Lab Instrument Log Acquisition and Analytics on AWS
Publication date: October 28, 2020 (Diagram history)
With this architecture, you can build a data pipeline to automate lab instrument log
ingestion, collate metadata, transform data, and send results to FDA-compliant electronic
laboratory notebooks. You can eliminate multiple manual reviews for drug
discovery and development
Lab instrument log analytics architecture diagram
The following steps describe the architecture:
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Lab instruments create output log files in Network File System (NFS) shares on premises.
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Deploy an agent on a virtual machine (VM) to read data from NFS storage.
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Use AWS DataSync to sync data from the NFS share to Amazon S3.
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A lab scientist invokes the client application to find the experiment output log file.
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The client application gets a token from Amazon Cognito and invokes the API with the experiment ID and Amazon S3 path.
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Amazon API Gateway validates the Amazon Cognito token and calls the processing Lambda function.
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The Lambda function reads the file from Amazon S3 and adds the experiment ID as a tag.
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The Lambda function transforms the file, applies business rules, converts data to JSON, and pushes it to Amazon OpenSearch Service.
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If the Lambda function fails, it writes the Amazon S3 file information to an error queue. A timed Lambda function reads from the queue to reprocess failed items.
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(Optional) A Lambda function maintains Amazon S3 file information with metadata in Amazon DynamoDB.
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The Lambda function sends a JSON response through API Gateway to the electronic lab notebook through the mobile client.
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The lab scientist accesses data in the electronic lab notebook and discovers or queries data through OpenSearch Dashboards.
Further reading
For additional information, see the following resources:
Diagram history
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| Change | Description | Date |
|---|---|---|
Initial publication | Reference architecture diagram first published. | October 28, 2020 |
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