Title of Invention

AN APPARATUS FOR MEASURING TISSUE ANALYTE SUCH AS GLUCOSE, IN VIVO

Abstract The invention discloses an apparatus for measuring a tissue analyte such as glucose, in vivo, comprising a first component (1701) configured to generate signals for a noninvasive measurement of said tissue analyte comprising a noninvasive sensor ,a communication interface (1706b) ,a control and processing system (1703), a memory means (1704) and a user interface; a second component (1702), configured to generate signals for an invasive reference measurement of said tissue analyte comprising an invasive analyte monitor such as a glucose monitor, and a communication interface (1706a); said first and second components electromagnetically coupled through a comunication link; and, means for using said reference measurement to optimize calibration of said apparatus in a calibration model comprising: a computer program means for optimizing said calibration, said program means embodied in said memory means; and a processing element configured to execute said program means, wherein said first component is adapted to collect non-invasive signals at an alternative sample site on a body located at a region other than body's fingure tips and toes, wherein said second component is adapted to make invasive measurements at a time corresponding to each of said one or more non-invasive signals from the first component, wherein said calibration model is adapted to control sample site disparity error in calibration of said non-invasive measurement using paired data points for analyte analysis at alternative sample site with substantially identical tissue matrix so that the discrepancy between analyte concentration at said alternative sample site and said alternative reference measurement site is reduced or eliminated.
Full Text AN APPARATUS FOR MEASURING A TISSUE ANALYTE
SUCH AS GLUCOSE, IN VIVO

BACKGROUND OF THE INVENTION
FIELD OF THE INVENTION
The invention relates generally to the calibration and maintenance of glucose
analyzers. More particularly, the invention relates to the use of alternative site
glucose determinations to improve algorithm development, calibration, and/or quality
control of noninvasive or implantable glucose analyzers.
BACKGROUND INFORMATION
Diabetes is a chronic disease that results in improper production and utilization of
insulin, a hormone that facilitates glucose uptake into ceils. While a precise cause of
diabetes is unknown, genetic factors, environmental factors, and obesity appear to
play roles. Diabetics have increased risk in three broad categories; cardiovascular
heart disease, retinopathy, and neuropathy. Diabetics may have one or more of the
following complications: heart disease and stroke, high blood pressure, kidney
disease, neuropathy (nerve disease and amputations), retinopathy, diabetic
ketoacidosis, skin conditions, gum disease, impotence, and fetal complications.
Diabetes is a leading cause of death and disability worldwide. Moreover, diabetes is
merely one among a group of disorders of glucose metabolism that also includes
impaired glucose tolerance, and hyperinsulinemia, or hypoglycemia.

DIABETES PREVALENCE AND TRENDS
Diabetes is an ever more common disease. The World Health Organization (WHO)
estimates that diabetes currently afflicts 154 million people worldwide. There are 54
million people with diabetes living in developed countries. The WHO estimates that
the number of people with diabetes will grow to 300 million by the year 2025. In the
United States, 15.7 million people or 5.9 per cent of the population are estimated to
have diabetes. Within the United States, the prevalence of adults diagnosed with
diabetes increased by six percent in 1999 and rose by 33 percent between 1990 and
1998. This corresponds to approximately eight hundred thousand new cases every
year in America. The estimated total cost to the United States economy alone
exceeds $90 billion per year. Diabetes Statistics. National Institutes of Health,
Publication No. 98-3926, Bethesda, MD (November 1997).
Long-term clinical studies show that the onset of complications can be significantly
reduced through proper control of blood glucose levels. The Diabetes Control and
Complications Trial Research Group, The effect of intensive treatment of diabetes on
the development and progression of long-term complications in insulin-dependent
diabetes mellitus, N Eng J of Med , 329:977-86 (1993); U.K. Prospective Diabetes
Study (UKPDS) Group, Intensive blood-glucose control with sulphonylureas or
insulin compared with conventional treatment and risk of complications in patients
with type 2 diabetes, Lancet. 352:837-853 (1998V. and Y. Ohkubo, H. Kishikawa, E.
Araki, T. Miyata, S. Isami, S. Motoyoshi, Y. Kojima, N. Furuyoshi, M. Shichizi,
Intensive insulin therapy prevents the progression of diabetic microvascular


complications in Japanese patients with non-insulin-dependent diabetes mellitus: a
randomized prospective 6-year study, Diabetes Res Clin Pract. 28:103-117 (1995).
A vital element of diabetes management is the self-monitoring of blood glucose
levels by diabetics in the home environment. However, current monitoring
techniques discourage regular use due to the inconvenient and painful nature of
drawing blood through the skin prior to analysis. The Diabetes Control and
Complication Trial Research Group, supra. As a result, noninvasive measurement of
glucose has been identified as a beneficial development for the management of
diabetes. Implantable glucose analyzers eventually coupled to an insulin delivery
system providing an artificial pancreas are also being pursued.
GLUCOSE MEASUREMENT HISTORY, APPROACHES, AND TECHNOLOGIES
Diabetes treatment has progressed through several stages. The combined
development of insulin therapy and in-home glucose determination led to a radical
improvement in the lives of diabetics. Home glucose determination has also
progressed through its own succession of stages. Urine tests for glucose have given
way to the invasive fingerstick glucose determinations that are more accurate but
somewhat painful, also presenting a possible biohazard. The development of
alternative site glucose determinations has somewhat mitigated the pain aspects, but
may have introduced a new difficulty as a result of temporal and spatial differences
in glucose between the well perfused fingertip and the less well perfused alternative
sites. Additionally, the biohazard issue remains. Current research is focusing on the
development of noninvasive technologies that will totally eliminate the pain


associated with glucose determination and fluid biohazard issues. Finally,
considerable progress has been made in implantable or full-loop systems
incorporating both glucose determination and insulin delivery that will result in the
realization of an artificial pancreas. Blood glucose determination may currently be
categorized into four major types:
• traditional invasive;
• alternative invasive;
• noninvasive; and
• implantable.
Due to the wide use of these modes of measurement and somewhat loose utilization
of terminology in the literature, a detailed summary of the terminology for each mode
of measurement is provided here in order to clarify usage of the terms herein.
In the medical field, the term 'invasive' is customarily applied to surgical methods
and procedures, generally involving at least some trauma or injury to the tissue, such
as cutting, in order to achieve their object. However, in the glucose determination
field, the term 'invasive' is defined relative to noninvasive. 'Noninvasive' clearly
describes methods, invariably signal-based, in which no biological sample or fluid is
taken from the body in order to perform a glucose measurement. 'Invasive' then
means that a biological sample is collected from the body. Invasive glucose
determinations may then be further broken into two separate groups. The first is a
'traditional invasive' method in which a blood sample is collected from the body from
an artery, vein, or capillary bed in the fingertips or toes. The second is an
'alternative invasive' method in which a sample of blood, interstitial fluid, or biological


fluid is drawn from a region other than an artery, vein, or capillary bed in the
fingertips or toes.
1. Traditional Invasive Glucose Determination
There are three major categories of traditional (classic) invasive glucose
determinations. The first two utilize blood drawn with a needle from an artery or
vein, respectively. The third consists of capillary blood obtained via lancet from the
fingertip or toes. Over the past two decades, this has become the most common
method for self-monitoring of blood glucose.
Common technologies are utilized to analyze the blood collected by venous or
arterial draw and finger stick approaches. Glucose analysis includes techniques
such as colorimetric and enzymatic glucose analysis. The most common enzymatic
based glucose analyzers utilize glucose oxidase, which catalyzes the reaction of
glucose with oxygen to form gluconolactone and hydrogen peroxide as shown by
equation 1, infra. Glucose determination includes techniques based upon depletion
of oxygen in the sample either through the changes in sample pH, or through the
formation of hydrogen peroxide. A number of colorimetric and electro-enzymatic
techniques further utilize the reaction products as a starting reagent. For example,
hydrogen peroxide reacts in the presence of platinum to form the hydrogen ion,
oxygen, and current; any of which may be utilized indirectly to determine the glucose
concentration, as in equation 2.



