Innolitics are more than a group of top SaMD engineers and reg consultants—they are trusted advisors and are like family. They are a one stop shop for AI/ML algorithm R&D, full stack web development, and FDA regulatory clearance. We built SmileDx, a dental CADe from scratch all without needing to raise external funding and within a reasonable timeframe.
Dr. Richard Ricci, DDS, MS, FAGD
CEO
I am happy to have "roped in" Innolitics into our medical device journey. Their ability to break down complex technical jargon into actionable insights is incredible. I have come to trust their business, technical, and regulatory sense—and so has the FDA so far. I recommend them to anyone looking for a one stop SaMD shop.
Dr. Andrea R. Cambria, DDS, FAGD
CFO
The Problem
Dentists face significant challenges in accurately detecting caries (cavities), periodontal disease (gum disease), and periapical radiolucencies in X-ray images. Traditional diagnostic methods often lead to missed or delayed diagnoses, which can result in more severe dental issues for patients. These undetected problems may progress, potentially requiring more invasive and costly treatments in the future. The need for a more reliable and efficient diagnostic tool has been a pressing concern in the dental community, as it directly impacts patient care and long-term oral health outcomes.
Highlights
Our engagement with Cube Click went from concept to a fully engineered web application. 510(k) clearance pending estimated Q2 2025.
The application, Smile Dx, significantly improves the performance of detecting caries (cavities) and periapical radiolucencies for most categories of patients and imaging equipment.
What We Did
The Smile Dx application shows boundaries of normal tooth anatomy in
X-rays. Here shown are jaw bone, enamel, dentin, nerves, and pulp.
In addition to segmenting normal anatomy, the Smile Dx application
identifies and segments caries (cavities).
In addition to segmenting normal anatomy, the Smile Dx application
identifies and segments Periapical radiolucencies (PARLs).
Cube Click developed Smile Dx, an innovative AI-powered dental diagnostic tool designed to assist dentists in identifying dental caries and periapical radiolucencies. Here's what we accomplished:
Built a robust web application using modern frameworks for both frontend and backend development
Implemented and trained deep-learning models for the automatic segmentation of dental anatomy in radiographs
Developed a user-friendly interface allowing dentists to upload, view, and analyze multiple dental X-rays simultaneously
Integrated advanced, custom image-processing techniques to enhance the visibility of dental structures and potential issues
Created a secure login system with tiered access privileges based on subscription types
Implemented an exam approval system and a patient portal for viewing approved results
Ensured compliance with regulatory requirements, including comprehensive documentation and risk management
Key Technologies
Svelte-based web UI
Django-based web server
Tensorflow-based ML models
Timeline
July 2021: Project started. Proof of concept developed, including initial model training with a small dataset and basic frontend functionality. Demo deployed using ngrok.
September 2021: Work on bone segmentation. Exploration of different approaches for handling various image types and edge cases.
January 2022: Updated model training with additional data. Generation of performance reports.
March 2022: SMILE Dx prototype completed
June 2022: Refinement of FDA pre-submission documents. Addressing security considerations and penetration testing.
July 2022: Completion of verification and validation testing. Finalization of regulatory documents and user manual.
June 2023: FDA pre-submission
December 2023: FDA standalone performance testing completed
March 2024: FDA multi reader multi case (MRMC) study completed for CADe indication
