This document outlines a collaborative initiative led by Findacure and Elsevier to address congenital hyperinsulinism, a rare genetic disease that can be life-threatening if untreated. The project emphasizes the importance of gathering and sharing informational resources to develop effective treatments and enhance patient care. Key features include a literature library, research landscape analysis, and methodology for identifying potential therapies through data integration and automated analysis.

1. Maria Shkrob, PhD, Project Manager, Elsevier Professional Services
m.shkrob@elsevier.com
March 8, 2016
Mobilizing informational resources
for rare diseases
When every piece matters

2. | 2
• A rare genetic disease
• Permanently excessive level of
insulin in the blood
• Develops within the first few days of life
Symptoms include floppiness, shakiness, poor
feedings, seizures, fits and convulsions.
 If not caught quickly can lead to brain
injury or even death.
 In the most severe cases the only viable
treatment is the removal of the
pancreas, consigning the patient to a
lifetime of diabetes.
Congenital hyperinsulinsm
is a UK
charity that is building the rare
disease community to raise
awareness, drive research and
develop treatments.
is partnering
with Findacure scientists to help
identify and evaluate treatments
for this devastating disease.

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Congenital hyperinsulinism library
In support of Findacure’s mission of education and knowledge sharing:
• Collection of papers focused on CHI sorted by disease and study type
• Access to all Elsevier’s ScienceDirect full-text publications covering CHI

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Why do we need literature?
PLACES
PEOPLE
GENES
DRUGS
INTERACTIONSPROPERTIES

5. | 5
The power of processed content
PEOPLE
GENES
DRUGS
INTERACTIONSPROPERTIES
DATA NORMALIZATION DATABASES TOOLS
PLACES

6. | 7
Research landscape analysis: connecting patients,
researchers and institutions
0 10 20 30 40 50 60 70
Stanley, C.A.
Hussain, K.
De Lonlay, P.
Rahier, J.
Ellard, S.
Flanagan, S.E.
Shyng, S.L.
Nihoul-Fekete, C.
Bellanne-Chantelot, C.
Robert, J.J.
Brunelle, F.
KEY AUTHORS
0 10 20 30 40 50 60 70 80
The Children's Hospital of Philadelphia
UCL Institute of Child Health
Hopital Necker Enfants Malades
University of Pennsylvania, School of…
UCL
Universite Paris Descartes
University of Pennsylvania
Cliniques Universitaires Saint-Luc,…
University of Exeter
Oregon Health and Science University
KEY INSTITUTIONS0 1 2
Ajinomoto CO., INC.
Arkray, INC.
Korea Research Institute…
ViviaBiotech, S.L.
Bassa, Babu V.
Commisariat a l'Energie…
Glaser, Benjamin
Kowa CO., LTD.
Kyowa Hakko Kogyo…
KEY PATENTS
• Most prolific authors and institutions,
based on full-text searching for terms
and synonyms
• Patent assignee names from Reaxys

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Research landscape analysis: collaboration
• Network of people and organizations collaborating in CHI space based on
co-authorship

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High level summary of full text publications
Tag cloud of titles and sentences discussing hyperinsulinism:
• Provides a very high level summary of a group of publications
• Gives overview of the terms and words being used when discussing the
disease
Sized by inversed document frequency (IDF),
colored by term frequency (TDF)
Sized by relevance, colored by trend

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Finding mechanisms and targets: text mining
• Text mining of 25M abstracts, 3.5M Elsevier and non-Elsevier full texts
• normalization of concept names
• normalization of different ways of saying the same thing
• makes text compatible with other sources of information negative effect

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Quick summary of what is known about CHI
• Text mining of 25M abstracts, 3.5M Elsevier and non-Elsevier full texts
• Identified proteins, small molecules, clinical parameters, diseases, and
biological functions, associated with CHI

