Разработан первый полевой тест на марихуану

1. Small Molecule Detection in Saliva Facilitates Portable Tests of
Marijuana Abuse
Jung-Rok Lee,†,§
Joohong Choi,‡,§
Tyler O. Shultz,†,§
and Shan X. Wang*,†,‡
†
Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States
‡
Department of Electrical Engineering, Stanford University, Stanford, California 94305, United States
*S Supporting Information
ABSTRACT: As medical and recreational use of cannabis, or
marijuana, becomes more prevalent, law enforcement needs a
tool to evaluate whether drivers are operating vehicles under
the influence of cannabis, specifically the psychoactive
substance, tetrahydrocannabinol (THC). However, the cutoff
concentration of THC that causes impairment is still
controversial, and current on-site screening tools are not
sensitive enough to detect trace amounts of THC in oral fluids.
Here we present a novel sensing platform that employs giant
magnetoresistive (GMR) biosensors integrated with a portable
reader system and smartphone to detect THC in saliva using
competitive assays. With a simple saliva collection scheme, we
have optimized the assay to measure THC in the range from 0
to 50 ng/mL, covering most cutoff values proposed in previous studies. This work facilitates on-site screening for THC and
shows potential for testing of other small molecule drugs and analytes in point-of-care (POC) settings.
Since 1970, cannabis has been classified as a Schedule I
substance under the Controlled Substances Act, indicating
a high potential for abuse and a lack of medical value.1
However, in light of evidence about its therapeutic effect,2,3
23
states and the District of Columbia in the United States have
recently legalized the medical use of cannabis. Four states
(Alaska, Colorado, Oregon, and Washington) have even
legalized its recreational use. These legislation changes have
raised concerns about individuals driving under the influence
(DUI) of marijuana. In fact, the states that have legalized the
drug have reported a substantial increase in cases of DUI of
cannabis.4−6
To regulate DUI drivers, on-site tests for one of
the most potent psychoactive agents in cannabis, Δ9
-
tetrahydrocannabinol (Δ9
-THC, or THC), similar to a
breathalyzer for estimating blood alcohol content (BAC), are
urgently needed. Although the gold standard for forensic
analysis of THC is chromatography combined with mass
spectroscopy using blood samples, the bulky equipment
required for this is not suitable for road tests, and collection
of blood would require testers to have training in taking blood
samples. Moreover, urine tests, which are the most widely used
method in drug testing, can detect only THC metabolites,
which only become detectable in urine at least several hours
after intake of cannabis, far past the window of intoxication and
impairment.7,8
Furthermore, there is preliminary evidence that
the concentration of THC in saliva can be correlated with
impairment.7,9
Thus, for road tests, oral fluids (saliva) are
preferred because they enable noninvasive and rapid measure-
ments of THC. However, two significant problems with on-site
screening of THC in oral fluids exist. The first is that no solid
scientific consensus exists on the cutoff concentration of THC
at which drivers’ performance is clearly impaired,8−10
even
though it is clear that THC impairs its users’ cognitive and
psychomotor abilities.11
A possible reason on the unestablished
cutoff is that pharmacokinetics of THC and its effect are
complicated because THC accumulates in fatty tissues due to
its high solubility in lipids.12
Therefore, the concentration of
THC at the time of measurement could be different from that
when a driver is behind the wheel or under the influence.12−14
Another reason could be that different studies have used
different techniques to detect THC in oral fluids, and this may
further generate discrepancies between the results. The second
problem with on-site screening is that current rapid test tools
are not sensitive enough to detect THC within the various
proposed ranges of cut-offs.7,15
To overcome these problems,
many research groups have developed various techniques to
detect THC in saliva.16−18
Here, we report a mobile technology that facilitates rapid and
precise measurement of THC in oral fluids using magnetic
biosensors. The technology is based on GMR biosensors, which
have been demonstrated to measure cancer,19
radiation,20
and
cardiovascular biomarkers,21
in conjunction with magnetic
nanoparticles (MNPs),22−27
after the advent of the initial
concepts.28
The miniaturized platform with disposable chip
Received: April 28, 2016
Accepted: July 19, 2016
Published: July 19, 2016
Letter
pubs.acs.org/ac
© 2016 American Chemical Society 7457 DOI: 10.1021/acs.analchem.6b01688
Anal. Chem. 2016, 88, 7457−7461

2. cartridges incorporates Bluetooth communication protocols,
which enable POC measurement and compatibility with any
types of smartphones or laptops equipped with Bluetooth ports
(Figure 1A). The GMR biosensor chip consists of 80 sensors
that can be individually functionalized for multiplex assays
(Figure 1B). A new concept of toroidal core coil for applying an
external magnetic field and a compact design of circuit board
reduced power consumption significantly and improved the
portability of the device (Figure S1).
