A multicenter trial of Vitestro’s system shows strong performance and patient acceptance, pointing to gains in preanalytical efficiency and specimen quality.
A newly published multicenter clinical study signals a potential shift in how clinical laboratories approach one of the most labor-intensive steps in the diagnostic workflow, namely phlebotomy.
Vitestro announced results from its Autonomous Blood Drawing Optimization and Performance Testing (ADOPT) trial, published in Clinical Chemistry, evaluating the performance, safety, and patient experience of its fully autonomous robotic phlebotomy system, Aletta.
In March, Dark Daily reported that Vitestro raised $70 million in Series B funding to accelerate development and commercialization of its robotic phlebotomy system, as clinical laboratories look to automation to address staffing shortages, improve workflow efficiency, and standardize blood collection quality. Later that month, Dark Daily’s sibling publication, The Dark Report, followed up the announcement with an analysis on what this means for business operations in the clinical lab.
Vitestro funded the study. Several study authors disclosed they are employees of Vitestro and hold stock options or equity in the company, while others also hold equity stakes.
Robotic Phlebotomy Shows Strong Performance and Workflow Gains
The study—conducted across several leading healthcare institutions in the Netherlands with additional patient acceptance data from the US—represents one of the first peer-reviewed, real-world evaluations of robotic blood collection in routine clinical practice.
For clinical laboratory professionals, the findings highlight growing momentum around automation in the preanalytical phase, an area historically prone to variability and operational inefficiencies.
The study included 1,633 patients across three outpatient phlebotomy settings and reported that the automated system had a 94.5% first-stick success rate when a suitable vein was identified. Performance remained strong across traditionally challenging patient populations, including those with high BMI (97.4%), difficult venous access (92.7%), and elderly patients (93.4%). Hemolysis rates were reported at 0.3%, and adverse events at 0.6%, both lower than rates typically associated with manual blood draws. All adverse events were classified as mild.
From a laboratory operations perspective, these metrics suggest potential improvements in specimen quality and reduced need for redraws. These factors directly impact workflow efficiency, turnaround time, and overall cost of care.
Equally notable for labs focused on patient-centered care, the study found that 90% of patients reported less, similar, or far less pain compared to manual phlebotomy, while 82% said they would prefer or were open to using the robotic system in the future. A separate US-based patient acceptance study found that 86% of patients were willing to use the technology.
Automation Moves Upstream as Labs Eye Preanalytical Standardization
“This multicenter study represents a significant milestone in the clinical validation of autonomous robotic phlebotomy in routine practice,” said Robert de Jonge, PhD, professor and head of the Department of Laboratory Medicine at Amsterdam University Medical Center. “The demonstration of strong performance and safety outcomes is critical to building clinical and laboratory confidence in this new approach. As laboratories advance automation across the diagnostic workflow, innovations like Aletta in the preanalytical phase will be instrumental in enabling more standardized, scalable, and integrated care delivery.”
The implications for clinical labs extend beyond performance metrics. As workforce shortages persist and demand for diagnostic testing continues to grow, automated solutions in specimen collection could help alleviate staffing pressures while improving consistency.
“From a laboratory perspective, consistency in the preanalytical phase is critical, yet often difficult to achieve in daily practice,” said Thijs van Holten, PhD, clinical chemist at St. Antonius Hospital. “Aletta introduces a standardized approach to diagnostic blood collection, with the potential to reduce variability, improve sample quality, and support more reliable diagnostic outcomes.” (Photo credit: St. Antonius Hospital)
While further validation and broader deployment will be needed, the study positions robotic phlebotomy as an emerging tool for labs seeking to modernize operations and reduce preanalytical errors.
For clinical laboratory professionals, the takeaway is clear: automation is moving upstream, and the preanalytical phase may be the next frontier for innovation, standardization, and scalable growth.
This article was created with the assistance of Generative AI and has undergone editorial review before publishing.
—Janette Wider
