- Biomarker discovery and validation
- Disease phenotyping
- Companion diagnostic development
Aigora curates fit-for-purpose real-world datasets and associated biospecimens to meet the requirements of complex precision medicine R&D.
Our datasets are built around the diverse R&D needs of pharmaceutical and biotechnology companies.
Real-world data to accelerate translational discovery.
Real-world data to advance clinical studies.
Real-world data to generate scientific and regulatory evidence.
Real-world data to develop and validate AI models.
We align on the research objectives, intended use case, and initial data requirements.
We evaluate data availability across our global network, engage clinicians to assess feasibility, and jointly refine project scope.
We provide a tailored proposal outlining deliverables, timelines, and commercial terms.
We coordinate participating sites, approvals, data extraction, and aggregation, while ensuring quality control and privacy safeguards.
We transfer the final regulatory-grade, research-ready dataset in the agreed format and structure for integration into customer systems
From feasibility assessment to regulatory-grade delivery, Aigora manages every stage of assembling fit-for-purpose research datasets.
We assess study requirements against our network's data, combine internal expertise with clinician input to evaluate feasibility, and refine data specifications while ensuring the final dataset aligns with study goals.
We assemble patient-level multimodal datasets integrating imaging, clinical, pathology, and molecular data, with associated biospecimens for customer-driven investigations.
We source data and biospecimens through hospitals, clinics, and biobanks across our global healthcare partner network, helping to secure sufficient eligible cases and diverse patient populations.
We deliver research-ready datasets, enabling life sciences teams to process data within their own systems rather than relying on dashboards or outsourced analyses.
We handle every step of data acquisition, including site selection and coordination, approvals, extraction, aggregation, curation, and quality control, removing operational burden from customers.
We set up and manage prospective data collection studies when retrospective data alone cannot meet project requirements.
Feasibility is established before data acquisition begins.
We assess your inclusion and exclusion criteria against data available across our healthcare partner network, with clinician input where appropriate, to determine whether sufficient eligible cases can be assembled for your study.
Retrospective when possible, prospective when necessary.
We design, set up, and manage protocol-aligned prospective studies to capture longitudinal variables or generate additional study-specific data. The entire process is managed end-to-end, including site selection, approvals, consent, data collection, and quality control.
Check out our case studies for representative examples.
Our experience spans a wide range of precision medicine use cases. We have delivered retrospective data acquisition projects and prospective data collection studies across multiple data modalities and clinical specialties for translational research, clinical development, real-world evidence generation, and AI applications.
More than image-only datasets.
Imaging data are integrated at the patient level with structured clinical, pathology, and molecular data. Where associated physical biospecimens are available, additional study-specific biomarker data can be generated through our partner laboratories.
Datasets are transferred to you.
Curated datasets are delivered directly into your infrastructure with appropriate commercial usage rights. There are no closed dashboards or federated read-only restrictions, and analyses are provided only if you request them.
Precision medicine R&D requires multiple data modalities linked at the patient level. We combine imaging, pathology, clinical, and molecular data from our healthcare partner network into datasets tailored to study objectives.

Medical imaging data across multiple modalities and clinical specialties, with associated reports and linked metadata.
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Structured and unstructured patient-level data, including demographics, diagnoses, procedures, medications, clinical notes, and outcomes.

Digital pathology images derived from biopsies, resections, and other specimen types, with associated metadata.

Specimen-level diagnostic information, including pathology findings, diagnostic classifications, specimen characteristics, and organ site details.

Molecular and biomarker test results, including genomic, transcriptomic, proteomic, and cytogenetic findings.

Biological specimens from corresponding data subjects, including tissue, blood, plasma, and serum.