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SPHN - Swiss sepsis study

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Presentation at DayOne event 28th Feb 2018

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SPHN - Swiss sepsis study

  1. 1. SPHN/PHRT driver project: Personalized Swiss Sepsis Study DayOne Meeting 28th February 2018 Clinical Microbiology Laboratory Medicine Adrian Egli, MD PhD Head Clinical Microbiology, University Hospital Basel Research Group Leader “Applied Microbiology Research”, Department Biomedicine SPHN/PHRT Driver Team
  2. 2. Sepsis has a profound impact… but what is it? § Bacterial infection progressing to sepsis is associated with1-6 § High morbidity § High mortality § Reduction of quality of life in survivors § Health care costs § Sepsis is a syndrome and not a disease 7,8 2DayOne presentation: Personalized Swiss Sepsis Study 27.02.2018 1 Dellinger RP et al. Crit Care Med 2013; 2 Kaukonen K-M et al. JAMA 2014; 3 ARISE committee Crit Care Resusc 2007 4 Iwashyna T et al. JAMA 2010, 5 Prescott HC et al. BMJ 2016; 6 Goodwin AJ et al. 2015; 7 Kaukonen K et al. NEJM 2015; 8 Singer M et al. JAMA 2016
  3. 3. The course of sepsis is highly heterogenous § Course and outcome of sepsis depends on § the causative pathogen § the infected patient § Rapid diagnosis of sepsis and the identification of the bacterial agent are critical steps towards a successful treatment outcome 3 Kumar A et al. Crit Care Med 2006 27.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  4. 4. Rapid bacterial identification is key … but more can be done! §  Patients with sepsis greatly benefit from personalized diagnostic assessment and treatment strategies. 4 Osthoff M, et al. CMI 2017 27.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  5. 5. Rapid bacterial identification is key … but more can be done! §  Patients with sepsis greatly benefit from personalized diagnostic assessment and treatment strategies. 5 1.  Identification of bacteria within 24h 2.  Faster initiation of optimal treatment 3.  30d-mortality 16.5% -> 8.3% Osthoff M, et al. CMI 2017 27.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  6. 6. Motivation for a sepsis focused driver project § Extraction and integration of clinical, laboratory, and –omics data in patients with presumed sepsis and its interpretation using machine learning may help to: § Develop multi-dimensional digital, molecular, and hybrid biomarkers à Recognize sepsis at a significant earlier stage à Reliably predict sepsis-related mortality § Determine the ideal physiological compartments and time-points for –omics technology for improved diagnostic granularity § Make data interoperable between centers § Set framework for personalized diagnostic and therapeutic research 627.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  7. 7. 7 Manuel Battegay (ID) Christoph Dehio (resistance) Adrian Egli (CM) Stephan Marsch (ICU) Martin Siegemund (ICU) Karsten Borgwardt (machine learning) Peter Bühlmann (statistics) Peter Keller (CM) Nicolai Meinshausen (statistics) Gunnar Rätsch (machine learning) Reto Schüpbach (ICU) Rainer Weber (ID) Nicola Zamboni (metabolomics) Annelies Zinkernagel (ID) Hans-Jakob Furrer (ID) Stephan Jakob (ICU) Stephen Leib (CM) Thierry Calandra (ID) Philippe Eckert (ICU) Gilbert Greub (CM) Laurent Kaiser (ID) Jerome Pugin (ICU) Jacques Schrenzel (CM) SPHN/PHRT collaborative network + SPHN/PHRT Network for Personalized Swiss Sepsis Study 27.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  8. 8. March 1, 2018R.J.Piso KSO 8 Sepsis research focused infrastructure