It is noted that a number of alternative site methodologies such as the
THERASENSE FREESTYLE (THERASENSE, INC., Alameda CA) collect blood
samples from regions other than the fingertip or toes. These technologies are not
herein referred to as traditional invasive glucose meters unless the sample is drawn
from the fingertip or toes despite having similar chemical analyses such as the
colorimetric or enzymatic analysis described above. However, the same device
utilized to collect blood via lancet from sample sites consisting of the fingertip or toe
is a traditional invasive glucose analyzer.
2. Alternative Invasive Glucose Determination
There are several alternative invasive methods of determining glucose
concentration. A first group of alternative invasive glucose analyzers have a number
of similarities to the traditional invasive glucose analyzers. One similarity is that
blood samples are acquired with a lancet. Obviously, this form of alternative
invasive glucose determination while unsuitable for analysis of venous or arterial
blood, may be utilized to collect capillary blood samples. A second similarity is that
the blood sample is analyzed using chemical analyses that resemble the colorimetric
and enzymatic analyses describe above. The primary difference, however, is that in
an alternative invasive glucose determination the blood sample is not collected from
the fingertip or toes. For example, according to package labeling, the
THERASENSE FREESTYLE meter may be utilized to collect and analyze blood from
the forearm. This is an alternative invasive glucose determination due to the location
of the lancet draw. In this first group of alternative invasive methods based upon


blood draws with a lancet, a primary difference between the alternative invasive and
traditional invasive glucose determination is the location of the site of blood
acquisition from the body. Additional differences include factors such as the gauge
of the lancet, the depth of penetration of the lancet, timing issues, the volume of
blood acquired, and environmental factors such as the partial pressure of oxygen,
altitude, and temperature. This form of alternative invasive glucose determination
includes samples collected from the palmar region, base of thumb, forearm, upper
arm, head, earlobe, torso, abdominal region, thigh, calf, and plantar region.
A second group of alternative invasive glucose analyzers is distinguished by their
mode of sample acquisition. This group of glucose analyzers has a common
characteristic of acquiring a biological sample from the body or modifying the surface
of the skin to gather a sample without utilization of a lancet for subsequent analysis.
For example, a laser poration based glucose analyzer utilizes a burst or stream of
photons to create a small hole in the skin surface. A sample of substantially
interstitial fluid collects in the resulting hole. Subsequent analysis of the sample for
glucose constitutes an alternative invasive glucose analysis, whether or not the
sample was actually removed from the created hole. A second common
characteristic is that a device and algorithm are utilized to determine glucose from
the sample. Herein, the term alternative invasive includes techniques that analyze
biosamples such as interstitial fluid, whole blood, mixtures of interstitial fluid and
whole blood, and selectively sampled interstitial fluid. An example of selectively
sampled interstitial fluid is collected fluid in which large or less mobile constituents
are not fully represented in the resulting sample. For this second group of alternative
invasive glucose analyzers sampling sites include: the hand, fingertips, palmar


region, base of thumb, forearm, upper arm, head, earlobe, eye, chest, torso,
abdominal region, thigh, calf, foot, plantar region, and toes. A number of
methodologies exist for the collection of samples for alternative invasive
measurements including:
• Laser poration: In these systems, photons of one or more wavelengths are
applied to skin creating a small hole in the skin barrier. This allows small
volumes of interstitial fluid to become available for a number of sampling
techniques;
• Applied current: In these systems, a small electrical current is applied to the
skin allowing interstitial fluid to permeate through the skin;
• Suction: In these systems, a partial vacuum is applied to a local area on the
surface of the skin. Interstitial fluid permeates the skin and is collected.
In all of the above techniques, the analyzed sample is interstitial fluid. However,
some of these same techniques can be applied to the skin in a fashion that draws
blood. For example, the laser poration method can result in blood droplets. As
described herein, any technique that draws biosamples from the skin without the use
of a lancet on the fingertip or toes is referred to as an alternative invasive technique.
In addition, it is recognized that the alternative invasive systems each use different
sampling approaches that lead to different subsets of the interstitial fluid being
collected. For example, large proteins might lag behind in the skin while smaller,
more diffusive, elements may be preferentially sampled. This leads to samples
being collected with varying analyte and interferent concentrations. Another
example is that a mixture of whole blood and interstitial fluid may be collected.
These techniques may be utilized in combination. For example the SOFT-TACT,


also known as the SOFTSENSE (ABBOT LABORATORIES. INC. Abbot Park ID.
applies suction to the skin followed by a lancet stick. Despite the differences in
sampling, these techniques are referred to as alternative invasive techniques
sampling interstitial fluid.
The literature occasionally refers to the alternative invasive technique as an
alternative site glucose determination or as a minimally invasive technique. The
minimally invasive nomenclature derives from the method by which the sample is
collected. As described herein, the alternative site glucose determinations that draw
i
blood or interstitial fluid, even _ microliter, are considered to be alternative invasive
glucose determination techniques as defined above. Examples of alternative
invasive techniques include the THERASENSE FREESTYLE when not sampling
fingertips or toes, the GLUCOWATCH (CYGNUS, INC., Redwood City CA) the ONE
TOUCH ULTRA (LIFESCAN, INC., Milpitas CA), and equivalent technologies.
A wide range of technologies serve to analyze biosamples collected with alternative
invasive techniques. The most common of these technologies are:
• Conventional: With some modification, the interstitial fluid samples may be
analyzed by most of the technologies utilized to determine glucose
concentrations in serum, plasma, or whole blood. These include
electrochemical, electroenzymatic, and colorimetric approaches. For
example, the enzymatic and colorimetric approaches described above may
also be used to determine the glucose concentration in interstitial fluid
samples;


• Spectrophotometries A number of approaches for determining the glucose
concentration in biosamples, have been developed that utilize
spectrophotometry technologies. These techniques include: Raman and
fluorescence, as well as techniques using light from the ultraviolet through the
infrared [ultraviolet (200 to 400 nm), visible (400 to 700 nm), near-IR (700 to
2500 nm or 14,286 to 4000 cm1), and infrared (2500 to 14,285 nm or 4000 to
700 cm'1)].
As used herein, the term invasive glucose analyzer encompasses both traditional
invasive glucose analyzers and alternative invasive glucose analyzers.
3. Noninvasive Glucose Determination
There exist a number of noninvasive approaches for glucose determination. These
approaches vary widely, but have at least two common steps. First, an apparatus is
utilized to acquire a signal from the body without obtaining a biological sample.
Second, an algorithm is utilized to convert this signal into a glucose determination.
One type of noninvasive glucose determination is based upon spectra. Typically, a
noninvasive apparatus utilizes some form of spectroscopy to acquire the signal or
spectrum from the body. Utilized spectroscopic techniques include, but are not
limited to: Raman and fluorescence, as well as techniques using light from ultraviolet
through the infrared [ultraviolet (200 to 400 nm), visible (400 to 700 nm), near-IR
(700 to 2500 nm or 14,286 to 4000 cm'1), and infrared (2500 to 14,285 nm or 4000 to
700 cm'1)]. A particular range for noninvasive glucose determination in diffuse
reflectance mode is about 1100 to 2500 nm or ranges therein. K. Hazen, Glucose
Determination in Biological Matrices Using Near-Infrared Spectroscopy, doctoral


dissertation, University of Iowa (1995). It is important to note that these techniques
are distinct from the traditional invasive and alternative invasive techniques listed
above in that the sample interrogated is a portion of the human body in-situ, not a
biological sample acquired from the human body.
Typically, three modes are utilized to collect noninvasive scans: transmittance,
transfleqtance, and/or diffuse reflectance. For example the signal collected, typically
consisting of light or a spectrum, may be transmitting through a region of the body
such as a fingertip, diffusely reflected, or transflected. Transflected here refers to
collection of the signal not at the incident point or area (diffuse reflectance), and not
at the opposite side of the sample (transmittance), but rather at some point on the
body between the transmitted and diffuse reflectance collection area. For example,
transflected light enters the fingertip or forearm in one region and exits in another
region typically 0.2 to 5 mm or more away depending on the wavelength utilized.
Thus, light that is strongly absorbed by the body such as light near water absorbance
maxima at 1450 or 1950 nm would need to be collected after a small radial
divergence and light that is less absorbed such as light near water absorbance
minima at 1300,1600, or 2250 nm may be collected at greater radial or transflected
distances from the incident photons.
Noninvasive techniques are not limited to using the fingertip as a measurement site.
Alternative sites for taking noninvasive measurements include: a hand, finger,
palmar region, base of thumb, forearm, volar aspect of the forearm, dorsal aspect of
the forearm, upper arm, head, earlobe, eye, tongue, chest, torso, abdominal region,
thigh, calf, foot, plantar region, and toe. It is important to note that noninvasive


techniques do not have to be based upon spectroscopy. For example, a
bioimpedence meter would be considered a noninvasive device. Within the context
of the invention, any device that reads a signal from the body without penetrating the
skin and collecting a biological sample is referred to as a noninvasive glucose
analyzer. For example, a bioimpedence meter is a noninvasive device.
An alternative reference method is a reference determination made at a location on
the body not including the fingertips and toes. An alternative reference includes both
an alternative invasive measurement and an alternative site noninvasive
measurement. Hence, an alternative site noninvasive measurement is a noninvasive
measurement made at physiological sites excluding the fingertips and toes.
4. Implantable Sensor for Glucose Determination
There exist a number of approaches for implanting a glucose sensor into the body
for glucose determination. These implantables may be utilized to collect a sample
for further analysis or may acquire a reading or signal from the sample directly or
indirectly. Two categories of implantable glucose analyzers exist: short-term and
long-term.
As referred to herein, a device or a collection apparatus is at least a short-term
implantable (as opposed to a long-term implantable) if part of the device penetrates
the skin for a period of greater than 3 hours and less than one month. For example,
a wick placed subcutaneously to collect a sample overnight that is removed and
analyzed for glucose content representative of the interstitial fluid glucose
concentration is referred to as a short term implantable. Similarly, a biosensor or


electrode placed under the skin for a period of greater than three hours that reads a
signal indicative of a glucose concentration or level, directly or indirectly is referred to
as at least a short-term implantable device. Conversely, devices described above
based upon techniques like a lancet, applied current, laser poration, or suction are
referred to as either a traditional invasive or alternative invasive technique as they do
not fulfill both the three hour and skin penetration parameters. As described herein,
long-term, implantables are distinguished from short-term implantables by having the
criteria that they must both penetrate the skin and be utilized for a period of one
month or longer. Long term implantables may remain in the body for many years.
Implantable glucose analyzers vary widely, but have at least several features in
common. First, at least part of the device penetrates the skin. More commonly, the
entire device is imbedded into the body. Second, the apparatus is utilized to acquire
either a sample of the body or a signal relating directly or indirectly to the glucose
concentration within the body. If the implantable device collects a sample, readings
or measurements on the sample may be collected after removal from the body.
Alternatively, readings or signals may be transmitted from within the body by the
device or utilized for such purposes as insulin delivery while in the body. Third, an
algorithm is utilized to convert the signals into readings directly or indirectly related to
the glucose concentration. An implantable analyzer may read signals from one or
more of a variety of body fluids or tissues including but not limited to: arterial blood,
venous blood, capillary blood, interstitial fluid, and selectively sampled interstitial
fluid. An implantable analyzer may also collect glucose information from skin tissue,
cerebral spinal fluid, organ tissue, or through an artery or vein. For example, an
implantable glucose analyzer may be placed transcutaneously, in the peritoneal


