10108359Using AI to support recruitment for rare cancer clinical trialsClosedLaunchpadInnovate UKRarecan Limited is a company based in the North East which aims to accelerate the introduction of new ways to treat patients with rare cancers. These account for 22% of all new cancer cases - a total of about 70,000 new cases per year in the UK alone. There are nearly 200 types of rare cancer- many cases only affecting only a few hundred people in the UK at any one time. Recently, there have been major advances in the development of new drugs used to treat rare cancers. This has led to a sharp rise in the need to recruit patients into clinical trials. No new treatments can be introduced into clinical practice until they are shown to be safe and to provide benefits over existing approaches in a clinical trial. However, recruitment into clinical trials is problematic in the case of precisely targeted drugs designed to treat patients with rare forms of cancer. Delays in recruitment are both frustrating for patients, who are keen to see new treatments made available as soon as possible, and for pharmaceutical companies where delays can mean extra costs amounting to many millions of pounds. RareCan is meeting the challenge of recruitment for rare cancer trials by adopting a patient-centric approach. Patients who register via our online portal ([www.rarecan.com][0]) give their consent to be contacted by one of our trial navigators who gather relevant clinical information from them and detailed information about their tumours. The details of all clinical trials are published on one of 18 primary registries. However, many of these are poorly curated and it is hard to access information about trials relevant to specific medical conditions. In addition, data is rarely presented in a way which is readily understood by non-experts In this project RareCan will use modern artificial intelligence methods to develop a dynamic database in which all trials relevant to patients with rare forms of cancer can be automatically matched against both clinical information and information about their tumour- thereby significantly reducing delays in trial recruitment. This technology will enable us to grow more rapidly with higher productivity over laborious and incomplete manual methods for trial matching and will help to stimulate inward investment into the North East both to ourselves and to the wider health sector. In addition, patients will be provided with readily understood information about the trials which may be suitable for them. [0]: http://www.rarecan.com