U.S. patent application number 15/951659 was filed with the patent office on 2018-08-16 for calibration of fluidic devices.
The applicant listed for this patent is Theranos IP Company, LLC. Invention is credited to Ian GIBBONS, Elizabeth A. Holmes, Shaunak Roy, Chengwang WANG.
Application Number | 20180231469 15/951659 |
Document ID | / |
Family ID | 37397025 |
Filed Date | 2018-08-16 |
United States Patent
Application |
20180231469 |
Kind Code |
A1 |
GIBBONS; Ian ; et
al. |
August 16, 2018 |
Calibration of Fluidic Devices
Abstract
The present invention provides methods of calibrating a fluidic
device useful for detecting an analyte of interest in a bodily
fluid. The invention also provides methods for assessing the
reliability of an assay for an analyte in a bodily fluid with the
use of a fluidic device. Another aspect of the invention is a
method for performing a trend analysis on the concentration of an
analyte in a subject using a fluidic device.
Inventors: |
GIBBONS; Ian; (Newark,
CA) ; WANG; Chengwang; (Palo Alto, CA) ; Roy;
Shaunak; (Palo Alto, CA) ; Holmes; Elizabeth A.;
(Palo Alto, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Theranos IP Company, LLC |
Newark |
CA |
US |
|
|
Family ID: |
37397025 |
Appl. No.: |
15/951659 |
Filed: |
April 12, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14867271 |
Sep 28, 2015 |
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15951659 |
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12986954 |
Jan 7, 2011 |
9182388 |
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14867271 |
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11388824 |
Mar 24, 2006 |
7888125 |
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12986954 |
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60721097 |
Sep 28, 2005 |
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60717192 |
Sep 16, 2005 |
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60705489 |
Aug 5, 2005 |
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60678801 |
May 9, 2005 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B01L 2300/0867 20130101;
A61B 5/150854 20130101; B01L 2300/044 20130101; A61B 5/1411
20130101; A61B 5/150099 20130101; A61B 5/157 20130101; A61B 5/14532
20130101; A61B 5/14546 20130101; Y10T 436/12 20150115; B01L
2300/0883 20130101; G01N 2500/00 20130101; G16H 40/63 20180101;
Y10T 436/143333 20150115; B01L 2300/0636 20130101; A61B 5/15142
20130101; B01L 2300/0816 20130101; A61B 5/412 20130101; A61B 5/417
20130101; G01N 33/54386 20130101; B01L 2300/021 20130101; B01L
2300/0887 20130101; B01L 3/50273 20130101; G01N 21/76 20130101;
A61B 5/1495 20130101; B01L 2300/023 20130101; B01L 2300/0877
20130101; G01N 33/5302 20130101; A61B 5/150251 20130101; G01N 33/50
20130101; A61B 5/150022 20130101; Y02A 90/10 20180101; Y10T 436/10
20150115; Y10T 436/11 20150115; B01L 2300/087 20130101; G01N 33/53
20130101; Y10T 436/115831 20150115; A61B 5/1427 20130101; A61B
5/150763 20130101 |
International
Class: |
G01N 21/76 20060101
G01N021/76; G16H 40/63 20180101 G16H040/63; G01N 33/543 20060101
G01N033/543; B01L 3/00 20060101 B01L003/00; A61B 5/00 20060101
A61B005/00; A61B 5/15 20060101 A61B005/15; G01N 33/50 20060101
G01N033/50; A61B 5/145 20060101 A61B005/145; A61B 5/151 20060101
A61B005/151; A61B 5/155 20060101 A61B005/155; G01N 33/53 20060101
G01N033/53; A61B 5/157 20060101 A61B005/157 |
Claims
1. A method for detecting an analyte contained in a biological
fluid sample, comprising: receiving a cartridge into a reader
assembly, the cartridge comprising: a sample collection unit
configured to receive the biological fluid sample; and an assay
assembly, wherein the assay assembly comprises a plurality of
reaction sites each having a reactant contained therein; receiving
a protocol associated with the cartridge at the reader assembly,
based on an identifier of the cartridge; flowing a portion of the
biological fluid sample to the reaction sites in response to
receiving the protocol such that the analyte contained in the
biological fluid sample reacts with a reactant within one of the
reaction sites and produces an optical signal indicating the
presence of the analyte; and detecting the optical signal with a
detection assembly included in the reader assembly.
2. The method of claim 1, further comprising: transmitting the
detected optical signal to an external device via a communication
assembly.
3. The method of claim 2, wherein the protocol is received via a
wired connection from the external device.
4. The method of claim 1, wherein the identifier is disposed on the
cartridge and comprises an identifier selected from one of a bar
code, an alphanumeric value, and a color.
6. The method of claim 1, further comprising: detecting the
identifier via an identifier detector; and transmitting the
identifier from the identifier detector to an external device for
the protocol to be determined by the external device; and
subsequently receiving the determined protocol at the reader
assembly.
7. The method of claim 1, further comprising: controlling, via a
controller, fluid flow of a first portion of the biological fluid
sample to a first reaction site including a first reactant and
fluid flow of a second portion the biological fluid sample to a
second reaction site including a second reactant different from the
first reactant, wherein the first and second reactants are
configured to react with different analytes contained in each of
the first and second portions of the biological fluid sample.
8. The method of claim 1, wherein the detection of the optical
signal is achieved via a charge coupled device having multiple
detection areas.
9. The method of claim 1, wherein the optical signal is a
luminescent signal.
10. The method of claim 1, wherein the sample comprises one of
blood and urine.
11. The method of claim 1, wherein the bounding area of a reaction
site is constructed from an optically opaque material.
12. The method of claim 1, further comprising: diluting the
biological fluid sample according to the protocol.
13. A method for detecting an analyte contained in a biological
fluid sample, comprising: inserting a cartridge into a reader
assembly, the cartridge comprising: a sample collection unit
configured to receive the biological fluid sample; and an assay
assembly, wherein the assay assembly comprises a plurality of
reaction sites each having a reactant contained therein; receiving
a protocol associated with the cartridge at the reader assembly,
based on an identifier; flowing a portion of the biological fluid
sample to the reaction sites in response to receiving the protocol
such that the analyte contained in the biological fluid sample
reacts with each reactant within the reaction sites and produces a
plurality of optical signals indicating the presence of or absence
of the analyte; detecting the optical signals with a detection
assembly included in the reader assembly; and transmitting the
optical signals to an external device for aggregation of the
plurality of signals by the external device.
14. The system of claim 13, further comprising analyzing the
aggregated signals to trend the presence of the analyte at various
time points over a given period of time, wherein the optical
signals are transmitted concurrently with performance of the
analyzing the aggregated signals to trend the presence of the
analyte.
15. The system of claim 13, further comprising analyzing the
aggregated signals to trend the presence of the analyte at various
time points over a given period of time, wherein the optical
signals are transmitted prior to performance of the analyzing the
aggregated signals to trend the presence of the analyte.
16. The system of claim 13, further comprising: performing on-board
calibration of the assay assembly.
17. The system of claim 13, wherein the sample comprises one of
blood and urine.
18. The system of claim 13, wherein the system is configured to
detect a plurality of analytes that generate distinct signals based
on the position of a particular reaction site.
19. The system of claim 13, wherein detecting of the optical
signals further comprising detecting that a luminescent signal is
present at a particular reaction site.
20. The system of claim 13, further comprising: detecting a second
signal from a sensor selected from one of a temperature sensor, a
conductivity sensor, a potentiometric sensor, or amperometric
sensor.
Description
CROSS-REFERENCE
[0001] This application is a continuation of U.S. application Ser.
No. 14/867,271, filed Sep. 28, 2015, which is a continuation of
U.S. application Ser. No. 12/986,954, filed Jan. 7, 2011 (now U.S.
Pat. No. 9,182,388), which is a continuation of U.S. application
Ser. No. 11/388,824, filed Mar. 24, 2006 (Now U.S. Pat. No.
7,888,125), which claims the benefit of U.S. Provisional
Application No. 60/678,801, filed May 9, 2005, U.S. Provisional
Application No. 60/705,489, filed Aug. 5, 2005, U.S. Provisional
Application No. 60/717,192, filed Sep. 16, 2005, and U.S.
Provisional Application No. 60/721,097, filed Sep. 28, 2005, each
of which are incorporated herein by reference in their
entirety.
BACKGROUND OF THE INVENTION
[0002] The discovery of a vast number of biomarkers implicated in a
wide variety of biological processes and the establishment of
miniaturized microfluidic systems have opened up avenues to devise
methods and systems for the prediction, diagnosis and treatment of
diseases in a point-of-care setting. Point-of-care testing is
particularly desirable because it rapidly delivers results to
medical practitioners and enables faster consultation.
