Nanophotonic Biosensors Within Lab on Chip Optical Systems

Daniel Hill

UMDO, Institut de Ciència dels Materials, Universitat de Valencia, Catedrático José Beltrán, Paterna, Spain

Keywords: Nanophotonics, Slot-Waveguides, Ring Resonators, Porous Silicon, Biosensing, Lab-on-Chip, Birefringence,

Quantum Dots.

Abstract: For ring resonator based sensors, volumetric limits of detection (LoD) of 510

–6

RIU and 8.3x10

−6

RIU

(refractive index units) for sensitivities of 246nm/RIU and 2169nm/RIU were reported from FP6 SABIO (at

1.31µm) and FP7 InTopSens (at 1.55µm) respectively. These compare well to the state of art of 7.6×10

−7

RIU

for a sensitivity of 163 nm/RIU, as does the porous alumina based membrane sensors in FP7 Positive with

their LoD of 5x10

-6

RIU. More interestingly for the membrane sensors, the standard deviation of their

measured values was below 5% and their flow through design with lateral distances to the sensor surface less

than a diffusion length permit fast response times, short assay times and the use of small sample volumes (<

100 µl). For protein binding recognition, within SABIO a surface LoD of 0.9 pg/mm

for anti-BSA on a

gluteraldehyde-covered surface was recorded, corresponding to a 125ng/ml anti-BSA solution, whilst in

InTopSens 5pg/mm

and 10ng/ml for biotin on a streptavidin coated surface was seen. For an assay of β-

lactoglobulin - anti-β-lactoglobulin - anti-rabbit-IgG –streptavidin conjugated CdSe quantum dots the Positive

sensors demonstrated a noise floor for individual measurements of 3.7ng/ml (25pM) for total assay times of

under one hour.

1 INTRODUCTION

Increasing demands for rapid, reliable and

economical near patient or in the field testing has led

to strong and growing trend towards in-vitro point of

care (PoC) sensing for clinical diagnosis, food safety,

environmental monitoring, safety and security (Fan et

al., 2008) (Hill, 2011). The demands for PoC sensing

that can be used, such as by a single medical

practitioner or in a remote field crop-testing

environment, are driven by their facilitation of a

massive socio-economic impact from the general

improvement of quality of life they would bring. PoC

sensing is enabled through the scaling of analytical

chemical and biological instruments down to a single

chip (Janasek et al., 2006) leading to: automation of

the analysis, increased mobility of the instrument,

shorter response times, reduced manual sample

handling, and a low cost per test. Typical

requirements for assay requirements consists of the

reliable and selective identification of extremely low

concentrations of biomarkers (infectious agents,

pesticides, cardiac markers, allergens etc.) from other

matter within small volumes of complex matrices

(e.g. whole blood, sputum swabs, faeces, cell

lysate…) within a few minutes. Furthermore, it

should have a commercially viable cost and be

useable by a relatively unskilled operator outside of a

lab environment. PoC in-vitro diagnostic devices are

therefore required to provide fast, sensitive and

selective analysis of assays, ideally in a parallel

format and therefore of a technology that permits the

fabrication of a high density of sensor ‘spots’ per chip

area, as well as negating the need for lengthy off-chip

sample preparation, all at an acceptable cost. To that

end, many of the new approaches that have been

explored are based on highly integrated sensors

within a Lab on Chip format (Ligler et al,, 2009).

At the core of these devices is the biosensor

(Brecht et al., 1995) and those based on optical

interrogation offer important advantages such as: 1)

non-invasive, safe and multi-dimensional (intensity,

wavelength, phase, polarization) detection; 2) well-

established tools from communication and Micro-

Nano technologies (MNT) industries (lasers,

detectors, waveguides) and 3) optical frequencies that

coincide with a wide range of physical properties of

bio-related materials.

Refractive index (RI) sensing is often used in real-

time monitoring of chemical processes and, when

used with separation techniques such as liquid

Hill D..

Nanophotonic Biosensors Within Lab on Chip Optical Systems.

