ValiRx Awarded Grant from Open University

Inaphaea is pleased to confirm it has been awarded a Knowledge Transfer Voucher ("KTV") to partner with The Open University ("OU"). This funding will be used to perform advanced imaging-based analysis of Inaphaea biolab's patient derived cell models. The project, which will run from 1st August 2025 to 30th September 2026, will utilise The Open University's expertise in biophysical and machine learning approaches for predicting self-organisation in tissues to build algorithms to assess drug responses in tumour spheroids. The three primary aims of the program are to carry out confocal microscopy of tumoroids provided by Inaphaea; to validate the use of the OU developed contractile network dipole orientation ("CONDOR") simulations to model these tumoroids and to strengthen links with Inaphaea for future grant applications.

Mark Eccleston, CEO of ValiRx commented "We are grateful to The Open University for its continued support across multiple ValiRx companies as we work with leading academic experts to advance our technical capabilities around advanced PDC models and cell-based testing. This is the third award we have received and is very timely given recent updates to the FDA Modernization Act 2.0, which expands regulatory safety and efficacy testing options to include 3D cell cultures as a viable alternative to animal testing. We have built multiple partnerships to expand and develop our capabilities in this area to deliver better products and services through Inaphaea and progress assets faster and further down the pipeline with in-house resources, ultimately leading to better therapeutic candidates from our various SPVs."

Jim Hague, Senior Lecturer at the Faculty of Science, Technology, Engineering & Mathematics, The Open University commented "In partnership with Inaphaea, we want to improve spheroid use as models for drug-development, with a focus on treatments for major cancers (an area of significant interest for our partner, especially triple-negative breast, colorectal and prostate cancers). Our biophysical and machine learning solutions allow us to obtain key additional information about spheroid structure and cell organisation, vital to assess the health of the spheroid tissue. Therefore, addressing an unmet need for analytic tools to understand how accurately spheroid responses to drug candidates represent real tissues."

The Directors of the Company take responsibility for this announcement.

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