To address Stem Pharm's requirements for handling their advanced human neural organoids and the associated complex data, Cloud303 devised a comprehensive solution leveraging various AWS life sciences services. The architecture was designed to support the storage, processing, and analysis of imaging, genomic, transcriptomic, and metadata from StemPharm's organoid models.
Data Storage and Management:
Amazon S3 was utilized as the primary storage solution for StemPharm's data, including images, genomic files, transcriptomic data, and metadata. S3's scalability, durability, and security features ensured that data was stored safely and accessible when needed. S3 buckets were organized in a hierarchical structure to enable efficient data retrieval and management.
Data Processing and Analysis:
AWS Batch was employed to manage and optimize the execution of various bioinformatics applications in sequence. AWS Batch enabled dynamic allocation of compute resources based on the workload requirements, ensuring cost-effective and efficient processing.
Workflow Orchestration and Optimization:
Nextflow pipeline scripts were developed to orchestrate data processing from S3 buckets. The pipeline scripts were designed to automatically manage the execution of multiple applications in sequence, such as bulk and single-cell transcriptomic analysis, image processing, and cell type-specific analysis, while also handling error recovery and parallelization for optimal processing.
Amazon EC2 instances, including c5.9xlarge, p3.2xlarge, and g4dn.xlarge, were provisioned to handle the diverse processing requirements of StemPharm's organoid data. EC2 instances were selected based on the specific requirements of each application in the Nextflow pipeline, ensuring optimal performance and cost-efficiency.
Data Security and Access Control:
A secure portal was developed to provide authentication and access control mechanisms for StemPharm's data stored in Amazon S3. AWS Identity and Access Management (IAM) was used to define user roles and permissions, ensuring that only authorized personnel could access specific data, images, and files.
Monitoring and Reporting:
AWS CloudWatch and CloudTrail were implemented to monitor the performance and usage of AWS resources. Custom dashboards were created to provide real-time insights into the status of the data processing pipeline, enabling StemPharm to quickly identify and address any issues.
By utilizing this architecture, StemPharm was able to securely store, process, and analyze the complex data generated from their advanced human neural organoids. The combination of AWS life sciences services and Nextflow pipeline scripts enabled seamless data processing, while the integration of machine learning and AI technologies empowered StemPharm to gain deeper insights into their organoid models for neurological drug discovery research.