DOI: 10.5220/0005259500600068

In Proceedings of the 3rd International Conference on Photonics, Optics and Laser Technology (PHOTOPTICS-2015), pages 60-68

ISBN: 978-989-758-093-2

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

chromatography or capillary electrophoresis,

universal solute detection systems can be created

(Markov et al., 2002). Within LoC devices, silicon

nanophotonics has found much use recently as

affinity sensors (Zinoviev et al., 2008) as the RI of

aqueous macromolecular solutions is linear with

macromolecule density (De Feijter et al., 1978) and

so the mass of bound macromolecules, such as

proteins, DNA, peptides, to a waveguide can be

derived from measurements of the surface evanescent

field. The commercially successful surface plasmon

resonance (SPR) based sensors (Brecht et al., 1995)

are such an example. Furthermore, the nanophotonic

sensors can be economically mass-produced in a

highly integrated format by using the same waferscale

microfabrication technologies as those sued for

electronic microchips. Thus, to bring the powerful

tool of highly integrated and reliable sensing into the

hands of a wider user base, there is a strong interest

in integrating nanophotonic sensors into LOC

platforms for PoC applications. In this paper we

compare various nanophotonic transducers from

three EC funded projects (FP6 SABIO, FP7

InTopSens and FP7 Positive) that due to their small

footprints and ease of integration with other on-chip

optical and fluidic functions are particularly

interesting as sensors for LoC devices. In doing so,

we also compare them to the state of art for each

technology type to fully put their advances into

perspective.

2 SABIO

2.1 SABIO Nanophotonic Sensors

Optical ring resonators consist of a set of waveguides

with at least one being a closed loop that is coupled

to some sort of light input and output, conceptually

analogous for light to acoustic whispering galleries.

When light of the resonant wavelength is passed

through the loop from input waveguide, it builds up

in intensity over multiple round-trips due to

constructive interference and is output to the output

bus or detector waveguide which serves as a detector

waveguide. The ring acts as a filter with its finesse

determining how many select few wavelengths will

be at resonance within the loop and its quality factor

to how lossless it is. Researchers have been studying

them since the 1980s (Tiefenthaler et al., 1984)

(Lukosz et al., 1988) (Tiefenthaler et al., 1989) and

inspired by Almeida et al’s demonstration (Almeida

et al., 2004) (Xu et al., 2004) of slot waveguides in

Figure 1: A top view of the layout of the nanofabricated

SABIO optical chip (occupying a 3x7mm

area): Light is

injected at the surface grating coupler (C) and split, by the

multi-mode interference splitter (B), to the six sensing

channels M1–M6 and the two reference channels REF1 and

REF2. Inset are an optical micro-graph of the splitter (B);

and electron micro-graphs of the grating coupler (C), and a

slot-waveguide ring resonator (A), with an enlargement of

the coupling region.

2004 the SABIO project targeted the implementation

of these in a ring resonator format for biosensing. Si

planar waveguide ring resonators, and even more so

slot-waveguides ring resonators are very attractive for

biosensing due to their small footprint, high Q-

factors, and compatibility with on-chip optics and

microfluidics (Sohlström et al., 2010). Their design

permits parallel sensor operation which not only

yields higher throughput by multiple analyses of one

sample, or simultaneous analyses of multiple

samples, but it can also provide reference channels for

drift compensation and control experiments. Such

reference measurements are particularly important for

automated labs-on-chips without temperature

stabilization. In SABIO the optical chip (Figure 1)

was designed with 6 measurement channels and two

reference channels, and channel to slot-mode

converters were used for conversion between the two

waveguide types before and after the ring resonator

coupling regions, where the bus slot-waveguides have

rail widths of 400 nm and a slot width of 200nm.

The coupling gap was 350 nm and in the sensing

ring, asymmetric slot-waveguides with the inner rail

widened to 550 nm were used for high optical

confinement and low bending loss. Details of the

choice of low pressure chemical vapour deposition

(LPCVD) silicon nitride on thermally oxidized

silicon wafer technology, as well as general design

rules for the chip, that led to measurements being able

to be made over a 7K operating window, without

external temperature control and individual sensor

calibration (Gylfason et al., 2010), are beyond the

scope of this paper.