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Building and refining the disease model
• Summary of the literature findings: CHI mutations
in the context of insulin secretion
• Generate hypotheses using:
 6.2M literature-extracted findings
 Functional annotations (e.g. Gene Ontology)
 >1800 pre-build pathways modeling disease and
normal states

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From pathways to treatments:
PipelinePilot implementation combines data sources
Automated analysis combines bioassay data with pathway data
Find all targets that could
be used to affect the
disease state
Query for each target to find
the activities for each
compound that are >6 log units
Collate data by compound to summarize the
targets/activities related to disease that the
compound hits
• Compute geometric mean of activities for ranking
• Rank by number of targets and geometric mean of
activities against targets
Step 1 Step 2
Step 3

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Automated analysis combines bioassay data with pathway data
From pathways to treatments:
• 88 Targets related to
hyperinsulinism with ≥3
literature references
• Full PathwayStudio
relationship information
• PathwayStudio also has all
compounds suggested as
treatments
Find all targets that could
be used to affect the
disease state
Step 1

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Automated analysis combines bioassay data with pathway data
From pathways to treatments:
Find all targets that could
be used to affect the
disease state
Query for each target to find
compounds that have high
affinity for them (>6 log units)
Step 1 Step 2
Targets based on
text mining
Approved
compounds

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Automated analysis combines bioassay data with pathway data
From pathways to treatments:
Mean of activities
among these targets
Mean of activities
among these targets
Targets and activities
for each compound
Drug-likeness
metrics for
sorting/classification
• All compounds that
were observed to bind
to targets in pathway
• Sorted by number of
active targets.
Too many targets may
suggest lack of specificity.
Find all targets that could
be used to affect the
disease state
Query for each target to find
compounds that have high
affinity for them (>6 log units)
Collate data by compound to summarize the
targets/activities related to disease that the
compound hits
• Compute geometric mean of activities for ranking
• Rank by number of targets and geometric mean of
activities against targets
Step 1 Step 2
Step 3

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Approved compounds that may treat hyperinsulinism
• Each binds to one or
more targets related to
the disease
• Can easily be obtained
and tested in preclinical
studies
• List includes a
compound known to
treat hyperinsulinism,
sirolimus

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From pathways to treatments:
PipelinePilot implementation output
Input:
“Congenital hyperinsulinism”
Output:
• Table of target information from PathwayStudio
• Table of compounds with targets, activities, and druglike parameters for each
compound
• SD file of compounds that may be efficacious, with clinical status (if any)
• Authors, Affiliations, Collaboration map
• List of papers

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Power of combining pathway
data with experimentally
verified binding data
• Not just theoretical pathways -
testable hypotheses.
Results in testable
ideas
• Many compounds are
already approved drugs,
can be tested in in-vivo
experiments
Concepts can be extended
to find novel compounds
• Use modeling tools to extract
common frameworks
• SAR to optimize activity for
new indication
• Compare with compounds
suggested as treatments as
found by text mining
From pathways to treatments:
PipelinePilot implementation summary

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Findacure: empowering patient groups and facilitating
treatment development
Parents:
• Learn more about the disease
• Find doctors and medical centers
Doctors:
• Learn more about the disease
• Explore case studies
• Collaborate
Researchers:
• Testable ideas for repurposing of generic drugs
• Knowledgebase to support the research of the disease
mechanisms
• Collaborate
Evidence to support 10 drug repurposing trials

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• Figured out what is really needed
• Went through all the content, resources and tools we have in our
possession
• Which is possible because information is normalized
• Once the output of interest is decided: automated answer-generation
Provide disease name and get:
 KOLs and institutes
 List of targets with supporting information
 Sorted list of approved drugs with supporting information
Summary

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Findacure / Elsevier collaboration
Dr Rick Thompson
Findacure
Dr Nicolas Sireau
Findacure
Dr Matthew Clark
Elsevier
Dr Maria Shkrob
Elsevier

22. Thank you
Welcome to our
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