Regions
MAIN/REGIONS
regions/
Regions
  1. Americas
  2. Asia & Oceania
  3. Europe
  4. Middle East & Africa
  1. Solutions
  2. Products
  3. Insights
  4. About
  5. Careers
  6. Contact Us
MAIN/search
MAIN/Solutions
Solutions/
SOLUTIONS
  • Research & Development
  • Real World Evidence
  • Commercialization
  • Safety & Regulatory Compliance
  • Technologies
LIFE SCIENCE SEGMENTS
HEALTHCARE SEGMENTS
THERAPEUTIC AREAS

Impacting People's Lives

"We strive to help improve outcomes and create a healthier, more sustainable world for people everywhere.

LEARN MORE
Harness the power to transform clinical development

Reimagine clinical development by intelligently connecting data, technology, and analytics to optimize your trials. The result? Faster decision making and reduced risk so you can deliver life-changing therapies faster.

Research & Development Overview
Research & Development Quick Links
Real World Evidence. Real Confidence. Real Results.

Generate and disseminate evidence that answers crucial clinical, regulatory and commercial questions, enabling you to drive smarter decisions and meet your stakeholder needs with confidence.

REAL WORLD EVIDENCE OVERVIEW
Real World Evidence Quick Links
See markets more clearly. Opportunities more often.

Elevate commercial models with precision and speed using AI-driven analytics and technology that illuminate hidden insights in data.

COMMERCIALIZATION OVERVIEW
Commercialization Quick Links
Service driven. Tech-enabled. Integrated compliance.

Orchestrate your success across the complete compliance lifecycle with best-in-class services and solutions for safety, regulatory, quality and medical information.

COMPLIANCE OVERVIEW
Safety & Regulatory Compliance Quick Links
Intelligence that transforms life sciences end-to-end.

When your destination is a healthier world, making intelligent connections between data, technology, and services is your roadmap.

TECHNOLOGIES OVERVIEW
Technology Quick Links
MAIN/Products
Products/
CLINICAL PRODUCTS
COMMERCIAL PRODUCTS
COMPLIANCE, SAFETY, REG PRODUCTS
REAL WORLD PRODUCTS

CASE STUDY

"Data in a Day

LEARN MORE
MAIN/Insights
Insights/
BLOGS, WHITE PAPERS & CASE STUDIES

Explore our library of insights, thought leadership, and the latest topics & trends in healthcare.

DISCOVER INSIGHTS
THE IQVIA INSTITUTE

An in-depth exploration of the global healthcare ecosystem with timely research, insightful analysis, and scientific expertise.

SEE LATEST REPORTS

INSTITUTE REPORT

"Global Trends in R&D 2024

READ MORE

EMEA Insights

"IQVIA thought leadership with a focus on EMEA.

Learn more

WHITE PAPER

"DCTs Deliver Big ROI

LEARN MORE

WHITE PAPER

"Capturing value at scale: The $4 billion RWE imperative

LEARN MORE
MAIN/About
About/
FEATURED INNOVATIONS
  • IQVIA Connected Intelligence™
  • IQVIA Healthcare-grade AI™
  • Human Data Science Cloud
  • IQVIA Innovation Hub
  • Decentralized Trials
  • Patient Experience powered by Apple
WHO WE ARE
NEWS & RESOURCES

INVESTOR RELATIONS

"Visit our investor relations site for more information.

LEARN MORE
Unlock your potential to drive healthcare forward

By making intelligent connections between your needs, our capabilities, and the healthcare ecosystem, we can help you be more agile, accelerate results, and improve patient outcomes.

LEARN MORE
IQVIA AI is Healthcare-grade AI

Building on a rich history of developing AI for healthcare, IQVIA AI connects the right data, technology, and expertise to address the unique needs of healthcare. It's what we call Healthcare-grade AI.

LEARN MORE
Your healthcare data deserves more than just a cloud.

The IQVIA Human Data Science Cloud is our unique capability designed to enable healthcare-grade analytics, tools, and data management solutions to deliver fit-for-purpose global data at scale.

LEARN MORE
Innovations make an impact when bold ideas meet powerful partnerships

The IQVIA Innovation Hub connects start-ups with the extensive IQVIA network of assets, resources, clients, and partners. Together, we can help lead the future of healthcare with the extensive IQVIA network of assets, resources, clients, and partners.

