Biomarker Data Repository for Drug Development
Powering FDA-qualified kidney safety biomarker research with secure data sharing—supporting over 26,600 trial participants and transforming drug development decision-making.
Biomarker qualification demands data at scale even across organisations that can’t easily share it
Qualifying a novel biomarker for regulatory use requires large, diverse, and well-governed datasets. But the data that would power qualification is scattered across dozens of independent studies, held by competing sponsors, and subject to complex data protection obligations.
Whether the goal is safety biomarker qualification, companion diagnostic development, or disease progression monitoring, organisations face the same structural barriers: fragmented data, mismatched standards, and governance frameworks that were never designed for multi-party collaboration. Without a purpose-built platform, the burden of building a repository falls on the science team — consuming resource that should be focused on analysis.
Data Fragmentation
Patient-level biomarker data is distributed across independent clinical trials, nonclinical studies, and registries. Without centralisation, datasets are too small to be reliably predictive for regulatory submissions.
Inconsistent Standards
Studies contribute data in incompatible formats and terminologies. Without rigorous harmonisation to standards like CDISC SDTM or OMOP, cross-study analysis is unreliable — or impossible.
Multi-Sponsor Governance
Managing data contributor agreements, access controls, and usage conditions across pharmaceutical companies, academic institutions, and regulators requires infrastructure most consortia don’t have.
IP & Regulatory Risk
Sponsors need confidence that contributing to a shared repository does not expose proprietary study data or prejudice ongoing regulatory submissions. Governance architecture must protect all contributors.
A complete platform for the biomarker repository lifecycle
The Aridhia DRE provides the secure, scalable infrastructure to build and operate a biomarker data repository — from initial data contribution through standardisation, governed access, and regulatory-grade analytics — without requiring sponsors to cede control of their data.
The platform handles the infrastructure complexity so research teams can focus on the science. Data contributors retain ownership of their submissions, and the platform enforces the governance rules that make collaboration safe and compliant.
Multi-Source Data Ingestion
Ingest patient-level biomarker data from clinical trials, nonclinical studies, observational registries, and real-world data sources. Flexible data ingest and indexing supports diverse submission formats while preserving provenance at every step.
Standardisation & Curation
Contributed dataset require harmonisation and validation to interoperable data standards — CDISC SDTM, OMOP, or consortium-specific models — ensuring consistency and comparability across studies and sponsors.
Trusted Access Framework
FAIR Data Services provides a searchable data and asset catalogue with integrated data access request (DAR) workflows. Administrators manage contributor agreements, usage conditions, and role-based permissions — all audited and traceable.
Integrated Analytics Workspace
Native R, Python, and SQL environments sit alongside Git versioning and support for specialised PK/PD modelling tools. AI/ML algorithms and validated statistical methods run within the same secure, audited environment used for regulatory-grade submissions.
Responsible AI (AIRA)
The offline AIRA framework enables LLM-assisted code generation, model development, and data analysis without any data leaving the secure boundary. No external API calls unless enabled, and audit trails of every AI interaction for reproducibility and compliance.
Federated Data Sharing
The open-source Federated Node enables analytical tasks to run against data held at partner sites without requiring data movement. Supporting both cross-site benchmarking and federated ML model training across institutional boundaries.
AI-Powered Discovery
Vector search in FAIR Data Services enables semantic discovery of datasets based on clinical meaning rather than exact terminology, surfacing relevant data even when study vocabulary varies across contributors.
Output Checking & Airlock
Outbound airlock controls enforce disclosure control and data conditions compliance before any result leaves the secure environment, providing the governance assurance required by data contributors and regulators alike.
Scalable Cloud Infrastructure
Azure cloud-based architecture with flexible compute, unlimited storage, and ISO 27001 + HITRUST certified security. Capable of scaling from a pilot repository of a few studies to a global consortium programme serving hundreds of users.
From concept to FDA-qualified biomarker panel
The C-Path Predictive Safety Testing Consortium (PSTC) Biomarker Data Repository (BmDR) illustrates what becomes possible for multi-sponsor scientific collaboration at scale.
Beginning with regulatory consultations in 2007, FDA qualification of a six-biomarker kidney safety panel in 2018, and migrating to the Aridhia DRE in 2024, the BmDR programme demonstrates the full lifecycle that a biomarker repository platform must support. From fragmented nonclinical data, through to a regulatory-endorsed qualification package used in active drug development programmes worldwide.
A 15-year path from data fragmentation to global regulatory acceptance
Critical Path Institute’s PSTC consortium brought together pharmaceutical sponsors, academic researchers, and regulators to address a specific problem: standard clinical biomarkers for drug-induced kidney injury — serum creatinine and estimated GFR — detect changes in renal function and injury only after substantial damage has occurred, contributing to costly late-stage drug failures and unnecessary animal testing.