To measure small molecules such as THC (molecular
weight, 314.5 Da), we employed competitive assays instead of
traditional sandwich assays, as demonstrated previously,16
because the small molecules usually lack two binding sites
(i.e., epitopes) required for the sandwich assays.29,30
Even
though these molecules have sufficient epitopes for binding to
two antibodies, the sandwich cannot be formed due to steric
hindrance. Our competitive assay requires only one type of
antibody that can recognize THC and link MNPs to the bound
THC on the surface of the biosensor via biotin−streptavidin
interaction (Figure 1C). The biotinylated antibodies were
added to the sample of interest that contained THC and
incubated for 15 min to bind to THC in the sample as
preincubation (details in Supporting Information). Then, 50 μL
of the mixture were added to the chip where bovine serum
albumin (BSA) and THC conjugated with BSA (THC-BSA)
were immobilized on different sensors to allow unoccupied
antibodies to bind to THC-BSA on the sensors for an
additional 15 min. After washing the chip, the chip cartridge
was inserted into the measurement reader, and 40 μL of
streptavidin-coated MNPs were introduced. The stray field
from the bound MNPs disturbs the magnetization of biosensors
underneath, which changes the resistance of the biosensor. The
changes in resistance, monitored as GMR biosensor signals
(ΔMR/MR0), are proportional to the number of bound
MNPs31
and have an inverse relationship with the concen-
tration of THC in the sample due to the nature of competitive
assays. Figure 1D shows the measurement signals for THC at 5
ng/mL spiked in saliva using the smartphone and customized
app shown in Figure 1A. To the best of our knowledge, this is
the first demonstration that GMR biosensors are capable of
detecting small molecules.
To collect saliva samples from drivers, we have developed a
simple sample collection strategy using a cotton swab, syringe,
and filter unit, which can be easily performed without any
trained medical professional (Figure 2). First, oral fluid is
collected with a cotton swab. The swab is then inserted into a
syringe and squeezed to release the fluid. This step replaces a
centrifuging process, which is not manageable on the road. The
filter unit attached to the syringe further removes viscous
mucus, food particles, and extra debris in the sample. This
approach could also address the contamination issue, previously
reported,32
that causes high concentrations of THC at the
initial measurement. In our testing, we collected saliva samples
from a donor in our research group who claimed to be drug-
free and used them to dilute THC.
Although there is no solid scientific consensus on the cutoff
concentration of THC, most previous studies have suggested
the values ranging from 2 to 25 ng/mL.9,15,33
To achieve better
sensitivity around this range, we optimized the concentration of
anti-THC biotinylated antibodies and incubation time. First,
Figure 1. GMR biosensor platform and competitive assays. (A) Left: a
measurement reader includes a toroid core coil, electrical circuits, and
Bluetooth module. The dimension of the reader is 105 mm × 90 mm.
