Peppermint’s platform is designed to provide a continuous, audited record of every visit, invoice and dollar a clinical research site is owed, according to the release.
The platform ingests data from a site’s clinical trial management software, cross-references it against payment history and trial contracts, invoices instantly and continuously and pursues collections, the release said.
Early users of the platform collect revenue three times faster, reduce overdue invoices by threefold and reduce by 20% the amount of time staff spend on billing, per the release.
With its new funding, Peppermint will expand its platform’s capabilities to include budget negotiation, expense management and clinical trial analytics, the release said.
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Peppermint Co-Founders David Freeman and VJ Thurimella met at X1, where they were the first business hire and first engineer, respectively, and helped build the financial infrastructure behind the consumer credit card business later acquired by Robinhood.
“At X1 and Robinhood, we helped build systems designed for precision and scale, to process billions of dollars every year,” Freeman said in the release. “We’re bringing that architecture to clinical research, converting earnings into friction-free collections that also provide [clinical research organizations (CROs)] and sponsors with cleaner data from the source.”
Peppermint’s seed funding round was led by Moxxie.
Alex Roetter, managing director and general partner at Moxxie, said in the release: “There is no standard financial infrastructure for clinical trial billing today. Every dollar a site is owed has to be reconstructed by hand from disconnected systems. Peppermint is bringing the discipline of modern FinTech to one of healthcare’s least-examined back offices.”
PYMNTS reported in March that AI agents are finding their footing in healthcare and pharma, with the use cases ranging from answering patient phone calls to selecting clinical trial sites.
The May edition of PYMNTS Intelligence’s “The Enterprise AI Benchmark Report” found that healthcare organizations have concentrated their AI investments in a handful of workforce and operational areas.
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