Ubiquitous Optical Healthcare Technologies (ubOHT) Programme Grant
Lead Research Organisation:
University of Cambridge
Department Name: Physics
Abstract
Vision: to drive and promote advances in optical biosensing capable of translation to low-cost monitoring, and to build a broad UK community in low-cost sensing for healthcare.
Precision medicine tailors healthcare to individual patient characteristics. We are now entering a new era of precision health, which shifts towards healthy individuals, asking how we prevent disease with appropriate interventions, prolonging healthy lifespans. New challenges include the urgent need for precise technologies to monitor individuals throughout life, and for improved methods to interpret this wealth of data.
Precision health demands new physical biosensors that are low-cost but elicit rich biochemical information and can be used outside the clinic. This frees up clinician-time and focusses scarce resources. It is vital to develop methods to extract/exploit downstream patient-specific information from the sensors. Current exemplars ('BioSensors 1.0') are wearable devices (such as Fitbit, Apple watch), which record only superficial parameters (eg. temperature, acceleration, blood oxygenation), while glucose/insulin sensors provide only very specific data; the major challenge of providing comprehensive analytical information with an affordable portable device remains key for healthcare. The SARS CoV-2 lateral flow tests popularised the notion of personalised disease testing and showed it can be a reality however they lack sensitivity, reliable and consistent interpretation, and robust reporting capabilities.
The leading groups assembled here have a track record of pioneering optical approaches for new paradigms in the biosensing domain, from conception through to market. Together, they propose to synergistically explore the underpinning fundamental science of 'BioSensors 2.0' and develop key demonstrators that address clinical needs while building a broader UK community of academics, SMEs, institutes, & clinicians to drive this paradigm to real demonstrators.
Current portable sensors are too simple and limited in their capability. Instead, we need to translate advanced lab-based technologies into portable devices. Systems aspects need care, while miniaturisation is challenging. Sensors should achieve multiplexing, use machine learning algorithms to interpret outcomes, auto-calibrate to ensure long term operation, survive changing conditions, and attain small-enough limits of detection required for various biofluids. This is a time-critical juncture, as other countries will start to develop in this space, though nothing explicitly exists yet- the NHS as the main UK provider may be a great driver.
We also focus on community building, with targeted activities to ensure the UK is placed to capitalise on sensor developments. Through building a Big Idea 'Making Senses' for the Research Councils across the wider Sensors ecosystem, our team identified with EPSRC the lack of UK leadership and joined-up academia-industry-govt networks. Engaging with a wide range of stakeholders from SMEs to large entities (NPL, CPI, LGC, Turing..) and multinationals (P&G, AstraZeneca,..), we find strong appetite and market pull for new types of biosensors with application domains beyond the hospital, as well as industrial settings. New ways to leverage light-matter interactions (in which the is UK internationally strong) for realistic biodiagnostics demands a broad interdisciplinary research focus. This confluence aims to develop entirely new industries of the future, and to energise the UK interdisciplinary science base, which is vital over the next 50 years as we realise the new paradigm of BioSensors 2.0.
Precision medicine tailors healthcare to individual patient characteristics. We are now entering a new era of precision health, which shifts towards healthy individuals, asking how we prevent disease with appropriate interventions, prolonging healthy lifespans. New challenges include the urgent need for precise technologies to monitor individuals throughout life, and for improved methods to interpret this wealth of data.
Precision health demands new physical biosensors that are low-cost but elicit rich biochemical information and can be used outside the clinic. This frees up clinician-time and focusses scarce resources. It is vital to develop methods to extract/exploit downstream patient-specific information from the sensors. Current exemplars ('BioSensors 1.0') are wearable devices (such as Fitbit, Apple watch), which record only superficial parameters (eg. temperature, acceleration, blood oxygenation), while glucose/insulin sensors provide only very specific data; the major challenge of providing comprehensive analytical information with an affordable portable device remains key for healthcare. The SARS CoV-2 lateral flow tests popularised the notion of personalised disease testing and showed it can be a reality however they lack sensitivity, reliable and consistent interpretation, and robust reporting capabilities.
The leading groups assembled here have a track record of pioneering optical approaches for new paradigms in the biosensing domain, from conception through to market. Together, they propose to synergistically explore the underpinning fundamental science of 'BioSensors 2.0' and develop key demonstrators that address clinical needs while building a broader UK community of academics, SMEs, institutes, & clinicians to drive this paradigm to real demonstrators.
