Insider Brief
- Octozi, an AI company automating clinical development workflows for pharmaceutical sponsors, has raised $3 million in seed funding led by Surface Ventures, with participation from Remarkable Ventures and prior backing from Debiopharm’s venture arm.
- The New York-based platform uses a human-in-the-loop design, combining large language models with deterministic clinical algorithms to accelerate data cleaning, reconciliation, review, and reporting for Phase III trials while keeping clinical teams in control.
- In a controlled study, Octozi’s AI increased data cleaning throughput roughly six-fold, cut reviewer error rates from 54.7 percent to 8.5 percent, and reduced false positive queries about fifteen-fold, with an accompanying economic analysis estimating savings of more than $5 million per Phase III oncology trial.
PRESS RELEASE — Octozi, an artificial intelligence company that automates clinical development workflows for pharmaceutical sponsors, has raised $3 million in seed funding. The round was led by Surface Ventures, with participation from Remarkable Ventures, and follows a prior investment from the venture arm of Debiopharm, a Swiss pharmaceutical company.
Clinical trials generate substantial volumes of data that must be cleaned, reconciled, and reviewed before a new treatment can gain a drug approval from regulators. Much of this work is performed manually by data managers, medical monitors, and safety teams, which adds time and cost to drug development.
Octozi’s platform integrates with existing clinical systems and uses a human-in-the-loop design in which clinical study teams retain oversight while AI automation accelerates data cleaning, data review, reconciliation, and reporting. The platform combines large language models with deterministic clinical algorithms and external medical knowledge so that outputs reflect clinical context, such as distinguishing an expected drop in platelet counts after chemotherapy from a discrepancy that requires review.
The platform already currently supports Phase III trials, a late stage of clinical development involving thousands of patients. In a controlled study described in a published research paper, Octozi’s artificial intelligence assistance increased data cleaning throughput approximately six-fold and reduced the reviewer error rate from 54.7 percent to 8.5 percent, while lowering false positive queries approximately fifteen-fold. An accompanying economic analysis of a representative Phase III oncology trial estimated savings of more than $5 million per trial.
“Most tools in this space put trial data on a dashboard and leave the analysis to clinical teams,” said Amit Patel, co-founder and chief executive officer of Octozi. “Octozi was built to perform that work alongside the people who own the data, with the human in control and the model handling tasks that previously took weeks of manual effort.””Octozi brings value to pharmaceutical companies in multiple ways,” said Gyan Kapur, managing partner at Surface Ventures. “It improves the quality of data submitted to regulatory bodies; it helps clinical development and data teams with their day to day work, allowing them to be less of a bottleneck in all the trials they may be managing; and it speeds up the time on specific tasks, which allow pharmaceutical companies to get data out faster to regulators, potentially speeding up time to market for life saving therapies.””Clinical development is one of the most expensive and time-consuming processes in any industry, and the data operations layer underneath it has barely changed in decades,” Patel said. “We think purpose-built AI, designed around how clinical teams actually work, can compress timelines, reduce risk, and bring down cost across the entire development cycle.”
About Octozi
Octozi is a New York-based artificial intelligence company that automates clinical trial data operations for pharmaceutical sponsors and contract research organizations. Its human-in-the-loop platform integrates with existing clinical systems to automate the cleaning, reconciliation, review, and reporting of trial data. More information is available at www.octozi.com.
