The Intelligence Layer
for Clinical Data
Clinical research generates vast volumes of complex data across trials, analytics systems, and regulatory submissions. Yet much of this data remains fragmented across platforms and workflows—making it difficult to maintain clarity, traceability, and regulatory confidence.
CARE2DATA transforms fragmented clinical data into governed, connected knowledge systems—enabling organizations to ensure accuracy, traceability, and compliance at scale.
Ensuring accuracy, traceability, and compliance remains a core clinical challenge
CARE2DATA was founded to address this challenge.
By combining deep life sciences expertise with structured knowledge modeling, CARE2DATA transforms complex clinical datasets into governed knowledge systems. Through ontology frameworks, semantic modeling, and intelligent validation approaches, we help organizations bring structure, context, and reliability to clinical data workflows in highly regulated environments.
Our approach enables life sciences organizations to move beyond fragmented datasets toward connected, trusted knowledge systems—ensuring accuracy, traceability, and compliance across the clinical data lifecycle.
Our Purpose
To bring
to clinical data
so pharmaceutical and life sciences organizations can make confident decisions and deliver better medicines faster.
Scientific Integrity
Care2Data believes that clinical data quality is not simply a technical requirement but a foundational element of scientific integrity.
Lifecycle Validation
With a core focus on validation and verification of clinical trial data across the entire clinical trial lifecycle, CARE2DATA ensures that data remains accurate, consistent, and reliable at every stage.
Regulatory Confidence
By structuring and governing data across the clinical trial lifecycle, we help organizations transform fragmented information into reliable knowledge that supports regulatory confidence and better healthcare outcomes.
Who We Are
CARE2DATA combines deep life sciences expertise with structured knowledge modeling to validate and operationalize complex clinical data in regulated environments.
Our team works at the intersection of clinical research, data standards, and knowledge engineering. By integrating domain expertise with semantic technologies, we help organizations ensure that clinical data remains accurate, traceable, and defensible across the research lifecycle.
Rather than treating data as isolated technical artifacts, we design systems that capture the meaning, relationships, and context behind clinical datasets—enabling organizations to operate with greater clarity and confidence.
What Distinguishes Us
CARE2DATA follows a validation-first philosophy
Our approach begins with governance, traceability, and audit readiness—not automation alone. Validation workflows remain structured, XAI-enabled, and aligned with evolving regulatory expectations across global health authorities and emerging AI guidance in drug development.
CARE2DATA treats validation and verification as a unified discipline: ontology-based semantic intelligence drives validation, while graph-based reasoning enables verification on the same knowledge foundation—ensuring accuracy, consistency, and scalability across all clinical data workflows.
Our approach emphasizes:
Governance-first design
Ensuring validation and verification processes support transparency, traceability, and regulatory compliance—including alignment with global regulatory frameworks and AI governance expectations.
Semantic intelligence
Using ontology frameworks to connect datasets through meaning and relationships rather than isolated rules, enabling context-aware validation.
Operational integration
Embedding governed intelligence within existing clinical workflows without replacing established systems.
Connected Intelligence
Turning Data into Connected, Trusted Knowledge
CARE2DATA connects isolated datasets into unified semantic models.
Through ontology frameworks and knowledge-driven modeling, we enable organizations to create structured knowledge systems that bring clarity and consistency to complex clinical data environments.
By treating knowledge as a strategic asset, organizations can unlock deeper insights from their clinical data.
These systems support:
Stronger collaboration across scientific and regulatory teams
Improved traceability across studies and datasets
Scalable foundations for analytics and AI initiatives
Regulatory Alignment
Clinical Standards & Compliance
Built for Regulatory-Grade Clinical Data Validation
CARE2DATA frameworks align with globally recognized clinical data standards, regulatory expectations, and data integrity principles.
By embedding these standards into validation and knowledge systems, we help organizations ensure clinical datasets remain traceable, conformant, defensible, and submission-ready.
CDISC Standards
Support for validation workflows aligned with CDISC standards such as SDTM, ADaM, SEND, CDASH, and TAUG, ensuring consistent and structured datasets for regulatory submissions.
Regulatory Expectations
Frameworks are designed to align with Guiding Principles of Good AI Practice in Drug Development, GCP, Study Data Technical Conformance Guide and others.
