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.
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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
- Alberto Clemente, Premier Research
- Andrew Green, Pfizer
- Balagopal Nair
- Chiranjeeb Das
- Eva Gjerlevsen Harreskov
- Evaldas Lebedys
- Jane Aziz, Robertson Centre for Biostatistics (Glasgow CTU), University of Glasgow
- Joshua Cox
- Lauren Gray
- Laurence Ghafar
- Linda Shostak
- Nandani Harit
- Nina Reyes, IQVIA
- Paulina Piotrowska, GlaxoSmithKline
- Peter Sec, Premier Research
- Rashida Rampurawala, GSK
- Rich Davies, CluePoints
- Safa Anwar, Imperial College London
- Santosh Karthikeyan Viswanathan, AstraZeneca
- Simon Clawson, Institute of Cancer Research – CTSU
- Tanya du Plessis (Chair), Bioforum
- Tim Armitage, Medidata
- Yuvarajan Parthiban
Intersted 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.