Combining the Strengths of Mid-IR and Raman Spectroscopies on Single Chip for Rapid Bedside Biomarker Diagnostics

Lead Research Organisation: University of Southampton
Department Name: Optoelectronics Research Centre (ORC)

Abstract

There is a pressing need for diagnostic tools that can produce results quickly from patients' bedsides and in doctors' surgeries. Rapid, accurate results will allow rapid therapeutic decisions and save lives at reduced cost. In contrast, existing technologies require transfer of samples to centrally located laboratories equipped with sophisticated instruments, and highly skilled personnel.

Bedside diagnostics using simplified, compact, versatile and efficient tools providing analysis results within a few minutes will therefore be a boon for many critically ill patients. In this project, we propose to develop two-in-one attenuated total reflection (ATR)/Raman chips that are compact, mass-producible, affordable, reliable, user-friendly and highly sensitive. The availability of such chips will enable the full potential and complementary nature of mid-IR molecular fingerprint and Raman spectroscopies to be exploited for bedside point-of-care diagnosis of critically ill patients who require rapid therapeutic decisions, meeting the ASSURED criteria set by the World Health Organisation (WHO).

For example, provision of rapid diagnostic information will be invaluable for preterm infants (24-30 weeks gestation), for whom treatment decisions must be made as soon after birth as possible. Due to their lung immaturity, such infants are at high risk of suffering from neonatal Respiratory Distress Syndrome (nRDS), which has a high rates of mortality and morbidity with a major long-term economic burden on healthcare services. Using nRDS as an exemplar, we propose to develop a compact, versatile, rapid and easily operable bedside diagnostic tool for the next-generation bedside point-of-care to provide a predictive diagnostic test for nRDS to inform treatment options.

The diagnostic device platform proposed here combines the complementary capabilities of fingerprint Mid-IR and Raman spectroscopies, each of which has been shown independently to be powerful biodiagnostic tool for specific biomarkers. In addition, we will employ a unique signal enhancement strategy that will simultaneously benefit both IR and Raman spectroscopies and significantly enhance their sensitivities. This new photonic technology and the portable diagnostic device proposed will not only underpin next-generation biomedical diagnostic applications but will also have major impacts in environmental monitoring and sensing including water pollution monitoring and trace toxic gas sensing.

Planned Impact

We propose to develop optical devices that are simple and low-cost that are ideal for performing combined mid-infrared (mid-IR) and Raman spectroscopies providing complementary information to identify and quantify biomarkers in a clinical environment, for rapid bedside biomedical diagnostics. These chips will be capable of near-instantaneous disease detection to advance a healthy society with reduced medical costs.

This research will offer economic impacts by creating industrial growth through the realisation of novel photonic devices (one of the key enabling technologies) and will also make societal impact by the provision of new clinical devices for the bedside point-of-care diagnosis, benefiting clinicians and general public. The bedside diagnosis of critically ill patients will enable rapid therapeutic decisions, saving lives, reducing the economic burden on healthcare services and creating a resilient nation.

We will conduct roadshows and outreach programmes in schools and hospitals and demonstrate the potential benefits of these photonic devices developed in this project for the next-generation bedside point-of-care diagnostics.

Working in collaboration with SIME Diagnostics Ltd we are in a position to enhance the UK's already strong position in the medical diagnostics sensors market. As the technologies mature during the project, we will explore further routes to commercialisation as the possibility of low-cost, mass produced systems becomes clear. To enable this, the protection and exploitation of the results are important and at Southampton we are well supported for this by the University's Research and Innovation Services (RIS). RIS have expertise in IP protection, the identification of potential users of research results, licensing, business planning and spin-outs.

This programme will be of great value to the next generation of research scientists and it provides excellent opportunities for training PhD/MSc students and postdoctoral researchers in a highly multidisciplinary environment in a field with great practical potential, coupled with state-of-the-art technologies. They will interact with staff from multiple disciplines, and meetings of the team will foster cross-disciplinary engagement and an understanding of translation from fundamental science to practical application, providing an excellent foundation for the research leaders of the future.
 
