For years, diabetes researchers have searched for biomarkers that will make it easier to identify and develop treatments for targeted patient populations, and thus improve the speed, safety and efficacy of drug development trials. There were many promising early results, with several biomarkers heralded as the next evolution of diabetes research, but in the end, none of them panned out.

The problem is that diabetes is a metabolic syndrome, and while diabetes related genetic abnormalities that indicate diabetes have been identified, scientists have not yet figured out the unique genetic, immunologic, and metabolic biomarkers that would enable them to predict which patient populations will develop the disease, who will respond to which drugs, and who will be most susceptible to side effects. Without that knowledge, researchers can’t develop specific drugs for targeted populations, which means drug trials have to be larger to encompass the entire diabetes community, which makes them more costly and time-consuming, and increases the risk of failure. 

In the meantime, we continue to rely on one biomarker for diabetes, HbA1c, also known as A1c. A1c refers to levels of glycated hemoglobin in the patient’s blood, providing clinicians with an overall picture of the patient’s average blood sugar levels over a specific period of time. This is useful, as the higher the A1c, the greater the risk of developing diabetes-related complications, but as biomarkers go it is a relatively crude measure. Because it only provides a single overall average, clinicians gain no insight into the A1c outliers, or more detailed trends, referred to as glycemic variability, that occur during the measurement period.

Due to the lack of success in biomarker research for diabetes, A1c is still our best indicator, which is creating significant research obstacles. As regulators increase requirements for proof of safety and efficacy across patient populations, it has made late stage diabetes research cost-prohibitive for most small and medium sized biotech companies. This is causing the most innovative minds in research to abandon diabetes studies for more achievable research outcomes. As a result, diabetes patients are missing out on innovations that could be developed if the trials were more feasible.

That is an unacceptable situation. Almost 30 million people in the US and nine percent of adults worldwide, suffer from diabetes. If we are going to address this global healthcare crisis, we must find new biomarkers to help streamline research and make it possible to deliver the same quality and efficacy of data with smaller faster trials so we can bring better treatment to market faster.

The role of CGM

There is one silver lining. While no new biomarkers have been identified, many researchers and physicians are embracing continuous glucose monitoring (CGM) to improve diabetes treatments. CGMs use tiny sensors embedded in patients’ abdomens that continuously track their glucose levels, capturing glucose values every five minutes and transmitting those data back to a receiver. These devices offer a balance to the A1c biomarker, providing thousands of data points, including highs and lows in the patient’s glucose levels over the course of time. Analysis of these data gives insights into how long a patient has been in or out of range and can also indicate trends that will help the clinician provide better treatment options.

While CGM isn’t an alternative to new biomarkers for diabetes, it does provide a backstory to compliment the A1c results, which benefits the entire diabetes community. This technology provides patients and care givers real world information about the patient disease status so they can better treat their condition; and it gives researchers a wealth of data in the trial environment to track patient results and identify trends more quickly. Regulators from the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) are paying close attention to the impact of. CGM. In 2012, EMA added strong recommendations to use CGM data for submittals in its diabetes guidance documents, which underscores the growing value of this data.

Until we find something better, CGM and A1c will be the tools that frame diabetes research and treatment for the foreseeable future.