[0003] Performing assays, particularly immunoassays, on
microfluidic systems of patient samples requires careful, precise
calibration using data gathered in parallel with the sample
measurement by measuring known standards or calibrators using the
same assay protocol and reagents, or data provided by a
manufacturer that are specific to a particular lot of reagents and
assay conditions. Generally, such manufacturer provided calibration
data are associated with strict temperature and other assay related
conditions. Such calibration information is critical in accurately
determining the relationship between the response or output from
the assay system and the analyte concentration in a sample. Errors
due to mis-calibration of distributed assay systems, especially in
the case of immunoassays and particularly in the case of
immunoassays that do not use "excess" reagents could lead to
significant errors in determining the concentration of an analyte
of interest.
[0004] There is therefore a significant need for methods that would
improve the calibration in hand held or disposable assay units,
particularly in those units where the sample and/or reagent volumes
are in the microliter and nanoliter ranges, where maintaining a
controlled temperature may be impractical, where the sample may not
be "clean" such that errors are caused by interfering substances,
or where it is difficult to maintain the desired conditions such as
temperature, reagent quality, or sample volume.
SUMMARY OF THE INVENTION
[0005] The present invention provides a method of improving the
accuracy of calibrating a fluidic system. The method comprises
providing a system for detecting an analyte in a bodily fluid from
a subject comprising a fluidic device for providing said bodily
fluid, said fluidic device having a calibration assembly and a
reader assembly for detecting the presence of said analyte,
measuring one or more parameters of a calibration curve associated
with said fluidic device, comparing said one or more parameters
with predetermined parameters associate with said fluidic device,
and adjusting a signal output by the ratio of said one or more
parameters and said predetermined parameters.
[0006] In one aspect of the method the predetermined parameters are
parameters determined at the time the fluidic device is
manufactured.
[0007] In another aspect of the method the predetermined parameters
are replaced with said measured one or more parameters to be used
in a calibration curve to scale a signal to determine said analyte
concentration.
[0008] The present invention provides another method of improving
the calibration of a fluidic system. The method comprises measuring
a first signal in an original sample comprising a known quantity of
an analyte, measuring a second signal after spiking said original
sample with a known quantity of said analyte, plotting the
difference between said first and second signals against a target
value, wherein said target value is a signal expected for said
known quantity of said analyte, and arriving at a best fit of
parameters by minimizing the sum of the square of the differences
between said target value and calculated analyte values.
[0009] In one aspect of the method the sample is provided to a
fluidic device, the fluidic device comprises a sample collection
unit and an assay assembly, wherein said sample collection unit
allows a sample of bodily fluids to react with reactants contained
within said assay assembly.
[0010] The present invention further provides a method of assessing
the reliability of an assay for an analyte in a bodily fluid with
the use of a fluidic device. The method comprises providing a
system, the system comprising a fluidic device, said fluidic device
comprising a sample collection unit and an assay assembly, wherein
said sample collection unit allows a sample of bodily fluid to
react with reactants contained within said assay assembly, for
detecting the presence of an analyte in a bodily fluid from a
subject, and a reader assembly for detecting the presence of said
analyte, and sensing with a sensor a change in operation parameters
under which the system normally operates.
[0011] One aspect of the method further comprises improving the
reliability of said assay by adjusting the operating parameters to
effect normal functioning of the system.
[0012] In one aspect the sensor is associated with the fluidic
device and is capable of communicating the change to the reader
assembly.
[0013] In some aspects the change is a change in temperature,
pressure, or the presence of moisture.
[0014] In one aspect the sensor is associated with the reader
assembly and is capable of communicating said change to an external
device.
[0015] One aspect of the method further comprises adjusting a
calibration step of said system.
[0016] One aspect of the method further comprises wirelessly
communicating said change via a handheld device.
[0017] Further provided in the present invention is a method of
performing a trend analysis on the concentration of an analyte in a
subject. The method comprises providing a fluidic device comprising
at least one sample collection unit, an immunoassay assembly
containing immunoassay reagents, a plurality of channels in fluid
communication with said sample collection unit and/or said
immunoassay assembly, actuating said fluidic device and directing
said immunoassay reagents within said fluidic device, allowing a
sample of bodily fluid of less than about 500 ul to react with said
immunoassay reagents contained within said assay immunoassay
assembly to yield a detectable signal indicative of the presence of
said analyte in said sample, detecting said detectable signal
generated from said analyte collected in said sample of bodily
fluid, and repeating the steps for a single patient over a period
of time to detect concentrations of said anayte, thereby performing
the trend analysis.
INCORPORATION BY REFERENCE
[0018] All publications and patent applications mentioned in this
specification are herein incorporated by reference to the same
extent as if each individual publication or patent application was
specifically and individually indicated to be incorporated by
reference.
BRIEF DESCRIPTION OF THE DRAWINGS
[0019] The novel features of the invention are set forth with
particularity in the appended claims. A better understanding of the
features and advantages of the present invention will be obtained
by reference to the following detailed description that sets forth
illustrative embodiments, in which the principles of the invention
are utilized, and the accompanying drawings of which:
[0020] FIG. 1 is an embodiment showing multiple components of the
present system.
[0021] FIG. 2 shows different layers of an exemplary fluidic device
prior to assembly.
[0022] FIGS. 3 and 4 illustrate the fluidic network within an
exemplary fluidic device.
[0023] FIGS. 5 and 6 illustrate a side view of an exemplary fluidic
device is combination with actuating elements of the reader
assembly.
[0024] FIG. 7 shows a typical assay dose-response data for a
two-step assay for TxB2.
[0025] FIG. 8 shows dose responses computed with and without errors
in calibration parameters.
[0026] FIG. 9 shows computed concentration errors produced by 1%
mis-estimation of A and D calibration values.
[0027] FIG. 10 illustrates calibration using a "differential"
approach.
[0028] FIG. 11 shows the verification of calibration using the
"1-point spike" method (log scale).
[0029] FIG. 12 shows the verification of calibration using the
"1-point spike" method (linear scale).
[0030] FIG. 13 shows dose-response of assays calibrated against a
plasma sample with a very low TxB2 concentration.
[0031] FIG. 14 shows use of spike recovery to eliminate calibration
errors of the "C" parameter.
[0032] FIG. 15 illustrates calculating differences in concentration
between two samples.
[0033] FIG. 16 illustrates an assay of plasma samples.
[0034] FIG. 17 shows the time course of assay signal
generation.
[0035] FIG. 18 shows the impact of change in calibration parameter
"A" on assay calibration.
[0036] FIG. 19 shows how a reference therapeutic index would be
computed.
[0037] FIG. 20 illustrates computing the therapeutic index.
[0038] FIG. 21 shows multiple regression analysis of the computed
therapeutic index.
[0039] FIG. 22 is an illustration of the relationship between
measured drug, analyte and biomarker concentration and therapeutic
index.
[0040] FIG. 23 is an illustration of the application of this
invention to minimize adverse drug reactions.
[0041] FIG. 24 shows exemplary patient input values.
[0042] FIG. 25 shows use of a therapeutic index to follow treatment
progression in an autism patient.
DETAILED DESCRIPTION OF THE INVENTION
[0043] One aspect of the present invention is a system for
detecting an analyte in a sample of bodily fluid. In some
embodiments a bodily fluid sample is taken from a patient into a
fluidic device comprising a sample collection unit, an assay
assembly, fluidic channels, and assay reagents. Using an assay, an
analyte present in the bodily fluid sample can generate a signal
indicative of the presence of the analyte. A reader assembly
comprising a detection assembly can then detect the signal. A
communications assembly can then transmit the detected signal to an
external device for processing. In preferred embodiments, the
external device comprises a protocol to run on the fluidic device
based on the identification of the fluidic device.
[0044] FIG. 1 illustrates an exemplary system of the present
invention. As illustrated, a fluidic device provides a bodily fluid
from a patient and can be inserted into a reader assembly. The
fluidic device may take a variety of configurations and in some
embodiments the fluidic device may be in the form of a cartridge.
An identifier (ID) detector may detect an identifier on the fluidic
device. The identifier detector communicates with a communication
assembly via a controller which transmits the identifier to an
external device. The external device sends a protocol stored on the
external device to the communication assembly based on the
identifier. The protocol to be run on the fluidic device may
comprise instructions to the controller of the reader assembly to
perform the protocol on the fluidic device, including but not
limited to a particular assay to be run and/or a detection method
to perform. Once the assay is performed on the fluidic device, a
signal indicative of an analyte in the bodily fluid sample may be
generated and detected by a detection assembly. The detected signal
may then be communicated to the communications assembly, where it
can be transmitted to the external device for processing, including
without limitation, calculation of the analyte concentration in the
sample.
[0045] FIG. 2 illustrates exemplary layers of a fluidic device
according to the present invention prior to assembly of the fluidic
device which is disclosed in more detail below. FIGS. 3 and 4
illustrate the fluidic network of an exemplary fluidic device. The
different layers are designed and assembled to form a three
dimensional fluidic channel network. A sample collection unit 4
provides a sample of bodily fluid from a patient. As will be
explained in further detail below a reader assembly comprises
actuating elements (not shown) that can actuate the fluidic device
to start and direct the flow of a bodily fluid sample and assay
reagents in the fluidic device. In some embodiments actuating
elements first cause the flow of sample in the fluidic device 2
from sample collection unit 4 to reaction sites 6, move the sample
upward in the fluidic device from point G' to point G, and then to
waste chamber 8. The actuating elements then initiate the flow of
reagents from reagent chambers 10 to point B', point C', and point
D', upward to points B, C, and D, respectively. The reagents then
move to point A, down to point A', and then to waste chamber 8 in a
manner similar to the sample.