Description Biomarker detection and concentration prediction from the spectroscopic data using machine learning have been developed. This will be useful for the biomedical diagnosis in a point of care setting, especially in a near-bedside. We have performed electromagnetic modelling of microstructured silicon surfaces to enhance the strength of spectroscopic signal and thereby increasing the signal to noise ratio to detect very low level of biomarkers present in a liquid sample. We have completed the fabrication of first generation of microstructured chips for on-chip spectroscopy and they showed enhanced performance compared to conventional Mid-Infrared spectroscopy. We have also shown using Raman spectroscopy that biomarkers in aqueous samples (for example body fluids) can be detected and quantified.
Exploitation Route When the chips are fully characterised and compact instrumentation to contain the chip and perform spectroscopy devised, they will be tested under clinical condition for performing bedside biomedical diagnostics.
Sectors Agriculture, Food and Drink,Chemicals,Digital/Communication/Information Technologies (including Software),Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology

URL https://doi.org/10.3390/s22051744
 
Description COVID-19: Aerosolized Surfactant Clinical Trial
Amount $1,298,313 (USD)
Funding ID INV-016631 
Organisation Bill and Melinda Gates Foundation 
Sector Charity/Non Profit
Country United States
Start 04/2020 
End 10/2020
 
Description Mid-infrared frequency comb generation using integrated chalcogenide microring resonators for on-chip spectrometers
Amount £11,825 (GBP)
Funding ID IEC\NSFC\201068 
Organisation The Royal Society 
Sector Charity/Non Profit
Country United Kingdom
Start 03/2021 
End 03/2023
 
Title Machine learning and chemometric analysis of spectroscopic data 
Description We have developed a machine learning model to diagnose the neonatal Respiratory Distress Syndrome (nRDS) in prematurely born infants based on the biomarkers present in the amniotic fluid or gastric aspirates. We have proved that the model effectively predicts the condition using the Mid-IR spectroscopic data collected from the mixture of biomarkers. 
Type Of Material Data analysis technique 
Year Produced 2021 
Provided To Others? Yes  
Impact Currently there are no quick diagnosis method to detect this symptom and appropriately treating them. Our approach will provide a rapid point of care diagnosis at the bedside and not only save many lives but will also reduce the economic burden on health services by reducing the longtime morbidity due to improper therapeutic decisions (because of the lack of diagnosis techniques). 
URL https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11651/2578818/ATR-based-infrared-s...
 
Title Modeling parameters of Si hemispherical domes for photonic nanojet generation 
Description This data set provide the parameters used to model the on chip photonic nanojet. 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
Impact In this work we have explored photonic nanojet generation in in Si platform, which have established so far because usually the photonic nanojets (PNJ) are useful only when the refractive of the material is less than 2- and Si has a refractive index of 3.4. We have studied the PNJ geration from Si hemispherical domes on Si substrate and established that the proposed design can overstep the refractive index limit and possible to use Si to generate photonic nanojets which opens up a wide field of applications including on-chip optical tweezers, opto-fluidics and focal plane arrays. 
URL https://eprints.soton.ac.uk/452810
 
Title Prediction of Neonatal Respiratory Distress Biomarker Concentration by Application of Machine Learning to Mid Infrared Spectra 
Description Dataset to support article by Ahmed, W.; Veluthandath, A.V.; Rowe, D.J.; Madsen, J.; Clark, H.W.; Postle, A.D.; Wilkinson, J.S.; Murugan, G.S. Prediction of Neonatal Respiratory Distress Biomarker Concentration by Application of Machine Learning to Mid-Infrared Spectra. In "Sensors" 2022, 22, 1744. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact Currently there are no dataset available for training machine learning algorithms to detect the ratio of lung surfactants DPPC and SM. Different ratios of DPPC and SM where prepared in lab. FT-IR spectrum of the lung surfactant are meticulously collected and analyzed. Data provided is corrected for humidity level and will be helpful in training future algorithms. 
URL https://eprints.soton.ac.uk/455045/
 
Title Training data set for chemometric analysis lung surfactants using FT-IR spectroscopy 
Description We have collected an extensive set of data consists of IR spectrum of lung surfactant with different DPPC and SM ratio to train the machine learning algorithm. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact Currently there are no dataset available for training machine learning algorithms to detect the ratio of lung surfactants DPPC and SM. Different ratios of DPPC and SM where prepared in lab. FT-IR spectrum of the lung surfactant are meticulously collected and analyzed. Data provided is corrected for humidity level and will be helpful in training future algorithms. 
URL https://doi.org/10.5258/SOTON/D1829
 
Title Training data set for chemometric analysis of lung surfactants using Raman spectroscopy 
Description We are collecting an extensive set Raman spectrum of lung surfactant in lipid vesicles are solid form to train the spectrum of lung surfactant to train the machine learning algorithm. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? No  
Impact Currently there are no dataset available for training machine learning algorithms to detect the ratio of lung surfactants DPPC and SM using Raman spectroscopy. We have prepared different ratios of DPPC and SM and Raman spectrum was collected and analyzed. Data provided is corrected for humidity level and will be helpful in training future algorithms. 
 
