Blood collection is among the most common procedures performed in healthcare, with applications across primary care, hospital clinics, emergency departments, inpatient units, surgery, oncology, chronic disease management, screening programs, clinical trials, and preventive care.

Although routine, the procedure is far from trivial. It requires selecting an appropriate vein, preparing the skin properly, handling equipment correctly, following the right tube-filling sequence, minimizing hemolysis, avoiding preanalytical errors, ensuring traceability, and taking the patient experience into account as many patients are anxious about needle sticks.

Precisely because phlebotomy is such a repetitive, seemingly stable task, it has appeared less susceptible to the kinds of disruptive changes seen in other areas of digital health.

Laboratory automation has already transformed many steps over the past several decades, including sample transport, centrifugation, aliquoting, analysis, validation, traceability, and reporting of results. But the first step in that process — drawing blood from the patient’s arm — has continued to rely on a trained professional.

Recently, the FDA authorized Aletta, a device developed by the Dutch company Vitestro, as the first standalone robotic system capable of drawing blood from an adult patient’s arm without direct manual intervention during the puncture.

The device received clearance through the FDA’s de novo pathway, which is used for novel low- or moderate-risk devices when no comparable predicate device exists.

This development is noteworthy because it represents more than just an incremental upgrade to laboratory equipment. It brings physical automation into a patient-care task that involves direct contact with the patient: venipuncture.

It also raises a broader question for clinicians and health systems alike: when does it make sense to automate a procedure that has traditionally been performed only by a healthcare professional, and under what circumstances might automation improve access, quality, safety, or efficiency without lowering the standard of care?

What Aletta Does and Does Not Do

Aletta is designed to perform routine venipuncture autonomously. According to the FDA’s description, the procedure remains under human supervision. A trained phlebotomist initiates the session and remains available to respond to incidents. The authorization allows a professional to supervise up to three devices simultaneously. This explains the organizational interest: the device does not eliminate the need for a professional’s presence, but it changes the ratio of staff to procedures.

The system guides the patient to place their arm on a fixed support via an instruction screen. Then, the patient or the supervisor initiates the procedure. Aletta uses near-infrared light and Doppler ultrasound to locate a suitable vein and distinguish it from an artery. If it does not identify a suitable vein, it does not attempt the procedure. When the vein meets the criteria, the device applies the tourniquet, prepares the skin, inserts the needle, fills the tubes, changes and inverts them, removes and disposes of the needle, and applies a dressing.

This sequence is important because it demonstrates the exact degree of automation: it is not merely a vein finder or an arm that assists with the puncture. The device aims to cover the entire blood draw procedure. However, the system’s architecture itself maintains points for human oversight. The supervisor verifies the order of the tubes and ensures they are properly filled after the procedure. In addition, the sample must be retrieved, transported, and analyzed in accordance with local laboratory protocols. Aletta does not replace the clinical laboratory nor does it perform sample analysis.

The FDA highlights several layers of safety. During the ultrasound scan, the device applies disinfectant to the skin. It must be cleaned by trained personnel between patients. If the patient moves too much, the needle automatically disengages and the extraction stops. Other internal sensors can pause the procedure and alert the supervisor if they detect unsafe conditions. The approach taken is not unmonitored device autonomy but rather limited autonomy with supervision and automatic shutdown under certain conditions.

The regulatory framework is also important. By granting de novo authorization, the FDA sets special controls for labeling, performance testing, and clinical studies.

In other words, the decision does more than allow the device to be marketed: it also establishes a regulatory category and a set of requirements that could serve as a template for later devices of the same kind. In that respect, the FDA’s move carries implications beyond Aletta itself.

Clinical Evidence and Limitations of the Evidence

The FDA’s authorization is based on clinical data. According to the agency’s press release, Aletta achieved successful puncture rates comparable to or higher than those of trained phlebotomists when the device performed the puncture. This was observed in patients with varying health conditions, in individuals who reported difficult venous access, and in participants with different skin tones. The FDA also noted that adverse events related to the device were infrequent and mild.

The main published study is the multicenter autonomous blood drawing optimization and performance testing trial, published in Clinical Chemistry in 2026. It was conducted at various outpatient phlebotomy departments in Netherlands and evaluated performance, safety, and patient experience. The study included two cohorts. In the first cohort, comprising 153 patients, laboratory results from samples obtained using the device were compared with those from manual phlebotomy. No statistically significant differences were observed in selected tests, confirming analytical equivalence for those parameters. In the second cohort, comprising 1633 patients, the routine use of the device was evaluated.

The reported results are significant. In patients in whom the device identified a suitable vein, the overall first-attempt success rate was 94.5%. The rate remained high in subgroups of interest: 92.7% in individuals reporting difficult venous access, 97.4% in patients with obesity, and 93.4% in those older than 65 years. Adverse events were mild and occurred in 0.6% of venipunctures performed with the device. About 90% of the patients reported pain that was minor or similar to that experienced during previous manual blood draws, and 82% stated they would prefer Aletta in the future or had no preference.

These are encouraging findings, but they should be interpreted with caution. The reported success rate applies only to patients in whom the system identified a suitable vein and moved forward with puncture. If no appropriate vein is detected, the device does not attempt the draw and the patient is instead referred for manual phlebotomy. That safety feature may reduce procedural risk, but it also limits real-world use because the system itself determines when an attempt is made.

As a result, overall performance should be assessed not just by success rates after an attempt but also by how many patients are excluded because they do not meet the system’s criteria, along with procedure time, workflow impact, and the need for manual intervention.

Automating a Clinical Procedure

But the fundamental question is not whether Aletta works as intended. The question is where it makes sense to use it. The answer likely lies not in “automating everything” but in identifying settings where the automation of phlebotomy adds value.

The first reasonable scenario involves high-volume outpatient centers, laboratories with many scheduled blood draws, hospitals with bottlenecks in the preanalytical phase, or systems facing a shortage of phlebotomists. The FDA itself links the authorization to the shortage of professionals trained in phlebotomy in the US. If a supervisor can monitor three devices, the system can increase capacity without increasing staff by the same proportion.

The second scenario is standardization. Manual phlebotomy involves variability: the professional’s experience, vein visibility, puncture technique, tourniquet duration, tube order, inversion, filling, handling, and transport conditions. Some laboratory errors stem from the preanalytical phase. A robotic system can reduce variability in repeatable steps, provided it is properly integrated with the laboratory and does not introduce new errors.

The third scenario is the patient experience. Many patients fear blood draws, have experienced failed punctures, or have difficult venous access. A system that avoids blind attempts, uses multimodal imaging, and does not proceed unless it identifies a suitable vein may be acceptable to some users. Published data suggest good acceptance, although it will be necessary to observe its performance in real-world practice, outside of study settings and with larger populations.

Undoubtedly, there is also a professional dimension. Blood collection is not merely a mechanical technique. In many settings, it is a moment of patient interaction — an opportunity to identify discomfort, provide explanations, alleviate anxiety, and observe the patient. Robotization can free staff from repetitive tasks, but it can also displace relational functions and informal monitoring. The challenge will be to redesign the workflow: what does the healthcare professional do when not directly performing the venipuncture, how do they monitor multiple devices, how do they respond to incidents, and how is care for vulnerable patients maintained?

The authors’ conflicts of interest can be found in the original text.

This story was translated from Univadis Spain, part of the Medscape Professional Network.