CGM technology has proven to be an essential tool in diabetes management, improving patient outcomes and reducing some of the burdens on healthcare systems. Demand for CGM devices is continuing to grow, driven by the rising prevalence of diabetes and increased access to these technologies for new and existing patient populations.

To capture this growing market, manufacturers need to ensure device designs align with user needs while refining innovative features to adapt to the evolving demands of different user groups.

Expanding Access and Broadening the User Base

The CGM market is growing rapidly and is expected to more than double from around $4 billion in 2020 to $10 billion by 2025. This growth is driven by expanded U.S. insurance reimbursement, now covering CGM technology for an additional 38.4 million adults with Type 2 diabetes. Though this is expected to improve outcomes for both patients and payers, it also presents new challenges for manufacturers, requiring them to adapt and tailor devices to new user types with different needs.

CGM technology is also becoming available to users outside of the traditional insurance channels through the FDA’s recent approval of over-the-counter (OTC) CGM devices. This will make proactive glucose monitoring available to those who may not have access through traditional insurance-backed routes.

Additionally, CGMs are being adopted by non-diabetic users in the fitness and wellness spaces. Health-conscious individuals are increasingly using them to gain data-driven insights into their body’s changing response to diet and exercise for proactive health management. These insights can lead to improved routines and performance or something as simple as selecting a breakfast that results in a smaller blood glucose excursion.

These shifting trends create new opportunities for CGM manufacturers to innovate and differentiate their offerings, ensuring they deliver solutions that meet diverse user demands in a rapidly evolving market.

Using Multi-Physics Modeling to Accelerate Development

Incorporating multi-physics modeling into the development process creates a deep understanding of the various mechanisms at play, enabling the rapid iteration of design parameters to optimize device performance for specific user needs.

Modeling tools, such as in silico simulation, provide a virtual environment to test sensor configurations, materials and interactions to replicate the complex conditions these devices must work under in vivo. This approach can save considerable time by identifying the critical parameters of performance, defining the operating window and pinpointing potential issues. This limits time-consuming testing and allows for the optimization of the design early on without the need for extensive physical prototyping.

Engineers can refine critical factors, like sensor geometry, membrane materials and layer thicknesses, quickly assessing how they affect sensor performance and how well each of these processes needs to be controlled in manufacture. By decreasing the number of prototypes needed and their associated lab-based testing cycles, in silico simulation can streamline the journey from initial concept to clinical validation.

Streamlining Development through Automated Testing

Automated testing systems are an invaluable resource in validating sensor performance efficiently and reliably. They enable high-throughput testing to evaluate sensor accuracy, reliability and performance under a variety of conditions in a robust and repeatable manner. While manual testing methods are low effort to set up initially, they can be labor-intensive and prone to error, and the data they deliver can vary in quality over time and between operators. Automation allows for continuous and repeatable testing across multiple sensor populations, simulating well-defined glucose fluctuations and environmental conditions over extended periods while reducing the need for manual intervention.

Automated testing can also help manufacturers meet regulatory requirements by producing documented sensor accuracy and reliability throughout the testing process. Data-driven insights can be gained across sensor designs and manufacturing batches, streamlining the development process and increasing confidence in the performance of device designs.

Emphasizing a Human Factors-Led Engineering Approach

A strong focus on human factors is needed to ensure that CGM devices are able to integrate seamlessly into users’ lives while meeting a diverse range of needs. Upfront insights into the requirements of different user groups—such as comfort, ease of use and accessibility—can guide the development of devices to enhance the patient experience. Designing with patient feedback from the start reduces the likelihood of major revisions, boosts adherence and speeds up the path to market acceptance.

Conclusion

As the CGM market continues to expand to support millions of new and varied users, innovative approaches that streamline development and prioritize different patient needs are critical. By leveraging modeling tools, robust streamlined automated testing processes and a human factors-led design and development approach, CGM developers can create new and innovative devices that address the evolving requirements of patients. In this fast-paced landscape, companies that deliver this are the ones that will set the standard, transforming diabetes care and advancing health outcomes on a global scale.