Scaling R&D Drug Discovery with Serverless. Faster go-to-market with Data Engineering

 In today’s competitive biotech landscape, accelerating drug discovery timelines is crucial. The blog “Scaling R&D Drug Discovery with Serverless. Faster Go-to-Market with Data Engineering” explores how modern pharmaceutical R&D teams can break through bottlenecks using a cloud-native approach.



Discover how leading biotech organizations are transforming their research operations by leveraging serverless computing and modern data engineering pipelines. With real-time ingestion, parallel processing, and automated workflows, R&D teams can now scale experimentation, process multi-omics data faster, and reduce time-to-insight — all without the burden of managing infrastructure.


This article takes you behind the scenes of how AntStack partnered with a global biopharma leader to streamline their data ecosystem. By integrating serverless architecture (AWS Lambda, Step Functions, Glue, and more), the team enabled faster hypothesis testing, improved data collaboration across departments, and unlocked predictive analytics capabilities through scalable ML pipelines.


Whether you’re a Chief Scientific Officer, a Bioinformatics Lead, or a Data Engineer in Life Sciences, this blog offers valuable insights on how to:


Reduce compute costs while increasing R&D throughput

Design elastic, event-driven data flows for complex experimentation

Improve reproducibility and visibility across distributed teams


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