cavity, in an artery, in muscle, or in an organ such as the liver or brain. The
implantable glucose sensor may be one component of an artificial pancreas.
Examples of implantable glucose monitors follow. One example of a CGMS
(continuous glucose monitoring system) is a group of glucose monitors based upon
open-flow microperfusion. Z. Trajanowski, G. Brunner, L Schaupp, M. Ellmerer, P.
Wach, T-Pieber, P. Kotanko, F. Skrabai, Open-flow microperfusion of subcutaneous
adipose tissue for on-line continuous ex vivo measurement of glucose concentration,
Diabetes Care, 20:1114-1120 (1997). Another example utilizes implanted sensors
that comprise biosensors and amperometric sensors. Z. Trajanowski, P. Wach, R.
Gfrerer, Portable device for continuous fractionated blood sampling and continuous
ex vivo blood glucose monitoring, Biosensors and Bioelectronics, 11:479-487 (1996).
Another example is the MINIMED CGMS (MEDTRONIC, INC., Minneapolis MN).
DESCRIPTION OF RELATED TECHNOLOGY
GLUCOSE CONCENTRATION MEASURED AT FINGERTIP VS. ALTERNATIVE
SAMPLING LOCATIONS
Many authors claim that alternative site glucose concentrations are equivalent to
fingerstick glucose determination. A number of examples are summarized below:
Szuts, et al. conclude that measurable physiological differences in glucose
concentration between the arm and fingertip could be determined, but that these
differences were found to be clinically insignificant even in those subjects in whom
they were measured. E. Szuts, J. Lock, K. Malomo, A. Anagnostopoulos, Althea,


Blood glucose concentrations of arm and finger during dynamic glucose conditions,
Diabetes Technology & Therapeutics, 4:3-11 (2002).
Lee, et al concluded that patients testing two hours postprandial could expect to see
small differences between their forearm and fingertip glucose concentrations. D.
Lee, S. Weinert, E. Miller, A study of forearm versus finger stick glucose monitoring,
Diabetes Technology & Therapeutics, 4:13-23 (2002).
Bennion, et al. concluded that there is no significant difference in HbA,C
measurements for patients utilizing alternative site meters off of the fingertip and
traditional glucose analyzers on the fingertip. N. Bennion, N. Christensen, G.
McGarraugh, Alternate site glucose testing: a crossover design, Diabetes
Technology & Therapeutics, 4:25-33 (2002). This is an indirect indication that the
forearm and fingertip glucose concentrations are the same, though many additional
factors such as pain and frequency of testing will impact the study.
Peled, et al. concluded that glucose monitoring of blood samples from the forearm is
suitable when expecting steady state glycemic conditions and that the palm samples
produced a close correlation with fingertip glucose determinations under all glycemic
states. N. Peled, D. Wong, S. Gwalani, Comparison of glucose levels in capillary
blood samples from a variety of body sites, Diabetes Technology & Therapeutics,
4:35-44 (2002).
Based upon a study utilizing fast acting insulin injected intravenously, Jungheim, et
al. suggested that to avoid risky delays in hyperglycemia and hypoglycemia


detection, monitoring at the arm should be limited to situations in which ongoing
rapid changes in the blood glucose concentration can be excluded. K. Jungheim, T.
Koschinsky, Glucose monitoring at the arm, Diabetes Care, 25:956-960 (2002); and
K. Jungheim; T. Koschinsky, Risky delay of hypoglycemia detection by glucose
monitoring at the arm, Diabetes Care, 24:1303-1304 (2001). The use of intravenous
insulin in this study was criticized as creating physiological extremes that influence
the observed differences. G. McGarraugh, Response to Jungheim and Koschinsky,
Diabetes Care, 24:1304:1306 (2001).
Equilibration Approaches
While there exist multiple reports that glucose concentrations are very similar when
collected from the fingertip or alternative locations, a number of sampling
approaches have been recommended to increase localized perfusion at the sample
site to equilibrate the values just prior to sampling. Several of these approaches are
summarized below:
Pressure: One sampling methodology requires rubbing or applying pressure to the
sampling site in order to increase localized perfusion prior to obtaining a sample via
lancet. An example of this is the FREESTYLE blood glucose analyzer
(THERASENSE, INC., supra). G. McGarraugh, S. Schwartz, R. Weinstein, Glucose
Measurements Using Blood Extracted from the Forearm and the Finger,
THERASENSE, INC., ART01022 Rev. C (2001); and G. McGarraugh, D. Price, S.
Schwartz, R. Weinstein, Physiological influences on off-finger glucose testing,
Diabetes Technology & Therapeutics, 3:367-376 (2001).


Heating: Heat applied to the localized sample site has been proposed as a
mechanism for equalizing the concentration between the vascular system and skin
tissue. This may be to dilate the capillaries allowing more blood flow, which leads'
towards equalization of the venous and capillary glucose concentrations.
Alternatively, vasodilating agents such as nicotinic acid, methyl nicotinamide,
minoxidil, nitroglycerin, histamine, capsaicin, or menthol can be utilized to increase
local blood flow. M. Rohrscheib, C. Gardner, M. Robinson, Method and apparatus
for noninvasive blood analyte measurement with fluid compartment equilibration,
U.S. Patent No. 6,240,306 (May 29,2001).
Vacuum: Applying a partial vacuum to the skin at and around the sampling site prior
to sample collection has also been utilized. A localized deformation in the skin may
allow superficial capillaries to fill more completely. T. Ryan, A study of the epidermal
capillary unit in psoriasis, Dermatologica, 138:459-472 (1969). For example, ABBOT
LABORATORIES, INC. utilizes a vacuum device at one-half atmosphere that pulls
the skin up 3.5 mm into their device. ABBOT maintains this deformation results in
increased perfusion that equalizes the glucose concentration between the alternative
site and the fingertip. R. Ng, Presentation to the FDA at the Clinical Chemistry &
Clinical Toxicotogy Devices Panel Meeting, Gaithersburg MD (October 29, 2001).
Calibration:

Glucose analyzers require calibration. This is true for all types of glucose analyzers
such as traditional invasive, alternative invasive, noninvasive, and implantable
analyzers. One fact associated with noninvasive glucose analyzers is the fact that
they are secondary in nature, that is, they do not measure blood glucose levels
directly. This means that a primary method is required to calibrate these devices to
measure blood glucose levels properly. Many methods of calibration exist.
Calibration of Traditional Invasive Glucose Analyzers:
Glucose meters or analyzers may be calibrated off of biological samples such as
whole blood, serum, plasmas, or modified solutions of these samples. In addition,
glucose analyzers may be calibrated with a range of whole blood samples, modified
whole blood samples, blood simulants, phantoms, or a range of chemically prepared
standards. Typically, these samples have glucose concentrations that span the
desired functionality range of the glucose analyzer. For glucose analyzers, this is
approximately 70 to 400 mg/dL Some go further into the hypoglycemic range, down
to 40 or even 0 mg/dL, while some go well into the hyperglycemic range, up to 700
or 1000 mg/dL
Calibration of Alternative Invasive Glucose Analyzers:
Alternative invasive glucose analyzers utilize many of the invasive glucose
calibration procedures. When calibrating the alternative invasive glucose meters that
utilize biological fluids such as blood or interstitial fluid as a reference, relatively
minor modifications to the traditional calibration approaches may be required.
Calibration of Noninvasive Glucose Analyzers:

One noninvasive technology, near-infrared spectroscopy, provides the opportunity
for both frequent and painless noninvasive measurement of glucose. This approach
involves the illumination of a spot on the body with near-infrared (NIR)
electromagnetic radiation, light in the wavelength range 700 to 2500 nm. The light is
partially absorbed and scattered, according to its interaction with the constituents of
the tissue. The actual tissue volume that is sampled is the portion of irradiated
tissue from which light is transflected or diffusely transmitted to the spectrometer
detection system. With near-infrared spectroscopy, a mathematical relationship
between an in vivo near-infrared measurement and the actual blood glucose value
needs to be developed. This is achieved through the collection of in vivo NIR
measurements with corresponding blood glucose values that have been obtained
directly through the use of measurement tools like the HEMOCUE (YSI
INCORPORATED, Yellow Springs OH), or any appropriate and accurate traditional
invasive reference device.
For spectrophotometric based analyzers, there are several univariate and
multivariate methods that can be used to develop the mathematical relationship
between the measured signal and the actual blood glucose value. However, the
basic equation being solved is known as the Beer-Lambert Law. This law states that
the strength of an absorbance/reflectance measurement is proportional to the
concentration of the analyte which is being measured, as in equation 3,


where A is the absorbance/reflectance measurement at a given wavelength of light, ε
is the molar absorptivity associated with the molecule of interest at the same given
wavelength, b is the distance that the light travels, and C is the concentration of the
molecule of interest (glucose).
Chemometric calibration techniques extract the glucose signal from the measured
spectrum through various methods of signal processing and calibration including one
or more mathematical models. The models are still developed through the process
of calibration on the basis of an exemplary set of spectral measurements known as
the calibration set and associated set of reference blood glucose values based upon
an analysis of fingertip capillary blood or venous blood. Common multivariate
approaches requiring an exemplary reference glucose concentration vector for each
sample spectrum in a calibration include partial least squares (PLS) and principal
component regression (PCR). Many additional forms of calibration are known, such
as neural networks.
Because every method has error, it is desirable that the primary device used to
measure blood glucose be as accurate as possible to minimize the error that
propagates through the mathematical relationship developed. While it appears
reasonable to assume that any FDA-approved blood glucose monitor should be
suitable, for accurate verification of the secondary method, a monitor having a
percentage error of less than 5 percent is desirable. Meters with increased
percentage error such as 10 percent may also be acceptable, though the error of the
device being calibrated may increase.

