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Digitising Pharma R&D: A webinar series

The pharmaceutical industry is undergoing a digital revolution. Now armed with more data than ever before, novel discoveries are just around the corner. Modern drug hunting is a data-driven process but dealing with such large datasets is a challenge.

With challenges around data quality, storage, improving AI and machine learning methods, there are many things to consider when digitalising a pharmaceutical lab.

Join us for this unique 3-part webinar series where we dive into the technologies that are driving modern drug development, now and in the future.

** Please note: by registering for one webinar you automatically gain access to all of the webinars in the series. You will receive your access link approximately one week before the webinar**

You can register by clicking here.

Webinar 1: The lab of the future: The impact of AI and automation on R&D

17th November – 3pm GMT/ 4pm CET/ 10am EST

With many companies innovating and investing in their big data, labs need to digitise quickly, so they don’t get left behind. With innovative technologies with promise, digitising the lab can help to foster innovation and get ahead of the game.

This webinar is focusing on tangible results from pharma of digitalising the lab with the latest AI/ML approaches, the considerations that were taken when implemented, and how they have streamlined processes, with use cases.

Getting left behind in the era of digital transformation – challenges and future directions – Cindy Novak, LCS, Lab operations, Systems Manager, BMS

Connections are everything: how to reach digital augmented research workflows – Andreas Steinbacher, R&D Informatics and Machine Learning / Artificial Intelligence Leader for Lab Automation, Roche

The importance of harnessing ML for R&D, opportunities and challenges – Sreetama Basu, Data Scientist, Merck

Building a streamlined drug discovery process using digital analysis of clinical and experimental data – Gabriel Musso, Chief Scientific Officer, Biosymetrics

Webinar 2: Digitising clinical trials

24th November – 3pm GMT/ 4pm CET/ 10am EST

The era of clinical trials as we know them is quickly coming to an end. Running a trial is expensive and there are commercial risks of failure. As the most critical stage of drug development, the outcomes affect the short- and long-term future of the company.

Most pharma companies are increasingly turning to digitising the trial process, to increase the sustainability, automate the process and increase patient adherence.

This webinar focuses on the promise and future directions of digital clinical trials.

“How will industry digital trial platforms bring patients on board: Learnings from MMyStudyWindow.comSonia Houston Pichardo, Digital Trials lead Europe, Boehringer Ingelheim

“Transforming patient engagement and clinical operations in early development” – Joerg Degen, Global Head of Early Development Informatics, Roche

“Surfacing insights across clinical trials and real-world data” – Jeff Evernham, Vice President, Customer Solutions, Sinequa

Webinar 3: Harnessing Data & Analytics at scale to transform R&D

1st December – – 3pm GMT/ 4pm CET/ 10am EST

Data is everywhere. Big data is becoming the norm in the biopharmaceutical industry. With evidence from research, clinical trials, and real-world data, generating insights and harnessing from this incredible resource is critical for R&D success.

But, how can you make the best use of this data? What technologies must you implement at scale? And how do you overcome the challenges of doing this within a time-constraining R&D lab?

Join us for this interactive panel session on the strategic use of Data & Analytics to transform pharmaceutical R&D.

Jennifer Wong, Head Real World Evidence, Americas, Sanofi

Huanyu Zhou, Sr Director and Head of Data Analytics and Non-clinical Statistics, Teva Pharmaceuticals

Ed Trautman, Vice President, Science and Clinical Analytics and Informatics, Pfizer

Jeff Evernham, Vice President, Customer Solutions, Sinequa

Photo credit: Business vector created by vectorjuice –

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