Posted on September 20th, 2021 by Ann-Marie Roche in AI & Data
AI and precision
medicine are both changing drug discovery and development as we know it.
Precision medicine that is powered by AI stands to be transformative,
especially for the treatment of rare diseases. Elsevier was recently part of a
collaboration that sought to demonstrate how AI precision medicine could lead
researchers to new treatments for brain tumors faster.
Here is an
overview of this exciting project:
THE
PLAYERS: Elsevier and
the Sinergia Consortium (DMG/DIPG Center at University Children’s Hospital
Zurich; ETH Zurich; the Centre for Molecular Medicine Norway), and the Open
Pediatric Brain Tumor Atlas project
THE
DISEASE TARGET: Diffuse
intrinsic pontine glioma (DIPG), a very aggressive type of brain tumor that
targets children and currently has no effective treatment
THE
PROJECT: Develop an AI
disease model that will assist with drug repurposing and support precision
medicine
THE
PROCESS: It started with
analyzing OMICs data for DIPG patients using Elsevier’s Biology Knowledge Graph
and complementary software in order to develop a molecular disease model. The
model was then further built and improved with more data (extracted through AI,
natural language processing and text mining technologies) along the way.
THE
RESULTS: The model was used
to identify approved drugs that inhibit the disease mechanism, which brought
the list of potential drugs down to 212. Further ranking scores were developed
to get to the 10 drugs with the most potential for experimental validation.
What
did it prove?
This project
showed how AI, NLP and text mining can effectively improve our understanding of
rare diseases to find the drug candidates with the most potential, which can
help researchers focus their efforts on the best leads in the search of
treatments for DIPG and other rare diseases.
To go further in-depth and learn more about how the team developed the disease model, read this Pharmafield article by Dr. Anton Yuryev, Professional Services Director at Elsevier.
You can also learn more by watching this recent webinar that Dr. Yuryev presented on AI disease modeling.
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