[0046] One of the advantages of the present invention is that any
reagents necessary to perform an assay on a fluidic device
according to the present invention are preferably on-board, or
housed within the fluidic device before, during, and after the
assay. In this way the only inlet or outlet from the fluidic device
is preferably the bodily fluid sample initially provided by the
fluidic device. This design also helps create an easily disposable
fluidic device where all fluids or liquids remain in the device.
The on-board design also prevents leakage from the fluidic device
into the reader assembly which should remain free from
contamination from the fluidic device.
[0047] In a preferred embodiment there is at least one reagent
chamber. In some embodiments there may be two, three, four, five,
six, or more, or any number of reagent chambers as are necessary to
fulfill the purposes of the invention. A reagent chamber is
preferably in fluid communication with at least one reaction site,
and when the fluidic device is actuated as described herein,
reagents contained in said reagent chambers are released into the
fluidic channels within the fluidic device.
[0048] Reagents according to the present invention include without
limitation wash buffers, substrates, dilution buffers, conjugates,
enzyme-labeled conjugates, DNA amplifiers, sample diluents, wash
solutions, sample pre-treatment reagents including additives such
as detergents, polymers, chelating agents, albumin-binding
reagents, enzyme inhibitors, enzymes, anticoagulants, red-cell
agglutinating agents, antibodies or other materials necessary to
run an assay on a fluidic device. An enzyme conjugate can be either
a polyclonal antibody or monoclonal antibody labeled with an
enzyme, such as alkaline phosphatase or horseradish peroxidase. In
some embodiments the reagents are immunoassay reagents.
[0049] In some embodiments a reagent chamber contains approximately
about 50 .mu.l to about 1 ml of fluid. In some embodiments the
chamber may contain about 100 .mu.l of fluid. The volume of liquid
in a reagent chamber may vary depending on the type of assay being
run or the sample of bodily fluid provided. In some embodiments the
reagents are initially stored dry and liquified upon initiation of
the assay being run on the fluidic device.
[0050] A variety of assays may be performed on a fluidic device
according to the present invention to detect an analyte of interest
in a sample. Using labels in an assay as a way of detection the
concentration of the analyte of interest is well known in the art.
In some embodiments labels are detectable by spectroscopic,
photochemical, biochemical, immunochemical, or chemical means. For
example, useful nucleic acid labels include 32P, 35S, fluorescent
dyes, electron-dense reagents, enzymes, biotin, dioxigenin, or
haptens and proteins for which antisera or monoclonal antibodies
are available. A wide variety of labels suitable for labeling
biological components are known and are reported extensively in
both the scientific and patent literature, and are generally
applicable to the present invention for the labeling of biological
components. Suitable labels include radionucleotides, enzymes,
substrates, cofactors, inhibitors, fluorescent moieties,
chemiluminescent moieties, bioluminescent labels, calorimetric
labels, or magnetic particles. Labeling agents optionally include,
for example, monoclonal antibodies, polyclonal antibodies,
proteins, or other polymers such as affinity matrices,
carbohydrates or lipids. Detection proceeds by any of a variety of
known methods, including spectrophotometric or optical tracking of
radioactive or fluorescent markers, or other methods which track a
molecule based upon size, charge or affinity. A detectable moiety
can be of any material having a detectable physical or chemical
property. Such detectable labels have been well-developed in the
field of gel electrophoresis, column chromatograpy, solid
substrates, spectroscopic techniques, and the like, and in general,
labels useful in such methods can be applied to the present
invention. Thus, a label includes without limitation any
composition detectable by spectroscopic, photochemical,
biochemical, immunochemical, electrical, optical, thermal, or
chemical means.
[0051] In some embodiments assays performed on the fluidic device
will generate photons in the reaction sites indicative of the
presence of an analyte of interest. To ensure that a given photon
count, for example, detected from a reaction site correlates with
an accurate concentration of an analyte of interest in a sample, it
is preferably advantageous to calibrate the fluidic device before
the detection step. Calibrating a fluidic device at the point of
manufacturing, for example, may be insufficient to ensure an
accurate analyte concentration is determined because a fluidic
device may be shipped prior to use and may undergo changes in
temperature, for example, so that a calibration performed at
manufacturing does not take into effect any subsequent changes to
the structure of the fluidic device or reagents contained therein.
In a preferred embodiment of the present invention, a fluidic
device has a calibration assembly that is similar to the assay
assembly in components and design. One difference is that a sample
is preferably not introduced into the calibration assembly.
Referring to FIGS. 3 and 4, a calibration assembly occupies about
half of the fluidic device 2 and includes reagent chamber 32,
reactions site 34, a waste chamber 36, and fluidic channel 38.
Similar to the assay assembly, the number of reagent chambers and
reaction sites may vary depending on the assay being run on the
fluidic device and the number of analytes being detected.
[0052] An additional method of improving the accuracy of a
calculated analyte concentration or pharmacokinetic or
pharmacodynamic parameter measured according to the present
invention is to provide a sensor on either the fluidic device or
reader assembly, or both, that can sense, for example, changes in
temperature or pressure that could impact the performance of the
present system.
[0053] A fluidic device and reader assembly may, after
manufacturing, be shipped to the end user, together or
individually. As a reader assembly is preferably repeatedly used
with multiple fluidic devices, it may be necessary to have sensors
on both the fluidic device and reader assembly to detect such
changes during shipping, for example. During shipping, pressure or
temperature changes can impact the performance of a number of
components of the present system, and as such a sensor located on
either the fluidic device or reader assembly can relay these
changes to, for example, the external device so that adjustments
can be made during calibration or during data processing on the
external device, or both. For example, if the pressure of a fluidic
device dropped to a certain level during shipping, a sensor located
on the fluidic device could detect this change and convey this
information to the reader assembly when it is inserted into the
reader assembly by the user. There may be an additional detection
device in the reader assembly to perform this, or such a device may
be incorporated into another system component. In some embodiments
this information may be wirelessly transmitted to either the reader
assembly or the external device. Likewise, a sensor in the reader
assembly can detect similar changes. In some embodiments, it may be
desirable to have a sensor in the shipping packaging as well,
either instead of in the system components or in addition to.
[0054] In some embodiments at least one of the different layers of
the fluidic device may be constructed of polymeric substrates. Non
limiting examples of polymeric materials include polystyrene,
polycarbonate, polypropylene, polydimethysiloxanes (PDMS),
polyurethane, polyvinylchloride (PVC), and polysulfone.
[0055] In some embodiments the reader assembly comprises an
identifier detector for detecting or reading an identifier on the
fluidic device, a controller for automatically controlling the
detection assembly and also mechanical components of the reader
assembly, for example, pumps and/or valves for controlling or
directing fluid through the fluidic device, a detection device for
detecting a signal created by an assay run on the fluidic device,
and a communication assembly for communicating with an external
device.
[0056] In preferred embodiments the reader assembly houses a
controller which controls actuating elements which may include a
pump and a series of valves to control and direct the flow of
liquid within the fluidic device. In some embodiments the reader
assembly may comprises multiple pumps. The sample and reagents are
preferably pulled through the fluidic channels by a vacuum force
created by sequentially opening and closing at least one valve
while activating a pump within the reader assembly. Methods of
using a valve and pump to create a vacuum force are well known.
While a negative pulling force may be used, a positive or pushing
force may also be generated by at least one pump and valve
according to the present invention. In other embodiments movement
of fluid on the fluidic device may be by electro-osmotic,
capillary, piezoelectric, or microactuator action.
[0057] FIGS. 5 and 6 illustrate an exemplary sequence to initiate
the flow of a reagent within the fluidic device. An actuation plate
18 in the reader assembly comprises a non-coring needle or pin 20
which when lowered flexes the top cover 16, as it is preferably
made of strong, flexible elastomeric material. However, the easily
rupturable foil 12 then ruptures due to the stress induced by the
flexing of top cover 16. Valves located downstream to the reagent
chamber 10 puncture different areas of foil in the fluidic device
and can then work in tandem with a pump within the reader assembly
to create a vacuum force to pull the reagent out of the reagent
chamber 10 into a fluidic channel 14 and then direct the flow of
the reagent to a reaction site. At least one valve is preferably
fluidically connected to a pump housed within the reader assembly.
One of the advantages of this embodiment is that no on-chip pump is
required, which, at least, decreases the size and cost of the
fluidic device, and allows the device to be disposable.
[0058] A reaction assembly preferably houses a detection assembly
for detecting a signal produced by at least one assay on the
fluidic device. FIG. 1 illustrates an exemplary position of a
detection device below the fluidic device after it is inside the
reader assembly. The detection assembly may be above the fluidic
device or at a different orientation in relation to the fluidic
device based on, for example, the type of assay being performed and
the detection mechanism.
