Invented by Paul V. Goode, Jr., James H. Brauker, Apurv Ullas Kamath, James Patrick Thrower, Dexcom Inc
The demand for analyte sensors has increased due to the need for accurate and real-time monitoring of various substances. For instance, in the healthcare industry, analyte sensors are used to monitor glucose levels in diabetic patients, which helps in managing their condition effectively. Similarly, in the food and beverage industry, analyte sensors are used to monitor the quality and safety of food products.
However, the data generated by these sensors needs to be processed and analyzed to derive meaningful insights. This is where the market for system and methods to process analyte sensor information comes into play. These systems and methods are designed to collect, process, and analyze data generated by analyte sensors.
The market for system and methods to process analyte sensor information is driven by the increasing adoption of analyte sensors across various industries. The healthcare industry is one of the major contributors to this market, as the demand for continuous glucose monitoring systems is increasing. Moreover, the growing awareness about the benefits of real-time monitoring of various substances is also driving the growth of this market.
The market for system and methods to process analyte sensor information is highly competitive, with several players offering a wide range of solutions. Some of the key players in this market include Abbott Laboratories, Dexcom, Inc., Medtronic plc, Roche Diagnostics, and Siemens Healthineers AG.
These players are focusing on developing innovative solutions that can provide accurate and real-time monitoring of various substances. For instance, Abbott Laboratories has developed a continuous glucose monitoring system that can provide real-time glucose readings every five minutes. Similarly, Dexcom, Inc. has developed a wearable sensor that can monitor glucose levels in diabetic patients.
In conclusion, the market for system and methods to process analyte sensor information is expected to grow at a significant rate in the coming years. The increasing adoption of analyte sensors across various industries and the growing demand for real-time monitoring of various substances are the major drivers of this market. The key players in this market are focusing on developing innovative solutions that can provide accurate and real-time monitoring of various substances.
The Dexcom Inc invention works as follows
Systems and methods to process sensor analyte information, including initiating calibration and updating calibration, evaluating clinical acceptance of reference and sensor data, and evaluating quality of sensor calibration. The stability of the sensor is determined by the initial calibration. A calibration set may be used to calibrate the sensor using one or more matched sensors and reference analyte pairs. After evaluating the calibration set, it is possible to update it based on new reference analyte information. Fail-safe mechanisms can be provided based upon clinical acceptance of analyte and reference data, and the quality of sensor calibration. Algorithms allow for the optimization of prospective and retrospective analyses of estimated blood analyte values from an analyte reader.
Background for System and methods to process analyte sensor information
Diabetes mellitus refers to a condition in which the pancreas is unable to produce enough insulin (Type I, insulin dependent), and/or insulin is not effective (Type 2, or non-insulin dependent). High blood sugar can lead to a variety of physiological problems, such as kidney failure, skin injuries, and bleeding into the vitreous. This condition is also known as diabetic. Hypoglycemia (low blood sugar), can be caused by an accidental overdose of insulin or by a normal dose insulin-lowering agent, accompanied by extreme exercise or inadequate food intake.
A self-monitoring glucose monitor (SMBG), is a device that a diabetic wears to monitor their blood sugar levels. This usually involves painful finger pricking. A diabetic will typically only test their glucose levels two to four times per day due to the inconvenience and lack of comfort. These time intervals are too far apart for diabetics to notice, often causing dangerous side effects. It is unlikely that a diabetic will be able to take a timely SMBG measurement. However, they will not be able to determine if their blood glucose level is increasing (higher or lower) based upon conventional methods. This will hinder their ability make informed insulin therapy decisions.
Systems and methods that provide accurate glucose measurements to diabetic patients continuously and/or in real-time are required so they can proactively take care of their condition and avoid hypo- or hyperglycemic events.” Reliable data processing is required to produce accurate and useful output for patients and doctors.
Similarly, systems or methods are required that provide continuous estimates of analyte values for a wide range of analytes (e.g. oxygen, protein, and vitamin) in order to provide retrospective and prospective data analysis to users.
Accordingly, systems are provided to retrospectively or prospectively calibrate a sensor. They also allow for the conversion of sensor data into calibrated data. The updating and maintaining of a calibration over time is possible. It is possible to evaluate received reference and sensor data for clinical acceptanceability and to assess the statistical acceptability of the calibration to ensure safe and accurate data output to a patient.
In a first embodiment, a method for initializing substantially continuous analyte sensors is provided. This includes: receiving a datastream from an analyte scanner, including one or two sensor data points; receiving data from a reference monitor including two or more data points; providing at most two matched data pair by matching sensor data with substantially time corresponding reference analyte data; creating a calibration set that includes the at least two matching pairs; and determining the stability of the continuous sensor.
In accordance with the first embodiment, the method of determining stability of the substantially continuous sensor involves waiting for a predetermined period of time between one minute and six weeks.
In accordance with the first embodiment, the method of determining stability of the substantially continuous sensor involves evaluating at most two data pairs.
In accordance with the first embodiment, the method of determining stability of the substantially continuous sensor includes the evaluation of one of pH, oxygen or hypochlorite and interfering species. The correlation of matched pairs, R value, baseline drift, baseline offset and amplitude are all evaluated.
In accordance with the first embodiment, the method also provides an audible or visual output to the user based upon the stability of the sensor.
In accordance with the first embodiment, the output is based on stability of the sensor. This includes at least one of a numeric estimated and estimated analyte values, a trend in analyte concentration and a graphic representation of an estimated value.
In accordance with the first embodiment, receiving sensor data also includes data from a substantially continuous glucose sensors.
In accordance with the first embodiment, receiving sensor data also includes data from an implantable sugar sensor.
In accordance with the first embodiment, receiving sensor data also includes data from a subcutaneously implantable glucose sensors.
In accordance with the first embodiment, receiving reference data also includes receiving reference from a self-monitoring glucose test.
In accordance with the first embodiment, downloading reference data is a step that includes receiving it via a cabled connection.
In accordance with the first embodiment, receiving reference data involves downloading reference data over a wireless connection.
In accordance with an aspect of the first embodiment the receiving of reference data from a Reference Analyte Monitor includes receiving within the receiver internal communication from the reference analyte Monitor integral to the receiver.
In accordance with the first embodiment, the process of creating a calibration set involves evaluating at most one matched pair of data using inclusion criteria.
In the first embodiment, receiving sensor data means receiving sensor data that has been algorithmically smoothed.
In accordance with the first embodiment, receiving sensor data involves algorithmically smoothing the data.
Click here to view the patent on Google Patents.