From functional drug profiling to multi-omics biomarker identification in paediatric solid tumors

Event Details
Date: 28.11.2022, 17:30 o'clock - 18:30 o'clock 
Location: N2045, Universitätsstraße 1, 86159 Augsburg
Organizer(s): Lehrstuhl für Biomedizinische Informatik, Data Mining und Data Analytics
Topics: Informatik, Gesundheit und Medizin
Series of events: Medical Information Sciences
Event Type: Vortrag
Speaker(s): Dr. Dina ElHarouni

Renommierte Wissenschaftlerinnen und Wissenschaftler unterschiedlicher Fachdisziplinen und Forschungsstandorte geben in der Reihe "Vortragsreihe Medical Information Sciences" Einblicke in aktuelle Fragestellungen, Forschungsbereiche und Anwendungsgebiete dieses zunehmend bedeutsamen Forschungsfeldes.


Within the INFORM registry study over 1.200 cases were molecularly profiled by early 2021, with the aim of identifying relevant therapeutic targets. While 50% of the patients were identified with druggable pathways, for only 5% high evidence targets were reported, and the remaining cases lacked any druggable alteration. Thus, an ex-vivo functional drug response profiling platform for pediatric solid tumors has been established within the INFORM study aiming to identify biomarkers and molecular mechanisms associated to drug response profiles for clinical translation. Despite the current experimental and computational developments in large drug profiling studies, a gap is still present in the translation of high throughput functional drug testing findings into clinical practice.



In this talk I will be focusing on a therapy response analysis pipeline that was developed with the implementation of pharmacokinetic data aiming to quantify therapy responses using a clinical approach. Moreover, I will tackle how I identified multi-omics biomarkers associated with metabolic drug sensitivities in pediatric solid tumors.



Dina ElHarouni has just completed her doctoral research in clinical bioinformatics at the department of pediatric neuro-oncology, German Cancer Research Center. She received her BSc. in pharmacy and biotechnology from the German University in Cairo and her MSc. from the same university where she worked on a pharmacogenomics study on pediatric ALL patients. Her PhD work focused on therapy response scoring and multi-omics biomarker identification for precision treatments in pediatric solid tumors. During her doctoral studies, she was nominated by the Helmholtz Association to attend the 70th Nobel Laureates meeting 2020/2021 and recently joined the Lindau alumni young scientists community. Moreover, she was the DKFZ Helmholtz Juniors representative for the year 2021. Currently Dina will be joining Dana Farber Cancer Institute as a postdoctoral researcher where she will be resuming her research passion under the theme of precision medicine and brain tumor research.

More events of this series of events "Medical Information Sciences"

More events: Lehrstuhl für Biomedizinische Informatik, Data Mining und Data Analytics

  • April 2024
    • 08
    • 09
    • 10
    • 11
    • 12
    • 13
    • 14
    • 15
    • 16
    • 17
    • 18
    • 19
    • 20
    • 21
  • April 2024 / May 2024
  • May 2024
  • May 2024 / June 2024
    • 20
    • 21
    • 22
    • 23
    • 24
    • 25
    • 26
    • 27
    • 28
    • 29
    • 30
    • 31
    • 01
    • 02
  • June 2024
    • 03
    • 04
    • 05
    • 06
    • 07
    • 08
    • 09
    • 10
    • 11
    • 12
    • 13
    • 14
    • 15
    • 16
  • June 2024
    • 17
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
    • 24
    • 25
    • 26
    • 27
    • 28
    • 29
    • 30
  • July 2024
    • 01
    • 02
    • 03
    • 04
    • 05
    • 06
    • 07
    • 08
    • 09
    • 10
    • 11
    • 12
    • 13
    • 14
  • July 2024
    • 15
    • 16
    • 17
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
    • 24
    • 25
    • 26
    • 27
    • 28
  • July 2024 / August 2024
    • 29
    • 30
    • 31
    • 01
    • 02
    • 03
    • 04
    • 05
    • 06
    • 07
    • 08
    • 09
    • 10
    • 11
  • August 2024
    • 12
    • 13
    • 14
    • 15
    • 16
    • 17
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
    • 24
    • 25
  • August 2024 / September 2024
    • 26
    • 27
    • 28
    • 29
    • 30
    • 31
    • 01
    • 02
    • 03
    • 04
    • 05
    • 06
    • 07
    • 08
  • September 2024
    • 09
    • 10
    • 11
    • 12
    • 13
    • 14
    • 15
    • 16
    • 17
    • 18
    • 19
    • 20
    • 21
    • 22
  • September 2024 / October 2024
    • 23
    • 24
    • 25
    • 26
    • 27
    • 28
    • 29
    • 30
    • 01
    • 02
    • 03
    • 04
    • 05
    • 06
  • October 2024
    • 07
    • 08
    • 09
    • 10
    • 11
    • 12
    • 13
    • 14
    • 15
    • 16
    • 17
    • 18
    • 19
    • 20
  • October 2024 / November 2024
    • 21
    • 22
    • 23
    • 24
    • 25
    • 26
    • 27
    • 28
    • 29
    • 30
    • 31
    • 01
    • 02
    • 03
  • November 2024
    • 04
    • 05
    • 06
    • 07
    • 08
    • 09
    • 10
    • 11
    • 12
    • 13
    • 14
    • 15
    • 16
    • 17
  • November 2024 / December 2024
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
    • 24
    • 25
    • 26
    • 27
    • 28
    • 29
    • 30
    • 01
  • December 2024
    • 02
    • 03
    • 04
    • 05
    • 06
    • 07
    • 08
    • 09
    • 10
    • 11
    • 12
    • 13
    • 14
    • 15
  • December 2024
    • 16
    • 17
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
    • 24
    • 25
    • 26
    • 27
    • 28
    • 29
  • December 2024 / January 2025
    • 30
    • 31
    • 01
    • 02
    • 03
    • 04
    • 05
    • 06
    • 07
    • 08
    • 09
    • 10
    • 11
    • 12
  • January 2025
    • 13
    • 14
    • 15
    • 16
    • 17
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
    • 24
    • 25
    • 26
  • January 2025 / February 2025
    • 27
    • 28
    • 29
    • 30
    • 31
    • 01
    • 02
    • 03
    • 04
    • 05
    • 06
    • 07
    • 08
    • 09
  • February 2025
    • 10
    • 11
    • 12
    • 13
    • 14
    • 15
    • 16
    • 17
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
  • February 2025 / March 2025
    • 24
    • 25
    • 26
    • 27
    • 28
    • 01
    • 02
    • 03
    • 04
    • 05
    • 06
    • 07
    • 08
    • 09
  • March 2025
    • 10
    • 11
    • 12
    • 13
    • 14
    • 15
    • 16
    • 17
    • 18
    • 19
    • 20
    • 21
    • 22
    • 23
  • March 2025 / April 2025
    • 24
    • 25
    • 26
    • 27
    • 28
    • 29
    • 30
    • 31
    • 01
    • 02
    • 03
    • 04
    • 05
    • 06

Search