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Review
. 2024 Apr 26;7(1):103.
doi: 10.1038/s41746-024-01102-y.

Levels of autonomy in FDA-cleared surgical robots: a systematic review

Affiliations
Review

Levels of autonomy in FDA-cleared surgical robots: a systematic review

Audrey Lee et al. NPJ Digit Med. .

Abstract

The integration of robotics in surgery has increased over the past decade, and advances in the autonomous capabilities of surgical robots have paralleled that of assistive and industrial robots. However, classification and regulatory frameworks have not kept pace with the increasing autonomy of surgical robots. There is a need to modernize our classification to understand technological trends and prepare to regulate and streamline surgical practice around these robotic systems. We present a systematic review of all surgical robots cleared by the United States Food and Drug Administration (FDA) from 2015 to 2023, utilizing a classification system that we call Levels of Autonomy in Surgical Robotics (LASR) to categorize each robot's decision-making and action-taking abilities from Level 1 (Robot Assistance) to Level 5 (Full Autonomy). We searched the 510(k), De Novo, and AccessGUDID databases in December 2023 and included all medical devices fitting our definition of a surgical robot. 37,981 records were screened to identify 49 surgical robots. Most surgical robots were at Level 1 (86%) and some reached Level 3 (Conditional Autonomy) (6%). 2 surgical robots were recognized by the FDA to have machine learning-enabled capabilities, while more were reported to have these capabilities in their marketing materials. Most surgical robots were introduced via the 510(k) pathway, but a growing number via the De Novo pathway. This review highlights trends toward greater autonomy in surgical robotics. Implementing regulatory frameworks that acknowledge varying levels of autonomy in surgical robots may help ensure their safe and effective integration into surgical practice.

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Conflict of interest statement

Author B.I.R. is the Chief Science Officer at Precision Neuroscience Corporation. The subject matter of this manuscript is unrelated to the work of that company and the work presented here was not funded by or connected with the work of that company. The other authors declare no financial or non-financial competing interests.

Figures

Fig. 1
Fig. 1. PRISMA flow diagram for identifying FDA-cleared surgical robotic devices.
Study selection process.
Fig. 2
Fig. 2. Levels of Autonomy in Surgical Robotics (LASR) taxonomy.
Characteristics of each level of autonomy.
Fig. 3
Fig. 3. Number of FDA-cleared surgical robots, classified by their level of autonomy.
a Current total surgical robots. b Cumulative count of new surgical robots over time by the year of first FDA clearance. c Cumulative count of FDA regulatory pathway taken by new surgical robots over time by the year of first FDA clearance.
Fig. 4
Fig. 4. Number of FDA-cleared surgical robots by intended specialty and subspecialty.
a By specialty. b By subspecialty.
Fig. 5
Fig. 5. Cumulative count of new surgical robots over time by the year of first FDA clearance.
Organized by surgical specialty.

References

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