Current portable sensors are too simple and limited in their capability. Instead, we need to translate advanced lab-based technologies into portable devices. Systems aspects need care, while miniaturisation is challenging. Sensors should achieve multiplexing, use machine learning algorithms to interpret outcomes, auto-calibrate to ensure long term operation, survive changing conditions, and attain small-enough limits of detection required for various biofluids. This is a time-critical juncture, as other countries will start to develop in this space, though nothing explicitly exists yet- the NHS as the main UK provider may be a great driver.
We also focus on community building, with targeted activities to ensure the UK is placed to capitalise on sensor developments. Through building a Big Idea 'Making Senses' for the Research Councils across the wider Sensors ecosystem, our team identified with EPSRC the lack of UK leadership and joined-up academia-industry-govt networks. Engaging with a wide range of stakeholders from SMEs to large entities (NPL, CPI, LGC, Turing..) and multinationals (P&G, AstraZeneca,..), we find strong appetite and market pull for new types of biosensors with application domains beyond the hospital, as well as industrial settings. New ways to leverage light-matter interactions (in which the is UK internationally strong) for realistic biodiagnostics demands a broad interdisciplinary research focus. This confluence aims to develop entirely new industries of the future, and to energise the UK interdisciplinary science base, which is vital over the next 50 years as we realise the new paradigm of BioSensors 2.0.
Organisations
- University of Cambridge (Lead Research Organisation)
- Hitachi Cambridge Laboratory (Project Partner)
- AstraZeneca (Project Partner)
- Wasatch Photonics (Project Partner)
- Spiden AG (Project Partner)
- Nokia Bell Labs (Project Partner)
- LGC (Project Partner)
- National Physical Laboratory (Project Partner)
- Owlstone Medical (Project Partner)
- Omnivision (Project Partner)
- EG Technology Ltd (Project Partner)
- The Alan Turing Institute (Project Partner)
- Unitive Design and Analysis Ltd. (Project Partner)
- Cambridge Consultants Ltd (Project Partner)
- Eastern Academic Health Science Network (Project Partner)
- NRBTech Ltd (Project Partner)
- Huawei Technologies (UK) Co Ltd (Project Partner)
- Procter & Gamble Limited (P&G UK) (Project Partner)
- Sony Precision Technology Europe GmbH (Project Partner)
Publications
Asgarnezhad-Zorgabad S
(2025)
Picocavity modal analysis: A multiple-scattering approach for picoscopic mode coupling
in Physical Review Research
Baumberg J
(2023)
Quantum Plasmonics in Sub-Atom-Thick Optical Slots.
Baumberg JJ
(2023)
Quantum Plasmonics in Sub-Atom-Thick Optical Slots.
in Nano letters
Blair S
(2024)
Green etching of indium tin oxide metasurfaces
in Optical Materials Express
Boehmke Amoruso A
(2024)
Uncovering low-frequency vibrations in surface-enhanced Raman of organic molecules.
Büehler A
(2025)
Guided Multispectral Optoacoustic Tomography for 3D Imaging of the Murine Colon.
in Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Groom M
(2024)
Microlens Hollow-Core Fiber Probes for Operando Raman Spectroscopy
in ACS Photonics
| Title | Data for "Design Rules for Catalysis in Single-particle Plasmonic Nanogap Reactors with Precisely Aligned Molecular Monolayers" |
| Description | Data for all figures in the manuscript (which is Open Access). In the excel .xls files are all the data for each suitable figure in the Open Access paper. The axes are labelled in these files. Fig. 2 | Plasmonic activity of the four NR types. Histograms of the dominant coupled mode wavelengths from dark-field spectra of >200 NRs and average spectra from each bin of (a) Au-on-Au, (b) Au-on-Pd, (c) Pd-on-Au, and (d) Pd-on-Pd NRs. Black dotted curves are Gaussian fits of histograms and the centre wavelength (?centre) from each fit is noted at the top. (e) Representative dark-field spectrum of each single NR. Normalized SERS spectra of (f) 4-BTP and (g) NC-BPT measured over 5min from each NR under ambient conditions without 2nd reactant, for 100 µW laser. From bottom to top: Au-on-Au (orange), Pd-on-Au (darker orange), Au-on-Pd (brown), Pd-on-Pd (grey), and DFT-simulated spectrum of isolated molecule (dashed). Fig. 3 | SERS spectra from each NR type in solution of CPBA and K2CO3. (a) Colourmaps of repeated SERS spectra (300 frames @ 1 s integration times). (b) Initial (t = 1 s, blue) and final (t = 5 min, red) SERS spectra from colourmaps in (a). (c) SERS spectra normalized by maximum intensity in solution over 5 min for each NR type. (d) SERS spectra of blue-shaded region in (c). From bottom to top: Au-on-Au (orange), Pd-on-Au (darker orange), Au-on-Pd (brown), and Pd-on-Pd (grey). Fig. 4 | Progress of SERS peak intensity ratio during Suzuki-Miyaura coupling reaction, comparing NRs to monolayer NP aggregates (MLaggs). (a,b) Dynamics of peak intensity ratio R_21 of 1572 cm-1 NC-BPT mode (?