Recursion

Recursion Accelerates Drug Discovery with New Data Pipelines Based on Confluent Cloud

Advances in machine learning, image processing and data science have opened unprecedented opportunities to accelerate the discovery of new drugs that hold the potential to dramatically improve and even save millions of lives. Recursion Pharmaceuticals has seized these opportunities by building a massively parallel system that combines experimental biology, artificial intelligence, automation and real-time event streaming.

Recursion decided to use event streaming with Confluent Cloud and Apache Kafka to minimize administrative overhead, enable faster iterations on experimental results and simplify migration by reusing existing microservices.

Recursion has already made significant strides in accelerating drug discovery, with more than 30 disease models in discovery, another nine in preclinical development, and two in clinical trials. With Confluent Cloud and the new streaming approach, the company has built a platform that makes it possible to screen much larger experiments with thousands of compounds against hundreds of disease models in minutes, and less expensively than alternative discovery approaches.

課題

Accelerate the drug discovery process by streamlining the analysis of biological image data

解決策

Use Confluent Cloud and Kafka to create a scalable, highly reliable data pipeline based on real-time event streaming

成果

  • Drug discovery pipeline stages accelerated
  • Flexible, highly available data pipeline established
  • Stable operation in production since launch
ケーススタディを読む
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“The scale and robustness of the system we built with Confluent Cloud have played a key role in accelerating our success in our mission of discovering new treatments and has helped us bring new treatments to human clinical trials.”

Ben Mabey

VP of Engineering, Recursion Pharmaceuticals

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