Although the above is well-understood, one aspect that is forgotten is that secondary
methods require constant verification that they are providing consistent and accurate
measurements when compared to the primary method. This means that a method
for checking blood glucose values directly and comparing those values with the
given secondary method is required. Such monitoring is manifested in quality
assurance and quality control programs. Bias adjustments are often made to a
calibration. In some cases the most appropriate calibration is selected based upon
these secondary methods. S. Malin, T. Ruchti, Intelligent system for noninvasive
blood analyte prediction, U.S. Patent No. 6,280,381 (August 28, 2001). This
approach is also known as validation.
The Problem;
Calibration of a noninvasive glucose analyzer entails some complications not
observed in traditional invasive glucose analyzers. For example, spectroscopic or
spectrophotometric based noninvasive glucose analyzers probe a sample that is not
entirely whole blood or interstitial fluid. Photons penetrate into the body, interact with
body layers and/or tissues and are detected upon reemerging from the body.
Hence, many possible interferences exist that do not exist in a prepared reference or
calibration sample. In addition, the interferences and matrices encountered are part
of a living being and hence are dynamic in nature. For these reasons, indirect
calibration is often attempted with traditional invasive reference glucose
determinations collected from the fingertip. This approach, however, introduces
errors into the noninvasive analyzer that are associated with sampling the reference
glucose concentration. One key source of error is the difference between glucose
concentrations at the site tested by the noninvasive glucose analyzer and the


reference site sampled with an invasive technology. Thus, it would be an important
advance in the art to provide methods for calibrating and maintaining signal-based
analyzers that addressed the negative effect on their accuracy and precision that
results from calibrating them based on invasive reference samples taken at sites
distant from the site of noninvasive sampling.
SUMMARY OF THE INVENTION
The invention provides methods for utilizing either alternative invasive glucose
determinations or alternative site noninvasive glucose determinations for calibrating
noninvasive or implantable glucose analyzers. Use of an alternative invasive or
alternative site noninvasive glucose determination in the calibration allows for
minimization of errors built into the glucose analyzer model, including errors due to
sampling, methodology, and error due to temporal and spatial variation of glucose
concentration within the subject's body. In addition, the method provides conversion
of glucose concentrations determined from noninvasive or alternative reference
determinations into traditional invasive glucose determinations. As described herein,
the use of an alternative invasive or noninvasive glucose determination for
calibration is also understood to include their utilization for glucose determination,
prediction, calibration transfer, calibration maintenance, quality control, and quality
assurance.
The use of alternative invasive or alternative site noninvasive reference
determinations provides a means for calibrating on the basis of glucose


determinations that reflect the matrix observed and the variable measured by the
analyzer more closely. Statistical correlations between noninvasive and alternative
invasive glucose determinations and traditional invasive glucose determinations may
then be utilized to adjust alternative site noninvasive or alternative invasive glucose
concentrations to traditional invasive glucose concentrations. The invention also
provides an apparatus in which a invasive stick meter is coupled to a noninvasive
glucose, analyzer for calibration, validation, adaptation, and safety check of the
calibration model embodied in the noninvasive analyzer.

BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 provides a plot of glucose measurements that demonstrates large
differences in glucose concentration between the fingertip and forearm according to
the invention;
Figure 2 provides a plot of glucose measurements that demonstrates a lag in
glucose concentrations determined from the forearm compared to the fingertip
according to the invention;
Figure 3 shows a plot of fingertip and forearm glucose concentrations that are well
correlated;
Figure 4 illustrates a plot that demonstrates historesis in glucose concentration
profiles resulting in differences in glucose concentration between the fingertip and


forearm even when glucose concentrations are at a local minimum with respect to
time according to the invention;
Figure 5 provides a plot of forearm glucose concentrations against corresponding
fingertip glucose concentrations with a relatively large error according to the
invention;
Figure 6 provides a plot of forearm glucose concentrations against corresponding
contralateral forearm glucose concentrations with a smaller error when compared to
Figure 5, according to the invention;
Figure 7 shows a block diagram of a noninvasive analyzer using alternative site
glucose determinations calibration and maintenance according to the invention;
Figure 8 shows a plot of predicted glucose concentrations versus reference forearm
glucose determinations according to the invention;
Figure 9 provides a plot of predicted glucose concentration versus traditional
invasive reference glucose concentrations;
Figure 10 provides a histogram demonstrating a statistical difference in the
histogram shift of predicted glucose concentrations versus fingertip and forearm
reference concentrations according to the invention;

Figure 11 provides a histogram demonstrating a statistical difference in the
histogram magnitude of predicted glucose concentrations versus fingertip and
forearm reference concentrations according to the invention;
Figure 12 provides a plot of subjects demonstrating dampened and lagged glucose
predictions versus traditional invasive reference glucose concentrations according to
the invention;
Figure 13 illustrates a concentration correlation plot of the series of subjects with
dampened and lagged glucose predictions versus traditional invasive reference
glucose concentrations according to the invention;
Figure 14 shows a plot of lag and magnitude adjusted glucose predictions overlaid
with traditional invasive glucose determinations according to the invention;
Figure 15 provides a concentration correlation plot of the lag and magnitude adjusted
glucose predictions versus traditional invasive reference glucose concentrations
according to the invention;
Figure 16 shows an algorithm-adjusted concentration correlation plot of predicted
glucose concentration versus traditional reference glucose concentrations according
to the invention; and

Figure 17 shows a block diagram of an apparatus including a noninvasive glucose
analyzer coupled with an invasive (traditional or alternative) glucose monitor
according to the invention.
DETAILED DESCRIPTION
The present invention reduces the error in the reference glucose concentration for
the calibration of glucose sensors and therefore leads to a more accurate, precise,
and robust glucose measurement system.
DIFFERENCE IN TRADITIONAL INVASIVE AND ALTERNATIVE INVASIVE
GLUCOSE CONCENTRATION
Initially, differences between traditional invasive and alternative invasive glucose
determinations are demonstrated. It is demonstrated here that the differences
between the alternative invasive glucose concentration from a site such as the
forearm and the glucose concentration from a traditional invasive fingerstick vary as
a function of at least time and location. Additional parameters include sampling
methodology, physiology, and glucose-analyzer instrumentation.
EXAMPLE #1
In a first example, variation of glucose concentration at locations in the body is
demonstrated at fixed points in time. A total of twenty diabetic subjects were run
through one of two glucose profiles each having two peaks so that the resulting


curves formed the shape of an 'M,' shown in part in Figure 1, over a period of eight
hours. Thus, glucose concentration started low at around 80 mg/dL, was increased
to approximately 350 mg/dL, and was brought back to about 80 mg/dL in a period of
about four hours. The cycle was immediately repeated to form an 'M'-shaped
glucose concentration profile. These profiles were alternately generated with intake
of a liquid form of carbohydrate (50 -100 g) or intake of a solid form of carbohydrate
(50 - 100g) in combination with insulin to generate the two excursions of the 'M'
profile. Traditional invasive fingertip capillary glucose concentrations were
determined every 15 minutes throughout the 8-hour period. Each fingertip
' determination was immediately followed by an alternative invasive capillary glucose
determinations wherein samples were collected from the volar aspect of the subject's
right and then left forearms. The resulting data set included 1920 data points (20
subjects * 3 sites/15 minutes * 32 draws/day). J. Fischer, K. Hazen, M. Welch, L.
Hockersmith, J. Coates, Comparisons of capillary blood glucose concentrations from
the fingertips and the volar aspects of the left and right forearms, American Diabetes
Association, 62nd Annual Meeting, (June 14, 2002). The 'M'-shaped profiles
described above may be induced according to procedures previously set forth in L.
Hockersmith, A method of producing a glycemic profile of predetermined shape in a
test subject, U.S. Patent Application Ser. No. 09/766,427 (January 18, 2001), the
entirety of which is hereby incorporated by reference as if fully set forth herein.
Four partial 'M' profiles from the above study are presented here. In Figure 1,
alternative invasive glucose concentrations measured at the forearm are
demonstrated to have both a dampened and a lagged profile versus the traditional
invasive fingertip glucose concentrations. For this individual, when the glucose


concentration was rising the forearm glucose concentrations are observed to be
substantially dampened, that is lower than the corresponding fingertip glucose
concentration. For example, at the 90 minute mark the fingertip glucose
concentration of 234 mg/dL is more than 100 mg/dL higher than either the left or
right forearm glucose concentration of 123 and 114 mg/dL, respectively. In addition,
the peak glucose concentration observed at the fingertip of 295 mg/dL is both larger
and occurred 30 minutes earlier than the peak forearm glucose concentration of 259
mg/dL. Finally, the forearm glucose concentrations have a small lag versus the
fingertip glucose concentrations. Figure 2 presents another glucose profile in which
many of the same effects just described are observed but to a lesser degree. For
example, the rising glucose concentrations of the alternative invasive forearm
glucose concentrations are still less than those of the traditional invasive fingertip
glucose concentrations, but the difference is smaller. A dampening and lag of the
alternative invasive peak are still observed. One measure of dampening is the range
of traditional invasive glucose concentrations minus the range of alternative invasive
glucose concentrations. In addition, the lag is more pronounced than in the previous
figure. Figure 3 demonstrates another example in which the forearm glucose
concentrations closely track those of the fingertip glucose concentrations. Finally,
Figure 4 demonstrates a historesis effect as a subject moves through subsequent
glucose excursions. That is, a lag observed in a forearm may still be observed at a
later time. In this case, dampening of the forearm glucose concentration is observed
at a glucose minimum relative to that of the fingertip glucose concentration. The
effects observed above are representative as a whole of the glucose profiles
observed in the study outlined above.


