Episode 9: The Future of Open Access Research Data

Episode 8: Data Sharing and Collaboration

As biopharma research and development continues to transform digitally, the industry as a whole struggles with guidance on how data and relevant metadata are captured, managed, and shared. Typically experimental data are siloed,

Sequencing is used to identify novel drug targets and genetically stratifying clinical trial patients, improving the power of precision medicine. However, the global disparity of genomic technologies is increasing.

Life science companies are looking to modernize their research environments and build the Lab of the Future. From early discovery to preclinical research, how can technology help automate the lab and accelerate discoveries?

What are the theories, algorithmic principles, and limitations of active learning? What are some current applications of active learning within BioPharma drug screening and optimization? How can active learning accelerate multi-dimensional drug discove...

What is the vision of interactive data exploration beyond enriching visualizations and facilitating the integration of data? Within the context of research, what are the challenges and opportunities in building next-generation visual analytics?

Artificial Intelligence (AI) and Machine Learning (ML) are big topics getting lots of attention within BioPharma. What is the role of AI/ML in genomics? How can we separate the hype of AI/ML from reality? Listen in to find out this and more.

Why are research organizations moving to the Cloud? Learn why they decided to initiate the move, what issues they’ve tackled, what their biggest challenges were, and where they’re going next.