[0059] A communication assembly is preferably housed within the
reader assembly and is capable of transmitting and receiving
information wirelessly from an external device. Such wireless
communication may be bluetooth or RTM technology. Various
communication methods can be utilized, such as a dial-up wired
connection with a modem, a direct link such as a T1, ISDN, or cable
line. In preferred embodiments a wireless connection is established
using exemplary wireless networks such as cellular, satellite, or
pager networks, or a local data transport system such as Ethernet
or token ring over a local area network. In some embodiments the
information is encrypted before it is transmitted over a wireless
network. In some embodiments the communication assembly may contain
a wireless infrared communication component for sending and
receiving information.
[0060] In preferred embodiments an external device communicates
with the communication assembly within the reader assembly. An
external device can wirelessly communicate with a reader assembly,
but can also communicate with a third party, including without
limitation a patient, medical personnel, clinicians, laboratory
personnel, or others in the health care industry.
[0061] In some embodiments the external device can be a computer
system, server, or other electronic device capable of storing
information or processing information. In some embodiments the
external device includes one or more computer systems, servers, or
other electronic devices capable of storing information or
processing information. In some embodiments an external device may
include a database of patient information, for example but not
limited to, medical records or patient history, clinical trial
records, or preclinical trial records. In preferred embodiments, an
external device stores protocols to be run on a fluidic device
which can be transmitted to the communication assembly of a reader
assembly when it has received an identifier indicating which
fluidic device has been inserted in the reader assembly. In some
embodiments a protocol can be dependent on a fluidic device
identifier. In some embodiments the external device stores more
than one protocol for each fluidic device. In other embodiments
patient information on the external device includes more than one
protocol. In preferred embodiments the external server stores
mathematical algorithms to process a photon count sent from a
communication assembly and in some embodiments to calculate the
analyte concentration in a bodily fluid sample.
[0062] A server can include a database and system processes. A
database can reside within the server, or it can reside on another
server system that is accessible to the server. As the information
in a database may contains sensitive information, a security system
can be implemented that prevents unauthorized users from gaining
access to the database.
[0063] One advantage of the present invention is that information
can be transmitted from the external device back to not only the
reader assembly, but to other parties or other external devices,
for example without limitation, a PDA or cell phone. Such
communication can be accomplished via a wireless network as
disclosed herein. In some embodiments a calculated analyte
concentration or other patient information can be sent to, for
example but not limited to, medical personal or the patient.
[0064] In some embodiments a sample of bodily fluid can first be
provided to the fluidic device by any of the methods described
herein. The fluidic device can then be inserted into the reader
assembly. An identification detector housed within the reader
assembly can detect an identifier of the fludic device and
communicate the identifier to a communication assembly, which is
preferably housed within the reader assembly. The communication
assembly then transmits the identifier to an external device which
transmits a protocol to run on the fluidic device based on the
identifier to the communication assembly. A controller preferably
housed within the reader assembly controls actuating elements
including at least one pump and one valve which interact with the
fluidic device to control and direct fluid movement within the
device. In some embodiments the first step of the assay is a wash
cycle where all the surfaces within the fluidic device are wetted
using a wash buffer. The fluidic device is then calibrated using a
calibration assembly by running the same reagents as will be used
in the assay through the calibration reaction sites, and then a
luminescence signal from the reactions sites is detected by the
detection means, and the signal is used in calibrating the fluidic
device. The sample containing the analyte is introduced into the
fluidic channel. The sample may be diluted and further separated
into plasma or other desired component at a filter. The separated
sample now flows through the reaction sites and any present
analytes bind to probes bound thereon. The plasma of sample fluid
is then flushed out of the reaction wells into a waste chamber.
Depending on the assay being run, appropriate reagents are directed
through the reaction sites to carry out the assay. All the wash
buffers and other reagents used in the various steps, including the
calibration step, are collected in wash tanks. The signal produced
in the reaction sites is then detected by any of the methods
described herein.
[0065] The term "analyte" according to the present invention
includes without limitation drugs, pharmaceutical agents, drug
metabolites, biomarkers such as expressed proteins and cell
markers, antibodies, serum proteins, cholesterol, polysaccharides,
nucleic acids, biological analytes, biomarker, gene, protein, or
hormone, or any combination thereof.
[0066] Communication between a reader assembly and an external
storage device allows for a reader assembly of the present
invention to download a fluidic device-specific protocol to run on
the fluidic device based on the identity of the fluidic device.
This allows a reader assembly to be used interchangeably with any
appropriate fluidic device described herein. In addition, the
external device can store a plurality of protocols associated with
a given fluidic device, and depending on, for example, a subject's
treatment regime or plan, different protocols can be communicated
from the external device to the reader assembly to be run on the
fluidic device to detect a variety of analytes. The external device
can also store a plurality of protocols associated not only with a
fluidic device, but also with a particular subject or subjects,
such that a protocol can be associated with a subject as well as
with a fluidic device.
[0067] In some embodiments a method of improving the accuracy of an
assay performed on a fluidic device used to detect an analyte in a
bodily fluid comprises providing a system for detecting the
presence of an analyte in a bodily fluid from a subject comprising
a fluidic device for providing said bodily fluid and a reader
assembly for detecting the presence of said analyte, and providing
a sensor to detect a change in said system which may alter the
accuracy of said detecting said presence of said analyte.
[0068] In some embodiments a sensor may be present either in the
fluidic device, the reader assembly, both, or in some cases it may
be advantageous to include a sensor in the packaging in which the
fluidic device and/or reader assembly are packaged. The sensor can,
for example without limitation, detect temperate or pressure
changes that may provide for an inaccurate analyte concentration
calculation. For example, if the temperature of reagents stored in
said fluidic device falls outside an acceptable temperature range,
this may indicate that the detection will not be accurate using the
then existing calibration and processing algorithms, for example.
Likewise, for example, the pressure in the pump in the reader
assembly may fall outside an acceptable range. In some embodiments
a moisture sensor is provided to detect the presence of moisture in
the cartridge before the assay begins. In some embodiments there
may be thiosyanate in one layer of the fluidic device and iron salt
in another layer, wherein a dye is formed when these are mixed,
whereby the dye is a visual indication of the presence of
moisture.
[0069] In some disposable systems, particularly in those where
sample acquisition is performed by the patient or end user,
measurement errors are not uncommon. Significant errors due to, for
example, patient handling of the sample, could be due to the sample
collection method. A patient may not collect the correct volume of
the sample, the collection may not be performed at the appropriate
time, or the sample may not be handled in an appropriate manner,
thus compromising the sample integrity. It may be advantageous when
using a disposable system in which the patient controls the initial
sample collection and handling to utilize methods for minimizing
the consequences of such errors by, for example, either alerting
the patient to repeat the test or use calibration steps to
compensate for such errors.
[0070] Immunoassays have a characteristic response similar in form
to the well-known Scatchard binding isotherm (Bound/Maximum Bound
(B/B0)=Ligand Concentration/(K+Ligand Concentration) where B is the
amount of the labeled analyte bound to a solid phase when analyte
is present, B0 is the amount bound when no analyte is present and K
is the dissociation constant. The mathematical form of such assay
responses is hyperbolic.
[0071] Results of immunoassays of the types described above are
typically analyzed using the known (ln-logit) or (log-logit)
functions, in which the assay label (for example in a two-step
process, alkaline phosphatase-labeled analyte) bound to a solid
phase when analyte is present in the assay ("B") is compared with
the amount bound when no analyte is present ("B0)" to provide the
ratio B/B0. Then, the "logit" function (logit=Log
[(B/B0)/(1-B/B0)]) is plotted against Log (Analyte Concentration)
resulting in a straight line. (Natural logarithms can also be used
instead of logarithms to base 10). The slope and intercept of this
plot can be used to derive simple equations that permit the
calculation of (a) assay signal as a function of analyte
concentration, or (b) analyte concentration as a function of assay
signal. An example of such analysis is shown in FIG. 21 using
Thromboxane as the analyte of interest. The best fit to the data is
given by Equation 1: Signal=(A-D)/(1+(Analyte conc./C) B)+D
[Equation 1], where A is the signal at zero analyte concentration,
D is the signal at infinite analyte concentration, C is the analyte
concentration reached at a signal level half way between A and D,
and B is a shape parameter. The relationship between analyte
concentration and signal is given by: Analyte
concentration=C*((((A-D)/(Signal-D)-1) (1/B)) [Equation 2], where
A, B, C and D are identical to the parameters used in Equation
1.
[0072] It is possible to compute errors that occur from
mis-calibration using the equations described herein above. (The
Analyte Concentration function from Equation 2 is differentiated
with respect to each potential variable A, B, C, D and Signal).
Estimates of the difference between the ideal value of the variable
and the actual value in the system are used as .DELTA. values in
the calculation
(.DELTA.(concentration)=(d(Concentration)/d(Param.))*.DELTA.Param).