Middle: a disposable cartridge is based on a customized design of
printed circuit board (PCB) integrated with a GMR biosensor chip
and reaction well. Right: a smartphone with customized app. (B)
Disposable cartridge. GMR biosensor chip was wire-bonded to the
customized PCB, and the reaction well was glued on top of the chip.
The GMR biosensor chip consists of 80 sensors, and the last row (8
sensors at the bottom) are used as electrical reference sensors. As an
example, capture probes (BSA or THC-BSA) were spotted on four
sensors in the middle. The scale bar is 500 μm. (C) Schematic of
competitive assay. Step 1: anti-THC biotinylated antibodies were
mixed with a THC-containing sample and preincubated to bind to
THC. Yellow circles represent THC. Step 2: the mixture was added to
the chip where BSA and THC-BSA were immobilized on different
sensors and incubated for unoccupied antibodies to bind THC-BSA.
Step 3: Unbound antibodies were washed, and MNPs were added to
the chip to read out the signals. (D) Real-time measurement signals.
The chip was added to the reader, and MNPs were then added to the
chip at ∼1.5 min. THC-BSA, BSA, and biotinylated BSA (Biotin-BSA)
were immobilized on different sensors, and signals from these sensors
were monitored. The signals are the average of 8 identical sensor
signals and referenced to the averaged signal from reference sensors.
The error bars represent standard deviations of 8 identical sensor
signals.
Figure 2. Saliva collection scheme. Step 1: A cotton swab, filter unit,
and syringe are prepared. Plunger of the syringe is completely pulled
out. The cotton swab is placed for 1 or 2 min in the mouth of an
individual who is being tested to fully absorb oral fluids. Step 2: The
filter unit is attached to the syringe, and the saturated cotton swab is
loaded into the syringe. Step 3: The cotton swab is squeezed using the
plunger, and the released fluid is collected in a test tube.
Analytical Chemistry Letter
DOI: 10.1021/acs.analchem.6b01688
Anal. Chem. 2016, 88, 7457−7461
7458

3. three different concentrations of antibodies (5, 1, and 0.5 μg/
mL) were tested with zero analyte and THC at 5 and 20 ng/
mL, respectively (Figure 3A). The antibodies at 5 μg/mL
showed less reduction in signals as the concentration of THC
increases compared to other antibody concentrations, which
results in a wider dynamic range. The concentration of 1 μg/
mL produced a fairly linear titration curve within the range,
while 0.5 μg/mL showed a steeper drop at 5 ng/mL of THC
but almost the same signal as 1 μg/mL of antibodies at 20 ng/
mL of THC. In addition, the mass concentrations of antibodies
(1 μg/mL) and THC (5 ng/mL) correspond to 7 nM and 16
nM in molar concentration, respectively. Considering the
bivalency of the antibody, the binding capacity is well-matched.
Thus, the depletion of antibodies by THC was effectively
monitored in the competitive assays, and we therefore used
antibodies at 1 μg/mL for subsequent experiments. To
determine an optimal time frame for incubation of a sample
mixture with the chip, three different incubation times (5, 10,
and 15 min) for the chip incubation were tested with 15 min of
preincubation (Figure 3B). The signals were saturated for
around 15 min, and the difference between signals of 0 and 5
ng/mL of THC was maximized in the case of 15 min of chip
incubation. Using these conditions (1 μg/mL of antibodies and
15 min/15 min incubation), we obtained a titration curve with
a dynamic range from 0 to 50 ng/mL of THC in saliva (Figure
3C). Furthermore, preincubation and chip-incubation times
were reduced to 5 and 10 min, respectively, and the GMR
sensor signals were taken at 5 min after adding MNPs instead
of 10 min to carry out the entire measurement within 20 min
(Figure S2). The result showed no significant loss in
performance. This was because the signal levels of 10 min
chip-incubation was fairly close to those of 15 min incubation
as shown in Figure 3B, and the sensor signals typically reached
their plateaus within less than 5 min after addition of MNPs as
shown in Figure 1D. Moreover, the result revealed that
preincubation time was still not a limiting factor when it was set
to 5 min. Since the preincubation is three-dimensional mixing
and binding between THC and antibodies, which is much faster
than binding of antibodies to THC on planar surfaces during
the chip-incubation, the preincubation could be further
reduced, compared to the chip-incubation. Without any
preincubation, THC in a wider dynamic range (0 to 200 ng/
mL) was detected with 5 μg/mL of antibodies within 3 min of
total assay time (Figure 3D), which showed promise for
roadside testing. In this case, a higher concentration of
antibodies warranted less chip-incubation time to obtain a
substantial signal of antibody binding to THC on the surface.
