Inavya Ventures Ltd Public Funding

The UK population is increasing and getting older, causing ever-increasing demand on the NHS. By 2033/34, the cost will reach 9.9% of national income. There's a pressing need to reduce NHS healthcare costs. There's also strong market demand to reduce healthcare costs in other global healthcare markets. For example, in the US, an estimated 125,000 lives are lost annually and additional healthcare expenditures of $290 billion are driven by non-adherence to medication; and, 10% of hospitalisations in older patients are considered avoidable through improved medication adherence. Medication non-adherence accounts for 50% of treatment failures and up to 25% of hospitalisations each year Studies show that 50-60% of patients with chronic illnesses miss doses, take the wrong doses, or drop off treatment in the first year. None of the reasons why patients are failing to adhere to medication are insurmountable. Wasted costs due to poor patient adherence are currently measured and reported retrospectively - and at population level. Yet, in reality, these costs accrue in real-time and are due to decisions made by individual clinicians and patients as they create and manage a patient's Care Plan. Project SAVER is an 18-month study with participation by Inavya, Imperial College Healthcare, and Ipsos. The research team will develop an economic tool enhancement to the existing Avatr technology, which will measure and report economic costs of medication adherence at the point of decision-making by clinicians and patients, delivering a step-change innovation for the NHS and global markets.

COVID-19 is causing health care providers globally to transform - including the NHS. To manage healthcare demand safely and optimally, hospitals are changing how patients access and use services. There is also considerable focus on prevention and developing remote care, in an effort to keep people healthy and outside of hospital - this is particularly true for 7.4 million people living with heart and circulatory diseases in the UK. Heart and circulatory diseases cause more than a quarter (27%) of all deaths in the UK. Around 80 percent of people with heart and circulatory diseases have at least one other health condition. Healthcare costs relating to heart and circulatory diseases are estimated at £9 billion each year. Cardiovascular disease cost to the UK economy (including premature death, disability and informal costs) is estimated to be £19 billion each year Black, Asian and Minority Ethnic (BAME) people are significantly more likely to develop and die early from coronary heart disease than white Europeans. African and African Caribbean people are at higher risk of developing high blood pressure and having a stroke than other ethnic groups. And, Africans, African Caribbeans and South Asians are more likely to develop Type 2 diabetes than the rest of the population. Obesity is also strongly associated with increased risk of COVID-19 deaths. As obesity contributes to coronary heart disease and type 2 diabetes and increased COVID-19 deaths. The very high prevalence of overweight and obesity in UK adults is a pressing concern (74% of Black people, 56% of Asians). It is clear that overweight and obesity can be prevented and reversed. To achieve excess weight loss, patient engagement - eating well and physical activity - is essential. There is clear evidence that BAME patients are significantly less likely to engage with healthcare providers and to follow their prescribed care plans. Although digital health services have good potential to promote health, they need to be culturally sensitive. There is a pressing need to reduce AI-bias, as it is limiting health for BAME populations. Project BAMBOOS aims to create a Social Prescription toolset to reduce levels of obesity and overweight in the BAME population. Losing excess weight will help to reduce risk for heart disease, diabetes and Covid-19 deaths, and related costs. To help people lose excess weight, the Social Prescription will leverage Avatr AI capability - enhanced with a new BAME ontology to be developed - to enable a user to generate a digital profile of their self. This profile is designed to support development of new knowledge, skills, and capabilities to help the person eat well and to take-up exercise, with their local neighbourhood optimally positioned as an enabler for weight loss. Taking a person-centred and contextualised approach - including co-development with BAME patients from Hammersmith Imperial Health - Inavya and Imperial Hammersmith Hospital will collaborate on this 9-month project. Our aim is to develop tools that support delivery of personalised medicine, enhanced with novel social prescription and AI that support weight loss for BAME patients.

Awaiting Public Project Summary

The project supports the management of long-term conditions related to Cardiovascular Diseases (CVD), which are the leading cause of death globally, representing 31% of all global deaths. People with cardiovascular disease or who are at high cardiovascular risk (due to the presence of one or more risk factors such as hypertension, diabetes, hyperlipidaemia or already established disease) need early detection and management using counselling and medicines, as appropriate. This proposal directly addresses the challenge by creating a service that helps improve methods and systems within a local health ecosystem based on the needs of the citizen at home and in the community, whereby pharmacist-led services in GP practices and community pharmacies are fully engaged as a key healthcare resource. The project aims to prevent CVD and improve clinical outcomes, helping to reduce costs and demand on NHS hospitals and GP practices. In doing so, the project will increase patient access to innovative technologies. The project is led by Inavya Ventures Ltd, a UK-based SME that has created the CE marked medical device 'AVATR' to help patients with chronic diseases, with current deployment at the National Heart Centre in Singapore and Einstein Hospital in Sao Paulo. Deployed on a smartphone, AVATR provides management and remote monitoring of data from medical-grade wearables and also contextual information from other sources, such as diet, exercise, GPS location, local air quality. Take-up of AVATR requires testing the performance of AVATR in order to quantify clinical and operational improvements, and cost-saving to NHS. The project is supported by Firza Primary Care (unfunded), which has access to over 600,000 NHS patients and delivers pharmacist-led clinical support services to 90 GP Practices throughout England; and GreenLife Pharma (unfunded), which provides technical, commercial and NHS clinical support services to 50 pharmacies to improve income growth and productivity while reducing expenditure. 42 of these pharmacies are owned by its parent company, Imaan Healthcare.During this four month project we aim to develop a detailed feasible plan to generate evidence directly from a local healthcare ecosystem of the clinical and cost-saving benefits of AVATR to the NHS. This evidence will enable AVATR to engage with the NHS and other markets, delivering commercial benefits to the partners, clinical improvements and cost saving to the NHS, and improved service to patients and citizens.

