Public Funding for Applied Nanodetectors Limited

Formaldehyde is a significant health risk, and International Agency for Research on Cancer (IARC) classifies formaldehyde as a human carcinogen. There are stringent formaldehyde exposure guidelines that exist for indoor air (80 ppb WHO) that can be even lower at the national level (e.g., France 8 ppb by 2023). People are exposed to formaldehyde from a variety of sources inside their homes. These include many everyday products, such as cosmetics, furniture, and detergents. With the growing health threat that formaldehyde poses, it is becoming more critical to monitor homes and other indoor spaces so that inhabitants can take action to minimise their exposure. Formaldehyde is usually measured by on-site batch sampling and off-site quantification in an external analytical laboratory. These procedures are expensive, time-consuming, require skilled personnel and do not allow on-site monitoring. Formaldehyde measurement in ambient air requires ppb-level detection sensitivity from a monitor. Furthermore, when used in indoor air monitoring, they must be selective to detect ppb-level formaldehyde concentrations in ambient air containing hundreds of compounds. Current products on the market require consumers to sacrifice sensitivity and selectivity for cost; low-cost sensors do not meet the goal of a low detection limit of 20ppb or give false positives to common chemicals such as ethanol. Applied Nanodetectors indoor air quality monitoring system (AND-IAQ01), can detect formaldehyde at ppb levels. It also measures key indoor pollutants, including carbon dioxide, particulate matter (PM2.5), and total volatile organic compounds (TVOC). This device complies with the essential requirements of all relevant harmonised and designated standards required for The UKCA (UK Conformity Assessed) marking. The product is commercially available via key specialist suppliers. The London Government Chemist (LGC) will evaluate our system performance by exposing the device to synthetic air/formaldehyde mixtures (down to 20 ppb) and evaluate the effect of confounding gases.

The project consists of an integrated software platform that provides connecting information for technical and non-technical stakeholders, facilitating the implementation and monitoring of Trustworthy AI within organisations. This platform comprises four main unique features: 1. Technical information platform 2. Non-technical information platform 3. Check-list 4. Chatbot The technical information platform converges up-to-date information about Trustworthy AI practices and learning resources in a comprehensive, easy-to-use tool with visual aids. This offers the AI practitioner adequate access to information that allows him to detect potential trustworthiness breaches and learn how to overcome them. Facilitated access to technical knowledge will help surpass extensive challenges with specialised skill shortages and the need for precise regulation and guidelines. The checklist consists of an interactive to-do list, which allows the AI practitioner to keep track of performance variation and model drifts, organising their progress in an easy-to-visualise manner. Both the AI practitioner and managing stakeholders have access to this list, facilitating top-down monitoring of preventative measures. The non-technical information platform supports the transformation of transforming technical text into summarised comprehensive content for managing stakeholders. The previous checklist functionality consists of two segments: the list and a drop-down connection to this non-technical informative platform. When clicking on one item of the check-list, a drop-down menu appears with a non-tech description of the problem in hand and the steps to resolve it (i.e. Fairness, Algorithm and Data Bias) in a way that informs the managing stakeholder of the general approach being taken to reach a Trustworthy AI solution. In improving internal communication between different levels of technical knowledge, the information provided to users by managing stakeholders will also become more complete and transparent, increasing adherence to AI tools. Finally, the connecting feature of the Chatbot provides support for both the AI practitioner in finding the necessary information in the technical platform and the managing stakeholders by answering specific questions about Trustworthy AI procedures based on non-technical documentation.

Indoor air quality (IAQ) is one of the leading environmental risks, which affects people's, comfort, health, and well-being. People spend around 90% of their time indoors, and daily exposure to indoor air pollutants may occasionally be more than 10 times higher than outdoor pollutant (EPA). It is estimated, for instance, that up to 20% of the population suffers from asthma and other allergic diseases caused by substances typically present in indoor environments. In addition, indoor pollutants such as tobacco smoke, radon, asbestos and formaldehyde may substantially contribute to the increase of cancer incidents in the population. The World Health Organization (WHO) estimates that 700,000 people per year die from poor breathing conditions. Clearly, IAQ has a significant impact on people's comfort and health. In this proposal, we plan to develop an ultrasensitive home-based IAQ sensing system that can detect adverse levels of pollution, predict and identify the pollution sources, and provide actionable suggestions to help people improve IAQ. Using this new system will enable users to correlate household tasks to pollution events and take action to reduce them. We believe this will lead to a behaviour change and positive action to reduce IAQ that affects their health. The new IAQ system would have the capability to detect and measure specific, high risk and common harmful pollutants and particulates alongside other indicators of IAQ and ventilation including carbon dioxide, ambient temperature and humidity. We would also use machine learning techniques to analyse the sensor data to accurately predict an increase in pollution levels, identify the potential cause and inform prevention and mitigation measures. The IAQ system would be designed to meet the user requirements and to also measure the pollution levels accurately. We would modify our gas sensor array platform to detect key common hazardous pollutants formaldehyde (<10ppb) and carbon monoxide (ppm). Our new pollution gas sensor array would be integrated with commercial sensors, (carbon dioxide, total volatile organics (TVOCs), particulate sensor, temperature and humidity and has Bluetooth connectivity) to make a new air IAQ system.

