Payments, Pain, and Pragmatic AI in Clinical Trials - Life Sciences Today Podcast Episode 47

Why It Matters

By automating payments and operational workflows and consolidating trial data, Ledger Run can cut administrative burden, reduce compliance risk and improve participant retention—potentially accelerating study timelines and lowering development costs for biopharma sponsors and CROs.

Summary

Ledger Run CEO John Chanichi describes his journey from engineering and consulting to building a business platform that streamlines clinical-trial operations, with a particular focus on participant payments, study logistics and data workflows. Ledger Run targets biopharma sponsors and CROs by replacing fragmented, manual processes—spreadsheets, ad-hoc payment vendors and siloed systems—with a single platform that centralizes payments, consent and operational data. The company emphasizes pragmatic AI and analytics to automate routine tasks, improve participant experience and ensure audit-ready compliance across trials. Chanichi frames the product as low-tech in concept but high-impact in execution, aiming to tackle persistent operational pain points that slow trials and inflate costs.

Original Description

We're excited to be back for another episode of the Life Sciences Today Podcast by Healthcare IT Today. My guest today is John Chinnici, CEO at Ledger Run. I talk with Chinnici about his journey from consulting (Andersen, IBM) to Viva, where he helped launch and grow Vault, and eventually to leading Ledger Run. Ledger Run focuses on the “unsexy but critical” operational layer of clinical trials: contracting and paying investigative sites. Chinnici explains how delayed, incorrect, and bureaucratic payments have become an accepted but damaging status quo in clinical research, despite sites running on razor-thin margins.

Ledger Run’s SaaS platform and services aim to ensure strict contract compliance, dramatically improve operational efficiency, and turn reliable payments into a competitive advantage for sponsors in site recruitment. Chinnici also argues that a major industry anti-pattern is pouring AI investment into volatile early research use cases while underinvesting in high-ROI operational applications such as automating invoice processing and other repetitive payment workflows.

For more great episodes of our Life Sciences Today Podcast, check out: https://www.healthcareittoday.com/category/life-sciences-today-podcasts/