Kinetic Model for Personalized HbA1c Estimation
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Solution Overview
Problem
Existing methods for estimating HbA1c levels, such as eHbA1c, are less reliable due to their reliance on static models and broad assumptions, leading to discrepancies with laboratory HbA1c test results, and are inconvenient for patients requiring frequent blood draws.
Innovation Solution
A kinetic model is developed to calculate a more reliable calculated HbA1c (cHbA1c) by modeling the kinetics of red blood cell glycation, elimination, and generation, using glucose levels and physiological constants like kgly and kage, which are variable for each individual.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a kinetic model with individual-specific physiological parameters is used, then measurement precision of HbA1c estimation is improved, but device complexity increases
Solution Approach 1:
The patent transforms the static model approach into a dynamic one by introducing individual-specific physiological parameters (kgly for glycation rate and kage for elimination rate) that vary between subjects. This parameter customization enables the kinetic model to accurately reflect each person's unique red blood cell behavior, thereby improving HbA1c estimation precision while managing the increased complexity through personalized parameter sets.
2Measurement precision
If frequent blood draws are performed for HbA1c testing, then measurement precision is improved, but loss of time and patient convenience deteriorate
Solution Approach 1:
The patent creates a virtual copy of the HbA1c measurement process by using a kinetic model that calculates HbA1c from continuous glucose monitoring data. This computational model replicates the information obtained from laboratory HbA1c tests without requiring actual blood draws, thereby maintaining measurement precision while completely eliminating the time loss and inconvenience associated with frequent laboratory visits.
3Device complexity
If static models with broad assumptions are used for eHbA1c estimation, then device complexity is reduced, but reliability deteriorates due to discrepancies with laboratory results
Solution Approach 1:
The patent transitions from static models with fixed assumptions to a dynamic kinetic model that incorporates time-dependent processes of red blood cell glycation and elimination. The model uses differential equations to describe the changing concentrations of glycated hemoglobin over time, allowing it to adapt to individual physiological variations and provide reliable HbA1c estimates that match laboratory results.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The kinetic model provides a more accurate and personalized estimation of HbA1c, allowing for better monitoring of glucose levels and diabetes management without the need for frequent blood draws, by deriving individual-specific physiological parameters.
Implementation Method 1
During normal circulation of red blood cells in a mammal such as a human body, glucose molecules attach to hemoglobin, which is referred to as glycosylated hemoglobin (also referred to as glycated hemoglobin).
Data Source
AI summary
Methods, devices, and systems may use a kinetic model to determine physiological parameters related to the kinetics of red blood cell glycation, elimination, and generation. Such physiological parameters can be used, for example, to determine a more reliable calculated HbA1c. In another example, a method may comprise: receiving a plurality of glucose levels over a time period; receiving a glycated hemoglobin (HbA1c) level corresponding to an end of the time period; determining at least one physiological parameter selected from the group consisting of: a red blood cell glycation rate constant (kgly), a red blood cell generation rate constant (kgen), a red blood cell elimination constant (kage), and an apparent glycation constant (K), based on (1) the plurality of glucose levels and (2) the HbA1c level; and adjusting a glucose level target based on the at least one physiological parameter.