Webinar: Using Machine Learning along the CMC Pathway in Pharma and Biotech

In modern life science research, it can feel all-too-common to find yourself grappling with complexities along the CMC development pathway, which result in delays, foregone discoveries, and challenges scaling products.

That's why our very own Philip Ramsey joined Patricia McNeill of Lundbeck to host an informative conversation on the challenges posed by the increasing complexity of biologic-based therapeutics and the processes that produce them.

It's our pleasure to share it with you: "CMC, SVEM, Neural Networks, DOE, and Complexity: It’s All About Prediction"

Throughout this 41-minute webinar recording, you'll discover why current analytical methods used by life science research and development staff are generally inadequate for complexity.

You will also explore an industry case study that uses SVEM Machine Learning, neural network models, and the hybrid experimental designs to produce accurate predictive models.

Check it out here and via the CoBaseKRM Slack Community where you can meet and collaborate with others shaping the future of scientific research