Imperial Cancer Research Technology

GHENT, Belgium--(BUSINESS WIRE)-- Confo Therapeutics, a leader in the discovery of novel medicines targeting G-protein coupled receptors (GPCRs), today announced the appointment of Stephen Dowd, PhD, MBA, to its executive team as Chief Business Officer (CBO). “We are thrilled to welcome Stephen to Confo and believe his considerable experience will make him an excellent addition to our team,” said Cedric Ververken, CEO of Confo Therapeutics. “Stephen is a seasoned industry expert with 25 years of experience working in biotechnology and pharmaceutical companies and has a proven track record in business development and R&D.” As part of the executive team, Stephen’s leadership will be key to the next stage of Confo’s corporate growth as it continues to advance its promising pipeline and maximize the value of its proprietary discovery platform. “I am excited to have this incredible opportunity at such a transformative stage of Confo’s development,” said Stephen. “With the significant enhancements made to its proven discovery engine and a rapidly evolving pipeline, Confo is well positioned to build upon its recent successes with the potential to produce multiple first-in-class and best-in-class medicines targeting GPCRs. I look forward to working alongside the team to advance the pipeline and expand the use of our invaluable platform across multiple therapeutic areas to ultimately benefit patients in need of new treatment options.” Stephen Dowd joins Confo from Rallybio, a clinical-stage Nasdaq-listed rare disease company where he served as Head of Business Development, Europe. Previously, Stephen served as Senior Director of Business Development at Kymab, a clinical-stage antibody-focused biotech which was sold to Sanofi in 2021 for $1.1 billion upfront and up to $350 million in milestones. He was also Head of Business Development at SNIPR Biome, a CRISPR microbiome therapeutics company. Earlier in his career, he held research leadership roles at GlaxoSmithKline and SmithKline Beecham. Stephen was awarded a PhD from the University of Dundee for his work at the Imperial Cancer Research Fund (now Cancer Research UK) and an MBA from Judge Business School at the University of Cambridge. About Confo Therapeutics Confo Therapeutics is the only GPCR company with a proprietary discovery engine that precisely targets desired GPCR conformations. This unique capability allows us to unlock a vast untapped potential for the discovery and development of breakthrough medicines. We are a clinical-stage company advancing a robust pipeline of large and small molecules focused on validated targets in endocrine and metabolic diseases, as well as addressing a broader array of critical unmet medical needs in collaboration with our partners. Our team of accomplished experts is dedicated to advancing our patent-protected technology, expanding our capabilities, and building out our pipeline to achieve the best possible therapeutic outcomes for patients. For more information, visit View source version on businesswire.com: Contacts Confo Therapeutics Dr. Cedric Ververken, CEO +32 (0) 9 396 74 00 Email: info@confotherapeutics.com Trophic Communications Desmond James +49 (0) 1516 7859086 Email: confo@trophic.eu Source: Confo Therapeutics View this news release online at:

A single MRI scan of the brain could be enough to diagnose Alzheimer's disease, according to new research. The research uses machine learning technology to look at structural features within the brain, including in regions not previously associated with Alzheimer's. The advantage of the technique is its simplicity and the fact that it can identify the disease at an early stage when it can be very difficult to diagnose. Although there is no cure for Alzheimer's disease, getting a diagnosis quickly at an early stage helps patients. It allows them to access help and support, get treatment to manage their symptoms and plan for the future. Being able to accurately identify patients at an early stage of the disease will also help researchers to understand the brain changes that trigger the disease, and support development and trials of new treatments. The research is published in the Nature Portfolio Journal, Communications Medicine, and funded through the National Institute for Health and Care Research (NIHR) Imperial Biomedical Research Centre. Alzheimer's disease is the most common form of dementia, affecting over half a million people in the UK. Although most people with Alzheimer's disease develop it after the age of 65, people under this age can develop it too. The most frequent symptoms of dementia are memory loss and difficulties with thinking, problem solving and language. Doctors currently use a raft of tests to diagnose Alzheimer's disease, including memory and cognitive tests and brain scans. The scans are used to check for protein deposits in the brain and shrinkage of the hippocampus, the area of the brain linked to memory. All of these tests can take several weeks, both to arrange and to process. The new approach requires just one of these -- a magnetic resonance imaging (MRI) brain scan taken on a standard 1.5 Tesla machine, which is commonly found in most hospitals. The researchers adapted an algorithm developed for use in classifying cancer tumours, and applied it to the brain. They divided the brain into 115 regions and allocated 660 different features, such as size, shape and texture, to assess each region. They then trained the algorithm to identify where changes to these features could accurately predict the existence of Alzheimer's disease. Using data from the Alzheimer's Disease Neuroimaging Initiative, the team tested their approach on brain scans from over 400 patients with early and later stage Alzheimer's, healthy controls and patients with other neurological conditions, including frontotemporal dementia and Parkinson's disease. They also tested it with data from over 80 patients undergoing diagnostic tests for Alzheimer's at Imperial College Healthcare NHS Trust. They found that in 98 per cent of cases, the MRI-based machine learning system alone could accurately predict whether the patient had Alzheimer's disease or not. It was also able to distinguish between early and late-stage Alzheimer's with fairly high accuracy, in 79 per cent of patients. Professor Eric Aboagye, from Imperial's Department of Surgery and Cancer, who led the research, said: "Currently no other simple and widely available methods can predict Alzheimer's disease with this level of accuracy, so our research is an important step forward. Many patients who present with Alzheimer's at memory clinics do also have other neurological conditions, but even within this group our system could pick out those patients who had Alzheimer's from those who did not. "Waiting for a diagnosis can be a horrible experience for patients and their families. If we could cut down the amount of time they have to wait, make diagnosis a simpler process, and reduce some of the uncertainty, that would help a great deal. Our new approach could also identify early-stage patients for clinical trials of new drug treatments or lifestyle changes, which is currently very hard to do." The new system spotted changes in areas of the brain not previously associated with Alzheimer's disease, including the cerebellum (the part of the brain that coordinates and regulates physical activity) and the ventral diencephalon (linked to the senses, sight and hearing). This opens up potential new avenues for research into these areas and their links to Alzheimer's disease. Dr Paresh Malhotra, who is a consultant neurologist at Imperial College Healthcare NHS Trust and a researcher in Imperial's Department of Brain Sciences, said: "Although neuroradiologists already interpret MRI scans to help diagnose Alzheimer's, there are likely to be features of the scans that aren't visible, even to specialists. Using an algorithm able to select texture and subtle structural features in the brain that are affected by Alzheimer's could really enhance the information we can gain from standard imaging techniques."

Cancer Research Technology, the oncology-focused development and commercialisation firm wholly owned by charity Cancer Research UK, has signed an exclusive worldwide licence with Italy’s Abiogen Pharma S.p.A regarding the antibody RFB4. The deal replaces an earlier license issued to the Pisa-based firm, and allows it to continue using RFB4, in combination with key technology from the University of Texas Southwestern Medical Center at Dallas, to develop its new therapies. In return, CRT will receive a signature fee, milestone payments and a percentage of future royalties. RFB4, originally developed by researchers at the Royal Free Hospital School of Medicine in London, which then passed ownership rights to Imperial Cancer Research Technology (before it became CRT), is an antibody against the B cell antigen CD22. CD22 is expressed in approximately 70% of B cell lymphomas and leukaemias, and therefore RFB4 has the potential to form part of future selectively-targeted therapies against such cancers. Abiogen is currently testing two such therapies in Phase I clinical trials. Further details were not disclosed.