Life sciences workloads on AWS combine two unusual demands: regulator-grade change management (GxP, 21 CFR Part 11) and HPC-scale data pipelines that don't fit anywhere else. We build environments that survive both audit and bioinformatics throughput.
GxP doesn't have to mean change tickets that take three weeks. We design IaC pipelines where the validation evidence is generated automatically by the same pipeline that ships the change.
Terraform plans + approvals + Config rules + CloudTrail = the change history a CSV auditor will accept.
Bioinformatics pipelines (GATK, Nextflow, Snakemake) on AWS Batch and ParallelCluster, lab data lakes in S3 with metadata-driven access, and HealthOmics-native workflow design.
EDC systems, eCRFs, clinical data warehouses, and pharmacovigilance pipelines. Manufacturing telemetry from production lines into AWS IoT and time-series stores. GxP scope, every layer.
FDA Software as a Medical Device (SaMD) platforms, device telemetry ingestion, and OTA update infrastructure. Cybersecurity controls aligned to the FDA's premarket guidance for medical device cybersecurity.
Pre-submission audit before the regulator gets eyes on your validation packet. Find the gaps now, not during the FDA's inspection.
Bioinformatics pipelines off ad-hoc EC2 fleets and onto Batch/HealthOmics. Lab systems off on-prem and into validated AWS environments.
Bedrock for protein-language models, SageMaker for custom predictors, and inference infrastructure that handles real research throughput.
Because they are. We build AWS environments that hold up to the regulator's questions and to your scientists' workloads.
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