To address this, the BmDR set out to aggregate patient-level data from clinical trials, nonclinical studies, and observational sources contributed by pharmaceutical companies globally. Rigorous standardisation and curation processes ensured that cross-study analysis was valid and the resulting qualification package met the evidentiary standards of FDA, EMA, and PMDA.
Now hosted on the Aridhia DRE, C-Path’s biomarker data and analytics platform supports multi-sponsor data contribution under strict governance, combined with integrated analytics for regulatory-grade submissions. The qualified panel of six urinary biomarkers is now incorporated into active drug development programmes across the industry — enabling more sensitive safety monitoring and better-informed go/no-go decisions.
Clin Pharmacol Ther. 2025 Nov 23;119(3):608–617. doi: 10.1002/cpt.70134
What the BmDR programme demonstrates: pharmaceutical sponsors, including Merck, AstraZeneca, Genentech/Roche, and Pfizer, have used the qualified biomarker panel to support both advancement and early termination decisions — effectively de-risking and improving trial success.
Platform applications across the biomarker lifecycle
The same infrastructure that supports organ safety biomarker qualification applies across a wide range of biomarker programme types. The Aridhia DRE is designed to adapt to the specific governance, standardisation, and analytical requirements of each.
| Programme Type | Key Platform Requirements | Representative Outcome |
|---|---|---|
| Organ Safety Biomarker Qualification | Multi-sponsor ingestion, CDISC data standards, regulatory-grade audit trails | Qualification dossier supporting regulatory submission (eg FDA, EMA, MHRA) |
| Companion Diagnostic Development | Patient stratification analytics, genomic data integration, GDPR-compliant sharing | Validated companion diagnostic aligned to therapeutic indication |
| Disease Progression Biomarkers | Repository for longitudinal patient registry, real-world data, federated multi-site access | Prognostic model informing trial design, disease progression, and endpoint selection |
| Pharmacodynamic Biomarker Programmes | PK/PD modelling integration, cross-study comparability, MIPD tools, custom tooling deployment | Target engagement evidence supporting dose selection and trial simulation tools |
| Multi-Organ Safety Expansion | Modular repository architecture, shared analytical methods, incremental contributor onboarding | Consolidated safety repository covering liver, kidney, cardiac, and skeletal muscle endpoints |
What a purpose-built biomarker repository enables
When biomarker data is properly aggregated, standardised, and governed, it changes what is scientifically and commercially possible — for the consortium, for individual sponsors, and ultimately for patients.
Earlier Safety Detection
Novel biomarkers qualified through sufficient aggregate data detect injury significantly earlier than standard-of-care measures, enabling dose cohort risk assessment before irreversible damage occurs.
Better-Informed Go/No-Go Decisions
More sensitive safety monitoring allows sponsors to make evidence-based advancement and termination decisions earlier in development, reducing costly late-stage failures and unnecessary patient exposure.
Reduced Animal Testing
Validated clinical biomarker data that translates robustly from nonclinical models supports decisions to reduce or refine animal studies, with the repository providing the cross-species evidence base required.
Regulatory Confidence
A centrally governed, auditable repository with validated analytical methods produces submissions that meet the evidentiary standards of FDA, EMA, and other global regulators, with provenance and reproducibility built in.
Cross-Study Pattern Recognition
Integrated multi-sponsor data enables identification of signals across diverse populations, dose regimens, and therapeutic areas that no individual study could reveal in isolation.
Platform Reuse & Expansion
Infrastructure built for one biomarker programme can be extended to new endpoints, organ systems, or disease areas, compounding the value of the initial investment across the consortium’s research.
Proven infrastructure for collaborative biomarker research
Aridhia has supported some of the most demanding data collaboration programmes in life sciences and healthcare — from the C-Path BmDR to rare disease research platforms for the FDA-funded RDCA-DAP initiative and international COVID-19 research infrastructure for the ICODA consortium. We bring deep operational expertise in deploying and sustaining secure environments for programmes where data governance is not optional.
Proven At Scale In Production
Deployed across global consortia supporting 84,600+ patient observations. Production infrastructure, not a proof of concept.
Regulatory Ready For Submission
ISO 27001 + HITRSUT certified with established track record supporting FDA, EMA, MHRA, and PMDA qualification programmes.
Federated By Design
Open-source Federated Node for cross-institutional analysis so data stays where it is, while results come to you.
Governed, Not Just Secure
Built-in data access request workflows, usage conditions, and FAIR metadata catalogue so governance scales with your consortium.
Build your biomarker repository on proven infrastructure
Whether you are launching a new consortium programme, expanding an existing repository, or exploring federated approaches to multi-site biomarker research — speak to our team.