no public description

The COVID-19 pandemic raises particular challenges for the 400,000 UK care home residents, their families and the key staff that look after them. Recent guidance from the British Geriatric Society has been developed to help care home staff and NHS staff who work with them to support residents through the pandemic. This guidance recommends that where possible, care home staff should be trained and equipped to measure vital signs including temperature, blood pressure, heart rate, pulse oximetry and respiratory rate. This will enable external healthcare practitioners to triage and prioritise support of residents according to need. We aim to develop a simple, low cost, portable device to monitor the essential vital signs providing useful actionable measurements in a few minutes. This device has direct relevance in the current COVID-19 crisis where it can be used alongside other front-line care solutions to identify and monitor people at risk of respiratory problems. It would be designed to be easy to use for care home staff. This new solution would protect them, and the people they care for improving their quality of life and help them live longer. The device, which could be directly utilised in care homes and community settings works by monitoring the lung function allowing very early indications of any abnormalities and also the progression of illness -- directly relevant in COVID-19, but with broader healthcare application beyond the current crisis. The impact funding will be fundamental in achieving the rapid market deployment of our innovative new device for the early detection of COVID-19 infections and identification of patients at risk of deterioration. The project has enabled a rapid technological development to prototype and the impact funding will allow us to progress the associated commercial developments at a pace that would otherwise be difficult. The funding will allow us to move ahead with health and safety assessment with external partners ahead of a clinical study to obtain clinical validation of the device. We will also progress our discussions with end users such care home managers, and other potential partners. We aim to thoroughly ‘field test’ and refine our value proposition, develop our business model and commercialisation plan. This further validation work will be inform our new business plan for a planned fundraising effort in the next 6-12 months to support full commercialisation, scale up, and growth. The ultimate impact will be in getting our product into the market where it will support a preventative model of care allowing for early intervention to keep people out of hospital and reduce the burden on the health care system. The project extensive will also position the company for future global growth. For example, COVID-19 has caused a massive acceleration in the use of telehealth. For example in the US consumer adoption has skyrocketed from 11 % of US consumers using telehealth in 2019 to 46% of consumers now using telehealth to replace cancelled healthcare visits.

Chronic Obstructive Pulmonary Disease (COPD) and asthma are leading causes of morbidity and mortality worldwide and have a significant economic and social burden. Significant challenges include delays in an accurate diagnosis, maintaining good disease control and the identification of exacerbations, which consume a disproportionate share of expenditure due to the high cost of treatment and hospital admissions. As a result, there is an unmet need for non-invasive, simple tests that can diagnose and monitor these conditions accurately. Breath analysis is one such non-invasive test whereby small quantities of volatile organic compounds (VOCs) can be detected in human breath; they form a personalized signature fingerprint of components that can be used for early diagnosis and disease monitoring. We plan to develop a standardized handheld breath test system (early prototype tested in the laboratory) to be used by clinicians and patients that could allow detection of exacerbations earlier and optimising accurate treatment depending on the pathological driver of the exacerbation. This would form part of a self-care program and home monitoring solution to guide personalized treatment plans in less than one minute. Our innovative new breath test system would be handheld, easy to use and internet enabled and significantly cheaper. It would use our unique sensor chip that can monitor many gases simultaneously with high accuracy and high sensitivity.