NanophotonicBiosensorsWithinLabonChipOpticalSystems

2.2 SABIO Measurements and

Discussion

In determining the volumetric RI sensitivity and limit

of detection for the SABIO chips, sensing

experiments were performed using a dilution series of

ethanol and methanol plugs in a running buffer of

deionized (DI) water. Full details of the sensing

experiments (Carlborg et al., 2010) are beyond the

scope of the paper including how a fitting algorithm

was used to determine more accurately the positions

of the drips in the ring characteristics, pushing down

the wavelength noise significantly to below the laser-

tuning step and the use of reference channels with DI

water to correct for drift. At 1300nm, an index

sensitivity of S

=246 nm/RIU was measured and the

sensor resolution (R) taken as 1.2pm, following the

convention of 3 standard deviations σ of the total

system noise, with the volumetric RI LOD given by

=R/S

and thus 5 x 10

-6

RIU.

The SABIO chip’s performance as a surface mass

sensor was studied by measuring the binding of anti-

bovine serum albumin (anti-BSA), injected in

increasing concentrations in a running buffer of

phosphate buffered saline (PBS), to a surface

selectively activated by a layer of the molecular linker

glutaraldehyde. From a saturation induced resonance

shift estimated at ∆λ=2.55 nm, with a surface density

of a monolayer (σ

) of anti-BSA measured at 2.0

ng/mm

by dual polarisation interferometry (DPI)

with the Farfield AnaLight 4D system, a mass

sensitivity, or S

=∆λ/σ

of S

=1.3 nm/(ng/mm

) was

measured. The surface mass detection limit, L

=R/S

where R is the sensor resolution, was determined at

0.9pg/mm

corresponding to a concentration of

125ng/ml anti-BSA in PBS solution.

The detection limits of 5 x 10

-6

RIU for volume

sensing and 0.9 pg/mm

or 125ng/ml for protein

binding,

compare favorably to other published ring

resonator results. These are primarily due to the use

of multiple transducers on the chip to compensate for

external disturbances, the high sensitivity of the slot-

waveguide ring resonators and the low system noise

of 1.2 pm from fitting an analytical model to the

spectrum, effectively due to utilizing all the

information available (Kazmierczak et al., 2009). As

seen ahead, this is in contrast to the approaches used

in the later projects InTopSens and Positive, neither

of which used a non-directly mass fabrication

compatible technology such as electron beam

lithography.

3 InTopSens

3.1 InTopSens Nanophotonic Sensors

Whereas the SABIO application required a chip

design with 6 ring resonator sensors, 64 were required

for the InTopSens application and therefore a far

smaller footprint per sensor. A starting point for

sensor development was therefore silicon-on-

insulator (SOI) ring resonators due to their higher

index contrast than those based on silicon nitride and

therefore potentially a higher degree of integration.

Moreover, they had previously demonstrated (De Vos

et al., 2007) a volumetric RI sensitivity of 70 nm/RIU

and LOD of 1.3x10

–5

RIU as well as a LOD of 7ng/ml

for protein binding (biotin-avidin) recognition.

Therefore for a suitably high degree of integration,

with an equal or better LoD, slot-waveguide racetrack

resonators with 100nm wide slots in SOI were

nanofabricated (Claes et al., 2009), with footprints of

just 13µm x 10µm, using the mass fabrication-

compatible optical lithography, opening the way

toward cheap, disposable chips in contrast to the

SABIO ring resonators.

3.2 InTopSens Measurements and

Discussion

Using aqueous salt solutions volumetric sensing

experiments with these SOI slot ring resonators,

demonstrated a refractive index sensitivity of 298

nm/RIU and a LOD of 4.2 x 10

-5

RIU (Figure 2). As

the sensitivity value lies within a range of theoretical

values from an empty slot to a liquid filled slot it

demonstrates that liquid has penetrated the narrow slot

region.

