Dentistry in the Information Age

Think of the impact CAD/CAM technology has made on the dental industry since its inception a few decades ago. Industrial-sized milling machines demonstrated that they were equally or even more capable of doing the fabrication work previously done manually by skilled technicians. These machines evolved quickly, became specialized, and shrank in size to affordable units that today can reside in any size laboratory or clinical practice. The evolution of 3D printers rose even faster, going from industrial-sized toy-makers to small-scale manufacturing equipment. These technologies are constantly evolving and will become only more capable and practical.

On the data acquisition side, dentists use digital radiology, intraoral scanners, face scanners, and functional movement recording devices for the accurate gathering and sharing of information about a patient's oral condition. Using all of this information, the laboratory can offer its recommendations based on its knowledge and experience, and communicate with the clinician and other team members to create a treatment plan with the best chance of success.

While digital technologies have been very beneficial to the evolution of our industry, there is a game-changer on the horizon that will allow us to connect the dots between patients, clinicians, materials, and digital acquisition/manufacturing techniques. This interconnected, data-based network will assist the laboratory, dentist, and patient to achieve successful and reliable treatment outcomes.

Many of us have heard of machine learning (ML) and artificial intelligence (AI) but don't fully understand how it works or how it could contribute to our lives. Put simply, these capabilities use computers to acquire data and apply it intelligently. Like people, these systems must be trained before they can put it to good use, and the more they use it, the better they get at it. Self-driving, or autonomous, vehicles are among the visible examples of this technology. If you think of the myriad possibilities and nuances of driving in today's cities and roadways, you can start to imagine how difficult it would be to program a computer to drive like we do. But self-driving cars are on the roads now, so how did scientists and researchers do it? The answer lies in data collection—lots and lots of it. They equipped cars with sensors to collect data by watching regular drivers operate their cars. The computer sensors observed us applying our human intelligence to the world around us and used machine learning to identify the very predictable behavior patterns that emerged. By connecting actions with positive or negative outcomes, the system learned to operate better and better.

How might this technology be applied to the dental industry? In the new digital world, nearly all of the patient's information has been virtually recorded. Years later we can look back at a patient's digitized charts: the scans of the mouth, the 3D models of their original restorations, and how any prosthetics have worn over time. With the benefit of these historical records, we can see which restorations survived long-term and how satisfied the patient was with the results. Now imagine doing this with the data history of millions of patients. Dental researchers could examine subtleties in treatment outcomes that could inform dentists' actions to improve future approaches. Blockchain technology with a central repository could even help to trace materials and see if defects in a specific lot of material contributed to failures.

Could gathering more information improve outcomes significantly? As stated earlier, each patient has unique facial movement patterns and bite forces. By recording these values, restorative teams could customize restorations to improve function and reduce adjustments. While many dental professionals are familiar with computer-aided design and manufacturing, few are familiar with CAE—computer-assisted engineering. Often used in industrial design, CAE relies on computers to assess the stresses an object will face and help the engineer create an optimized design. Construction engineers learned through CAE that they did not have to use solid steel beams to support buildings, as I-beams proved to be just as strong while much lighter and less costly. Nature's equivalent is our bones. They are strong but they are not solid. Past the compact cortical bone material is an internal saffold of spongy or trabecular bone structures that significantly reduce what our bones would weigh if they were solid. What if we applied this approach to designing dental restorations? What if there were a way that some of the material could be strategically removed to reduce the weight but not the performance of the restoration? There now are emerging technologies such as ceramic printers that can create similar internal scaffolds. By combining CAE with the patient's bite forces and movement records, we can design a restoration that functions perfectly and is optimized for factors like weight and performance. There are also applications using multiple restorative materials; by creating an interconnection between manufacturing machines and robotics, these hybrid machines will be able to work on the same part cooperatively. Biological advantages to CAE technology can also help us determine the ideal number of implants and more appropriate locations to reduce strain on the body and reduce the probability of failure.

Using CAE, intelligently made parts could include sensors embedded into restorations for real-time feedback of forces in the mouth. If excessive or potentially destructive forces are detected in advance, interventions can be undertaken prior to restoration failure. Additionally, other elements could be installed into restorations, such as those that gather energy from the body to power other mechanisms. Occlusal overloading of implants is a leading cause of failure because the patient has no proprioception—they don't know how hard they are biting. How can we inform implant patients that they are biting too hard? With an embedded device, a heavy bite could be interrupted with a gentle vibration; this immediate feedback could help the patient learn to bite correctly. Looking well into the future, perhaps we can create a biomechanical device that can restore nerve function and help patients feel their implant-supported teeth.

New data-driven technologies can also help increase patient satisfaction with the treatment outcome. When replacing lost teeth, technicians create restorations that aim first to restore function, but many patients are equally driven by their desire to restore their appearance. When prescribing restorations, the clinician will provide some esthetic guidance to the laboratory, such as on the shade, but most of the design is often left to the laboratory's discretion. CAD smile design software has helped reduce remakes by communicating designs to the clinician prior to manufacturing. However, even if the laboratory and clinician agree on a design, there is no guarantee the patient will react positively. Today, with the advent of virtual reality and augmented reality technologies, the clinician can show the patient many different static or live designs, which then can be digitally shared with the patient's friends and family prior to the start of any treatment or fabrication. What if we could monitor the patient's reaction to each of these designs to detect which esthetic outcome is subliminally preferred? Neuromarketing is an emerging science that examines what drives people's decisions to buy or not buy certain products.

By better understanding what people want, restoration professionals can help patients feel more comfortable with their treatment plan, which will ultimately influence its success and increase the patient's satisfaction with the result. At the end of the day, making patients happy is what our industry has always been about. The continuing technological revolution will simply give us more tools to attain this goal.

George Coburn
Co-Founder of Perfit Dental Solutions
Co-Founder of Trispera Dental
Kelowna, BC, Canada

1. Institute for the Future. Realizing 2030: A Divided Vision of the Future. https://www.delltechnologies.com/content/dam/delltechnologies/assets/perspectives/2030/pdf/Realizing-2030-A-Divided-Vision-of-the-Future-Summary.pdf. Published July 2017. Accessed May 21, 2019.