A healthtech startup founded by a NHS doctor in London, Abtrace uses machine learning to learn from patients’ health records and suggests tests proactively. This startup just secured £2.1 seed million funding to transform how GPs detect and treat long-term health conditions.
Eyes to rollout new GP practices
The investment round was led by the Lisbon-based VC fund Faber along with participation from Ganexa Capital. Also, it includes £1 million in project funding from Innovate UK. Previously, Abtrace secured £2 million in pre-seed funding from EIT-Health’s Wild Card venture builder programme and UK Research & Innovation.
The funds will be used to roll the technology out to new GP practices across the UK and expand their engineering and data science teams.
Abtrace co-founder and CEO, Dr Umar Naeem Ahmad said: “Abtrace is part of the paradigm shift: from reactive to proactive care, from late diagnosis to early detection, from healthcare records that just store data to intelligent predictive systems that use it to improve and save lives. Our results so far have been hugely encouraging and we’re delighted that these investors have made it possible to expand our reach to help more patients.”
Sofia Santos, Partner at Faber, said: “We are very excited to support Abtrace’s bold ambition and to be backing them at such an early stage. The transformative potential of their solution for primary care is a perfect example of how data solutions can make healthcare systems more effective and ensure patients receive tailored, timely care in a human way.”
Founded in 2018, Abtrace has built a unique AI tool which can plug-into the Electronic Health Record (EHR) database and identify which tests or treatments a patient with a long-term health condition needs or might benefit from. The software allows GPs and healthcare assistants (HCAs) to make more informed decisions, automate key elements of disease monitoring, and ensure patients receive consistent, effective care.
By acting as an intelligent layer on top of the EHR, the system suggests actions based on an individual’s medical history as well as learning from a wider pool of data points – prompting proactive early interventions and spotting trends that might otherwise be missed.
Overall, the technology will enable the management of long-term health conditions to move from a reactive, often piecemeal approach, to a proactive process informed by rich data.
Going forward, the platform’s machine learning and natural language processing technology will also be used to spot the early signs of emerging conditions. By taking into account a patient’s symptoms or health issues over a period of time, Abtrace’s machine learning algorithm will be able to more accurately recognise the first signs of serious conditions, including cancer. The team is developing the application of this product in partnership with the NHS, academic partners and cancer charities.
Following a pilot project involving several GP practices and 15,000 patients, Abtrace led to a 30 per cent reduction in the number of HCA appointments needed and halved the number of repeat prescriptions that required a GP appointment to process it. As a result, practices using the platform saw a significant decrease in their covid-induced backlog of appointments and an increase in patient satisfaction.