In a similar manner, the assay can be further tailored to adjust
the sensitivity and dynamic range by changing antibody
concentration and incubation time if the cutoff concentration
of THC is beyond the current range.
Since the binding of the antibodies to THC is a
thermodynamic process, the temperature affects the assay
results and there are day-to-day variations in measurement
signals due to temperature fluctuations, chip-to-chip variations,
or incubation time variations. Thus, to increase accuracy of the
assay and minimize the measurement variation, we have
designed a two-compartment cartridge where two reaction
wells are installed on a GMR biosensor chip to measure both
the sample of interest and a reference sample simultaneously
with the same chip (Figure 4A), which ensures that both
samples experience the same experimental condition including
temperature, incubation time, and biochip fabrication. Since
two samples are measured with the same chip at the same time,
all measurement variation such as chip-to-chip variation,
Figure 3. Optimization of the assay and titration curves. (A)
Sensitivity and dynamic range tuning with antibody concentration.
Three antibody concentrations (5, 1, and 0.5 μg/mL) were tested with
3 different sample concentrations (0, 5, and 20 ng/mL), respectively.
The signals at 5 and 20 ng/mL were normalized by the signal at 0 ng/
mL for each antibody concentration for comparison. (B) Optimization
of chip incubation time. The antibodies at 1 μg/mL were used to
detect both THC at 0 and 5 ng/mL with 3 different chip incubation
durations. A 15 min preincubation was performed to mix the sample
with antibodies. The data point is denoted with an asterisk if Welch’s t-
test shows p < 0.01. (C) Titration curve of the assay with saliva
samples. The concentration of THC in the sample varied from 0 to
100 ng/mL. The biotinylated antibodies at 1 μg/mL and 15 min
preincubation/15 min chip incubation were used. (D) 3 min assays
using single step incubation without preincubation. The mixture of the
sample and antibody was immediately added to the chip and incubated
for 2 min. The concentration of the antibodies was 5 μg/mL, and the
signals were obtained 1 min after adding MNPs. The signals are the
average of 4 identical sensors, and the error bars represent the
standard deviations.
Figure 4. Two-compartment cartridge. (A) Customized design of two-
compartment cartridge. A GMR biosensor chip was wire-bonded to
the PCB, and a two-compartment reaction well with a gasket made of
polydimethylsiloxane (PDMS) was assembled on the chip. Each
compartment includes 20 biosensors. (B) Simultaneous THC
measurement of two samples. Saliva samples containing THC at 0
and 5 ng/mL, respectively, were measured with the same chip using
the two-compartment cartridge. The average and standard deviation of
signals from 4 THC-BSA coated sensors in each compartment (blue
and red) are shown. The p-value was determined using Welch’s t-test.
Analytical Chemistry Letter
DOI: 10.1021/acs.analchem.6b01688
Anal. Chem. 2016, 88, 7457−7461
7459

4. temperature fluctuation, and reagent variation can be reduced
or even eliminated. For demonstration, saliva samples
containing 0 and 5 ng/mL of THC, respectively, were
measured with the two-compartment cartridge (Figure 4B).
