with or without cancer
Our team
Meet our Board
Founder & CEO
Ani Haykuni
Two-time cancer survivor
Holds an MBA from Oxford University, an MPS from State University of New York and Syracuse University, and MSc (Hon) & Bsc (Hon) in Engineering. Founder of Ani Haykuni Cancer Treatment Support Foundation.
Brings 15+ years experience in management and healthcare.
Non-Executive Director
Dr Bandhana Rawal
Physician scientist, held senior executive roles at Welcome Trust and Cancer Research UK and four global Pharma companies.
Board Director at Worldwide Healthcare Trust and Central London Community Healthcare Trust
Non-Executive Director
Dr Latha Parvataneni
Independent Pharma Physician, held senior executive positions and worked with Top 10 Pharma companies.
Executive MBA – WBS Scholar, University of Warwick
Meet our Advisors
Clinical Advisor
Professor Daniel Palmer
BSc, MBChB, FRCP, PhD
North West Cancer Research Fund Professor and Honorary Consultant in Medical Oncology, University of Liverpool
Academic & Scientific Advisor
Professor Bill Greenhalf
Professor in Medical Oncology in the University of Liverpool and is the Operational Director of the Liverpool Good Clinical Practice Laboratory Facility
Advisor
Richard Auburn
Senior Licencing and Ventures Manager in the Digital Health, MedTech and Bioinformatics team at Oxford University Innovation. Richard focuses on technologies that include genetics, genomics, software and/or data.
Advisor
Sandra Ainsua Martinez
Licensing and Venture Manager at Oxford University Innovation. Holds a DPhil in organic chemistry from the University of Oxford, working under the programme “Oxford Innovative Organic Synthesis for Cancer Research” (OxIOSCR) and MSc from the University of Geneva.
Brings years of experience at the interface of cutting-edge research and innovation.
AI/Machine Leaning Advisor
Tingting Zhu
Biomedical Engineer, Royal Academy Engineering Research Fellow at the Department of Engineering Science, University of Oxford.
Tingting's work involves the development of machine learning for understanding complex patient data, with an emphasis on Bayesian inference, deep learning, and applications involving the developing world.