Data Orchestration in Life Sciences: AWS-Powered Strategies for AI, ML, and Scale

In this PTP LinkedIn Live Lunch and Learn, host Jon Myer welcomes Scott Scheirey, PTP’s Director of Cloud Architecture, to break down the complexities of data orchestration in life sciences. This 15-minute session delivers fast, actionable insights into how life sciences organizations can eliminate data silos, streamline workflows, and accelerate AI and machine learning initiatives using AWS and managed IT services for life sciences.

Watch the full video on YouTube

The Complexity of Life Sciences Data

Life sciences organizations handle a range of sensitive and structured data—from genomics and proteomics to imaging and real-time lab instrumentation. As Scott Scheirey explains, orchestration isn't just about data transfer; it’s about routing, transforming, and structuring that data to be usable for research, insights, and decision-making. Compared to other industries, biotech IT support must be tailored to high-throughput environments and evolving research methods, often delivered through managed IT for labs.

Breaking Down Silos to Unlock Latent Data

Data silos are common in research labs, where genomics, imaging, and proteomics operate independently. PTP works with teams to centralize and standardize access using tools like Amazon S3, enabling collaborative insight generation. Cross-domain synergy is essential for uncovering latent relationships and driving real-time discovery in clinical research and beyond. This is where IT services for biotech labs and IT infrastructure for life sciences companies come into play.

How AWS Supports Scalable Data Orchestration

Scott outlines how AWS services—including AWS Batch, AWS HealthOmics, and AWS Step Functions—support high-performance orchestration pipelines. These tools empower research teams to scale workflows, reduce latency, and meet compliance requirements like HIPAA and GxP across geographies, supported by HIPAA-compliant MSP for biotech and IT services for CROs.

From Startups to Scale: Tailoring the Strategy

For biotech startups, the orchestration challenge often begins with centralizing fragmented data and building minimal pipelines. More mature organizations, on the other hand, face challenges related to optimization, automation, and cost-efficiency. PTP tailors its approach to help companies at any stage unlock the value of their data with IT consulting for biotech startups and MSP services for lab compliance.

Laying the Groundwork for AI and ML

Data orchestration is foundational to AI and machine learning success. Without structured, formatted data, training and inference become ineffective. PTP ensures clients have the infrastructure and workflow automation in place to power these models efficiently, supporting life sciences IT support for everything from clinical trials to drug discovery with research data IT services and scientific computing IT support.

Steps to Orchestration Success

Key Orchestration Steps

1. Centralize data using Amazon S3 or other cloud-native storage platforms.
2. Define and deploy pipelines aligned with key research use cases.
3. Leverage orchestration tools like Nextflow and AWS Step Functions for automation.
4. Continuously evaluate and refine pipelines to enhance performance and reduce cost.

This approach supports sustainable growth through managed cloud services for life sciences and scalable IT managed service provider for biotech companies.