Research Data and ML Pipelines for Life Sciences by Dedicatted

Bioinformatics, research informatics and data science teams at pharmaceutical, biotechnology and research-tools companies, digital biomarker and clinical trial technology providers, and health networks with research programmes. The buyer is a Head of Bioinformatics, Director of Data Science or Research IT lead who needs governed, findable research data and models that can be reproduced and reviewed.

Instrument output, imaging, biomarker and assay tables, sequencing data and clinical records sit in disconnected tools and shared drives, moved by hand-run scripts. Researchers wait on extracts, training is ad hoc and hard to reproduce, and nobody can show a reviewer which dataset snapshot and code produced the model in use, or which service touched which record.

Readiness assessment. A source inventory, a governance gap review, and the target lakehouse and ML platform design with a phased roadmap.

Governed research data layer. Data lands in Amazon S3 under an AWS Lake Formation and AWS Glue lakehouse with a searchable catalogue and row and column level access by team and study, queried through Amazon Athena and SageMaker Studio, with AWS Transfer Family for vendor data. Customer-managed AWS KMS keys, AWS CloudTrail and Amazon Macie are in place from the first dataset. AWS HealthImaging for DICOM, AWS HealthOmics sequence stores and workflows, and AWS HealthLake for FHIR records are added where the data needs them.

ML pipeline build, per model family. Amazon SageMaker AI pipelines for one imaging, biomarker or omics model family: versioned training, experiment tracking, model registry, an endpoint or batch inference, and drift monitoring, orchestrated by AWS Step Functions and AWS Batch, with Amazon FSx for Lustre only while training runs, plus an evaluation report.

Curation and QC agents add-on. Amazon Bedrock agents over Knowledge Bases of your protocols and SOPs draft dataset metadata, QC flags and run summaries behind Bedrock Guardrails; a scientist approves before anything is published. Amazon Comprehend Medical flags protected health information in clinical text for redaction where it is in scope.

Operations. A monthly service for pipeline operations, scheduled retraining, drift response and cost and access reviews, with a quarterly audit evidence pack for research IT and compliance.

Health data controls. Where protected health information is involved, Dedicatted requires a Business Associate Addendum between the customer and AWS before that data is loaded and uses HIPAA-eligible AWS services only.

Amazon SageMaker AI, AWS Glue, AWS Lake Formation, Amazon S3, Amazon Athena, AWS Transfer Family, AWS Step Functions, AWS Batch, Amazon FSx for Lustre, AWS KMS, AWS CloudTrail and Amazon Macie. Where the data needs them: AWS HealthImaging, AWS HealthOmics, AWS HealthLake and Amazon Comprehend Medical. For curation agents: Amazon Bedrock.

• Researchers pull governed, catalogued datasets themselves; time from request to dataset is measured at the start and again after go-live.
• Every production model traces to a registered version, the dataset snapshot and the code commit that produced it.
• Sensitive data is classified and every read and write is logged, so a reviewer can see which service touched which record.
• Storage and compute follow data temperature, with a monthly cost and access review.

Under a signed statement of work, Dedicatted is delivering a governed, team-scoped research data foundation for a US biopharmaceutical company, consolidating instrument output, imaging and vendor-delivered research data on Amazon S3, AWS Glue, Amazon Athena and Amazon SageMaker AI with AWS KMS encryption. Dedicatted also runs managed platform operations on Amazon EKS and Amazon MSK for a US digital biomarker company's ML platform, where every clinical trial endpoint must trace back to the model version and raw signal that produced it. Dedicatted holds the AWS Glue Service Delivery designation.

Dedicatted is an AWS Premier Tier Services Partner in Toronto and Montreal, Canada, the first Canadian partner with both AWS AI Competencies and the only Canadian AWS Partner with the AWS Digital Sovereignty Services Competency. We deliver across Canada, the United States and Europe in English and French, with Canadian data residency in AWS Canada (Central) and Canada West (Calgary). We design for PHIPA and Quebec Law 25 in Canada, HIPAA in the United States and GDPR in Europe.

This service provisions resources in your AWS account that AWS bills to you: the services above that your scope uses, such as Amazon S3, SageMaker AI training and endpoints, AWS Batch and FSx for Lustre. We deploy with Terraform under a scoped IAM role you grant and can revoke, removed at handover unless the monthly service continues.