ALCOA++ Data Integrity Principles
Ensuring data remains Attributable, Legible, Contemporaneous, Original, Accurate, along with Complete, Consistent, Enduring, and Available.
GAMP5 Principles
Development frameworks aligned with GAMP5 guidance for regulated systems, ensuring traceability, governance, and methodological reliability.
Knowledge Management
From Information Silos to Decision-Ready Systems
Many life sciences organizations struggle with information scattered across systems, documents, and teams.
CARE2DATA embeds governed intelligence into operational workflows, enabling organizations to transform disconnected information into scalable and decision-ready systems.
This improves:
Data Discoverability
Knowledge Reuse
Governance & Traceability
Readiness for Regulatory review
The result is a stronger foundation for accurate clinical decision making.
Semantic Architecture
Ontology: The Foundation of Scalable Intelligence
Ontology provides the semantic backbone that connects data, rules, and standards.
CARE2DATA designs ontology frameworks that harmonize datasets across clinical research systems, enabling consistent definitions, relationships, and context. By leveraging knowledge graph architectures, these frameworks map relationships across clinical entities, creating context-rich, interconnected data that goes beyond traditional rows and columns.
Through ontology-driven systems, organizations can:
Harmonize data across diverse sources
Improve semantic search and data discovery
Strengthen data lineage and traceability
Enable advanced analytics and AI initiatives
Ontology ensures that clinical data is not only connected—but understood.
Research Foundation
Research & Scientific Foundation
CARE2DATA's work is grounded in continuous research across clinical data standards, knowledge modeling, and intelligent validation systems—forming the foundation of how we differentiate and innovate in clinical data validation and verification.
Our research-led approach enables us to move beyond conventional validation tools, transforming fragmented data ecosystems into structured, governed knowledge assets that eliminate information silos and strengthen clinical data integrity at scale.
Our team combines expertise in life sciences, ontology engineering, and advanced data science to develop frameworks that enhance the reliability, transparency, and contextual understanding of clinical research data.
Through research collaborations and academic partnerships, CARE2DATA continues to advance methods in:
Knowledge graph–driven validation
Validation of clinical datasets through interconnected knowledge structures and semantic relationships.
Semantic Interoperability
Connecting clinical data ecosystems through shared ontologies and standardized semantic models.
Explainable AI (XAI)
Transparent validation and root cause analysis powered by interpretable AI models.
Anomaly Detection
Graph-based models that surface data anomalies and inconsistencies across clinical datasets.
This research-driven approach enables CARE2DATA to develop intelligent systems that support stronger data quality, traceability, and regulatory confidence across the clinical trial lifecycle—while continuously evolving to address emerging complexity in clinical data environments.
Collaborations
Academic & Research Partnerships
CARE2DATA collaborates with leading academic institutions to advance ontology-driven AI, semantic intelligence, and explainable AI (XAI), strengthening the scientific and analytical foundations on which our platforms are built.
Vision & Mission
Vision
To accelerate drug discovery and enable the delivery of high-quality medicines earlier by becoming the most trusted global clinical research technology partner.
We pursue this vision by enabling fully validated, intelligent systems that strengthen the quality, integrity, consistency, and reliability of data throughout the clinical trial lifecycle.
Mission
To ignite a transformative shift in clinical research by delivering Data Quality as a Service.
Through intelligent validation and verification systems, we improve the efficiency, accuracy, and conformance of clinical trial submission datasets, analysis datasets, and clinical reports.
Our mission is to help organizations prevent regulatory resubmissions caused by data quality issues while establishing higher standards of quality, consistency, and accuracy prior to regulatory submission.
Our Team
Leadership
Giri Balasubramanian
CEO & Co-Founder
Gopinath Viswanathan
CTO & Co-FounderCARE2DATA Milestones
From Data to Knowledge.
From Knowledge to Confidence.
CARE2DATA helps life sciences organizations move from fragmented datasets to connected intelligence and trusted knowledge systems.
By combining life sciences expertise with semantic modeling, validation frameworks and AI RAG systems, we enable organizations to strengthen compliance, accelerate insight, and operate with greater confidence across clinical research.