Figure 2: A comparison between the experimental

resonance wavelength shift of a normal-waveguide based

ring resonator and the theoretical and experimental

resonance wavelength shift of a slot-waveguide based ring

resonator for top refractive index.

PHOTOPTICS2015-InternationalConferenceonPhotonics,OpticsandLaserTechnology

After silanizing the sensor surface protein binding

experiments (biotin-avidin recognition) showed a

limit of detection of 10ng/ml (Claes et al., 2009), or

5pg/mm

. The saturation shift was 3.5 times that of the

SABIO device, lying between the theoretical values

for avidin binding only outside of the slot and for it

lying both inside and outside of the slot. Thus,

although it demonstrated that surface chemistry for

selective label-free sensing of proteins can be applied

inside a 100 nm wide slot region for a smaller foot

print slot waveguide sensor, it also showed a poorer

LoD compared to the SABIO device. Principally the

poorer LOD was due to a lower resolution or quality

factor mostly caused by bending and mismatch losses

although sidewall inclination, roughness from

silicon’s greater sensitivity to nanofabrication

limitations, the presence of a biochemical layer, and

absorption also contributed.

In an aim to improve the LoD whilst maintaining

a small footprint other ring resonators were fabricated

whose designs were based on modifications to

existing (slot) ring resonator waveguide sensors such

as:

• The use of notch ring resonator filters instead of

add-drop filters

• Increasing the sensor circumference

• Switching to 1300nm where water is less

absorbent

• Combining quasi-TE and quasi-TM modes

One such ring resonator demonstrated a

volumetric limit of detection of 5x10

–6

RIU through

aqueous salt solution sensing experiments and an

improved surface mass LOD of 2pg/mm

for protein

binding (biotin/avidin) experiments corresponding to

10ng/ml. Another was based around the use of the

Vernier effect through suitably designed cascaded ring

resonators that were folded to permit high integration.

For these (Claes et al., 2010), aqueous salt solution

sensing experiments demonstrated a volumetric

sensitivity of 2169nm/RIU and a limit of detection of

5x10

–6

RIU, equal to that of the larger SABIO

sensors, promising a favourable protein binding limit

of detection.

4 POSITIVE

4.1 Positive Nanophotonic Sensors

Planar nanophotonic sensors such as those in SABIO

and InTopSens have demonstrated LODs that meet

the criteria of analyte concentration measurements for

many applications. However, although some require

lower LoDs still, many sensors, including those in

SABIO and InTopSens, are far from becoming a

reality within commercial PoC diagnostic platforms

for other reasons. These include poor planar

integration, high fabrication costs, but most

importantly a slow time to response and subsequently

long times to assay result as well as the need for large

sample volumes and subsequently expensive

reagents. For example in both SABIO and InTopSens

the time taken to go from steady state concentration

to another was over 40 minutes and therefore assays

took typically far in excess of an hour whilst response

times to an analyte and/or reagent injection into their

microfluidic systems were typically in excess of 5

minutes. Furthermore, whilst SABIO and InTopSens

sensors required millilitres of blood, along with

millilitres of costly reagents, applications that test

young children can be limited to the ~100 µl of blood

taken by finger prick collection. All of these

deficiencies in both of these projects, and many

others, are due to the use of 2D or planar sensors and

the long path lengths of the analytes to their surfaces

relative to their diffusion lengths, arising from the

common use of lateral flow geometry in sensor

cartridge design.

Nanostructured materials like porous silicon (PSi)

or porous alumina (AAO) have however recently

gained special attention for sensing, due to their 3D

design allowing higher surface areas per unit planar

area for capturing analytes than planar biosensors,

permitting lower detection limits (Lazzara et al.,

2011) and higher integration of assays. Due to the use

of reflectrometric interference spectroscopy (RIfS)

however, optical biosensors based on porous

membranes (Orosco et al., 2009) (Tsang et al., 2012)

(Alvarez et al., 2009) (Kumeria, Kurkuri et al., 2012)

can have their pores only open at one end and the

diameters of those limited to 100nm to avoid light

scattering (Kumeria & Losic, 2012). With that

structure, the delivery of the analytes into the pores is

therefore mainly governed by the stationary flux

produced by electrostatic interactions, resulting in

slow responses and so long sensing times.

