Towards a Precision Medicine Approach Based on Machine Learning for Tailoring Medical Treatment in Alkaptonuria.

Journal: International journal of molecular sciences
Published Date:

Abstract

ApreciseKUre is a multi-purpose digital platform facilitating data collection, integration and analysis for patients affected by Alkaptonuria (AKU), an ultra-rare autosomal recessive genetic disease. It includes genetic, biochemical, histopathological, clinical, therapeutic resources and quality of life scores that can be shared among registered researchers and clinicians in order to create a Precision Medicine Ecosystem (PME). The combination of machine learning application to analyse and re-interpret data available in the ApreciseKUre shows the potential direct benefits to achieve patient stratification and the consequent tailoring of care and treatments to a specific subgroup of patients. In this study, we have developed a tool able to investigate the most suitable treatment for AKU patients in accordance with their Quality of Life scores, which indicates changes in health status before/after the assumption of a specific class of drugs. This fact highlights the necessity of development of patient databases for rare diseases, like ApreciseKUre. We believe this is not limited to the study of AKU, but it represents a proof of principle study that could be applied to other rare diseases, allowing data management, analysis, and interpretation.

Authors

  • Ottavia Spiga
    Department of Biotechnology, Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy.
  • Vittoria Cicaloni
    Toscana Life Sciences Foundation, 53100 Siena, Italy.
  • Anna Visibelli
    Department of Biotechnology, Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy.
  • Alessandro Davoli
    Hopenly s.r.l., 41058 Vignola, Italy.
  • Maria Ausilia Paparo
    Hopenly s.r.l., 41058 Vignola, Italy.
  • Maurizio Orlandini
    Department of Biotechnology, Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy.
  • Barbara Vecchi
    Hopenly S.r.l., Vignola, Modena, Italy.
  • Annalisa Santucci
    Department of Biotechnology, Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy.