OmicsBank Raises $2.25M to Expand Global Clinical Data Infrastructure for Drug Development and Healthcare AI
核心洞察
OmicsBank (搜索) secured $2.25 million in seed funding from Redesign Health (搜索) to expand its clinical data infrastructure across the U.S., Asia, and the Middle East.
The company's network spans more than 90 hospitals and diagnostic labs, encompassing longitudinal EHR data from 12.5 million patients, 30 million DICOM images, 6 million pathology slides, and 500,000 genome sequences.
The platform aims to address the underrepresentation of large global populations in drug development datasets, noting that South Asian populations account for roughly 25% of the world's population yet only about 2% of participants in large-scale genomic studies.
OmicsBank (搜索), a San Francisco-based clinical data infrastructure company, has raised $2.25 million in seed funding from global venture capital and technology firm Redesign Health (搜索). The investment, announced August 25, 2026, will support the company's expansion across the United States, Asia, and the Middle East, while broadening access to clinical and multi-omics data from underrepresented populations for drug development and healthcare AI applications.
The company, founded in 2025 by Sumit Sinha and Vijay Goel, connects fragmented hospital data for drug development, real-world evidence research, and healthcare AI. Its technology is now deployed across more than 90 hospitals and diagnostic laboratories in Asia, where it standardizes and de-identifies multimodal data at the source. The network currently includes longitudinal electronic health record (EHR) data from 12.5 million patients, more than 30 million DICOM medical images, 6 million pathology slides, and approximately 500,000 genome sequences.
Addressing a Data Representation Gap
OmicsBank (搜索) targets a central challenge in clinical research and healthcare AI: the underrepresentation of large global populations in the datasets used for drug development, biomarker discovery, and model training. India alone represents nearly 20% of the world's population, while South Asian countries collectively account for roughly 25%, yet research cited by the company indicates these populations make up about 2% or less of participants in large-scale global genomic studies.
"Drug development and healthcare AI are becoming increasingly sophisticated, but the data powering them still represents a relatively narrow slice of the world," said Sumit Sinha, Co-Founder and CEO of OmicsBank (搜索). "We've built the infrastructure to make rich clinical and biological data from Asia and other underrepresented populations available for research, ethically and at scale, while remaining compliant with local and international laws."
Representation is only part of the challenge. Hospital data remains fragmented across EHRs, labs, imaging, pathology, and other systems, making it difficult to build longitudinal patient records that link diagnoses, treatments, and outcomes. OmicsBank (搜索)'s infrastructure standardizes and de-identifies information within the hospital environment, connecting clinical events with imaging and multi-omics data.
Platform Capabilities and Applications
The company's offering spans FHIR and OMOP CDM-structured EHR data, along with imaging, genomic, transcriptomic, proteomic, phenomic, and metabolomic datasets and biospecimens. OmicsBank (搜索) said its process operates under IRB and ethics committee approvals and is ISO 27001-certified and HIPAA- and GDPR-compliant.
For pharmaceutical, biotechnology, and AI organizations, the resulting datasets support disease research, biomarker discovery, treatment-response analysis, and model training and evaluation. Participating hospitals can also use the infrastructure to search their own clinical archives, identify research cohorts, and support prospective studies.
OmicsBank (搜索) already works with pharmaceutical and biotechnology organizations across oncology, neurology, cardiology, nephrology, endocrinology, immunology, and dermatology. The company is also collaborating with frontier AI organizations on pre-training, post-training, and reinforcement learning for clinical and multimodal models.
Expansion Strategy
In the U.S., OmicsBank (搜索) is pursuing a two-sided strategy. The company plans to give drug developers, contract research organizations (CROs), and AI companies access to research-ready data from Asia, while partnering with U.S. health systems to add more populations to its standardized longitudinal network.
With the new funding, OmicsBank (搜索) will expand its hospital footprint across the Middle East and Southeast Asia and develop GPU-enabled research environments for AI model training, reinforcement learning, biomarker discovery, real-world evidence, and computational biology.
"They saw early that the lack of well-structured, representative clinical data was becoming a constraint on drug development and research, and they moved quickly to do something about it," said Neil Patel, Head of Ventures at Redesign Health (搜索).
"Making medical and pharmaceutical research more representative of emerging-market populations is not only a matter of inclusion. People underrepresented in medical research make up the majority of the world's population," said Oscar Ramos Moreno, Managing General Partner at Orbit Ventures (搜索), who led OmicsBank (搜索)'s pre-seed round in 2025.