As in Figure 5, alternative invasive glucose determinations collected from the volar
aspect of each subject's left and right forearm are plotted against the time-
associated traditional invasive fingertip reference glucose concentration for all
subjects in a concentration correlation plot overlaid with a Clarke error grid. The
standard error of the forearm glucose concentrations versus the fingertip glucose
concentration is relatively large at 37.7 mg/dL with an F-value of 4.43. The best fit of
the data-yields a slope of 0.76 and an intercept of 41.4 mg/dL. This is consistent
with dampened and delayed forearm glucose profiles relative to the fingertip and
results in only 73.8% of the points falling in the 'A' region of the Clarke error grid.
The glucose determinations collected from the volar aspect of each subject's left and
right forearm are plotted against each other for all subjects on a Clarke error grid in
i
Figure 6. The standard error of the left forearm glucose concentrations versus the
right forearm glucose concentration is reduced to 17.2 mg/dL with an F-value of
16.0. The best fit of the data yields a slope of 0.96 and an intercept of 8.3 mg/dL.
This is consistent with a reduction in the dampening and delay of left forearm
glucose profiles relative to the right forearm glucose concentrations and results in
95.8 percent of the points falling in the 'A' region of the Clarke error grid. A slope of
0.96, combined with the low standard error, indicates that the capillary blood glucose
values of the left and right volar forearm would be similar.
These data suggest several conclusions:
• during a glucose excursion, substantial differences are often observed
between the capillary blood glucose of the untreated forearm and the fingertip;


• fast changes in blood glucose concentration magnify differences between the
measured blood glucose concentration of the fingertip and forearm while the
relative errors are proportional to the glucose concentration;
• during periods of rapid change in blood glucose concentration, differences
between the forearm and fingertip give rise to a higher percentage of points in
less desirable regions of the Clarke error grid;
• the measured blood glucose concentrations of the volar aspect of the left and
right forearms appear similar; and
• finally, these findings are consistent with the phenomenon of decreased
perfusion into the forearm versus that of the fingertip, leading to a dampening
and/or lag in the glucose profile.
These conclusions are consistent with those reported in the circulatory physiology
literature and that relating to sampling approaches of alternative invasive glucose
analyzers. It has been reported that blood flow in the fingers is 33±10 mL/g/min at
20°C while in the leg, forearm, and abdomen the blood flow is 4-6 mL/g/min at 19-
22°C. V. Harvey, Sparks, skin and muscle, in: Peripheral Circulation. P. Johnson,
ed., p.198, New York (1978). This is consistent with the observed differences in
localized blood glucose concentration. When glucose concentrations vary rapidly a
difference develops throughout the body in local blood glucose concentrations as a
result of differences in local tissue perfusion. For example, the blood flow in the
fingers of the hand is greater than in alternative sites. This means that the blood
glucose in the fingertips will equilibrate more rapidly with venous blood glucose
concentrations. Furthermore, the magnitude of differences in local glucose
concentrations between two sites is related to the rate of change in blood glucose


concentrations. Conversely, under steady-state glucose conditions, the glucose
concentration through-out the body tends to be uniform.
An additional study demonstrated that localized variations in the glucose
concentration in the dorsal versus volar aspect of the forearm are small versus
differences between the glucose concentrations observed in either forearm region
versus that of the fingertip. J. Fischer, K. Hazen, M. Welch, L. Hockersmith, R
Guttridge, T. Ruchti, physiological differences between volar and dorsal capillary
forearm glucose concentrations and finger stick glucose concentrations in diabetics,
American Diabetes Association, 62nd Annual Meeting (June 14,2002).
Another study demonstrated very small localized variation in glucose concentration
within a region such as the dorsal aspect of the forearm with observed differences
approximating the scale of the error observed in the reference method. The glucose
concentrations in the forearm are not observed to vary within three inches laterally or
axially from a central point of the forearm.
In addition to differences in perfusion, the local permeability of tissue to diffusion and
the local uptake of glucose during exercise or other activity can cause non-uniform
distribution of glucose in the body. Finally, when the noninvasive variable and the
reference glucose concentration are not measured simultaneously, an additional
error can occur when glucose is varying in the body.
Physiology
The following physiological interpretations are deduced from these studies:

• during times of glucose change, the glucose concentration as measured on
the arm can lag behind that of the fingertip;
• a well-recognized difference between the fingertip and the forearm is the rate
of blood flow;
• differences in circulatory physiology of the off-finger test sites may lead to
differences in the measured blood glucose concentration;
• on average, the arm and finger glucose concentrations are approximately the
same, but the correlation is not one-to-one. This suggests differences
between traditional invasive glucose concentrations and alternative invasive
glucose concentrations are different during time periods of fasting and after
glucose ingestion;
• the relationship of forearm and thigh glucose levels to finger glucose is
affected by proximity to a meal. Meter forearm and thigh results during the
sixty and ninety minute postprandial testing sessions are consistently lower
than the corresponding finger results;
• differences are inversely related to the direction of blood glucose
concentration change;
• rapid changes may produce significant differences in blood glucose
concentrations measured at the fingertip and forearm; and
• for individuals, the relationship between forearm and finger blood glucose may
be consistent. However, the magnitude of the day-to-day differences has
been found to vary. Finally, interstitial fluid (ISF) may lead plasma glucose
concentration in the case of falling glucose levels due to exercise or glucose
uptake due to insulin.


Utilization of the Difference in Traditional Invasive and Alternative Invasive Glucose
Concentration
The discrepancy between the glucose level at the non-invasive measurement site
versus the reference concentration presents a fundamental issue in relation to
calibration. A calibration is generally a mathematical model or curve that is used to
convert the noninvasively measured variable such as absorbance, voltage, or
intensity to an estimate of the glucose concentration. Determination of the
calibration is performed on the basis of a set of paired data points composed of
noninvasive variables and associated reference blood glucose concentrations
collected through a blood draw. Any error introduced by the reference method is
propagated into any error associated with the indirect method as an uncertain,
imprecise, and/or biased calibration.
Method
The invention provides a method of developing a calibration based on either
traditional or alternate invasive reference glucose measurements. The percentage
error in the reference glucose concentration is reduced through the application of
one or more techniques that improve correspondence between the reference
glucose concentration and the glucose concentration reflected in the variable
measured by the sensor, herein referred to as the "sensor variable", thus producing
a superior exemplary set of calibration data for calculating the calibration curve or
model. Both noninvasive and implantable glucose analyzers require a calibration
because they rely on measurement of glucose indirectly from a blood or tissue
property, fluid, parameter, or variable. While the target application is typically an


optical sensor, any device that measures glucose through a calibration falls within
the scope of the invention. Examples of such systems include:
• near-infrared spectroscopy (700-2500 nm), O. Khalil, Spectroscopic and
clinical aspects of non-invasive glucose measurements," Clin Chem, 45:165-
77(1999);
• far-infrared spectroscopy;
• mid-infrared spectroscopy;
• Raman spectroscopy;
• fluorescence spectroscopy;
• spectroscillating thermal gradient spectrometry, P. Zheng, C. Kramer, C.
Barnes, J. Braig, B. Sterling, Noninvasive glucose determination by oscillating
thermal gradient spectrometry, Diabetes Technology & Therapeutics, 2:1:17-
25;
• impedance based glucose determination;
• nuclear magnetic resonance;
• optical rotation of polarized light;
• radio wave impedance;
• fluid extraction from the skin;
• glucose oxidase and enzymatic sensors;
• interstitial fluid harvesting techniques (e.g. microporation or application of a
small electric current) or glucose electrode; and
• microdialysis.
As previously described, the calibration set constitutes a set of paired data points
collected on one or more subjects; and generally includes glucose concentrations


