Precision AI Pty, Ltd. · Class II · Cleared Jan 21, 2025
| K-number | K243955 |
| Device name | Precision AI Surgical Planning System (PAI-SPS) |
| Applicant | Precision AI Pty, Ltd. |
| Product code | QHE |
| Device class | Class II |
| Decision date | Jan 21, 2025 |
| Decision | Substantially Equivalent |
| Regulation | 888.3660 |
The Precision AI Surgical Planning System (PAI-SPS) is a software and hardware system for pre-surgical planning of shoulder joint arthroplasty (replacement). The software creates a 3D model of the patient's shoulder from CT scans to help surgeons visualize and plan implant positioning. Patient-specific surgical guides and biomodels are then manufactured via 3D printing to transfer the surgical plan to the operating room.
The subject device uses the same code base, software technology, and fundamental design verification/validation methods as the predicate device K233992. The main differences are the addition of new implant system components from Enovis and Lima manufacturers that surgeons can select during planning, and extension of hardware compatibility with these additional implant systems. Core functionality (visualization, measurement, reconstruction, annotation, editing) remains identical.
Not stated in this summary. The document references FDA guidance documents on software submissions and design controls (21 CFR 820.30) but does not cite specific consensus standards such as ISO or ASTM.
Substantial equivalence is established because the subject device has the same intended use (positioning shoulder components), same fundamental technology, same code base, and identical core functionality as the predicate. The additions of new implant system compatibility are treated as non-clinical extensions that do not raise different safety or effectiveness questions, supported by previous testing for accuracy, biocompatibility, sterility, and dimensional stability that apply to the subject device. Previous cadaver and bone model testing on the predicate are considered applicable.
View the full FDA submission: accessdata.fda.gov