You are here > Biopharmaceutical
Glossaries & Taxonomies Homepage > Informatics >
Predictive Analytics poster with links
Predictive analytics glossary & taxonomy
Evolving Terminology for Emerging Technologies
Revisions? Mary Chitty firstname.lastname@example.org
October 25, 2018
presented BioIT World Boston MA April 2015
Software for predictive analytics is making this activity more accessible
to people without deep programming or statistical experience.
Pharmaceutical predictive analytics applications
include business/competitive intelligence, clinical trial modeling,
outcome prediction, predictive toxicology, patent analysis, technology
sensing and others,. Related topics include data visualization, data
integration, data mining, deep learning, machine learning, probabilistic
forecasting, text mining and knowledge management. Information
professionals can bring relevant experience in data curation and query
formulation to contribute to this process.
How Big Data Can Revolutionize Pharmaceutical R&D, Jamie Cattell, Sastry
Chilukuri, and Michael Levy, McKinsey, April
After transforming customer-facing
functions such as sales and marketing, big data is extending its reach to
other parts of the enterprise. In research and development, for example,
big data and analytics are being adopted across industries, including
making enterprise elephants dance (gangnam style) , Andy Palmer, Tamr,
Boston Data Festival, 2014
Start with the questions not the answer…
Ask aspiration/transformational questions…. embrace the ambiguity…. Do not
boil the ocean. Internal and external data BOTH important.
Nate Silver, The Signal and the
Noise: Why most predictions fail – but some don’t, Allen Lane, 2012.
The fashionable term now is “Big Data”… This exponential growth in
information is sometimes seen as a cure-all…. Before we demand more of our
data, we need to demand more of ourselves.
2005-2014 % increase 1,486%
articles predictive analytics 1975-2014
1990-2014 1107% increase
Terminology and key concepts
encompasses a variety of statistical techniques from modeling, machine
learning, and data
analyze current and historical facts to make predictions about
future, or otherwise unknown, events. .. The core of predictive analytics
relies on capturing relationships between
explanatory variables and
the predicted variables from past occurrences, and exploiting them to
predict the unknown outcome. It is important to note, however, that the
accuracy and usability of results will depend greatly on the level of data
analysis and the quality of assumptions.
Wikipedia accessed April 12 2015
Predictive Model Markup Language, Data Monitor Group
leverages statistics to predict outcomes. Most
often the event one wants to predict is in the future, but predictive
modelling can be applied to any type of unknown event, regardless of when
it occurred. For example, predictive models are often used to detect
crimes and identify suspects, after the crime has taken place.
In many cases the model is chosen on the basis of detection
theory to try to guess the
probability of an outcome given a set amount of input data, Wikipedia
accessed April 12, 2015
Related concepts: deep
learning, machine learning, neural nets, text mining, data integration,
collaboration, next generation sequence data analytics, correlating
patient genotypes and clinical trial results, biosensors and remote
monitoring and wearable devices, real world data
glossaries & taxonomies: informatics Overview
Gartner IT Glossary
StatSoft Statistics Glossary
Accenture, Predictive Health Analytics
Cortellis Regulatory Analytics, Thomson
IBM Business Analytics for life sciences
Recorded Future, Competitive Intelligence
SAS Analytics for Life Sciences
StatSoft, Pharmaceutical Solutions
Excel Power Pivot
Other companies of interest include: Tamr
FDA Sentinel Initiative
A national electronic system that will transform FDA’s ability to track
the safety of drugs, biologics, and medical devices once they reach the
market is now on the horizon. Launched in May 2008 by FDA, the Sentinel
Initiative aims to develop and implement a proactive system that will
complement existing systems that the Agency has in place to track reports
of adverse events linked to the use of its regulated products.
Articles appear in a wide and scattered variety of journals. Relevant
American Health & Drug Benefits, Engage Communications
Big Data, Mary Ann Liebert
Bioanalysis, Future Science
management : journal of the Healthcare Financial Management Association.
Journal of Pharmaceutical & Biomedical Analysis, Elsevier
Statistical Methods in Medical Research, Sage Publications
Statistics in Medicine, Wiley
Value in Health, Elsevier
Fierce Big data
Predictive Analytics Today
Predictive analytics can be used to identify pharmaceuticals trends and
predict outcomes and identify probabilities for R&D successes and
failures. Similar questions can be asked for various drug targets or
indications and replicated.
This is a work in progress.
Please let me know of other useful resources and developments.
Electronic version with links available at
Thanks to Eric Stubbs, Information Specialist, Otsuka and Richard
Steel, Science Intelligence Analyst, Genzyme for their lists of software
summarized for the Pharmaceutical & Health Technologies Division Listserv,
and to Mark Burfoot, Novartis, particularly for his observation about the
power of articulating what you are not interested in,
to look for other unfamiliar terms
IUPAC definitions are reprinted with the permission of the International
Union of Pure and Applied Chemistry.