Building the foundation for AI-ready next-generation labs
The lab of the future is here.
Life science organizations that want to discover cures and new diagnostics faster should build strong, AI-ready data foundations—especially when it comes to laboratory data. At Deloitte, we’re making this a reality. Through our alliance with Amazon Web Services (AWS), we’re revolutionizing the path to discovery with our Lab of the Future solution: an innovative instrument-to-insights data flow that streamlines the journey from siloed data sources to valuable, reusable data products.
The outcomes of AI-ready data foundations powering labs are both strategic and practical, including:
- Faster insights through fewer manual steps and enhanced productivity;
- Increased compliance enabled by lineage tracking and broad governance; and
- Contextualized metadata and a centralized, user-friendly data catalog.
Accelerating ‘instruments to insights’ and building AI-ready data foundations
Our Lab of the Future accelerators help organizations modernize laboratory data management and unlock the potential of their data assets. Built on AWS cloud-native, open, and standards-based modular components, our solution enables three important stages of the unified lab data experience.
- Data Mover/Monitor and Control Tower: The first step in building AI-ready data foundations is connecting lab data from instruments and systems of record—for example, Electronic Lab Notebooks (ELNs), Sample Management Systems (SMS), and Laboratory Information Management Systems (LIMS)—to the cloud. Our Data Mover/Monitor and Control Tower solution, built on AWS Data Sync and AWS IoT Greengrass, easily scales across global labs and supports most instrument types. With a centralized user interface, lab data owners can onboard labs, configure instrument data transfers based on business rules or triggers, and receive important alerts in real time. Integrated dashboards with AI insights also provide visibility into data transfer performance and instrument utilization, streamlining lab operations end to end.
- Intelligent data pipeline: Configurable pipelines tailored to specific modalities process raw data based on the instrument. Our intelligent parser agents, built on AWS Agent Core, Bedrock, and Strands, dynamically interpret different file formats, select the correct parser from a parser library, and adapt to source/target drift by automatically generating new parsers as required. Files are then parsed and standardized to a target data model such as the Allotrope Simple Model (ASM) but the solution is designed for flexibility, to allow seamless transition to a different data model as needed. Automated data pipelines enrich laboratory information with bi-directional meta data exchange with ELNs/LIMS and other metadata management systems, providing crucial experiment context to scientists. Ontology and semantic mapping then aligns all data with industry standards or bespoke client vocabularies, significantly enhancing interoperability and data usability. A critical workflow step includes automated metadata extraction to capture key attributes about the instrument, run, experiment, and sample levels essential to enable data usage and analytics.
- Data catalog: The final stage makes processed, enriched metadata easily accessible to scientists and stakeholders through a data catalog, powered by SageMaker Unified Studio. This catalog organizes data products by project, study, experiment, and sample, providing a user-friendly interface that simplifies searching and retrieval. Governance integration with access controls streamlines data discovery and access, enhancing collaboration and data-sharing across teams. As clean and standardized data—with all the relevant metadata—becomes readily findable, accessible, and reusable, next-generation laboratories can deliver on the impact and scale of an AI-ready Lab of the Future.
Architecture for our Lab of the Future solution
The Lab of the Future solution is purpose-built to support scalable, secure, and universally available laboratory operations across diverse environments, instrument types, and data sources. Developed in close collaboration with AWS, it leverages AWS-native services to enable reliable data transfers, advanced metadata enrichment, data lineage, intelligent searching, an R&D data mesh, and broad support for artificial intelligence/machine learning (AI/ML) and Generative AI (GenAI) workloads.
Our Lab of the Future solution features a modular architecture that effectively integrates on-premises and cloud-native components, optimizing performance, flexibility, and compatibility with existing client systems. Our Lab of the Future can support multiple regions and a data push (pushed from on-premises) or pull (pulled from the cloud) model.
