Symphera: Revolutionizing laparoscopic surgery through automated in-body tool switching

Laparoscopic surgery, performed >15M/year, is a cornerstone of modern care, offering benefits like faster recovery, reduced pain, & lower infection risks. However, frequent manual instrument changes (20–50/procedure) create critical inefficiencies, consuming 22% of surgery time, adding as much as 20 to 40 minutes to operations, & costing healthcare systems >€16Bn/year in preventable costs. These disruptions force surgeons to break focus, increasing errors, delaying emergency responses, & contributing to longer surgeries, higher complication rates, & poorer patient outcomes. For healthcare providers, these inefficiencies escalate operating room (OR) costs, reduce patient access, & hinder workflow optimization. Patients face increased risks of infections, tissue damage, & prolonged recovery times. We address these challenges with the Symphera System, an innovative laparoscopic surgery solution featuring automated in-body instrument switching. Like a multipen, it transitions seamlessly between up to eight instrument tips in ≤3 seconds, eliminating 85% of instrument change time. This reduces workflow disruptions, allowing surgeons to complete 80% of procedure time with the system, recover 15 to 30 minutes of OR time per surgery, & cut costs by between €750 to €1,500/procedure. The system preserves tactile feedback for precision & provides data for surgical insights that optimize training, protocols, & patient outcomes. By addressing €16B in inefficiencies, Symphera streamlines surgical workflows & improves resource utilization. To bring the Symphera System to market, we aim to complete in-human trials to validate safety & efficacy, secure FDA 510(k) & CE certification (class IIb). This will involve testing in simulated operating environments, design finalization, scalable GMP-compliant manufacturing, & regulatory submissions supported by robust clinical data. Scaling will focus on expanding production, enhancing device functionality & a PMCF to generate real-world data