Beyond Time in Range
Advancing glycemic risk assessment in diabetes through dynamic interpretation of glucose and insulin data
Limitations of existing metrics
Modern diabetes metrics—such as Time in Range (TIR) and the coefficient of variation (CV)—provide essential summaries of glucose exposure and overall control. However, they do not capture every pattern that may contribute to acute or long-term harm, and many clinically recognised patterns remain insufficiently validated for use in reports, guidelines, or treatment targets. This site presents my independent research into CGM metrics intended to more comprehensively capture such patterns.
Toward a dynamic interpretation
A central premise of my research is that glycemic harm is unlikely to be fully captured by aggregate glucose metrics alone, even when used in combination; risk may depend on the broader dynamic metabolic state arising from interactions between glucose level, rate and direction of change, insulin activity, and recent glycemic history. By starting from clinical observations and individual glucose–insulin traces, the goal is to identify pattern-first hypotheses that can be tested in larger datasets and ultimately translated into practical metrics, thresholds, reference ranges, and visualisations.
About me
I have lived with type 1 diabetes for 14 years. I have a PhD in Engineering Science from the University of Oxford and a background spanning academic research and senior engineering roles in the technology industry, with extensive experience in statistical analysis, modelling, and optimisation. My research on glycemic variability and CGM interpretation has been published in Diabetes Care, Diabetes Technology & Therapeutics, and the Journal of Diabetes Science and Technology.
Contact
Get in touch at robert.richardson.phd@outlook.com for enquiries, collaborations, or feedback.
Robert Richardson 