The cloud-first design takes full advantage of AWS services—including AWS DataSync, AWS IoT Greengrass, Amazon S3 (including S3 Tables), AWS Lambda, Amazon SQS, Amazon SNS, Amazon API Gateway, Amazon EventBridge, Amazon SageMaker Studio, Amazon Athena, AWS Glue, Amazon Bedrock, AWS AgentCore, Amazon RDS, Amazon EC2, Amazon ECS, Amazon EKS, AWS Batch, and Amazon Managed Airflow—to ensure the solution remains both scalable and reliable.
Lab of the Future Architecture
As instruments generate lab data (1), the Lab of the Future monitors instrument storage on premises (2a) via AWS IoT Greengrass or from the cloud (2b). When thresholds are met or inactivity is detected, it alerts Control Tower (3), which triggers AWS DataSync (4) (with configurable filters) to transfer required data to the cloud (5). Lab Operations managers can configure and monitor transfers and pipelines in the Control Tower interface (6), while Managed Workflows for Apache Airflow and AWS Batch pipelines transform data and publish metadata to a repository and catalog (e.g., SageMaker Studio) (7). Metadata can also be pushed or pulled from external systems (e.g., ELN/LIMS). Both the metadata and transformed data can be analyzed using GenAI or AI/ML tools.
Being highly modular, clients can integrate, extend, or replace Lab of the Future components and integrate using a rich set of APIs. The solution makes it easy to enable or integrate with custom analytics frameworks or third-party tools on the platform. Ultimately, Lab of the Future empowers organizations to accelerate innovation, simplify data management, and unlock actionable insights from their laboratory data.
Spend a day in the Lab of the Future
To really understand the transformative impact of an AI-ready data foundation, let’s observe a scientist who’s enjoying the capabilities of a next-gen lab firsthand. Dr. Maya Rivera is a fictionalized scientist and quality oversight lead at a biopharma, whose daily workflow has been drastically enhanced by our Lab of the Future solution.
Since implementing our Lab of the Future’s Automated Data Transfer capability, the instrument and lab system data transfers happen automatically, completely abstracted from Dr. Rivera’s daily activities. Her morning begins with a notification from the lab’s AI assistant: Her stability assay results are ready for review. Manual file transfers from instruments or time-consuming pulls from the ELN/LIMS are no longer part of her routine. Submitting tickets to engage data engineers for missing files or troubleshooting data transfers has become a thing of the past.
When she needs data, Dr. Rivera taps into the new Data Management capability, searching the intuitive data catalog herself or through her AI agent. Reviewing her results, she spots an interesting degradation pattern and requests similar stability profiles from the past six months across her organization.
Thanks to the new Intelligent Data Transformation, Dr. Rivera can access the additional data points she needs within seconds. Her catalog search pulls in standardized, contextualized results not just from her lab but from other colleagues as well. What took days to analyze now takes only moments, enabling her to make immediate connections between research and manufacturing data.
Later, during a meeting, Dr. Rivera’s colleague, Professor Williams, requests access to original mass spectrometry data. Through the full Data Catalog, Dr. Rivera simply authorizes a secure data package that includes relevant experimental contexts organized by project, study, and sample.
With data flowing efficiently from instruments and systems to insight via efficient Data Acquisition, Transformation, and Management, Dr. Rivera now spends her days focused on advancing discoveries that help patients.
And at the end of her day? Dr. Rivera’s productivity has soared, and her ability to make new, previously unthinkable discoveries has become a reality.
Accelerating the path to discovery through AI-ready data
Our Lab of the Future solution revolutionizes how life sciences organizations leverage their data ecosystem. By freeing scientists from data wrangling, next gen labs powered by laboratory automation software accelerate discovery, unlock deeper insights from existing data, and enable confident deployment of advanced AI/ML.
But the real power of an AI-ready Lab of the Future solution like ours is its ability to empower researchers to pursue new questions and drive data-driven breakthroughs. Our Lab of the Future isn’t simply about improving data capture and management—it’s about dramatically accelerating valuable discoveries.
Are you ready to take the next steps now toward an AI-ready Lab of the Future?
Seshamalini Srinivasan
Mileidy Giraldo, PhD
Manish Patel