The choice of a porous membrane based biosensor

in the FP7 Positive project was based on the

constraints of its application that required the

detection of 16 different proteins found in

concentrations of 0.24ng/ml upwards in serum

sample volumes of 100µl samples within 15 minutes

of their introduction into the instrument. In order to

meet all of the application criteria, freestanding

macroporous AAO membranes with 200 nm pore

diameters were used, to allow analyte molecules to

flow-through the pores less than a diffusion length

from the assay surface on the pore walls, breaking the

NanophotonicBiosensorsWithinLabonChipOpticalSystems

mass transport limitations (Yanik, 2010) (Guo, 2011),

and so effectively targeting their delivery, for real-

time biosensing responses.

With the pores of macroporous AAO membranes

perpendicular to their planar surface, any induced

birefringence is very sensitive to the refractive index

of the material within the pores (Alvarez, 2011)

(Alvarez, 2012), and this was used as a sensing

mechanism (Alvarez, Sola et al., 2013) in an optical

polarimetry based experiment (Figure 3).

In the experiment, the AAO pore walls within the

membrane were functionalized with an epoxysilane

before being spotted with -Lactoglobulin protein

and the binding first of rabbit anti--lactoglobulin and

then a secondary antibody anti-rabbit

Immunoglobulin G was monitored in real-time. The

membrane itself is affixed with a 1 μm thick layer of

PMMA (Poly(methyl methacrylate)) resist to a 500

μm thick 15 by 15 mm piece of single side polished

silicon wafer support, with a 750 μm diameter

opening (Figure 4). Prior to the biosensing

experiment, a bulk refractive index sensitivity of

5.2x10

-6

refractive index units was measured from

signal responses to different concentrations of NaCl

solutions for the mounted membranes within a flow

cell.

Figure 3: (a) Layout of the optical polarimetric readout

platform used for measuring the phase retardation within

the membranes from phase locked loop measurements

using a 980nm laser diode. (b) Scheme of fluidic setup

integrated within a flow-cell where the mounted membrane

is placed and whose inlet port is connected to a pressure

controller providing a constant pressure flow.

Figure 4: Picture of a freestanding membrane mounted on a

silicon support.

4.2 Positive Measurements and

Discussion

Recently this approach was repeated for

immunosensing (Alvarez 2014), by coating the

membrane with a functional copolymer,

copoly(DMA-NAS), through a novel procedure that

has demonstrated less non-specific binding, and

therefore greater selectivity, and more stability over

time for immobilized allergens than epoxysilane

(Platt, 2014). Specifically this polymer was

previously demonstrated to immobilize allergens on

different materials, such as glass, nitrocellulose,

silicon (Cretich, 2010) and more recently on a

SiOxNy DPI chip (Platt, 2014), whilst allowing an

efficient measurement of their interactions with

allergen-specific Immunoglobulin E (IgEs) in

complex matrices of serum, proving its suitability as

a non-fouling coating and that it is robust to allergen

storage.

Prior to the immunosensing experiments in order

to obtain both the bulk sensitivity, and its

reproducibility a series of bulk refractive index

experiments with the polarimetry setup were carried

out (Sola, 2015), on ten different copolymer

functionalized macroporous alumina membranes,

with an allergen immobilized on the pore surfaces

(Figure 5), on silicon supports and mounted within a

flowcell. Briefly, after purging with CO

, PBS-T

(PBS, 0.02% (v/v) Tween 20) was flown through the

membranes for fifteen minutes in order to obtain a

base line, before flowing four solutions of NaCl in

PBS with concentrations ranging from 0.2% (m/v) to

2% (Figure 6).

Figure 5: The immunoassay carried out in a macroporous

alumina membrane. β-lactoglobulin protein was used as the

immobilized antigen for the detection of rabbit anti-β-

lactoglobulin. Biotinylated secondary antibody (anti-rabbit-

IgG) and streptavidin coated CdSe quantum dots were used

to increase the signal produced by the primary antibody.

