Page 63
Notes:
conferenceseries
.com
Volume 7, Issue 5 (Suppl)
J Clin Trials, an open access journal
ISSN:2167-0870
Clinical Trials 2017
September 11-13, 2017
September 11-13, 2017 San Antonio, USA
4
th
International Conference on
Cl inical Tr ial s
Integration of clinical study data to support trial simulation activities
Raj Bandaru
Sanofi Pharmaceuticals, USA
L
ike much of the pharmaceutical industries, we at Sanofi are also experiencing a shift in clinical development strategies to
adopt more digital technologies and analytics placing greater emphasis on data and model driven approaches. We have set
up a strong integrated capability across quantitative systems models, disease progression models and empirical models driving
a rigorous clinical trial simulation process to inform design and key decisions in our clinical research. To this end, access to
historical clinical trial data has been central. However, using clinical study data for broader clinical research use has several
limitations and challenges. We are implementing several processes and intelligent informatics solutions to enable easier access
to clinical study results and conducting integrated analytics using state of the art methods and tools. Here we describe some of
the informatics solutions we are developing and how these could eventually be applied to support trial submission activities.
One example is in the use of a machine learning methods to index data and make it searchable without compromising data
security or patient privacy. We are also applying intelligent approaches to data de-identification and harmonization across
multiple studies to support meta-analysis. A pilot effort using a learning based approach to data harmonization has shown
significant promise and we are exploring other applications including management of metadata and terminologies using
machine learning approaches. Some challenges however still exist primarily in the governance of data access and patient privacy
issues. We are working on developing clear rules and guidelines that will eventually also help with automating data governance
activities. Another challenging area will be in handling genomic and digital health data and we foresee an opportunity for
automated machine learning algorithms to help in not only managing the data, but to also discover patterns and associations
to clinical outcomes.
Biography
Raj Bandaru heads a data analytics and knowledge management function in Translational Informatics at Sanofi Pasteur. He is championing the adoption of cloud
and big data analytics at Sanofi, bringing advances in clinical research together with big data and digital technologies. Over the past two decades, he has led
data management and analysis across research and clinical development at various pharmacy and biotech companies and most recently led a data and analytics
consulting practice. He has an MBA from Babson College, with a focus on clinical informatics and operations research and also holds graduate degrees in statistics
and genetics.
raj.bandaru@sanofi.comRaj Bandaru, J Clin Trials 2017, 7:5 (Suppl)
DOI: 10.4172/2167-0870-C1-019