With the measurement using the two-compartment cartridge,
the tester can easily determine whether the test result is positive
or negative by the difference between the signals of two
samples. For example, if it is assumed that the cutoff
concentration is 5 ng/mL (reference sample) and the sample
without THC (0 ng/mL) is collected from a driver, the test
result is negative, i.e., a higher signal than the reference sample
means negative, and a signal lower than or equal to the
reference is positive.
To investigate whether the competitive assay could be
applicable to other small molecules, we performed measure-
ment of morphine (285.3 Da) by replacing THC with
morphine. The sensors were coated with morphine-BSA in
lieu of THC-BSA, and antimorphine antibodies at 0.1 μg/mL
were used. The signals from zero analyte, morphine at 10 and
100 ng/mL showed statistically significant differences (Figure
S3).
In summary, we have demonstrated that the miniaturized
GMR biosensor platform enables rapid and precise detection of
THC in saliva. This platform validated the technical feasibility
for on-site screening on drivers under the influence, and our
results showed that the technique could be used to establish the
cutoff concentration of THC, performing the tests without any
delays involved with transferring samples to the clinical
laboratories. In addition, the platform is capable of detecting
THC in blood (Figure S4), because GMR biosensors are
matrix-insensitive.19
Thus, the correlation between concen-
trations of THC in blood and saliva, which is currently
controversial,7,9,33,34
could be addressed with a more accurate
comparison using the same measurement modality. With the
multiplexing capability of the GMR biosensor chip, the next
generation of the platform could include metabolites of THC
on the sensors to simultaneously detect THC and its
metabolites in blood and urine. This multiplex measurement
would allow researchers to study the pharmacokinetics of the
drug more rigorously. Furthermore, because it has been
recently reported that 11-nor-9-Carboxy-THC (THC-
COOH) in saliva could be a better biomarker to detect
cannabis use,35
it would be interesting to measure THC-
COOH and THC together to increase the accuracy of the test
and develop a new criterion of cutoff. In addition, if there is a
better biomarker that can reveal THC’s pharmacodynamics in
the brain and the relationship with its concentration in blood or
saliva, it could be a more precise indicator for the level of
impairment. However, there is a potential limitation of testing
THC in saliva. THC in saliva is thought to originate from oral
mucosal depots, not from blood.32
Thus, if cannabis is
consumed through edibles it would be difficult to detect
THC in saliva. Lastly, since the competitive assays are
applicable to detection of any type of small molecules, the
platform could be used to detect different drugs such as heroin
and cocaine in addition to THC and morphine as well as to
detect therapeutic small molecule inhibitors in cancer treat-
ments.36,37
■ ASSOCIATED CONTENT
*S Supporting Information
The Supporting Information is available free of charge on the
ACS Publications website at DOI: 10.1021/acs.anal-
chem.6b01688.
Full experimental details, electronics, 20 min assays,
morphine measurement, and measurement of THC in
blood (Figures S1−S4) (PDF)
■ AUTHOR INFORMATION
Corresponding Author
*E-mail: sxwang@stanford.edu. Fax: +1 (650) 736-1984.
Author Contributions
§
J.-R.L., J.C., and T.O.S. contributed equally.
Notes
The authors declare the following competing financial
interest(s): J.-R.L., T.O.S., and S.X.W. have related patents or
patent applications assigned to Stanford University and out-
licensed for potential commercialization. S.X.W. has stock or
stock options in MagArray, Inc., which has licensed relevant
patents from Stanford University for commercialization of
GMR biosensor chips.
■ ACKNOWLEDGMENTS
This work was supported in part by Stanford Center for
Magnetic Nanotechnology and Skippy Frank Translational
Fund. J.C. acknowledges the STX Foundation fellowship. We
would like to acknowledge the XPRIZE Foundation and Nokia
Sensing XCHALLENGE competition for motivating the design
of the platform.
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Analytical Chemistry Letter
DOI: 10.1021/acs.analchem.6b01688
Anal. Chem. 2016, 88, 7457−7461
7461