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Niederer SA, Smith NP. Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?. J Physiol. 2016;594(23):6849-6863doi: 10.1113/JP272003.
Niederer, S. A., & Smith, N. P. (2016). Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?. The Journal of physiology, 594(23), 6849-6863. https://doi.org/10.1113/JP272003
Niederer, Steven A, and Smith, Nic P. "Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?." The Journal of physiology vol. 594,23 (2016): 6849-6863. doi: https://doi.org/10.1113/JP272003
Niederer SA, Smith NP. Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?. J Physiol. 2016 Dec 01;594(23):6849-6863. doi: 10.1113/JP272003. Epub 2016 Jul 03. PMID: 27121495; PMCID: PMC5134392.
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J Physiol. 2016 Dec 01;594(23):6849-6863. doi: 10.1113/JP272003. Epub 2016 Jul 03.

Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?.

The Journal of physiology

Steven A Niederer, Nic P Smith

Affiliations

  1. Department of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, The Rayne Institute, 4th Floor Lambeth Wing, London, SE1 7EH, UK.
  2. Engineering School Block 1, University of Auckland, Level 5, 20 Symonds Street, Auckland, 101, New Zealand.

PMID: 27121495 PMCID: PMC5134392 DOI: 10.1113/JP272003

Abstract

Heart disease continues to be a significant clinical problem in Western society. Predictive models and simulations that integrate physiological understanding with patient information derived from clinical data have huge potential to contribute to improving our understanding of both the progression and treatment of heart disease. In particular they provide the potential to improve patient selection and optimisation of cardiovascular interventions across a range of pathologies. Currently a significant proportion of this potential is still to be realised. In this paper we discuss the opportunities and challenges associated with this realisation. Reviewing the successful elements of model translation for biophysically based models and the emerging supporting technologies, we propose three distinct modes of clinical translation. Finally we outline the challenges ahead that will be fundamental to overcome if the ultimate goal of fully personalised clinical cardiac care is to be achieved.

© 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

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