that span the expected range of glucose variation. Each paired data point includes a
reference glucose value and an associated value or values of the sensor variable.
The invented method relies on a variety of processes that improve the reference
values of the calibration set, which can be used independently or together.
First is a process for calibrating using a calibration set of paired data points including
a reference glucose value from a traditional invasive method or an alternative
invasive method and a noninvasive sensor measurement. This first process is
based on the recognition that glucose tends to be uniform throughout the tissue
under steady state conditions and that perfusion is the dominant physiological
process leading to differences in glucose under dynamic situations. Within the
context of this first process, a number of techniques are suggested for improving
reference values with respect to their corresponding sensor values:
• Paired data points are collected at intervals that allow determination of the
rate of glucose change. For example, traditional invasive glucose
determinations and noninvasive signals may be generated every 15 minutes
for a period of four hours. The resulting calibration set is limited to paired data
points with a corresponding rate of glucose change less than a specified
maximum level.
• Calibration data is collected during periods of stasis or slow change in glucose
concentration. The rate of acceptable change in glucose concentration is
determined on the basis of the tolerable error in the reference values. For


example, a rate of change of 0.5 mg/dL/minute may be found to be
acceptable;
• Under dynamic conditions, the circulation at a measurement site is perturbed,
both for an alternative invasive measurement site for calibration and later for
measuring glucose utilizing an alternative invasive glucose analyzer.
Enhancement of circulation in the forearm or alternate testing site, for
example, causes the local glucose concentrations to approach those of the
fingertip. As described above, methods for perturbing circulation may include
ultrasound, or a variety of surface applications that cause vasodilatation,
mechanical stimulation, partial vacuum, and heating;
• Patients are screened according to the discrepancy between their traditional
invasive glucose concentration at a fingertip or toe and an alternative invasive
glucose determination at the alternative invasive site. For example, subjects
with significant discrepancy between the glucose concentration in the fingertip
and the local tissue volume sampled through a near-infrared device, such as
a forearm, would not be used for calibration. Subjects having a small
difference in glucose concentration between the traditional invasive and
alternative invasive measurement site would be used for calibration. On this
basis subjects are further screened for device applicability for subsequent
glucose predictions; and
Using post-processing techniques, the sensor's estimate of the glucose
concentration is corrected. The method utilizes an estimate of the time lead
or lag between the two glucose concentrations from a cross-correlation or
time series analysis and a correction using an interpolation procedure. A


similar correction would correct for a dampening of the noninvasive signal
relative to a traditional invasive signal.
In a second process, careful site selection assures that reference values reflect the
concentration of glucose in the sensor variable. According to this process, blood,
serum, plasma, interstitial draws, or selective interstitial sample acquisitions are
taken from a tissue site that is either near the sensor sample site or has been
designed/determined to reflect the sample site. For example, when noninvasive
(sensor) near-infrared measurements are taken for calibration on a forearm, it is
possible in some individuals to collect a capillary blood draw from an alternative
invasive sample site such as the same forearm or from the opposite forearm. The
blood draws are taken in a manner that maintains perfusion equivalence to the
noninvasive sample site.
It is noted that alternative invasive glucose determinations acquire samples from
varying depths. Some acquire interstitial fluid from just below the epidermal later
while others penetrate into capillary blood or subcutaneous fluids. Because a
noninvasive glucose analyzer can be tuned to sense glucose concentrations from
different depths, a logical choice of a reference device is an alternative invasive
analyzer sampling from a similar depth in the skin. For example, a near-IR glucose
analyzer functioning in the 2100 to 2300, 1550 to 1800, or 1100 to 1350 nm region
acquires signal from approximately 1.5, 3, and 5 mm, respectively. Similarly, a
glucose analyzer functioning within 50 nm of 1450, 1900 or 2500 nm samples at
depths of less than 1 mm. Hence, noninvasive technologies that rely on tissue
volumes primarily including the epidermis indirectly measure primarily interstitial


glucose concentrations and may benefit from alternative invasive glucose analyzers
sampling the interstitial fluid from the epidermis versus an alternative invasive
glucose analyzer that samples blood from the dermis.
Finally, glucose varies dynamically through time in individuals. When a glucose
determination through a blood or interstitial sample cannot be taken simultaneously
with the sensor variable an error can exist due to the time differential. A technique
for reducing this error is based on interpolation and extrapolation of the reference
glucose values to the time the sensor variable was collected.
INSTRUMENTATION
Noninvasive
A number of technologies have been reported for measuring glucose noninvasively
that involve the measurement of a tissue related variable. Examples include but are
not limited to far-infrared absorbance spectroscopy, tissue impedance, Raman, and
fluorescence, as well as techniques using light from the ultraviolet through the
infrared [ultraviolet (200 to 400 nm), visible (400 to 700 nm), near-IR (700 to 2500.
nm or 14,286 to 4000 cm-1), and infrared (2500 to 14,285 nm or 4000 to 700 cm-1)].
These techniques share the common characteristic that they are indirect
measurements of glucose. A calibration is required in order to derive a glucose
concentration from subsequent collected data. In the past, capillary finger blood
glucose and venous blood glucose have been utilized to generate these calibrations.
However, as has been shown, these traditional invasive glucose determinations do
not always represent the glucose concentration at the sampled site.


A number of spectrometer configurations are possible for collecting noninvasive
spectra of body regions. Typically, a spectrometer, also called a sensor, has one or
more beam paths from a source to a detector. A light source may comprise a
blackbody source, a tungsten-halogen source, one or more LED's, or one or more
laser diodes. For multi-wavelength spectrometers a wavelength selection device
may be utilized or a series of optical filters may be utilized for wavelength selection.
Wavelength selection devices comprise dispersive elements such as one or more
plane, concave, ruled, or holographic grating. Additional wavelength selective
devices include an interferometer, successive illumination of the elements of an LED
array, prisms, and wavelength selective filters. However, variation of the source
such as varying which LED or diode is firing may be utilized. Detectors may in the
form of one or more single element detectors or one or more arrays or bundles of
detectors. Single element or array detectors maybe fabricated from InGaAs, PbS,
PbSe, Si, MCT (mercury-cadmium-tellurium), or the like. Light collection optics such
as fiber optics, lenses, and mirrors are commonly utilized in various configurations
within a spectrometer to direct light from the source to the detector by way of a
sample. The mode of operation may be transmission, diffuse reflectance, or
transflectance. Due to changes in performance of the overall spectrometer,
reference wavelength standards are often scanned. Typically, a wavelength
standard is collected immediately before or after the interrogation of the tissue, but
may also occur at times far removed such as when the spectrometer was originally
manufactured. A typical reference wavelength standard would be polystyrene or a
rare earth oxide such as holmium, erbium, or dysprosium oxide.


The interface of the glucose analyzer to the tissue includes a patient interface
module and light such as near-infrared radiation is directed to and from the tissue
either directly or through a light pipe, fiber-optics, a lens system, or a light directing
mirror system. The area of the tissue surface to which near-infrared radiation is
applied and the area of the tissue surface the returning near-infrared radiation is
detected from are different and separated by a defined distance and their selection is
designed to enable targeting of a tissue volume conducive to measurement of the
property of interest. The patient interface module may include an elbow rest, a wrist
rest, and/or a guide to assist in interfacing the illumination mechanism of choice and
the tissue of interest. Generally, an optical coupling fluid is placed between the
illumination mechanism and the tissue of interest to minimize specular reflectance
from the surface of the skin.
A preferred embodiment of the sensor 700, shown in Figure 7, is a spectroscopic
measurement system that includes a tungsten halogen near-infrared radiation
source, a wavelength selection filter 702 passing 1100 to 1900 nm light, fiber optics
703 for conveying the source photons to an in-vivo skin sample, an interface 704 to
the forearm of a patient, fiber optic collection optics 705 for gathering diffusely
reflected and transflected radiation from the skin to a grating, and an InGaAs array
706 to detect the radiation, electronic means 707 for converting the resulting signal
into a glucose concentration and a display (not shown). D. Klonoff, Noninvasive
blood glucose monitoring, Diabetes Care, 20:3:433 (March, 1997).

The sample site constitutes the point or area on the subject's body surface the
measurement probe contacts and the specific tissue irradiated by the spectrometer
system. Ideal qualifies for a sample site include: 1) homogeneity, 2) immutability;
and 3) accessibility to the target analyte. Noninvasive glucose analyzers commonly
use the fingertip as a sampling site. However, several alternative sampling sites are
possible, including the abdomen, upper arm, thigh, hand (palm or back of the hand)
or ear lobe, in the preferred embodiment, the volar part of the forearm is used. In
addition, while the measurement can be made in either diffuse reflectance or diffuse
transmittance mode, the preferred method is diffuse reflectance. Scanning of the
tissue can be done continuously when the tissue area being tested is not affected by
pulsation effects, or the scanning can be done intermittently between pulses.
The collected signal (near-infrared radiation in this case) is converted to a voltage
and sampled through an analog-to-digital converter for analysis on a microprocessor
based system and the result displayed.
Implantable:
In an alternate arrangement, the system or a portion of the system is implanted, and
the measurement is made directly on soft tissue, muscle, a blood vessel or skin
tissue within the body. In this configuration, the measurement is made in a manner
that is non-invasive to the probed tissue although the system or a portion of the
system is implanted within the body. For example, the peritoneal cavity is a suitable
location for implantation and both the probing signal source and detection system
are implanted. In the preferred embodiment, telemetry is employed to transfer data
or actual analyte readings to a remote location outside the body. Alternately, a


