Personalized Medicine: Effective through AI in Transplantation Medicine – New Prediction Models

Project network provides innovative IT platform for clinical data integration, model development and Validation –
Presentation of research results at the annual meeting of the European Society for Blood and Bone Marrow Transplantation

The new data integration, model development and validation platform “XplOit”, which is provided by a project network under the leadership of the Fraunhofer Institute for Biomedical Engineering IBMT, facilitates the development and verification of these prediction models.

The innovative platform prepares data sets in such a way that they can be used for systems medicine research. Through effective predictive models for complications after stem cell transplantation, the joint project “XplOit” creates the basis for the future use of artificial intelligence in transplantation medicine.

The “XplOit” consortium will present its project results on March 25 at the 45th Annual Meeting of the European Society for Blood and Marrow Transplantation in Frankfurt, Germany (Messe Frankfurt, Forum level C, Room Kolleg, 2:30-3:45 pm, http://www.xploit-idsem.de/xploit-workshop-auf-dem-ebmt-am-25-maerz-2019.html). The first predictive AI models for allogeneic stem cell therapy provide sustainable results and will be presented at a workshop together with the “XplOit” platform.

New and effective prediction models

The “XplOit” platform has been tailored over the last 3 years for the development and validation of predictive models to improve treatment after stem cell transplantation. The transplantation of haematopoietic stem cells from donors is used, for example, for the treatment of various forms of leukaemia. Disease relapses are feared.

The first precise prediction models, which individually predict possible complications for each patient, will be available in the “XplOit” platform in 2019. This will enable life-threatening complications to be identified more quickly and treated earlier than today, such as the dreaded transplant vs. host reaction. Project coordinator Stephan Kiefer explains: “The comprehensive analysis of patient data creates for the first time the option for predicting individual disease progression. With the prototypes of the prediction models, we will enter clinical validation in March and refine our results.”

The BMBF project “XplOit” facilitates and accelerates the time-consuming process of providing and combining clinical data, developing and validating models, and making them available for clinical use. A newly developed generation of advanced semantic data integration and information extraction tools makes this easier.

Predictive models can help clinicians diagnose and treat their patients. To develop these mathematical predictive models, a wide variety of clinical patient data from the information systems must be collected, harmonized and analyzed on a large scale. In the present project “XplOit”, data protection is ensured when dealing with personal and sensitive patient information.

The complex prediction models obtained from the analysis of the data are first validated in the further course of the project and checked for their prediction accuracy before they can be used successfully in practice.

Partnership-based research for XplOit

The joint project “XplOit” is implemented by an internationally experienced, multidisciplinary team of experts from the fields of medicine, systems biology, computer linguistics as well as medical and bioinformatics. It is coordinated by the Fraunhofer Institute for Biomedical Engineering IBMT, which is in charge of the development of the “XplOit” platform and contributes core components to information extraction, integration and analysis.

The Institute for Formal Ontologies and Medical Information Science at Saarland University is primarily responsible for the platform's semantic integration framework. The company Averbis contributes tools for information extraction from clinical text documentations. Computer scientists from the Department of Pediatric Oncology and Hematology at Saarland University are responsible for data protection and develop pseudonymization tools and the system's modelling workbench.

The model development itself is carried out by the Medical Informatics Methods Department of the Eberhard-Karls-University Tübingen and the Clinical Pharmacy Department of the Saarland University. Clinical expertise and data are provided by the Clinic for Bone Marrow Transplantation and the Institute for Virology of the University Hospital Essen as well as by the Clinic for Internal Medicine I – Oncology, Hematology, Clinical Immunology, Rheumatology and the Institute for Virology of the University of Saarland. From March 2019, the clinical partners will validate the predictive models for stem cell transplantation developed with the help of the “XplOit” platform, coordinated by the Institute of Virology at Saarland University

XplOit is funded within the initiative i:DSem – Integrative Data Semantics in Systems Medicine by the Federal Ministry of Education and Research.

Duration: 01.03.2016 – 28.02.2021, Project website: http://www.xploit-idsem.de/

Fraunhofer IBMT

The Fraunhofer Institute for Biomedical Engineering IBMT is a device and technology developer for the solution of individual research and development tasks in the fields of biomedical/medical engineering, molecular and cellular biotechnology, bioprocesses & bioanalytics, cryo(bio)technology and nano(bio)technology, ultrasound technology, biomedical microsystems, neuroprosthetics and implants, health information systems, theranostics, (mobile) laboratory technology as well as laboratory automation including inline/online process monitoring. The Fraunhofer IBMT has been working in the field of stem cell research for more than 15 years and has extensive cell line stocks in industrially and clinically structured biobanks for the cryogenic storage of valuable samples (liquids, cells, tissue fragments).

Dipl.-Inform. Stephan Kiefer
Fraunhofer Institute for Biomedical Engineering
Project Coordinator XplOit
Telephone: +49 (0) 6897/9071-406
E-Mail: stephan.kiefer@ibmt.fraunhofer.de

http://www.xploit-idsem.de/xploit-workshop-auf-dem-ebmt-am-25-maerz-2019.html (March 25, 2019 at the 45th Annual Meeting of the European Society for Blood and Marrow Transplantation in Frankfurt, Germany
http://www.xploit-idsem.de/ (Project Website)

Media Contact

Dipl.-Phys. Annette Maurer-von der Gathen Fraunhofer-Institut für Biomedizinische Technik IBMT

All news from this category: Life Sciences

Articles and reports from the Life Sciences area deal with applied and basic research into modern biology, chemistry and human medicine.

Valuable information can be found on a range of life sciences fields including bacteriology, biochemistry, bionics, bioinformatics, biophysics, biotechnology, genetics, geobotany, human biology, marine biology, microbiology, molecular biology, cellular biology, zoology, bioinorganic chemistry, microchemistry and environmental chemistry.

Back to the Homepage

Comments (0)

Write comment

Latest posts

Researchers confront optics and data-transfer challenges with 3D-printed lens

Researchers have developed new 3D-printed microlenses with adjustable refractive indices – a property that gives them highly specialized light-focusing abilities. This advancement is poised to improve imaging, computing and communications…

Research leads to better modeling of hypersonic flow

Hypersonic flight is conventionally referred to as the ability to fly at speeds significantly faster than the speed of sound and presents an extraordinary set of technical challenges. As an…

Researchers create ingredients to produce food by 3D printing

Food engineers in Brazil and France developed gels based on modified starch for use as “ink” to make foods and novel materials by additive manufacturing. It is already possible to…

By continuing to use the site, you agree to the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

Close