We live in a new era of biological medicines. They have transformed how we think about and treat disease, providing an arsenal of engineered cellular machinery that expand the landscape of druggable targets and promise one-time cures for previously untreatable sickness.

To engineer and understand this new class of therapeutics, the biotech industry is using methods in high throughput experimentation and automation to build and test biological designs at an unprecedented scale. These techniques are run by interdisciplinary teams of scientists with backgrounds in biology, computer science and robotics, and they generate lots of large and uninterpretable raw data.

Data platforms, the software infrastructure needed to store, analyze and interpret this new flood of multi-omics data, have become the cornerstone of the modern biotech. These systems are enormous engineering projects, sources of great resource and time expenditure, but are crucial to the discovery process and are becoming increasingly intertwined with work at the bench. Because dysfunctional software infrastructure can become an experimental bottleneck, it is critical we develop best practices to build and maintain these systems.

There is currently no forum for experienced engineering teams building these systems to come together, pool their collective knowledge and discuss their work. A place to share creative solutions to problems, present interesting platform architectures and help others avoid expensive mistakes. 

This one day conference is dedicated to the craft of building data platforms that engineer biologics.