LEARN MORE
Proven, faster DCT solutions

IQVIA Decentralized Trials deliver purpose-built clinical services and technologies that engage the right patients wherever they are. Our hybrid and fully virtual solutions have been used more than any others.

LEARN MORE
IQVIA Patient Experience Solutions powered by Apple

Empowering patients to personalize their healthcare and connecting them to caregivers has the potential to change the care delivery paradigm. IQVIA and Apple are collaborating to bring this exciting future of personalized care directly to devices patients already have and use.

LEARN MORE
MAIN/Careers
Careers/
WORKING AT IQVIA

Our mission is to accelerate innovation for a healthier world. Together, we can solve customer challenges and improve patient lives.

LEARN MORE
LIFE AT IQVIA

Careers, culture and everything in between. Find out what’s going on right here, right now.

LEARN MORE

WE’RE HIRING

"Improving human health requires brave thinkers who are willing to explore new ideas and build on successes. Unleash your potential with us.

SEARCH JOBS
MAIN/Contact Us
Contact Us/
Blog
When the copy is as good as the real thing: The (forged) art of Generative Adversarial Networks
Chris Steel, Senior Director, Machine Learning / Artificial Intelligence
Harry Wang, Duke University
Jul 13, 2018
  • Blogs
  • When the copy is as good as the real thing: The (forged) art of Generative Adversarial Networks

It’s hard to deny that machine learning and artificial intelligence is on the rise. In fact, it’s seemingly everywhere, largely as a result of faster computational processes and more optimized methods that have accelerated technologies (new and existing) in all sectors of the modern world.

One such technology are Generative Adversarial Networks (GANs), introduced in 2014 by a group of researchers, led by Ian Goodfellow, at the University of Montreal. GANs are a fascinating and innovative combination of game theory and deep learning through the conjunction of two competing (“adversarial”) neural network models. The idea is to use one model to generate samples (the generator), and another model (the discriminator) to take samples from both the generator and the training data, and then discern between the two. These two models are trained concurrently to the point where the generated samples are indistinguishable from real data by the discriminator. A common analogy is a forger (generator) who learns to forge art until an art expert (discriminator) can no longer recognize the forged art from the real art.

Needless to say, the potential is immense, and its application to solving key questions in healthcare is tantalizing.

One notable project underway comes from a group of researchers at the Department of Biomedical Informatics at Columbia University, who are attempting to use GANs to predict drug-induced laboratory test trajectories.

In another area, Neuromation, a company specializing in AI advancements in medicine, has attempted to use GANs to do drug discovery – creating and identifying lead molecules that are most likely to have desired properties.

IQVIA is even pioneering investigation into the potential for GANs to generate synthetic patient data to overcome issues related to privacy and sparse data such as the case with rare diseases. Since data for these diseases are sparse to begin with and most machine learning models need a certain threshold of data to become accurate, GANs could be useful to generate synthetic data that can be as realistic as possible. This would be a watershed moment for an area that struggles desperately to gather enough data to understand diseases and help patients in need. It would also be an important step forward in patient privacy and solving long-standing concerns over protected health information (PHI).

Of course, while it’s easy to be intoxicated by the possibilities, it’s important to temper our excitement and be realistic about the current limitations. Notably, the standard caveats of machine learning still apply, especially regarding how the data used in training must be a complete representation of the predictors.

Additionally, it is possible that the results the GANs create could be physically impossible or not feasible when dealing with drug creation or health record generation. This is due in part to the models being unable to “explain” why their output is correct. And so GANs require skill domain experts (human data scientists, in fact) that understand the healthcare space as well as the science. A simple example of this is using GANs to generate film screenplays. Although a well modeled GAN could create a correctly structured screenplay, the plot might not be well developed and may be prone to continuity errors (as happened with this sci-fi film – although the model that produced this screenplay did not have a discriminator model to validate it). It is but another important example of the relevance – and even the necessity – of domain expertise and human oversight in the development of truly optimal machine learning technologies.

Of course, all of this is just the tip of the iceberg in the conversation of how machine learning can improve, develop, and optimize the healthcare sector. The technology and potential of GANs is just developing, but its impact is already undeniable.

Contact Us