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Figure 6: A sensorgram showing the signal response from

flowing several solutions of various concentrations of NaCl

in deionized water through a macroporous AAO membrane.

Measured polarimetric responses for all

membranes when fitted with a linear curve gave a

mean sensitivity of 5.2 radians RIU

-1

(rad RIU

-1

) with

a standard deviation equal to 0.2 rad RIU

-1

(Figure 7)

which is ~4% of the average sensitivity value (which

envisions a good reproducibility for these

membranes, a necessity for a commercial device).

This corresponds to a LoD of 5x10

-6

RIU from a

measurement system resolution of 2.7x10

-5

rad

(Alvarez, Serrano et al., 2013). Thereafter, each

immunosensing experiment began by first

introducing a running buffer of PBS-T for 15 minutes.

In a first experiment the activity of the immobilized

allergens were tested (Figure 8) using concentrations

of 1 μg/mL (6.7 nM) for the first and secondary

antibody and a concentration of 2.5 nM for

streptavidin coated CdSe quantum dots (SA-QD).

Firstly, the baseline obtained during the buffer rinse

showed good stability, demonstrating that the antigen

is stably immobilized on the polymer coated surface.

Figure 7: Overlaid phase retardation changes for ten

different alumina membranes as a function of refractive

index changes from different NaCl solutions.

Figure 8: A sensorgram showing the signal response due to

the binding of the first and secondary antibodies, followed

by the SA-QD.

After recording a stable baseline during six

minutes the first antibody rabbit anti-β-lactoglobulin

was injected during 10 minutes, followed by a six

minute rinse with the running buffer before the

secondary antibody anti-rabbit IgG was injected

during 10 minutes. As the secondary antibody is

polyclonal, a larger response is observed for this,

compared to the binding of the initial primary

antibody. After further rinsing, the SA-QDs were

added as a signal enhancer at a concentration of 2.5

nM, which was sufficient to saturate the captured

secondary antibodies. Due to the size of the SA-QDs

an enhancement of 5 times is observed in the signal

over the response produced by the secondary

antibody. Each sandwich assay, employing both a

secondary and tertiary binding, took less than one

hour reducing assay time fivefold and analyte

Figure 9: An overlay of the signal responses produced by

the SA-QD when the concentration of the first antibody is

increased from 5 ng/mL to 1000 ng/mL.

NanophotonicBiosensorsWithinLabonChipOpticalSystems

consumption by three orders of magnitude compared

to biosensors based on porous membranes in flow-

over configurations (Tsang, 2012). From

measurements (Figure 10) a LoD was calculated at

33.7ng/ml (225pM). The reductions in assay time,

sample and reagent volumes as well as response time

are clearly advantages that result from the use of a

flow through mechanism with analyte path lengths to

the sensor walls less than a diffusion length, and a

parameter related to these values is the capture

efficiency. This was determined (Sola, 2015) by the

use of a fluorescent flow-through capture assay using

Cy3 labelled streptavidin which, when combined with

modelling (Figure 11), was also used to provide pore

size distribution information for the AAO

membranes. Compared to a conventional planar

biosensors, they show much higher efficiency for

analyte capture from solution (17% vs 32%), which is

Figure 10: Phase retardation change upon injection of 2.5

nM SA-QD over biosensing experiments using a range of

primary AB concentrations (5-1000ng/mL). The fitted line

corresponds to a 1:1 binding model of K

228 ng/mL and

max

of 7.7 mrad.

Figure 11: Amount of SA-Cy3 captured by biotinylated

AAO membrane as a function of eluted sample volume.

Lines show the fit to a mass transport to the membrane

model with three pore sizes, assuming a fixed small pore

size of 200nm at fitted 82.9% number density, 314nm at

17% and 1.4 m at 0.1%

ultimately limited by the demonstration of a

distribution of pore sizes rather than the declared

nominal pore diameter. The combination of porous

membranes and SA-QD detection also raises the

potential for other transduction mechanisms to be

explored in these devices, such as fluorescence,

colorimetric or back-pressure measurement.

