study specification tool aimed at standardizing protocol structure from the start. PwC's Intelligent Clinical Trials product claims to have digitized more than 5,000 protocols with 90 percent extraction accuracy, primarily for benchmarking and scenario modeling.
Most of those competitors concentrate on the authoring side—helping sponsors write protocols in a structured format from day one. Concordare's angle differs, and perhaps that's strategic. It meets sponsors and sites where they already are, taking existing protocols in any format and converting them into a digital model. That approach could appeal to organizations with legacy studies or sponsors unprepared to overhaul their entire protocol development process.
Then again, it could also mean Concordare is building a bridge to a world that's already moving past it.
Business Model and Pricing Opacity
Concordare operates a B2B SaaS model with annual licenses and per-protocol conversion fees, according to its Gust profile. An F6S listing suggests pricing starts around $3,300 per month, though the company hasn't confirmed that figure publicly. That ambiguity is common for early-stage software companies still testing price sensitivity, but it complicates assessment for potential customers.
The target market includes research sites, sponsors, and contract research organizations. Concordare's messaging emphasizes a "site-first" approach—tools that sites can deploy quickly without heavy IT implementation. For sponsors, the pitch centers on standardization: one conversion process, one set of documents distributed across all sites. CROs managing multiple studies for multiple sponsors might use Concordare to impose consistency across their portfolios.
The company's website includes a careers page with a note that "new roles coming soon." LinkedIn lists its size at 2 to 10 employees. Concordare incorporated in Delaware in June 2024 and registered in New York that December—barely a year in operation.
The company's tagline—"Don't read studies, run them"—captures the operational mindset. It's punchy, maybe a bit too neat. Clinical trials have long been burdened by administrative overhead that pulls coordinators away from patients and into spreadsheets. If Concordare's platform delivers on its claims, shaving weeks off startup timelines and reducing manual busywork, it could find a receptive market.
The bigger question is whether the CPTM format gains traction as an industry standard, or remains a proprietary layer sitting atop CDISC and USDM conventions. Standards battles in healthcare IT are brutal and slow. Interoperability with the broader ecosystem will determine whether Concordare becomes essential infrastructure—or just another conversion tool in an already crowded toolbox.
For now, the company is betting that tired research coordinators and cost-conscious sponsors are willing to take a chance on automation. Time, and probably a few more pilot programs, will tell if that bet pays off.
