Authors: Lokesh Lagudu
Abstract: The drug discovery processes necessitate an updated, sophisticated, secure, and scalable data pipeline owing to the rising scale and complexity. This framework describes a continuous, cloud-native architecture capable of comprehensive data governance throughout the entire drug discovery lifecycle. Researchers can achieve real-time, fault-tolerant, and scalable ingestion, integration, transformation, and delivery workflows using Docker, Kubernetes, Apache Kafka, as well as AWS, GCP, or Azure clouds. The framework also solves the silos and reproducibility issues alongside compliance to the industry’s rigorous security policies. It demonstrates orchestration and containerization and modular and reusable pipeline components, expediting the cooperation of computational biologists and bioinformaticians. Beyond just automation, this cloud-native approach provides observability and scalability for fluctuating workloads. In integrating these secure, orchestrated pipelines, pharmaceutical research teams can make agile, well-informed decisions which accelerates innovation in personalized medicine and data-centric therapeutic development.