Errors in calibration are reflected in erroneous values of A, B, C
and D. Each of these parameters is influenced by a different
factor. For example, temperature effects on calibration of
immunoassays will have the strongest impact on the A, C and D
parameters of the ln-logit calibration, while likely having a
minimal impact on the shape parameter B. The detected signal, which
in turn can be used to determine the analyte concentration, is
biased by one or more of the following reader assembly and fluidic
device characteristics: optics used in the instrument for signal
measurement, temperature control; most chemical processes are
highly temperature sensitive, including enzyme reactions, and
equilibrium between antigens and antibodies; timing of assay steps;
calibration relative to an "ideal" instrument; the inability of the
patient to manually recalibrate the fluidic device when used;
dimensions of the fluidic device; volume of the assay assembly and
its shape; fluid movement within the device; timing and uniformity
of fluid movement; efficiency in mixing (most assay methods used in
disposables and employ microfluidics would involve some mixing).
The following reagent variations can also contribute to a biased
detected signal: reagent quantity; reagent dissolution (if it is in
dry form); changes in activity of reagents following manufacture
(instability) (This is particularly important for "distributed
systems" where the disposable useful life is typically determined
by reagents which can, for example, lose 20% of their activity. If
they can be used without significantly compromising assay
performance, the shelf-life of many expensive disposables could be
extended several fold and severe constraints on disposable storage
(refrigeration and the like) can be relaxed). In addition, when
calibration is performed at the factory, small errors in the
estimation of the calibration parameters can result in error in the
calculated analyte concentration.
[0073] The magnitudes of these calibration errors and consequently
errors introduced in estimating analyte concentrations can be quite
significant. FIG. 7 shows the dose-response data for a two-step
assay for Thromboxane. The top curve (Logit.test) in FIG. 8 shows a
typical (ln-logit) assay response. When we adjust the level of the
highest signal (A) and the lowest signal (D), shown as "Shift zero
signal" and "Shift 100% signal", respectively, the curves shift as
seen in FIG. 8. The corresponding computed values of error in the
concentration that would be calculated from Equation 2 were large
(>20% across the entire range of the assay) as shown in FIG. 9.
In FIG. 8, the signal is normalized by subtracting the D value from
the signal and dividing the difference by (A-D):(Signal-D)/(A-D).
This yields what is usually described as B/B.sub.0 (the ratio of
bound label at a given analyte concentration to that at zero
analyte level). The ln-logit function was modified by adding 10% of
(A-D) to D or subtracting 10% of (A-D) from A before recalculating
the normalized signals (corresponding to two types of significant
calibration error (shifting the value of A or D respectively). At
signal levels intermediate between A and D the change made was
adjusted by 10%*(Original signal-D)/(A-D). FIG. 9 shows that when
modifications of only 1%*(A-D) were made, and concentration of the
analyte was computed, errors in concentration were still
significant at certain parts of the analyte concentration
range.
[0074] Conventionally, a calibration exercise is performed in
parallel with assaying the sample. This is, however, impractical in
a self-contained, disposable assay system intended to be compact
and inexpensive. To address any calibration challenges that may
occur while assaying analytes using a fluidic device of the present
invention, in some embodiments parameters A, or in preferred
embodiments A and D, of Equation 1 described herein above, are
measured within the fluidic device rather than using manufacturer's
values or an external device. The value(s) is compared with the
parameter values estimated when the fluidic device was calibrated
by the manufacturer. Signal results are then adjusted using the
following equation: Signal.sub.adjusted=Signal*(A.sub.factory
calibration/A.sub.measured within the assay) and the original
calibration equation (Equation 1) is then used to calculate the
analyte concentration. Alternatively, A and D values measured at
the time of assay are substituted for the A and D values obtained
during factory calibration. Typically the (A/D) calibration
measurement would be made in a buffer sample, preferably for each
analyte (in a multiple analyte assay device), or one analyte only,
if each assay responds similarly to the various factors that alter
the calibration parameters.
[0075] In some embodiments of this invention, the calibration
parameters of Equation 1 are corrected using differential
calibration. The following example using Thromboxane B2 as the
analyte illustrates this approach. Thromboxane B2 (TxB2) (1.25 mg)
was dissolved in a mixture of dimethylsulfoxide (342 .mu.l) and
water (342 .mu.l). To this, 5 .mu.l of a solution of
1-(3-(dimethylamino)propyl)-3-ethyl-carbodiimide hydrochloride in
water (0.1 g/ml) and 10 .mu.l of a solution of
n-hydroxy-succinimide in water (0.1 g/ml) were added. After 1 hour
at room temperature the resulting NETS-ester of TxB2 was used in
the preparation of TxB2 labeled with alkaline phosphatase
(described below) without further purification. Alkaline
phosphatase (bovine intestine, Sigma-Aldrich) was dissolved in
phosphate-buffered saline at 1 mg/ml. To 1 ml of this solution 120
.mu.l of the NETS-ester of TxB2 was added and the mixture allowed
to react for 1 hour at room temperature. The enzyme-TxB2 conjugate
was then purified overnight by dialysis against tris-buffered
saline containing MgCl.sub.2.
[0076] Described is an example of a two-step enzyme immunoassay
where TxB2 is the analyte. Samples and mouse monoclonal anti-TxB2
(15 .mu.l of Cayman Chemical Kit Catalog number 10005065,
appropriately diluted into Assay Designs buffer) were added to
384-well plates to which anti-Mouse IgG had been immobilized
((Becton Dickenson 356177)). The sample was 30 .mu.l of plasma
diluted 1:4 with assay buffer (Assay Designs Correlate-CLIA.TM. kit
910-002) and supplemented with known concentrations of TxB2. Other
types of sample (for example TxB2 dissolved in assay buffer) can be
substituted.
[0077] Plates were covered to prevent evaporation and incubated at
room temperature with gentle mixing (100 rpm) on an orbital shaker
for 12 hours. The contents of the wells were then removed by
aspiration. Thromboxane-labeled with alkaline phosphatase (25 .mu.l
diluted 1:1500 with assay buffer) was added and incubated at room
temperature for 2 minutes. The contents of the wells were removed
by aspiration and wells washed thrice with 100 .mu.l wash buffer
(from the Assay Designs Kit 910-002).
[0078] Enzyme bound to the wells was then measured by addition of
40 .mu.l Lumiphos.TM. 530 substrate solution which contains
(4-methoxy-4-(3-phosphate-phenyl-spiro-[1,2-dioxetane-3,2'-adamantane])).
Incubation was allowed to proceed for 1 hour with orbital mixing
and the luminescent product measured in a Molecular Devices MD5
Spectrometer (0.5 second integration time).
[0079] FIG. 7 shows the typical assay dose-response data for a
two-step assay for TxB2. Using Equation 1, the parameters A, B, C
and D are fitted to the curve shown in FIG. 7. As described herein,
even small changes in values of the parameters A and D can have a
significant impact on the measured concentration. Thus, any errors
in computing A and D are magnified in the estimated analyte (TxB2)
concentration. This concept is illustrated in FIGS. 8 and 9, where
even a 1% change in (A-D) resulted in significant errors in
estimating TxB2 concentrations in the samples. In FIG. 8, the
signal is normalized by subtracting the D value and dividing the
difference by (A-D) viz: (Signal-D)/(A-D). This calculates what is
commonly described as B/B0 (the ratio of bound label at a given
analyte concentration to that at zero analyte level). The
(ln-logit) function was modified by adding 10% of (A-D) to D or
subtracting 10% of (A-D) from A before recalculating the normalized
signals (corresponding to two types of significant calibration
error (shifting the value of A or D respectively). At signal levels
intermediate between A and D, the change made was adjusted by
10%*(Original signal-D)/(A-D). FIG. 9 shows the computed errors in
estimating the analyte concentrations for a 1% error in estimating
A and D. As can be seen for the low analyte concentrations, the
errors are pronounced even for small errors in the calibration
parameters A and D.
[0080] FIGS. 10-13 illustrate an embodiment of this invention where
the sample containing an unknown analyte concentration is spiked
with a known concentration of the analyte to minimize calibration
errors. Spiking can be achieved by a variety of methods, for
example, by incorporating analyte in known quantities to the assay
well during manufacture of the fluidic device. Separate spike wells
could also be accommodated in the fluidic device described herein.
FIG. 10 shows calibration using differences between signal response
between unspiked and spiked samples. The amount of the spiked
analyte is indicated by x2 and the original (endogenous
concentration in the sample) is denoted as original concentration
or x1 (pg/ml). The difference in signal between unspiked and spiked
sample is plotted against the signal for the original concentration
for various amounts of known amount of analyte (spike) introduced
into the sample. The (ln-logit) parameters (for the top curve in
FIG. 10) are shown in Table 1.
TABLE-US-00001 TABLE 1 Original Calibration Parameters for Data
Shown in FIG. 10 A 3.37E+04 B 1.01E+00 C 2.10E+02 D 3.56E+03
[0081] The data shown in the top curve in FIG. 10 were used in a
recalibration exercise by calibrating against the difference in
signal for each original concentration level and each level spiked
with 200 pg/ml analyte. Equation 3 shown below was empirically
derived and is useful in calculating the original endogenous
concentration of analyte. The best-fit parameter values in Table 2
were computed by minimization of the sum of the square of the
differences between target and calculated analyte values.