Description Collaboration with IIT Madras (India) on the newly formed Centre of Excellence: Centre of Excellence on Advanced Biochemical Sensing and Imaging Technologies (ABSIT) 
Organisation Indian Institute of Technology Madras
Country India 
Sector Academic/University 
PI Contribution Initiating collaborative research on biochemical sensing based on the photonic platform we are developing.
Collaborator Contribution The Centre of Excellence brought together a multidisciplinary team of experts from departments of Physics, Electrical Engineering, Chemistry, Biotechnology with similar research interests in Sensing and Imaging. Collaborating with this team of scientists and engineers, will provide us opportunity to flourish with complementary skills and achieve wider impacts on the biomedical diagnostics research.
Impact This is a multidisciplinary collaboration involving Physics, Electrical Engineering, Chemistry and Biotechnology.
Start Year 2020
 
Description Collaboration with Ningbo University, China 
Organisation Ningbo University
Country China 
Sector Academic/University 
PI Contribution This collaboration was initiated as part of a joint Royal Society/NSFC International Exchange Programme. The research team at Southampton wrote the proposal on novel on-chip Mid-IR sources for application in biomedical sensing and submitted to the Royal Society
Collaborator Contribution Our partners submitted a proposal to NSFC for joint funding with complementary research on the materials research i.e. advanced materials required for device fabrication at Southampton
Impact Joint funding and collaborative research (ongoing)
Start Year 2021
 
Description Collaboration with University Hospital Southampton 
Organisation University Hospital Southampton NHS Foundation Trust
Country United Kingdom 
Sector Hospitals 
PI Contribution This collaboration was initiated as part of effort to extened the phtonic chips for diagnois of ARDs.
Collaborator Contribution Our partners will collect samples from patients.
Impact Working on the ethical statment
Start Year 2022
 
Description SIME Diagnostics Limited (Collaborating Project Partner) 
Organisation SIME Diagnostics Limited
Country United Kingdom 
Sector Private 
PI Contribution The sensing platform developed will be first patented and then commercial exploitation will be sought through this partner.
Collaborator Contribution This partner will help with the clinical application and commercialisation of the sensing platform
Impact Yes, Multidisciplinary involving Photonics, Nanotechnology, Artificial Intelligence and clinical point of care.
Start Year 2020
 
Description Light Express laser show on Scinence and engineering day. 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact The University of Southampton runs a yearly Science and Engineering Day on campus which invites the public to explore research conducted at the university through interactive workshops and talks. A member of our group volunteered on the Science and Engineering Day with the University's Light Express laser show (7th May 2022) and has helped to organise the show at this year's festival (18th March 2023) as part of their role as Equity, Diversity and Inclusion and Outreach Officer for the University of Southampton Optics and Photonics Society. The show runs for approximately 40minutes, during which time the audience learn some important concepts in optics and photonics such as total internal reflection, and how light is used in their daily lives (i.e. optical fibres for the internet).
Year(s) Of Engagement Activity 2022
 
Description Light wave road show 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact Research group member had helped run workshops on campus for Year 8 (12-13 year old) students based on spectroscopy as part of the University of Southampton's award-winning Light Wave program on 24th November 2022. Participants made spectroscopes from CDs and card, enabling them to identify the gases in different lamps (i.e. helium) from their component colours. This introduced the ideas of absorption and emission, from which some research projects using spectroscopy were discussed, including our own work on biomolecular detection.
Year(s) Of Engagement Activity 2022
URL https://www.lightwave.soton.ac.uk/about
 
Description News about the project in national online magazines 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Media (as a channel to the public)
Results and Impact The main purpose of this news release was to create awareness among common public and show the potentials of multidisciplinary research, especially the role of photonic devices in rapid biomedical diagnostics in point of care settings. During the national lockdown restrictions, we thought that this is the alternative to reach the common public with our idea.
Year(s) Of Engagement Activity 2020
URL https://www.theengineer.co.uk/nrds-rapid-test-southampton/
 
Description Optics workshops for the general public 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Undergraduate students
Results and Impact A number of workshops on optics were run for the general public as part of Southampton Festival for Arts and Humanities. Activities included making kaleidoscopes and spectroscopes with a range of age groups from primary school to adults. Those attending gained an understanding of reflection and refraction, and how optical fibre communications work. These activities were also used to help explain some of the photonics research being carried out at the University of Southampton.
Year(s) Of Engagement Activity 2021