"Applied Nanodetectors (AND) propose to investigate the feasibility of a low cost fractional exhaled nitric oxide (FeNO) breath test for the diagnosis of asthma for use in primary care settings. The rapid and accurate diagnosis of asthma and identification of patients would be essential to ensure that adequate treatment, including hospitalisation when necessary, is implemented as early as possible. This type of diagnostic techniques would lead to more efficacious treatments and help to reduce the burden of disease. Asthma is mainly diagnosed principally on the basis of a careful clinical history taken by a clinician. However, studies of adults diagnosed with asthma suggest that up to 30% do not have clear evidence of asthma. Recent NHS asthma guidelines have recommended the need for objective testing using FeNO that would offer a significant improvement to current practise. We will work on innovatively integrating this new FeNO sensor into a handheld device for use by healthcare professionals. A low-cost gas sensor fabricated using active nanomaterial metal oxide (MOx) gas sensor array for the detection exhaled nitric oxide in exhaled breath associated with the diagnosis and management of asthma. This sensor would be integrated with Applied Nanodetectors sensor electronics and a new prototype would be developed in this project. Nanomaterial formulations will be deposited onto plastic substrates and subsequently modified to selectively detect FeNO and has exhaled gas flow rates. The disposable FeNO gas sensor will be then excited using Applied Nanodetectors new patented innovative technique and then exposed to test gases mixtures to optimize the sensor performance. The target is to provide breakthrough technology in diagnostics which can potentially significantly lower measurement costs and improve diagnostic testing. This would lead to a reduction in costly drugs given to people misdiagnosed and also early diagnosis will ensure patients get the appropriate treatment leading to improve outcomes. Exploitation of these project results will lead to development of prototype that can used for clinical validation and clinical utility studies."

"We propose to investigate the feasibility of a point of care (POC) exhaled breath test for the diagnosis of asthma for use in primary care setting. The rapid and accurate diagnosis of asthma and identification of patients would be essential to ensure that adequate treatment, including hospitalisation when necessary, is implemented as early as possible. This type of diagnostic techniques would lead to more efficacious treatments and help to reduce the burden of disease. Asthma is mainly diagnosed principally on the basis of a careful clinical history take taken by a clinician. However, studies of adults diagnosed with asthma suggest that up to 30% do not have clear evidence of asthma. There is a critical need for objective testing using fractional exhaled nitric oxide (FeNO) and detection of volatile organic compounds (VOCs) that would offer a significant improvement to current practise. We will work on innovatively integrating these two new sensor elements into a handheld device for use by healthcare professionals. A low-cost gas sensor fabricated using active nanomaterial metal oxide (MOx) gas sensor array and flexible polymer substrates for the detection FeNO and VOC biomarkers in exhaled breath associated with the diagnosis and management of asthma. A new flow sensor fabricated using new nanomaterial formulations that can detect and measure gas flow that could be used to make lung function measurements. Nanomaterial formulations will be carefully formulated and deposited onto plastic substrates and subsequently modified to selectively detect FeNO and VOC biomarkers. The printed FeNO gas sensor will be then excited using Applied Nanodetectors new patented innovative excitation technique and then exposed to test gases mixtures to optimize the sensor performance. The target is to provide breakthrough technology in diagnostics which can potentially significantly lower measurement costs and improve diagnostic testing. This would lead to a reduction in costly drugs given to people misdiagnosed and also early diagnosis will ensure patients get the appropriate treatment leading to improve outcomes. Exploitation of these project results will lead to development of prototype that can used for clinical validation and clinical utility studies."

Applied Nanodetectors has developed a sensor array platform that can be used for a number of market opportunities. Each sensor array is composed of different sensor elements produced using specific nanomaterials, which can be used for chemical and biosensors. This sensor array can be designed in the same physical space and allows forward integration into the same package. Which would dramatically reduce costs and ease the manufacturing complexity. Our sensor arrays combine sensory data from different sensor elements to provide information that is more accurate and dependable than that which would be acquired from individual sensors. There are many different applications for our sensor platform and we have a significant market pull from the healthcare and other market sectors. A key market requirement is to integrate our sensor die into a smart sensor module, that would include signal conditioning, analogue-digital conversion, signal processing and digital output. In this project, we plan to develop manufacturing methods and integration techniques to develop a smart hybrid sensor module.

Millennium Develop Goal 7c - to reduce by half the 4 billion people without sustainable access to safe drinking water - has encouraged rapid growth in water quality testing. Despite this, exposure to high levels of arsenic & fluoride through contaminated drinking water remains a global health problem, affecting an estimated 300m people worldwide & over 6m people in Mexico. Chronic exposure to arsenic leads to numerous health issues, including skin lesions & cancers, while long-term exposure to fluoride leads to bone and joint deformities and dental problems. No cure exists for either; the only solution is to prevent excessive exposure through affordable testing & filtration. In this project the teams will collaborate to develop novel test strip-based field tests for both that will be rapid, easy-to-use & affordable, while also developing a novel fluoride filter to go along with an arsenic filter developed previously. The teams will develop a smartphone app that will help to map the problem & will develop prototypes of the low-cost electronic readers. The new sensors & lab-scale filter with be validated in field trials in one of the worst affected regions of Mexico.

