Maximize the value of your data with Genpact FAIRBricks

For years, the life sciences industry has championed the FAIR principles. Everyone agrees that making data findable, accessible, interoperable, and reusable is the key to unlocking its potential. However, putting these principles into practice at an enterprise scale has proven difficult. The result is a persistent drag on innovation. Time-to-insight slows, outcomes are inconsistent, and collaboration between teams and technologies remains a challenge.

This isn't a technology problem; it's a paradigm problem. Pouring data into a lake without a clear framework for its use creates a swamp, not a reservoir of knowledge. Your investments in advanced analytics and AI are more effective when the underlying data is structured, described, and ready for reuse.

Genpact FAIRBricks is an accelerator that moves beyond theory. Built on the Databricks platform and guided by a proven playbook, it offers an end-to-end framework that makes scientific data FAIR by design, from the moment it is ingested to the point of analysis. It provides a framework to help transform raw data into a reusable, interoperable knowledge asset, supported by proven methodologies. This is not about adding another layer of complexity. It's about simplifying and standardizing how data is managed within the systems you already use. Genpact FAIRBricks uses Databricks and its Unity Catalog to create a unified data fabric where every dataset is managed with precision.

Here's how it works:

• Findable: Datasets are assigned persistent identifiers and indexed with rich metadata, helping make them easy to discover through simple searches. No more hunting through disparate systems for the information you need

• Accessible: Databricks' Unity Catalog manages data lineage and access controls in a way that aligns with global standards, enabling both traceable and secure data

• Interoperable: A semantic layer, informed by established ontologies and controlled vocabularies, creates a shared language across your research ecosystem. This aligns structured data and its context, allowing different datasets to be combined and analyzed

• Reusable: By the time data reaches the "gold" layer in the medallion architecture, it is fully searchable, interoperable, and validated. This helps transform it from a static resource into a dynamic asset ready for machine learning and advanced analytics

To prove the power of this approach, Genpact FAIRBricks uses a focused demonstration built on the Genome Data Commons (GDC) pancreatic cancer dataset. This dataset acts as a "steel thread," showing a complete path from raw, unstructured data to refined, insight-ready information.

The process starts with raw genomic data in the "bronze" layer, where it is staged and cataloged. As it moves to "silver," the accelerator applies standard identifiers, vocabularies, and a purpose-built Clinical Biomarker Ontology. By the "gold" layer, the data is aligned to specific consumption patterns, fully searchable, and evaluated against key competency questions. This end-to-end demonstration illustrates how FAIR data principles can be practically implemented. 

Genpact FAIRBricks integrates several foundational capabilities, informed by implementations in large pharmaceutical organizations.

• A FAIR playbook: This defines clear policies for identifiers, cataloging, and provenance, along with recommended ontologies for key scientific domains

• Reference data management: It provides a central hub for managing the vocabularies and mappings that power the semantic layer

• Standards-based cataloging: It uses Databricks' Unity Catalog with established standards like Data Catalog Vocabulary (DCAT) and Provenance Ontology (PROV-O) to help maintain consistency

• Automated data validation: Conformance is enabled through Shapes Constraint Language (SHACL), a language for validating data and metadata

• Simplified data consumption: The framework enables faceted exploration of FAIR data products, making it easy for researchers to find what they need

The implications for pharmaceutical R&D are profound. By implementing a FAIR-by-design approach, organizations may improve data onboarding times, reduce redundant processing, and build the semantic backbone required for AI-driven research. When metadata, lineage, and access controls are built in from the start, researchers are better equipped to trace results, repurpose datasets, and collaborate effectively. For IT leaders, Genpact FAIRBricks shows how to extend existing investments in Databricks to help deliver advanced data management capabilities without adding new infrastructure. For R&D leaders, it acts as a blueprint for accelerating the entire discovery pipeline. It's about moving faster, thinking bigger, and creating a more collaborative research environment to ultimately deliver better treatments to patients.

The future of scientific discovery depends on high-quality, interoperable data. Genpact FAIRBricks demonstrates that this future is already here. It's time to stop building data silos and start building trust, transparency, and reusability into every dataset from day one. 

Your data could hold the key to your next breakthrough. Let us help you unlock it. Discover how Genpact's expertise in digital transformation and data intelligence supports the implementation of FAIR principles and accelerates your journey to discovery.

Contact us today to learn more about Genpact FAIRBricks.