The document discusses leveraging analytics tools and ontologies to understand and compare the safety profiles of drugs. It notes that one of the key factors in drug approval is safety, and understanding the safety landscape of competing drugs is important. The approach presented aggregates adverse event data from clinical trials to create a heat map comparing safety profiles of different drugs or classes. This allows users to easily identify areas of safety concerns or differences between drug candidates.

1. Copyright © 2013 Thomson Reuters
Quickly answer common questions about drug
safety across classes of drugs or competing drug
candidates. How leveraging analytics tools and
powerful ontologies can help you easily identify
areas of interest or concern.
One of the key differentiators in bringing a drug
to market is its safety profile. The regulatory
and public focus on adverse events is growing.
Understanding the safety landscape around a
class of drugs or comparing the safety profiles
of competing drug candidates is an imperative.
The most reliable source of safety data is adverse
events reported in clinical trials which are typically
disclosed in journal articles and presentations
at meetings. The challenge is to aggregate the
information across multiple trials, for multiple
interventions so that you can assess the entire
landscape – rather than searching for results trial
by trial. Questions that typically arise are:
• Is the safety data on my drug sufficiently
better than the current gold standard to
warrant approval?
• Why is my competitor continuing with this
drug candidate when reports of its efficacy
aren’t very encouraging?
• What adverse events are reported in the
literature for a particular intervention or class
of drugs?
APPROACH
In this case, a heat map approach can present
aggregated information in a way that easily
identifies areas of interest or concern. To drive this
type of analysis, we leverage powerful ontologies
from Thomson Reuters Cortellis™. These allow you
to select drugs for comparison by their mechanism
of action or disease, or individually by their trade,
approved name, chemical, or lab-code identifiers.
Adverse events are reported by their Cortellis
indication terms and grouped into MEDDRA
classes so you can see, for example, whether Drug
A’s side effects are mostly cardiovascular while
Drug B’s are mostly gastrointestinal. The intensity
of the heat map can be toggled between number
of patients affected, percentage of patients, or
numbers of trials in which the adverse event has
been reported. Users can then drill down into the
details of individual trials, summarized from the
original paper or meeting presentation.
ASSESSING DRUG SAFETY IN CLINICAL TRIALS
Leveraging analytics to answer common questions about drug safety across classes of drugs
or competing drug candidates
By Tim Miller, Vice President Product Management & Analytics
The regulatory and public focus
on adverse events is growing.
Understanding the safety
landscape around a class of
drugs or comparing the safety
profiles of competing drug
candidates is an imperative.
Tim Miller, Vice President Product Management
& Analytics

2. ABOUT THOMSON REUTERS
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RESULTS
In this example (Figure 1) we compare 2 VEGF
inhibitors. The side-by-side comparison shows the
percent affected aggregated over the trials in the
Cortellis database presented as a gradient from
green (low) to red (high). Grey cells indicate where
the trial reports the adverse event but doesn’t
give numbers affected. The adverse events are
grouped by MEDDRA classes, which makes it easy
to see that the adverse events of the first drug are
chiefly rash and diarrhea; whereas those of the
second drug are emesis, nausea, and fatigue.
LEARN MORE
To learn more about dynamic, hosted analytics, reach
Tim at tim.miller@thomsonreuters.com
ASSESSING DRUG SAFETY IN CLINICAL TRIALS
Copyright © 2013 Thomson Reuters
FIGURE 1:
THOMSON REUTERS
CLINICAL SAFETY
VISUALIZATION COMPARING
SIDE EFFECTS OF TWO DRUGS.
Details of the trial(s) in which
the adverse event was reported
appear on selecting one of the
cells in the heat map. In this
case we have selected the GI
bleeding adverse event (colored
blue). In the details panel below
are key facts about the trial plus a
manually curated abstract of the
adverse events including more
detail than can be presented
in the image. There are also
embedded links to Cortellis and
to the trial registry. This approach
reduces the need to search for
safety results trial-by-trial.
AUTHOR BIO
Tim Miller has worked within the
Thomson Reuters organization
for 30 years, and specializes in
the interface between Science
and IT. In his current role Tim
focuses on bioinformatics,
cheminformatics, semantic
technologies, and text/data
mining &visualisation, specifically
as they apply to the Pharma
space. Tim holds a bachelor’s
degree in Chemistry from
the University of York and a
bachelor’s degree in Law from
the University of London. He is a
Chartered Chemist (Member of
the Royal Society of Chemistry)
and a Chartered Information
Technology Professional (Member
of the British Computer Society)