Concentration=C*((A-D)/((Signal-D) (1/B))+E [Equation 3].
TABLE-US-00002 TABLE 2 Calculated Parameter Values for 1-point
Spike Calibration A 1.20E+02 B 1.996189 C 292.7824 D -0.14393 E
-287.931
[0082] This calibration was verified as shown in FIG. 11 (log
scale) and FIG. 12 (linear scale). Note the regression equation was
calculated for data in linear form. The formula resulted in near
perfect results.
[0083] The results of one embodiment of this invention are shown in
FIG. 13, where the extent of the recovery of the spike signal is
used to correct for the concentration of the value of the unspiked
sample. This method has the advantage that changes in the parameter
C in the (ln-logit) equation due to, for example, reagent
instability, are accounted for. The method involves the following
steps: calculate x1 (endogenous conc.), and x2 (spike conc.) using
original calibration; calculate recovery of spike as %
(x2-x1)/spike [Equation 4]; correct x1 by recovery factor:
(x1*100/Spike recovery) [Equation 5].
[0084] This was tested with the calibration curve shown in FIG. 10
and the original calibration parameters of Table 1. As shown in
Table 3, it was possible to use spike concentration values from
100-500 pg/ml and C values that varied from 500 to 50 such that the
actual signals corresponding to the modified C values were changed
very significantly from what had been the case with the original C
value and the spike recovery (calculated with the original C value
ranged from 42-420% respectively, yet the recovery of the unspiked
sample (once corrected for the recovery of the spike) was 100% over
the entire calibration range. This effect is graphically
illustrated in FIG. 14, where the C parameter is varied between 50
and 500 (a ten fold range), but the corrected values for the
analyte concentration (x1) accurately reflects the expected analyte
concentration.
TABLE-US-00003 TABLE 3 Effects of changes in the C parameter on
spike and original analyte recovery at two original concentration
levels x1 x2 S x2 recovery x1 recovery C Pg/ml S (x1) pg/ml (x1 +
x2) % % 500 100 2.88E+04 500 1.73E+06 42 100 210 100 2.40E+04 500
1.13E+04 100 100 50 100 1.36E+04 500 5.83E+03 420 100 500 316
2.21E+04 500 1.50E+04 42 100 210 316 1.56E+04 500 9.66E+03 100 100
50 316 7.61E+03 500 5.25E+03 420 100 500 100 2.88E+04 200 2.25E+04
42 100 210 100 2.40E+04 200 1.60E+04 100 100 50 100 1.36E+04 200
7.80E+03 420 100 500 316 2.21E+04 200 1.84E+04 42 100 210 316
1.56E+04 200 1.22E+04 100 100 50 316 7.61E+03 200 6.16E+03 420
100
[0085] In Table 3, x1 is the endogenous concentration and x2 is the
spike concentration; S is the signal level corresponding to the
designated analyte concentration; x2 recovery is the apparent
recovery of x2 and x1 recovery is calculated (using Equation 5)
after compensating for x2 recovery (using Equation 4).
[0086] The spike level must be carefully chosen. The optimal level
will be a compromise between the operating range of the assay and
the likely range of concentrations of samples. If it is too low,
the change in signal caused by the spike will be too small to be
reliably measured. If it is too high, the assay response will be
too shallow to reliably measure the spike. The ideal spike level
would change the measured signal by much more than the standard
deviation in the signal. In the above example, the assay range had
been adjusted to make measurements for sample with concentrations
in the range of about 0 to about 500 pg/ml and spikes of about 200
to about 1000 pg/ml would likely be useful.
[0087] In some embodiments the following various guidelines for
choosing spike levels can be followed: spikes should change the
observed signal across the desired range by at least 10%; spikes
should be in the same range as the anticipated mid range of sample
concentrations; spikes should be less than about three times the
original C value. Note that the useful part of the dose-response is
from about 0.2*C to about 5*C.
[0088] The following example illustrates the estimation of
endogenous TxB2 concentrations using spike recovery. Two citrated
human plasma samples were analyzed by the two-step assay. Aliquots
of the samples were also supplemented (spiked) with known
concentrations of TxB2 prior to assay. Some samples were also
supplemented with indomethacin (0.1 mM) and/or EDTA (5 mM). Samples
were stored either flash-frozen then thawed or refrigerated
unfrozen prior to assay. These procedures generated a set of
samples with various original endogenous concentrations (storage
and freezing and thawing tends to cause platelet activation and
production of TxB2; indomethacin inhibits TxB2 production).
[0089] The results of the above experiment are shown in FIG. 13.
Sample 5A was known to have a very low TxB2 concentration
(estimated to be <10 pg/ml). When the dose-response of the assay
in sample 5 was used to calibrate the assay, the concentration was
assumed to be zero. Dose responses for the other samples 4A, 4N, 5N
were then plotted and it was observed that their response
corresponded to higher concentrations of TxB2 and could be fitted
to the 5N response by moving each to the left (in the direction of
lower concentration) by an amount corresponding to removing a
certain fixed TxB2 concentration from each the known spike levels.
All the samples had responses that were almost identical in shape
to that of sample 5N. When the curves fitted as closely as possibly
to the A5 curve, the concentration of TxB2 notionally removed
corresponds to the estimate of the TxB2 concentration in the
sample.
[0090] The original data of FIG. 13 were represented in FIG. 15 by
the best fit (ln-logit) approximation. The Solver function in
Microsoft Excel was used to compute a value of TxB2 that caused the
A5 response to approximate that of the sample N5. As can be seen,
this generated a good fit and the computed value (471 pg/ml) is an
estimate of the concentration difference between TxB2 levels in the
two samples.
[0091] In another embodiment of our invention a single point can
could be used (all the points fit closely to the calibration curve,
so any single point could have been used) rather than a multi point
spike that was illustrated in the earlier FIGS. 10-13. The
following experiment illustrates this concept. Two plasma samples
were spiked to many levels of TxB2 and assayed by the two-step
method. Assays were calibrated using buffer calibrators rather than
plasma-based materials. Results are presented in FIG. 16. Plasma
was analyzed as described earlier. Data in FIG. 16 are plotted on a
log scale. The concentration of unspiked samples was calculated
from the calibration and the concentration of spiked samples taken
as "endogenous+spike." Results are plotted only for the spiked
samples. As can be seen, there was desirable correlation between
the calculated and known values over the range of about 50 to about
10,000 pg/ml. When recovery was estimated for spikes in the range
about 40 to about 2,500 pg/ml, the correlation was 99.7%.
[0092] Spike recovery method for correcting the calibration
parameters are useful for compensating temperature effects on
immunoassays in self-contained disposable analytical systems, also
some times referred to as handheld analytical systems or assay
systems. As is well known, instabilities in temperature during an
assay introduce significant errors in the estimated analyte
concentration. Temperature effects on calibration of immunoassays
have the strongest impact on the A, C and D parameters of the
(ln-logit) calibration. It is likely that the B (shape) parameter
is minimally affected by temperature changes. As shown above, the
spike recovery method can correct for errors introduced in the C
parameter and hence could be an excellent approach for correcting
temperature induced errors in computing the calibration parameters
of the (ln-logit) equation. Similarly, normalizing signal levels to
the zero analyte calibrator level, as described earlier, can
compensate for errors in the A and D parameters, which are again
negatively influenced by temperature changes.
[0093] Internal calibration and/or spike recovery means of
calibration have significant advantages over conventional
factory-calibration methods. One obvious advantage is that two
quantities of assay-related information are used to compute the
assay result rather than one, which improves the reliability of the
assay. A second advantage is that this approach compensates, to a
large extent, reagent instability. Another advantage is that
several instrument, assay environment, and procedural variables are
factored into the assay results.
[0094] Other uncontrolled changes in system response, besides
temperate change, can also negatively impact the computed A and D
parameters. For example, FIG. 17 shows the time course of the
signal generation during an assay. To correct for these errors, one
embodiment of the claimed invention is to compare assay signals B
in a fluidic device with the B0 signal so to eliminate errors due
to variation of the absolute value of assay signals due to
uncontrolled changes in system response. This concept was verified
by the following experiment.
[0095] A competitive immunoassay for TxB2 was set up using the
protocol described in Assay Designs Product Literature for their
corresponding Correlate-CLEIA kit (catalog 910-002). An alkaline
phosphatase conjugate was prepared as described earlier and was
diluted 1:112,000 and substituted for the kit conjugate. A and D
parameters are the calibration parameters used in the (log-logit)
fit to the assay response. Best fit values were obtained at each
time point. Note that at zero time the A and D parameters are not
measured, but all signal values would be (are known to be) zero.
The ratio D/A was multiplied by 1e6 so as to be presentable on the
same scale. The A and D values when plotted against time vary
significantly, particularly the A value (zero analyte). As seen
from the straight line with practically zero slope, the scaled D/A
remains constant over the time span.