Chronic obstructive pulmonary disease (COPD) is a prevalent lung disease (3 Million in UK) that accounts for a major burden in the UK in terms of morbidity (25,000 deaths a year) and health care costs (£4bn). COPD is punctuated by exacerbations which are episodes of increased respiratory symptoms associated with systemic and airway inflammation. Most exacerbations however are either triggered by viral or bacterial infection, a diagnostic test which could confirm the presence of of pathogenic airway bacteria would be useful in helping guide physicians in prescribing appropriate medication. In this project we will investigate the viability of using a nanomaterial based printed SERS sensor array to detect bacteria in sputum samples to predict the onset of exacerbations. We will use SERS for identification and discrimination of bacteria based on their detected spectral fingerprints.

We propose to investigate the feasibility of producing high resolution lithographic electrodes and printed active material gas sensors on polymer substrates using ink-jet and aerosol jet techniques for the detection of compounds (VOCs) in exhaled breath associated with the diagnosis and management of diabetes. Nanomaterial mixtures will be carefully formulated and deposited onto plastic substrates and subsequently modified to selectively detect VOCs. The printed gas sensors will be then excited using Applied Nanodetectors new patented innovative UV excitation technique and then exposed to test gases mixtures to optimize the sensor performance.The feasibility of making low cost gas sensors on plastic substrates for a diabetes breath test is novel and innovative. The main objectives are A) to design, fabricate and test a pre-industrial evaluation test sensor array on a range of plastic substrates to be used as a breath test for diabetes. B) explore the deposition of sensitised nanomaterial deposition system for active area coatings. C) Evaluate suitability for a range of gases for monitoring of diabetes (VOC’s) and benchmark performance against existing Si based technology.

Diabetic ketoacidosis (DKA) is a dangerous condition and the leading cause of hospitalization and the main cause of morbidity and death in children and adolescents with type 1 diabetes. Earlier diagnosis of blood ketones facilitates the prevention of ketoacidosis, as well as prompt treatment. Most ketone testing is routinely undertaken using dipstick test strips for urinalysis. Urine ketone strips are semi-quantitative and patients find it unpleasant and inconvenient to provide a urine sample. Quantitative exhaled acetone detection and analysis is an ideal alternative method. In this feasibility project we propose to investigate the feasibility of fabrication of an exhaled gas acetone sensor array using inkjet printed nanomaterials (nano-carbon or metal oxide based) and measure their initial performance. Our approach would be to use highly sensitive nanomaterials and proprietary organic polymer coatings which are highly selective and insensitive to humidity.

Awaiting Public Project Summary

This feasibility study will evaluate new business models related to integrated systems and embedded electronics for our new asthma diagnostic device to manage respiratory disease in the home. The total costs incurred, due to asthma in Europe is €17.7 billion per and 30 million people in Europe currently were suffering from asthma and 6 million of them suffered severe asthma. The NHS is now looking for new technology solutions to focus on managing asthma patients in the community to make the required efficiency gains and savings. In this project we will engage with the NHS consultants to understand their requirements for asthma patients. We will then analyse and produce new business models based on the nine elements of the Business Model Canvas. Each model will be evaluated using business development criteria and presented to the NHS to get their feedback.

The proposed design study is to assess the feasibility of developing a hand held reusable non-invasive breath test device for blood glucose monitoring and diabetes self-managment of diabetes. Diabetes is one of the biggest health challenges facing the UK today; recent estimates show that it costs the NHS £9 billion a year. Blood glucose monitoring is a reliable and essential requirement of disease management and control. For each blood glucose test, a single use test strip and lancet is required plus storage containers for carrying these items and sharp waste containers for disposal. The test process is very difficult to use, inconvenient and has a large environment impact in terms of waste and safe disposal. We would produce a design specification for the new product to reduce the overall environmental impact, from starting material, manufacture, product use and final disposal. The design specification will lead to reduced environmental impact without degrading performance.

The rapid identification of bacterial pathogens associated with infections in community acquired pneumonia (CAP) using a simple diagnostic test is critical for effective patient care and this would reduce the financial burden of treatment and antibiotic prescriptions. Breath analysis is a non-invasive rapid process whereby small quantities of volatile organic compounds (VOCs) can be detected in human breath, and they can form a fingerprint that can be used for early disease detection and diagnosis. Volatile metabolites are produced by different bacteria types. This project will investigate the use of nanosensor based arrays to detect, distinguish and quantify the volatile metabolites associated with common bacterial and viral infections, which would form the basis of a breath diagnostic test for CAP. A nanosensor array will be optimized and then exposed to simulated gas mixtures which will represent a typical breath sample from a patient with bacterial or viral infections.