transcutaneous connector is employed. After transfer, the data or concentration are
then processed and displayed to the user or heath care provider. Three different
embodiments of the implanted system are disclosed. The first, a consumer version,
is used for incremental or continuous applications requiring intensive analysis of
body analytes (e.g., glucose). A particularly useful application is nocturnal
monitoring of glucose and detection or prediction of hypoglycemic events. In the
second, the system is employed in a health care facility and the analyte is monitored
via a computer or health care provider. A third embodiment of the implanted system
is for use in a closed-loop insulin delivery system. In this embodiment the system is
a sub-component of an artificial pancreas and used to monitor glucose levels for
insulin dosage determination via an insulin pump.
In implantable embodiments, an alternative invasive or noninvasive reference
glucose concentration or set of concentrations may be utilized with paired
implantable signals in order to calibrate an implantable glucose analyzer. This is
essentially the same as utilizing an alternative invasive glucose analyzer to calibrate
a noninvasive glucose analyzer as discussed above. Utilization of an alternative
invasive or noninvasive reference is beneficial in instances when the implantable
glucose analyzer is sampling fluids or tissues that have perfusion similar to that of
the alternative invasive sites. For example, a semi-implantable device may be
placed into the subcutaneous tissue or an implantable device may be placed into the
peritoneal cavity. Both of these regions may have dampened and lagged glucose
concentrations that are similar to alternative invasive glucose determinations or
noninvasive glucose determinations from regions that are not well perfused. Hence,


the reference values will more closely represent the implantable signals. This will aid
in calibration design and maintenance as above.
CORRECTION OF ALTERNATIVE INVASIVE TO TRADITIONAL INVASIVE
GLUCOSE CONCENTRATION
In building a glucose calibration model, a number of measurement parameters must
be considered. The selection of measurement parameters will greatly affect
predicted glucose concentrations from subsequent spectra. For example, for
glucose determination based on near-IR spectral measurements, parameters include
sample selection, preprocessing step selection, and actual model parameters such
as the number of factors in a multivariate model. In view of the demonstrated
difference in glucose concentration between traditional and alternative
measurements, selection of the appropriate set of glucose reference concentrations
is also important.
For example, a model may be based on a calibration set that utilizes alternative
invasive forearm glucose concentrations from the dorsal aspect of the forearm and
near-IR noninvasive glucose determinations from the forearm. By using such a
model to predict glucose concentrations from subsequent spectra, the subsequent
measurements for a large number of subjects will correspond to the values of the
calibration set more closely than if the calibration set were based on traditional
invasive glucose determinations from a fingertip. The importance of parameter
selection is described in greater detail below. Furthermore, a method for correcting
measurements based on a calibration set of traditional invasive glucose


determinations to approximate those based on a set of alternative invasive
determinations is provided.
EXAMPLE
A single calibration model was applied to 4,980 noninvasive spectra collected from
the volar.aspect of the forearm of twenty-six subjects covering 233 unique visits
utilizing nine instruments collected over a period of eight months. Each subject was
tested every fifteen minutes for a period of approximately eight hours. The resulting
glucose predictions were compared to both traditional invasive reference fingertip
and alternative invasive reference forearm glucose concentrations.
A concentration correlation plot of the predicted glucose concentrations versus the
forearm reference glucose concentrations is presented in Figure 8. A Clarke error
grid analysis for this data demonstrates that 81.9 and 17.9 percent of the data falls
into the A and B region, respectively. Thus, 99.8 percent of the data are predicted
clinically accurately versus the alternative invasive reference forearm glucose
concentrations. However, as shown in Figure 9, accuracy diminishes when plotted
against the corresponding traditional invasive reference fingertip glucose
concentrations. Clarke error grid analysis still results in 96.9% of the data in the 'A'
or 'B' regions; however, only 51.5% fall into the 'A' region. The correction
methodology follows:
For each subject, lag of the predicted glucose concentration versus reference
glucose concentrations for both fingertip and forearm determination is


calculated. In order to account for the difference between the predicted
values and the reference, a phase correction is calculated using a cross-
covariance based algorithm by sliding the x-axis (time vector) of the predicted
values a fixed amount to synchronize the predicted and reference values. A
histogram of the resultant lags is presented in Figure 10. Lags for the forearm
are observed to range up to sixty-two minutes. The peak of the lag for the
comparison against the forearm and the fingertip is approximately ten and
33.6 minutes, respectively. This indicates that the model substantially tracks
the forearm glucose concentrations better than glucose concentrations from
the fingertip, a result of the model being built with forearm glucose
concentrations.
For each subject, a magnitude correction is calculated comparing the
predicted glucose concentrations to each of the fingertip and forearm glucose
concentration reference profiles. The magnitude correction constitutes the
difference between the glucose concentration ranges of the predicted and
reference values. It is observed that the average difference between the
predicted and reference glucose concentrations is less for the forearm
reference glucose determinations than it is for the fingertip reference glucose
determinations. A ratio of the range of the predicted values versus the range
of the reference values is calculated for each subject's visit. A histogram of
the resulting ratios representative of the magnitude difference is presented in
Figure 11. The histogram demonstrates ratios closer to one for the forearm
glucose concentration range with peak values for the forearm and fingertip of
0.71 and 0.55, respectively.


A third parameter not utilized in this particular model is a correction of the
frequency of glucose profile versus time. Thus, the rate of glucose increase
to a peak value and the rate of a subsequent decline may differ for traditional
invasive glucose determinations and alternative invasive glucose
determinations, and this profile shape difference or period may be corrected.
It is here noted that specific examples of parameter calculations are presented, but
that those skilled in the art will immediately appreciate that the lag, dampening, and
frequency parameters and similar parameters utilized to characterize population
differences may be calculated in a number of ways, any of which are consistent with
the spirit and scope of the invention. For example, phase correction may be
performed with techniques such as a Bessel filter, warping of the time axis and re-
sampling, development of a wavelet-based model and subsequent time
compression, or shifting. Similarly, magnitude correction may be performed with a
simple multiplication factor after centering the data to either the mean or single data
point, a multiplication factor dependent upon the rate of change, a multiplication
factor dependent upon time, a multiplication factor dependent upon the tissue state,
or a multiplication factor dependent upon the type of diabetes or class of tissue.
Additionally, it is noted that incomplete vectors may still be utilized to determine
these or similar parameters.
A multi-step correction method may then be implemented utilizing one or more of
these parameters. In one example, a shift correction is followed by a magnitude
correction. First, the mean shift value of 33.6 minutes is subtracted from the


prediction time vector. Second, a magnitude correction is performed, initially, the
shift corrected data is mean centered. Then, the resulting glucose concentrations
are divided by 0.55. Finally, the mean of the shift corrected data is added to the
resulting vector of data.
The two-step correction with parameters of a shift adjustment of 33.6 minutes and a
scaling factor of 0.55 produced above is here applied to a set of 7 daily visits from a
total of 3 subjects representing noninvasive spectra collected from 3 near-IR glucose
analyzers. The fingertip reference glucose concentrations and noninvasively
predicted glucose concentration profiles are presented in Figure 12. The
noninvasive glucose concentrations predicted from spectra collected from the
forearm are clearly damped and lagged versus the corresponding traditional invasive
glucose determinations. The corresponding concentration correlation plot overlaid
with a Clarke error grid is presented in Figure 13. The algorithm corrected glucose
profiles and corresponding concentration correlation plot is presented in Figures 14
and 15, respectively. Notably, the lag and dampening have been greatly reduced.
The respective statistics for the uncorrected and corrected glucose concentrations
reveal an obvious improvement in accuracy. The statistics for the uncorrected and
corrected glucose concentrations are Clarke 'A' region: 49.7 and 80.5%; r: 0.78 and
0.96, F-value: 2.38 and 10.9, standard error 54.4 and 26.0 mg/dL, respectively.
The two-step correction demonstrated above was applied to the entire data set. The
corrected predicted fingertip glucose concentrations are presented in a concentration
correlation plot superimposed onto a Clarke error grid, Figure 16. The corrected
glucose concentrations result in 97.8% of the points falling into the 'A' or 'B' region of


the Clarke error grid. The correlation coefficient, F-Value, and r value each showed
a corresponding increase. In addition, the algorithm allows conversion back and
forth between forearm and fingertip glucose concentrations.
While the preceding description has been directed primarily to calibration sets that
include invasive reference measurements, embodiments of the invention are
possible, that employ noninvasive reference measurements. The above data
emphasize the importance of taking reference measurements at a site having
perfusion equivalence to the sampling site. Accordingly, the principles previously
discussed are equally applicable to calibrations developed using noninvasive
reference measurements, rather than invasive reference measurements.
INTEGRATED GLUCOSE ANALYZER
An integrated glucose analyzer 1700 that utilizes alternative invasive or traditional
invasive glucose determinations in combination with noninvasive measurements is
shown in Figure 17.
The invention includes a first component 1701 that measures an analytical signal
from the body to determine the body's glucose concentration. Numerous
noninvasive devices have been described above. In one embodiment of the
invention, a near-infrared spectrometer configured for a noninvasive diffuse
reflectance measurement from the forearm may be utilized. The first component
1701 includes a control and processing element 1703 for executing computer-