_2) to 1532 cm-1 mode of 4-BTP (?_1) for (a) NRs and (b) MLaggs (note multiplied by x5). (c,d) Peak intensity ratio of 2255 cm-1 NC-BPT mode (?_3) to ?_1 for (c) NRs and (d) MLaggs. (e) Laser-driven catalytic conversion yields at t = 1 s (darker bars) and t = 5 min (for NRs) or t = 30 min (MLaggs) (lighter hatched bars). (f,g) Slow rate constants (k_slow) fitted from (a-d) using two-step kinetics. (h) Schematic molecular alignment in NPoM and MLagg geometries, showing thiols bound to one or both facet surfaces. Labels 1-6 as defined in (a,b). Suppl. Fig. 2 | Cyclic voltammograms of Au (0 ML Pd) and Au@Pd NPs with different coverages of Pd Suppl. Fig. 6 | Time-series SERS spectra of 4-BPT from individual NRs in ambient conditions Suppl. Fig. 7 | Time-series SERS spectra of NC-BTP from individual NRs in ambient conditions Suppl. Fig. 8 | Laser-power dependent SERS spectra Suppl. Fig. 9 | DFT-calculated vibrational modes Suppl. Fig. 10 | SERS spectra from each NR type in solution of phenylboranic acid (PBA) and K2CO3 Suppl. Fig. 11 | Lorentzian peak fitting results for NRs Suppl. Fig. 12 | Progress of 1550 cm-1 mode intensity during the reaction Suppl. Fig. 14 | Averaged SERS of MLaggs before and after reaction Suppl. Fig. 15 | Time-series SERS spectra colormaps from MLaggs during reaction Suppl. Fig. 16 | Lorentzian peak fitting results for MLaggs Suppl. Fig. 17 | SERS spectra with 785 nm laser excitation Suppl. Fig. 18 | Peak analysis results of Au and Pd MLaggs at different laser powers Suppl. Fig. 20 | DFT-calculated projected density of states (PDOS) of surface atoms Suppl. Fig. 21 | Electrochemical characterization of Au@Pd films |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/374647 |
| Title | Research Data supporting "Extensive photochemical restructuring of molecule-metal surfaces under room light" |
| Description | This repository record contains the data of all main and supplementary information figures of the manuscript. The data are in txt files or excel files, tab seperated, and with columns labelled. All further information is contained in the captions of the manuscript. The data are organized in folders for each figure, with files named according to the figure number and panel. The experiment data are collected by Python code and simulated by Python and MATLAB, There are also some FDTD and DFT simulation data. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/366306 |
| Title | Research Data supporting "Uncovering low-frequency vibrations in surface-enhanced Raman of organic molecules" |
| Description | Data from each of the molecules (used in the main figures of the paper) is contained in the .h5 files of each relevant folder, with wavenumbers in the corresponding file. The data for this publication is contained in the files in this deposit. The paper is open access so all the information is publicly accessible, and we refer to all figure captions and the full methods section. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/370645 |
| Title | Research data supporting "Controllable Multimodal Actuation in Fully Printed Ultrathin Micro-Patterned Electrochemical Actuators" |
| Description | This dataset contains profilometry and nanoindentation data, optical and SEM images, motion tracking and electrical measurement data, codes to analyse the data, and videos. The dataset is split into 3 zipped folders, each including a readme file to further explain the contents. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/363348 |
| Title | Research data supporting "In-situ electrochemically regenerated ultrathin active SERS sensors" |
| Description | This dataset contains the data of all main and supplementary information figures of the manuscript. The data are in txt files, tab separated, and with columns labelled. All further information is contained in the captions of the manuscript. The data are organized in folders for each figure, with files named according to the figure number and panel. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| URL | https://www.repository.cam.ac.uk/handle/1810/364406 |