5 DISCUSSION

Table 1: A comparison of the three principle sensors from

the three EC projects along with the state of art.

Senso

olumetri

oD (RIU)

rotein

ass LoD

(pg/mm

)

rotein

concen -

ration

esponse

ime

esult

(

mins)

Sample

olume

(ml)

SiN slo

510

–6

125

ng/ml

>300 >>60 5

SOI slo

4x10

−5

ng/ml

>300 >>60 5

ernier

5x10

–6

NA NA >300 >>60 5

em -

rane

5x10

-6

ng/ml or

225pM

<1 <60 0.1

SOA 8×10

−7

? 60fM <1 8 Small?

Figure 12: An analysis of the LoD from the principal sensor

technologies within the three EC projects compared to

others in the literature. The x-axis is the log of the

wavelength resolution and the y-axis is the log of the device

sensitivity in terms of wavelength shift per RIU. The

grayscale then represents LoD 0. The SABIO sensor is

labelled as Carlborg whilst the initial InTopsens sensor is

labelled as Claes. A green continuous line on the graph

represents the LoD of the Positive sensor. As the sensor

uses a phase based measurement instead of wavelength,

neither its sensitivity nor resolution can be plotted for a

specific point.

1 10 100 1000 10000

Anti b-Lactoglobulin concentration (ng/mL)

Phase Retardation Change (mrad)

0.5

1.5

2.5

02468101214

Sample Volume (mL)

Moles of Protein Captured (nmol)

0.5

1.5

2.5

Total Moles of Protein Flowed

(nmol)

Total SACy3 Bound

Small Pore

Medium Pore

Large Pore

total bound fit

Total Flowed

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When comparing the results from the principle sensor

mechanisms used within the three EC projects one

can see (Figure 12) their volumetric limits of

detection are similar but still an order of magnitude

below that of the state of art (SOA) for nanophotonic

sensors (Iqbal, 2010).

Comparisons for protein mass or concentration

LODs are difficult to make as they depend on the

surface chemistry and exact protein used but all of

three sensors are similar and inferior to the SOA. The

POSITIVE sensor does however compare favourably

with the SOA in terms of response time, size of

sample and possibly time to result although the latter

two are assay dependent making them difficult to

compare especially given the lack of quantitative

information for sample volumes used for the SOA

results. It also probably has a far higher efficiency for

analyte capture and if other transduction mechanisms

were used simultaneously, it could have a far superior

specificity, a very important parameter for many

applications that rarely appears in academic

publications.

6 CONCLUSIONS

In comparing various optical biosensors developed

within three EC funded projects we have observed

that firstly, they all have similar volumetric limits of

detection, on the order of 10

−6

RIU whereas limits of

detection for proteomic assays vary and are difficult

to compare with the data coming from different

assays. It is noteworthy however that for the

POSITIVE sensor total assay times were far less as

were response times and minimum volumes of

analyte necessary making it comparable at least in

those regards to the state of art or nanophotonic

sensors and interesting for certain applications.

Research in non-planar sensors, although

currently facing more fabrication technology

challenges than the planar types, can be expected to

provide some very interesting results in the near

future.

ACKNOWLEDGMENTS

As project manager of all three projects there are

many contributors with whom I have worked directly

and am most grateful for their efforts. I thank Jesus

Alvarez, Hans Sohlström and Kristinn Gylfason for

their photonics contributions in both SABIO and

POSITIVE. Other direct contributors to the SABIO

work summarized here are Andrzej Kaźmierczak,

Fabien Dortou, Laurent Vivien, Jon Popplewell,

Gerry Ronan and Carlos A. Barrios. Other direct

contributors to the INTOPSENS work summarized

here include Tom Claes and Peter Bienstman. Further

direct contributors from the POSITIVE project for

article include Marcus J Swann, Laura Sola, Marina

Cretich, Marcella Chiari and Tormod Volden. As I

review the collaborative projects SABIO,

INTOPSENS and POSITIVE, many others have

contributed.

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PHOTOPTICS2015-InternationalConferenceonPhotonics,OpticsandLaserTechnology