readable instructions and at least one storage element 1704, such as a memory,
having executable program code embodied therein for converting a series of
reflected near-IR signals, collected from the forearm or other tissue site, into a
corresponding series of blood glucose values.
A second component 1702, that provides either a traditional invasive or alternative
glucose measurement, is electronically coupled 1706a and b to the first component.
Preferably, the second component provides measurements having five percent error
or less.
The above program code also includes code for:
• extracting the data from the traditional second component 1702;
• storing the invasive blood glucose values extracted from the second
component 1702 in the storage element 1704 of the first component 1701;
and
• using the stored invasive blood glucose values for calibration, calibration
assignment, validation, quality assurance procedures, quality control
procedures, adjustment, and/or bias correction, depending on the current
mode of operation.
For example, in the case of calibration, finger stick-based blood glucose values
are collected concurrently with noninvasive spectra to form a calibration set of
paired data points. The set is used to calculate a mathematical model suitable
for determination of blood glucose on the basis of a noninvasive measurement,
such as a spectrum. As a second example, in the case of bias adjustment,


invasive blood glucose determinations are collected with the first noninvasive
glucose determination of the day and utilized to adjust the noninvasive glucose
concentration to the reference glucose determination. The adjustment parameter
is utilized until a new invasive reference glucose determination is collected.
The above program code also includes code for:
• prpviding a comparison and evaluation of the finger stick blood glucose value
to the blood glucose value obtained from the noninvasive near-infrared diffuse
reflectance measurement.
In one embodiment, information is communicated to the first component 1701 from
the second component 1702. Alternatively, the second component 1702 may
containing processing and storage elements, instead of the first component.
Noninvasive glucose measurements are configured to operate in modes
(transmission, diffuse reflectance, and transflectance) as described above on body
parts as described above.
Finally, although the preferred embodiment employs fingerstick measurements, any
measurement having sufficient accuracy and precision can be used as the reference
measurement.
There is a pronounced disadvantage to conventional systems, in which a primary
device and a secondary device are separate and distinct from each other.
Secondary measurements must be compared to primary measurements, in order to
validate the secondary measurements. Conventionally, comparison requires the


consumer to manually input a blood glucose value from the primary device
(traditional or alternative invasive glucose analyzer) into the secondary device
(noninvasive or implantable glucose analyze) for comparison. An inherent risk to
such an approach is the improper input of the primary glucose value into the
secondary device, thus resulting in an invalid comparison.
Advantageously, the integrated glucose analyzer eliminates the necessity for the
patient to manually input an invasive measurement for comparison with the
noninvasive measurement. A second advantage is the ability to utilize a single case
for both components with a similar power supply and display. This results in fewer
elements that a person with diabetes need carry with them. An additional advantage
is a backup glucose analyzer in the event of the noninvasive glucose analyzer failing
to produce a glucose value as may be the case with very high or hypoglycemic
glucose concentrations. A third advantage is traeeability. The time difference
between a reference glucose determination from an invasive meter and a
corresponding noninvasive glucose reading may be critical in establishing a
correction to an algorithm such as a bias. An automated transfer of the glucose
value and the associated time greatly reduces risks in usage of a noninvasive
analyzer that requires such a correction. Finally, the transfer of glucose and time
information into the noninvasive analyzer digital storage means eases subsequent
analysis and data management by the individual or a professional.
This technology may be implemented in healthcare facilities including, but not limited
to: physician offices, hospitals, clinics, and long-term healthcare facilities. In
addition, this technology would be implemented for home-use by consumers who


desire to monitor their blood glucose levels whether they suffer from diabetes,
impaired glucose tolerance, impaired insulin response, or are healthy individuals.
Additionally, an embodiment is possible in which the first and second components
are separate analyzers, the first component configured to measure glucose
noninvasively, and the second component configured to perform either alternate
invasive or traditional invasive measurements. In the current embodiment, first and
second components are electronically coupled by means of a communication
interface, such as RS232 or USB (universal serial bus). Other commonly-known
methods of interfacing electrical components would also be suitable for the
invention,, such as telemetry, infrared signals, radiowave, or other wireless
technologies. Either embodiment provides the above advantages of eliminating the
possibility of invalid measurements by doing away with the necessity of manual data
entry.
Although the invention has been described herein with reference to certain preferred
embodiments, one skilled in the art will readily appreciate that other applications may
be substituted for those set forth herein without departing from the spirit and scope of
the present invention. Accordingly, the invention should only be limited by the claims
included below.

We Claim :
1. An apparatus for measuring a tissue analyte such as glucose, in vivo, comprising
- a first component (1701) configured to generate signals for a noninvasive
measurement of said tissue analyte comprising a non-invasive sensor ,a
communication interface (1706b) ,a control and processing system (1703), a memory
means (1704) and a user interface ;
a second component (1702), configured to generate signals for an invasive reference
measurement of said tissue analyte comprising an invasive analyte monitor such as a
glucose monitor, and a communication interface (1706a);
- said first and second components electromagnetically coupled through a comunication
link; and,
means for using said reference measurement to optimize calibration of said apparatus
in a calibration model comprising: a computer program means for optimizing said
calibration, said program means embodied in said memory means; and a processing
element configured to execute said program means,
- wherein said first component is adapted to collect non-invasive signals at an
alternative sample site on a body located at a region other than body's fingure tips
and toes,
- wherein said second component is adapted to make invasive measurements at a time
corresponding to each of said one or more non-invasive signals from the first
component,
- wherein said calibration model is adapted to control sample site disparity error in
calibration of said non-invasive measurement using paired data points for analyte
analysis at alternative sample site with substantially identical tissue matrix so that the
discrepancy between analyte concentration at said alternative sample site and said
alternative reference measurement site is reduced or eliminated.

2. The apparatus as claimed in Claim 1, wherein said tissue analyte comprises glucose.
3. The apparatus as claimed in Claim 2, wherein said second component comprises one
of: an alternative invasive glucose analyzer; and a traditional invasive glucose analyzer.
4. The apparatus as claimed in Claim 2, optionally comprising: memory means for
storing any of said measurements..


5. The apparatus as claimed in Claim 3, wherein said first component comprises a near-
IR glucose analyzer.
6. The apparatus as claimed in Claim I, wherein said first component and said second
component are integrated.
7. The apparatus as claimed in Claim 1, wherein said first component and said second
component are separate units.
8. The apparatus as claimed in Claim 7, wherein said first component and said second
component are wirelessly electromagnetically coupled.
9. The apparatus as claimed in Claim 8, wherein said first component and said second
component are wirelessly electromagnetically coupled through any of telemetry, infrared
signals, and radiowaves.

The invention discloses an apparatus for measuring a tissue analyte such as
glucose, in vivo, comprising a first component (1701) configured to generate
signals for a noninvasive measurement of said tissue analyte comprising a noninvasive
sensor ,a communication interface (1706b) ,a control and processing
system (1703), a memory means (1704) and a user interface; a second
component (1702), configured to generate signals for an invasive reference
measurement of said tissue analyte comprising an invasive analyte monitor such
as a glucose monitor, and a communication interface (1706a); said first and
second components electromagnetically coupled through a comunication link;
and, means for using said reference measurement to optimize calibration of said
apparatus in a calibration model comprising: a computer program means for
optimizing said calibration, said program means embodied in said memory
means; and a processing element configured to execute said program means,
wherein said first component is adapted to collect non-invasive signals at an
alternative sample site on a body located at a region other than body's fingure
tips and toes, wherein said second component is adapted to make invasive
measurements at a time corresponding to each of said one or more non-invasive
signals from the first component, wherein said calibration model is adapted to
control sample site disparity error in calibration of said non-invasive
measurement using paired data points for analyte analysis at alternative sample
site with substantially identical tissue matrix so that the discrepancy between
analyte concentration at said alternative sample site and said alternative
reference measurement site is reduced or eliminated.

Documents:

1177-kolnp-2004-granted-abstract.pdf

1177-kolnp-2004-granted-assignment.pdf

1177-kolnp-2004-granted-claims.pdf

1177-kolnp-2004-granted-correspondence.pdf

1177-kolnp-2004-granted-description (complete).pdf

1177-kolnp-2004-granted-drawings.pdf

1177-kolnp-2004-granted-examination report.pdf

1177-kolnp-2004-granted-form 1.pdf

1177-kolnp-2004-granted-form 3.pdf

1177-kolnp-2004-granted-form 5.pdf

1177-kolnp-2004-granted-gpa.pdf

1177-kolnp-2004-granted-reply to examination report.pdf

1177-kolnp-2004-granted-specification.pdf


Patent Number 230207
Indian Patent Application Number 1177/KOLNP/2004
PG Journal Number 09/2009
Publication Date 27-Feb-2009
Grant Date 25-Feb-2009
Date of Filing 13-Aug-2004
Name of Patentee SENSYS MEDICAL INC.
Applicant Address 7470 WEST CHANDLER BLVD, CHANDLER, AZ 85226
Inventors:
# Inventor's Name Inventor's Address
1 MONFRE STEPHEN L 1289 EAST PALO BLANCO WAY GILBERT, AZ 85296
2 HAZEN KEVIN H 1534 W.ISLANDIA DRIVE, GILBERT, AZ 85233
3 RUCHTI TIMOTHY L 1501 WEST SEA HAZE DRIVE, GILBERT AZ 85233
4 BLANK THOMAS B 2922 E TULSA STREET, CHANDLER AZ 85225
5 HENDERSON JAMES R 7043 S. 27TH WAY PHOENIX, AZ 85040
PCT International Classification Number A 61 B 5/00
PCT International Application Number PCT/US2003/006426
PCT International Filing date 2003-03-03
PCT Conventions:
# PCT Application Number Date of Convention Priority Country
1 60/362,899 2002-03-08 U.S.A.
2 10/377,916 2003-02-28 U.S.A.
3 60/362, 885 2002-03-08 U.S.A.