Health Valley Event 2025

13 mrt 2025 | Nijmegen, Nederland

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Ton Coolen

Founder/CEO

Saddle Point Science Europe

Nijmegen, Nederland

1 profielbezoekParticipant

Saddle Point Science Europe develops novel mathematical, statistical and computational techniques to address the data analytics challenges of modern medicine.

Organisatie

Saddle Point Science Europe

Saddle Point Science Europe

Bedrijf - eHealth

Nijmegen, Nederland

Saddle Point Science Europe BV is a biomedical data science company. It is the European R&D centre of the Saddle Point Science group. It is dedicated to developing novel mathematical, statistical and computational techniques to address the data analytics challenges of modern medicine, to allow more precise prediction of treatment responders and clinical risk. Predicting which patients are most likely to respond to a given treatment has the potential to improve treatment results, lower treatment costs, and lessen side effects for patients. In addition, data analysis methods that require fewer patients would aid the development of new therapies for rare diseases. Our company addresses the above challenges through research based on novel Bayesian inference and advanced mathematical techniques. We focus on innovation, collaboration, patient-centricity, and continuous learning in addressing these challenges. We implement our advanced new algorithms in user-friendly industry-standard software, tailored to be used by medical researchers and professionals.
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Over

  • 1990 -- PhD theoretical physics, Utrecht

  • 1991 -- postdoc, university of Oxford

  • 1995 -- reader, King’s College London

  • 2000 -- professor, King’s College London

  • 2005 -- carer representative & board member,

    Royal Marsen NHS Foundation Trust

  • 2011 -- Head, Institute for Mathematical and Molecular Biomedicine, King's College London

  • 2016 -- founder/CEO, Saddle Point Science

  • 2020 -- professor, Radboud University

  • 2022 -- founder/CEO, Saddle Point Science Europe

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Vaardigheden

  • research management
  • mathematical innovation

Interesses

  • high-dimensional inference and outcome prediction
  • prospective treatment responder identification
  • Personalized medicine