Brazil is the largest country in South America with over 200 million people and São Paulo is the largest city, with over 12 million people. Due to a rapidly ageing population in Brazil, providing effective and affordable healthcare services to elderly and vulnerable people is a growing healthcare challenge across the country. We are working with hospital clinicians at Albert Einstein Hospital in São Paulo to develop a technology platform for remote monitoring of chronic disease patients, enabling real-time healthcare intervention outside of hospital and at scale. This will use a patient smartphone App to help the patient to comply with the careplan set by their doctor, including reminders for taking medication, medical readings and making appointments, as well as personalised diet and exercise options. A linked doctor App will support the doctor to make actionable decisions about the patient’s health based on real-time patient information. This will improve healthcare and quality of life for people with chronic diseases, and also reduce hospitalisation and healthcare cost, supporting UN SDG 3 – Good Health and Wellbeing. The patient App will also recommend options to patients to improve health based on their medical condition and overall health status by raising awareness of local services and activities that can help them to live healthier and better lives. We are also developing a City Explorer web application that heatmaps the São Paulo neighbourhoods of Bom Retiro and Higienópolis according to how accessible local services, such as healthcare and transportation, are for residents with different mobility options, such as walking, public transport, and private car. This can also be extended to a larger scale. We are engaging with stakeholders in city planning, such as urban planners and developers, so they can use the City Explorer to gain increased insight into the most effective ways to improve the reach of city services to meet the needs of local communities optimally, based on differing demographics. This supports UN SDG 11 – Sustainable Cities and Communities. We are strengthening the relationship between the CityZen project partners by sharing knowledge, skills and experience across all partners and by developing a commercial agreement for all partners. Through the CityZen website and by running workshops locally, we are developing a CityZen network to strengthen the healthcare and smart cities ecosystem in São Paulo and Campinas City and help Brazilian organisations to make international links. This supports UN SDG 17 – Partnership.

CityZen aims to research and develop a machine learning technology platform that to deliver highly personalised and contextual mobile-based services for people living in city environments, with an initial focus on developing transformational approaches to advanced mobile healthcare delivery (e.g. heart monitoring) and activities of daily living, such as shopping, eating and exercise.

Dati project aims to use the increasing amount of personal data generated by individuals to gain insights into user needs and behaviours - and in doing so deliver unique benefits back to individual users and their service providers. With Dati we aim to deliver a step-change improvement on existing ‘find-near-me’ applications, which are not fully personalised or able to adjust to changes in user needs and behaviours. Our feasibility study seeks to identify specific elements of user needs and behaviours that are essential in delivering a compelling customer proposition. The output of the study will be the complete design specification and working prototype of Dati. User Push: With user permission, Dati will collect, collate and manage securely a user’s personal, behavioural and contextual data. Such data may include ‘static’ information – such as their stated preferences about travel, pleasure, food or health-driven choices. Data may also include the user’s ‘dynamic’ information, which may feed into the Dati platform from smart devices – including user’s smartphone and wearables – open data silos, social media profiles and activities, past consumption data, search-related interactions or the user’s explicit ratings. Data provided by the user enables the creation of a user profile (a personal ‘brand’ identity). User Pull: With the highly contextualised information provided by the user, Dati is able to scan perhaps thousands of service and product offerings (restaurants, leisure, shops, transport, etc) and deliver back to the user best-match context-specific options - all done without the need to enter any search information. The suggested options will know the geolocation of a user, and may be informed by additional dimensions, such as the time of the day, environmental and weather conditions, proximity of social and professional networks, user’s health, mood, and other attributes which, collectively, represent the user’s interest at any given time and place. The suggested options may well include price and time-savings benefits to users. Dati Technology: As a new and novel technology, Dati will deliver this transformational user experience via a unique (and protectable, exploitable) semantic and linked data layer. Dati will use ‘COMPOSE’ (www.compose-project.eu), a highly scalable, cloud-ready and open-source big data and linked-service technology in order quickly to build and deploy the Dati service discovery and recommendation back-end. To cope efficiently with multiple streams of personal and behavioural data pushed from Internet enabled devices – such as, beacons, sensors, smartphones and wearables – Dati will use the powerful ‘COMPOSE’ Internet of Things data streaming functionality. As the customer-facing presentation front-end, Dati will improve the ‘Best4Me’ mobile application technology, a unique and personalised social feeds aggregation channel with topic-based filtering features.