  9. 9. Goals of SPHN part § Build the infrastructure framework in the context of personalized medicine. § Connection of Swiss University Hospitals, in particular intensive care units, infectious diseases clinics, microbiology diagnostic laboratories and research institutions. § Definition of ethical and governance standards. § Complex clinical data sets will be harmonized for improved data interoperability and comparability between centers. 927.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  10. 10. Working packages for SPHN funding part 10 WP1 Definition of ethical framework and governance structure WP2 Requirement analysis WP3-5 IT specification of target architecture & interface/functions WP6 Realization of connection to scientific data analysis platform 27.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  11. 11. Goals of PHRT part § Sepsis study to build and test infrastructure: § Early recognition of sepsis § Prediction of mortality § Machine learning algorithms to discover novel biomarkers: § digital § molecular § hybrid § Selection for patients, time points, compartments for –omics parts. § Statistical machine learning will allow to provide feedback regarding data quality (interoperability and reproducibility) back to SPHN IT infrastructure. 1127.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  12. 12. Working packages for PHRT funding part 12 WP7 Digital Biomarker Discovery WP8 Molecular biomarker discovery: -  Metabolomics (Zamboni) -  Immunophenotyping (Calandra) -  Human genomics (Calandra) -  Shot-gun metagenomics (Greub & Schrenzel) -  Bacterial whole genome sequencing (Egli) WP9 Hybrid Biomarker Discovery WP10 Reproducibility 27.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  13. 13. Envisioned impact on Personalized Health § Joint SPHN/PHRT proposal on sepsis offers: § Impact on individual patients promises to be drastic § Highly innovative possibilities for basic & clinical research, pharma, and diagnostic companies § Best global sepsis data collections/cohort § Apply for national and international grants, commercial funding § Continue the line of work beyond 2020 including clinical trials § Personalized Swiss Sepsis Study will put Switzerland at the forefront of personalized diagnostic and treatment research on sepsis. 1327.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  14. 14. Questions? Ideas? 14 §  Contact: Any team member of the Personalized Swiss Sepsis Study Dr. Adrian Egli, MD PhD Clinical Microbiology, University Hospital Basel Applied Microbiology Research, Department of Biomedicine Email: adrian.egli@usb.ch Phone: +41 61 556 57 49 Prof. Karsten Borgwardt, PhD Machine Learning & Computational Biology Lab, ETH Zurich Email: karsten.borgwardt@bsse.ethz.ch Phone: +41 61 387 32 20 27.02.2018DayOne presentation: Personalized Swiss Sepsis Study
  15. 15. List of investigators at each centers §  University of Basel / University Hospital Basel §  Manuel Battegay (ID): manuel.battegay@usb.ch §  Christoph Dehio (basic): christoph.dehio@unibas.ch §  Adrian Egli (CM / SPHN / -omics): adrian.egli@usb.ch §  Stephan Marsch (ICU): stephan.marsch@usb.ch §  Martin Siegemund (ICU): martin.siegemund@usb.ch §  University of Bern / Inselspital §  Hans-Jakob Furrer (ID): hansjakob.furrer@insel.ch §  Stephan Jakob (ICU): stephan.jakob@insel.ch §  Stephen Leib (CM): stephen.leib@ifik.unibe.ch §  University of Zurich / University Hospital Zurich §  Peter Keller (CM): pkeller@imm.uzh.ch §  Reto Schüpbach (ICU): reto.schuepbach@usz.ch §  Rainer Weber (ID): rainer.weber@usz.ch §  Annelies Zinkernagel (ID): annelies.zinkernagel@usz.ch §  University of Lausanne / University Hospital Lausanne (CHUV) §  Thierry Calandra (ID / -omics): thierry.calandra@chuv.ch §  Philippe Eckert (ICU): philippe.eckert@chuv.ch §  Gilbert Greub (CM / -omics): gilbert.greub@chuv.ch §  University of Geneva / University Hospital Geneva (HUG) §  Laurent Kaiser (ID): laurent.kaiser@hcuge.ch §  Jerome Pugin (ICU): jerome.pugin@unige.ch §  Jacques Schrenzel (CM / -omics): jacques.schrenzel@hcuge.ch §  ETH Zurich §  Karsten Borgwardt (machine learning / PHRT): karsten.borgwardt@bsse.ethz.ch §  Peter Bühlmann (statistics): peter.buehlmann@stat.math.ethz.ch §  Nicolai Meinshausen (statistics): meinshausen@stat.math.ethz.ch §  Gunnar Rätsch (machine learning): raetsch@inf.ethz.ch §  Nicola Zamboni (-omics): zamboni@imsb.biol.ethz.ch

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