[0096] The above experimental data were then analyzed by
normalizing the assay signal (B) to signal at zero analyte
concentration (B0). Using this normalized signal (B/B0),
(log-logit) best fits were obtained for each time point and
averaged. Concentrations of analyte were computed using these
calibration parameters for each time. FIG. 18 shows the derived
concentrations that were plotted against the A parameter derived
for each individual time point. Each line corresponds to different
analyte levels (pg/ml) ranging from about 39 to about 10,000 pg/ml.
As can be seen from FIG. 18, although signal values changed by
about 2-fold during the course of the experiment, the derived
analyte concentration was essentially constant over the analyte
concentration spanning a range of about 39 to about 10,000 pg/ml.
The variation of calculated concentration was computed and found to
average only 2.7% over the calibration range of 39-625 pg/ml (which
spans most of the range).
[0097] A calibration spike can be enabled by adding analyte to the
antibody (or other solid phase capture agent) during manufacturing,
and then drying. subsequently adding analyte to the appropriate
well during manufacturing (then drying), or adding analyte to a
portion of assay buffer which is then routed to the appropriate
well. Methods 1 and 2 have a risk which is that the spiked analyte
could be flushed from the well as sample or buffer enters. This may
be handled in one of several ways such as relying on the tightness
of the antigen: antibody interaction for the brief time the well is
subject to flowing sample or buffer (which exit from the well), or
careful management of liquid flow and placing the spike well as
that most distal to the incoming liquid (last well to fill has the
least flow through).
[0098] Errors in measuring analyte concentrations could also be due
to variability in the pre-analysis phase. The primary cause of this
type of errors is due to the patient collecting an incorrect volume
of sample or where the sample integrity has been compromised.
Errors due to incorrect sampling volume can by corrected by a
variety of means. One method is to measure the volume of the sample
during a pre-processing step. If the measured volume is
significantly different from the expected volume, the patient could
be instructed to provide a new sample. This could be accomplished
by, for example, the wireless communication with the external
device as described herein. Alternatively, the analytical methods
or algorithms on the external device could be recalibrated to
compensate for the change in the sample volume. The recalibration
could be using any of the standard calibration techniques or the
modifications to the calibration process, which have been described
herein.
[0099] The following is a description of one embodiment of a method
for determining the accuracy of the volume of the sample provided
to the sample collection unit of a fluidic device described herein.
The sample collection unit can be lined with conductive elements
spaced apart at known separations--similar to the graduations on a
measuring cylinder or jar. The location of each conductor can
correspond to a specific sample volume. As fluid comes into contact
with the conductor, the measured conductivity of that conductor
would be markedly increased. By identifying the highest placed
conductor that has undergone the conductivity change, the volume of
the sample in the sample collection unit can be computed.
[0100] Alternatively, if the sample volume has to meet a minimum, a
conductive element could be placed at the appropriate level in the
well. When the cassette is introduced into the handheld (or the
sample holder is introduced in the analytical system), thereby the
patient has indicated that she has completed the sampling process,
and if the conductivity of the sensor remains at the baseline
level, it could be easily concluded that the patient has not
provided the required sample volume. The patient could be given the
appropriate feedback such as replacing the sample or replenishing
it. Alternatively, the back-end server or computer at the network
headquarters could be informed of the issue and appropriate
corrective measures taken. An alternative to the electrical sensing
for the correct volume could be using known optical sensing
means.
[0101] Sample integrity could be affected by many factors, some
intrinsic to the patient and some that are extrinsic. Following are
some of the sources of errors in sample integrity: (i) mixing of
interstitial fluid with blood; (ii) variability in the hematocrit
concentration; (iii) hemolysis; and (iv) activation of platelets
and sample clotting.
[0102] Occasionally, interstitial fluid may leak from a
finger-puncture wound and could mix with blood. Alternatively, if
the patient had liquid on her hands due to washing prior to
obtaining a blood sample, such liquid could also mix with blood
plasma. Both fluids mentioned, above, interstitial fluid and wash
liquid, contain no red cells and would mix with the blood plasma.
When the amount of interstitial fluid is large so that the
effective hematocrit is very low, the measured concentration of the
external standard (fluorescein) would be low. This signal could be
used to conclude that the sample is inappropriate for analysis and
that it could lead to incorrect results. When blood is contaminated
by water (which has low conductivity), it would be possible to
detect this by measuring the conductivity of the fluid part of the
sample (blood plasma has a characteristic high conductivity not
subject to variation from day-to-day or individual-to-individual).
If the measured conductivity of the sample is lower than the plasma
conductivity, it is likely that the sample has been
contaminated.
[0103] Errors could also be due to incorrect operation of the
instrument and means of detecting and compensating those errors are
described below. One source of error could be that the disposable
is not properly accommodated in the handheld system. Having a
sensor detect and report the proper mating of the disposable in the
handheld would be one means of avoiding this problem. Another
source of errors is from the fluidic system, where there may be an
issue with where the sample is applied in the sample well and the
volume of the applied sample. This could again be addressed by the
use of appropriate sensors which detect the application of a sample
and report on the adequacy of the volume that is applied. Other
fluidics related problems could be blocked channels, insufficient
reagents, bubbles, etc., all of which again could be detected and
reported by the use of appropriate sensors.
[0104] In some embodiments any of the errors described herein can
be measured using sensors located on either the fluidic device or
the reader assembly. In some embodiments an error messages could be
displayed on an LCD screen in the reader assembly using the
processing power of the microchip on the handheld. Alternatively, a
signal from the sensors could be communicated to the external
device which can then relay an error message to either the reader
assembly or a third device such as a PDA or cell phone. Such action
could be a message communicated to the patient in the form of an
audio, video or simple text message that the patient could receive.
In some embodiments the external server can transmit corrected
calibration parameters to the reader assembly to compensate for any
of the errors described herein.
[0105] In yet another embodiment, after the identifier is detected
by an identifier detector as described herein to determine, for
example, a protocol, if a signal transmitted by a sensor doesn't
match the expected value for the sensor signal, then the external
device can transmit a pre-programmed alert based on each cartridge
bar code and sensed signal to either, for example, an LCD display
on the reader assembly or to a handheld device, to take a
designated action. Nonlimiting examples of error alerts, the
problems they indicate, and required action to be taken are, for
example:
TABLE-US-00004 Error Code Symbol Problem Action Er1 Thermometer
Temperature out of Wait until Temp >10 or <35 C. range Er2
Blood drop Blood sample too If detected w/in 15 minutes of first
small sample add more blood, other wise use new cartridge Er3
Battery Power disruption Do not start test until power resumes Er4
Bar code symbol Cartridge expired Run test on a non expired
cartridge Er5 Line through Cartridge already Run test on a new
cartridge fluidic device used Er6 Phone receiver No Cell Phone Do
not start test until in coverage coverage area Er7 Line through a
box Reader malfunction Call Theranos Er8 Bottle with a "C"
Calibration overdue Run Calibration standard, then run in the label
test
[0106] After the identifier detector detects the identifier to
determine a protocol and any sensed signals are detected and either
patient notification is complete or calibration parameter are
updated, the fluidic device calibration can occur, followed by the
appropriate assay.
[0107] Despite the corrective actions described here, the generated
analyte concentrations values could still be erroneous. For
example, the actual analyte concentration could be well outside the
expected range, and thus the calibration parameters used may be
incorrect. Values which are unlikely, impossible or inconsistent
with prior data for a particularly patient could be flagged and
subjected to a software review. Values with suspect accuracy can be
communicated to the appropriate decision maker, such as the
patient's physician.
[0108] The concept of the reference therapeutic index (TI) and how
it is computed is illustrated in FIGS. 19 and 20. A TI is computed
from a retrospective analysis of many measured parameters,
including the blood concentrations of drugs of interest, their
metabolites, other analytes and biomarkers in blood that change
concentrations due to the drugs the patient is consuming,
physiologic parameters (such as blood pressure, respiratory rate,
body temperature, heart rate, etc.), and clinical parameters that
indicate disease progression (such as angina, stroke, infarct,
etc.). Typically, many serial measurements would be made for the
many treated patient and corresponding controls (unmedicated or
placebo treated). The clinical parameter would be an "outcome
parameter" (OP). The other measured parameters can be "input
parameters" (IP).
[0109] For the retrospective analysis and TI computation, data from
many subjects and their respective output and input parameters,
including subject's relevant details such as height, weight, race,
sex, family history, etc., would be populated in a database. Each
candidate outcome parameter (stroke, infarct, angina, death, etc.)
will be subject to multiple regression analysis against input
parameters.
[0110] The multiple regression analysis is performed for each
candidate OP versus all available IPs. Database columns are
constructed by using each IP, each IP 2, and all cross-terms
(IPi*IPj). The analysis is then performed using the equation:
OPi=(a*IP1+b*IP2+ . . . n*IPn)+(aa*IP1 2+bb*IP2 2+ . . . +nn*IPn
2)+(aaa*IP1*IP2+bbb*IP1*IP3+ . . . +nnn*IPn-1*IPn), where a . . .
n, aa . . . nn, aaa . . . nnn are arbitrary constants.
[0111] Multiple regression analysis establishes the best fit to the
equation and indicates which IPs are strong candidates for
inclusion. Weakly correlated IPs are dropped and the analysis
repeated until each candidate OP has an optimal relation to the
remaining IPs. The therapeutic index will then have the form:
TI=a*IP+cc*IP3 2+nnn*IP3*IP5+ . . . (Equation 6).
[0112] FIG. 20 illustrates the computation of a TI and the use of
the TI concept for determining therapeutic efficacy (the
therapeutic index is also indicated by the term efficacy index).
The example illustrated in FIG. 20 shows the time course of
successful drug therapy of a disease state (such as
atherosclerosis) that is indicated by three biochemical analytes
represented by parameters A, B and C. The disease is treated (with
for example a Statin) starting on day zero.
[0113] Parameters A, B and C are measured daily using an ambulatory
system as described herein. At the outset, relative to "ideal
levels", Parameter A (for example LDL-cholesterol) is elevated,
Parameter B (for example HDL-cholesterol) is low and Parameter C
(for example, alanine aminotransferase, an indicator of liver
damage) is normal. All parameters (A, B, C) are presented
normalized to their respective ideal level. As therapy proceeds,
the drug causes the levels of A and B to approach normal values but
at different rates. Analyte C remains normal indicating the drug is
not causing liver damage. The relative risk of an outcome for the
patient is represented by an initially unknown TI. As described
above, TI is a surrogate to the outcome parameter that reflects the
physiological functions of the patient (blood pressure, etc.) or
other pre-identified factors in a patient record and can be
indicative of improvement in the patient's condition. We further
assume that parameter TI is influenced by parameters A and B. In
certain cases, at the beginning of the study this relationship
remains to be determined.
[0114] Data from the monitoring system (device input) and the
patient input are analyzed by multiple regression of TI and
measured values A, B and C, as described above. In the example
shown, these data are analyzed using multiple regression analysis,
which fits parameter TI as a function of parameters A, B, C and
their squares and the pair-wise cross terms (A*B, etc.) As shown in
FIG. 20, for the simulated values shown in FIG. 19, an excellent
fit was obtained (R 2=0.99) when all parameters were included. It
is evident from inspection of the fit that most of the parameters
can be eliminated leaving only A and A*B. When this is done the fit
is still very good (R 2=0.95).
[0115] The multiple regression derived function is not identical to
the base function which generated the first candidate TI data, but
works well to compute an estimate of TI from (typically fewer)
measured parameters, prior to clinical validation, if necessary.
The appropriate threshold levels of TI, or the optimum TI is termed
as TI.sub.ref (or "action threshold value".) Expert review can then
determine the optimum therapeutic index for that particular patient
or patient class. If the computed TI exceeds the preset TI.sub.ref,
appropriate action can be taken. An appropriate action could be
alerting the physician, stopping the medication or the like. As can
be understood, the appropriate TI.sub.f for a patient would be
decided based on the healthcare provider's judgment for that
individual patient. The form of the TI is derived as a one time
exercise using expert analysis of the data set derived from
clinical studies and/or existing clinical information.
[0116] Once the TI.sub.ref is identified, then the use of this
parameter is illustrated in FIG. 22. Methods of measuring drug,
analyte and biomarker concentrations and conducting a two-way
communication with a database using a fluidic device and reader
assembly are described in detail herein. The time course of various
measured and computed parameters are shown in FIG. 22. The curve
indicated CBX Dose illustrates the time course of a drug that is
taken on a regular basis. The plotted values are normalized to what
would be considered as "ideal levels" for that measurement. For
example, if the expected ideal blood concentration of CBX is 100
ng/ml and if the measured concentration in blood is 100 ng/ml, the
parameter value is 1.0 (with no offset) for CBX. Similarly, the
concentrations of CXB, a metabolite of CBX, biomarkers Tx-M and
PGI-M, which vary in response to the concentrations of the drug and
the disease state, are also normalized to their ideal values and
plotted. All the drug, analyte and biomarker concentrations could
be measured using a system as described herein. As explained above,
the TI.sub.ref for this particular patient is plotted on FIG. 22 as
a flat line. Using the parameter values (a . . . n, aa . . . nn,
aaa . . . nnn) of Equation 6 and the measured input parameters
(IP), the current TI for the patient is calculated. If the computed
TI exceeds the TI.sub.ref value, then an alert can be generated.
The alert could be targeted to the patient's healthcare provider,
who in turn can take the appropriate action. An appropriate action
could be to watch the patient closely for other clinical
indications and/or alter the dosage and drugs the patient is
taking.
[0117] FIGS. 22 and 23 illustrate the concept as to how when the
computed TI exceeds the TI.sub.ref a proactive action could avert
an ADR. In FIG. 23, the patient's TI exceeded TI.sub.ref about day
15. The patient is monitored closely and as the TI values continue
to increase after day 30, the physician intervenes and reduces the
dosage. This action starts lowering the TI for the patient and
ultimately retreats to an acceptable level about day 60.
[0118] One or more individuals or entities that are involved in the
care of the patient (nurses, physicians, pharmacist, etc.) can be
alerted when the computed TI exceeds the TI.sub.ref so that they
could take the appropriate action. Additionally, trends can be
discerned and appropriate action taken before a TI reaches a
particular value.
[0119] In some embodiments many different analytes can be measured
and construed as input parameters, IPs, while computing the TI.
Such analytes that may be used are described herein. Additionally,
the can be expanded or modified depending on the disease area as
well. The appropriate list of parameters relating to certain
diseases and drug treatments, for example, cancer and infectious
diseases and patient on NSAIDS, are disclosed herein.
[0120] In another aspect of this invention, the TI is calculated
using information derived from the patient's biological sample and
patient information that is non-drug related, the device input. For
example, in an ambulatory setting, information relating to
concentration of drug, metabolite and other biological markers can
be detected in blood as described herein. The patient can also
input many non-drug related personal parameters. This "patient
input" can relate to the patient's personal information, for
example, height, weight, gender, daily exercise status, food
intake, etc. The patient input could also be provided by the
patient's healthcare provider. An example of a patient input
parameter and the input means is shown in FIG. 24.
[0121] In some embodiments the device input and patient input are
used to compute the TI. A reference TI for the patient is already
known using retrospective analysis of the data contained in the
database. In formulating the TI using multiple regression analysis,
the parameters such as those shown in Equation 6 are used. The same
parameters are then used with the device input and patient input to
compute the TI. Comparing the TI to the TI.sub.ref, it is possible
to determine the efficacy of the therapy. If the TI falls within a
pre-determined range of TI.sub.ref, then the treatment is
considered to be efficacious. Values below that range indicate that
the treatment is ineffective and values higher then the range are
considered to be undesirable and could lead to adverse events.
[0122] Another example illustrates the implementation of this
invention for studying the efficacy of therapy in diseases where it
is difficult to make frequent measurements and the efficacy of the
treatment is difficult to quantify. An example is determining the
efficacy of drug therapy in children with autism. Frequent sampling
and concomitant laboratory analysis is impractical for children.
Abnormalities in blood concentrations of certain metals are
implicated in autism. Hence, following the blood concentration of
certain metals, for example, zinc, in autistic children might shed
light on the efficacy of an intervention. However, it has been
reported that lowered concentrations of Zn, for example, due to a
treatment does not imply that the therapy is working. It is an
indicator, but not a definitive surrogate for determining
therapeutic efficacy. Computing a TI and comparing it to a
reference level would better indicate the efficacy. This is
illustrated in FIG. 25 by simulating the concentration of various
pertinent markers and their change due to a drug intervention in an
autistic child.
[0123] The program can involve monitoring subjects and matched
control individuals over time for toxic metals, surrogate markers
for metals (metallothionein, etc.), and other biochemical markers.
Subjects are those prone to, or afflicted with autism; controls are
situation-matched people. It is not mandatory that there be a
situation-matched control. The scenario assumes that during the
study a significant "event" occurs. Events could be movement into a
more or less risky environment or initiation of therapy. Subjects
could be frequently monitored for several parameters (device input)
using the ambulatory system described herein. Additional laboratory
assays that are not determinable in the ambulatory system could be
performed at a lower frequency using laboratory assays. Additional
data such as patient information, local environment, use of drugs,
diet, etc. would be logged (patient input). Of particular interest
to this scenario is information such as exposure to lead, mercury
etc.
[0124] The time course shown in FIG. 25 envisages an event
(initiation of therapy) at 33 days. The subject who is exhibiting
abnormal levels of CP and MT, gradually reverts to normal levels of
markers. The TI captures the risk or safety level of the subject
based on all information. The study will define the best inputs to
determine TI.
[0125] As described above, TI can be used for determining the
efficacy of drug treatment. A similar approach is also well suited
for determining the efficacy of drugs during clinical trials.
Additionally, this approach could be beneficially used to identify
sub-groups of patients who respond well or poorly to a given
treatment regimen. The ability to segregate responders from
non-responders is an extremely valuable tool. The concept of using
TI can be used not only during a therapeutic regimen, but for
performing diagnostic tests to determine, for example, whether or
not a patient is in need of a biopsy after a complete examination
of prostate specific markers.
* * * * *