Data Science DMEG
The Data Science DMEG explores the fast-moving field of data science in clinical research. The group focuses on the practical application of advanced analytics, machine learning, and artificial intelligence to clinical trials, aiming to improve data quality, optimise trial efficiency, and uncover deeper insights.
By drawing on the collective expertise of its members, the group identifies best practices, shares real-world case studies, and provides guidance on integrating data science into research strategies. It also works to connect traditional data management methods with innovative data science tools, helping the clinical research community make the most of new technologies.
Through webinars, white papers, and collaborative discussions, the Data Science DMEG helps shape the future of clinical data management.
Data Science DMEG
The Data Science DMEG explores the fast-moving field of data science in clinical research. The group focuses on the practical application of advanced analytics, machine learning, and artificial intelligence to clinical trials, aiming to improve data quality, optimise trial efficiency, and uncover deeper insights.
By drawing on the collective expertise of its members, the group identifies best practices, shares real-world case studies, and provides guidance on integrating data science into research strategies. It also works to connect traditional data management methods with innovative data science tools, helping the clinical research community make the most of new technologies.
Through webinars, white papers, and collaborative discussions, the Data Science DMEG helps shape the future of clinical data management.
Resources
The Data Science DMEG is beginning to build a collection of resources to support the integration of data science in clinical research. The first of these is “The Implementation of the Evolving Clinical Data Science Role,” a collaborative document outlining key concepts and considerations for developing clinical data science capabilities.
Resources
The Data Science DMEG is beginning to build a collection of resources to support the integration of data science in clinical research. The first of these is “The Implementation of the Evolving Clinical Data Science Role,” a collaborative document outlining key concepts and considerations for developing clinical data science capabilities..
Explore key insights on clinical data science roles and team development.
View Here 〉
Members
Tanya du Plessis | DMEG Chair
Chief Data Strategist and Solutions Officer | Bioforum
Tanya du Plessis | DMEG Chair
Chief Data Strategist and Solutions Officer | Bioforum
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- Akhila Vallabhaneni
- Andrew Green, Pfizer
- Balagopal Nair
- Chiranjeeb Das
- Deepika Dean, PureCDM
- Dorien Druyts, Novo Nordisk
- Emily Givens, PPD
- Eva Gjerlevsen Harreskov
- Evaldas Lebedys, SCOPE International
- Hari Priya, Merck Group
- Helen Poliviou, PureCDM
- Jane Aziz, Robertson Centre for Biostatistics (Glasgow CTU), University of Glasgow
- Joe Freeman, NNIT
- Kian Norouzi
- Lauren Gray
- Laurence Ghafar
- Linda Shostak, University of North Carolina Wilmington, Campbell University, Durham Technical Community College
- Magdalena Wozniak, GlaxoSmithKline
- Melha Battou, Pfizer
- Nina Reyes, IQVIA
- Oriana Hauer
- Paulina Piotrowska, GlaxoSmithKline
- Peter Sec, Premier Research
- Rich Davies, CluePoints
- Santosh Karthikeyan Viswanathan, ACDM Board
- Simon Clawson, Institute of Cancer Research – CTSU
- Tanya du Plessis (Chair), Bioforum
- Tim Armitage, Medidata
- Yuvarajan Parthiban, VHypotenuse
Interested in Joining?
The Data Science DMEG welcome new members and input to this group. If you would like to be a part of the discussions and shape the future of this new process, please click here.