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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.com

Raj Bandaru, J Clin Trials 2017, 7:5 (Suppl)

DOI: 10.4172/2167-0870-C1-019