SBIR Fast-Track: Providing Timely, Inexpensive, and Comfortable Earmolds (EMs) for Hearing Loss (HL) Patients using Computed Axial Lithography (CAL) 3D Printing

The broader/commercial impact of this Small Business Innovation Research (SBIR) Fast-Track project is to commercialize Computed Axial Lithography, an innovative 3D printing technique that offers high speed and geometric flexibility. Unlike traditional 3D printing, Computed Axial Lithography creates an entire object in one step, eliminating the need for support structures and enabling smooth, rapid production. This technology has significant potential in healthcare, particularly for custom medical devices. This allows for quick, same-day delivery of personalized devices, such as prosthetics, splints, and hearing aids, bypassing long wait times associated with traditional manufacturing methods. By producing high-quality, cost-effective components faster, this can help meet growing healthcare demand, allowing care providers to serve a significantly larger number of patients. Insurance companies may also benefit from the increased efficiency and offer broader coverage at reduced costs. Starting with audiology, our commercial model will include hardware sales, software subscriptions, and consumables to maximize market potential and serve a larger patient base. This Small Business Innovation Research (SBIR) Fast-Track project focuses on advancing computed axial lithography for the in-clinic fabrication of personalized medical devices. This technique uses a photosensitive resin within a rotating cartridge, which is polymerized volumetrically through a spatial light modulator that projects a sequence of tomographic projection images. This innovative technique allows for the rapid production of centimeter-scale, freeform geometries in seconds, without the need for support structures, and achieves nanoscale smoothness in the finished objects. The project addresses two key technical challenges: 1) developing a soft, biocompatible material with the necessary mechanical properties for custom medical devices—such as earmolds and hearing aids—while maintaining high printing accuracy, and 2) delivering a clinically viable, user-friendly software workflow for single-appointment, high-accuracy custom device production. To overcome the first challenge, the team will formulate a silicone-based acrylate functional resin, characterizing the photopolymerization kinetics and utilizing simulations to optimize the computed axial lithography printing process. The second challenge will be tackled by creating a machine learning model to automate the optimization of projection images, enabling rapid and precise device fabrication in a single appointment. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.