Abstract Around 14% of the world’s population currently represents more than 75% of oncology clinical trials and genomic datasets, with the majority derived from individuals of Caucasian ancestry. Precision oncology drugs developed over the past decade have been validated largely on this skewed representation. As a result, targeted therapies often perform inconsistently in regions with the highest cancer burden, leading to reduced effectiveness, increased toxicity, and substantial economic losses from failed clinical applicability. To address this unmet need, we developed a global real-world clinical genomic platform through a bilateral collaboration between India and Germany. This platform links major oncology centers in India with the Global Precision Medicine research group in Heidelberg, one of Europe’s largest precision-oncology and clinical-trial hubs. At its core, we developed a novel digital interface for structured clinical data capture at source, supported by clinician training and AI-based integration of epidemiological, diagnostic, imaging, and pathology information. We also introduced deep whole genome sequencing with tumor-matched controls using a nationwide snap-frozen workflow, coupled with tumor transcriptome sequencing as part of our multi-omics program. All multimodal data are processed through a validated analytical framework for alignment, variant calling, expression profiling, biomarker annotation, and molecular tumor board integration. With our platform, we aim to generate real-world multi-omics data for 10,000 genetically diverse patients across India, forming one of the largest clinically annotated oncology datasets from underrepresented populations globally. Initial integration shows that multi-institutional datasets can be harmonized with European pipelines, enabling high-quality sequencing and structured clinical annotation. Early analyses suggest genomic and transcriptional differences compared to European cohorts, including variation in mutational signatures, copy-number profiles, and immune-related states. These insights support the development of context-specific biomarkers and decision-support modules tailored to underrepresented populations. In conclusion, our platform delivers two parallel value additions. Clinically, it identifies additional actionable mutations, supports combinatorial therapy recommendations, and reveals missed diagnostics. Scientifically, the high-resolution dataset enables biomarker discovery, patient-stratification models, and early identification of therapeutic vulnerabilities. Together, our clinical genomics platform provides a scalable blueprint for integrating underrepresented populations into global cancer genomics and positions these cohorts as essential contributors to the future of precision oncology. Citation Format: Shubhankar Sood, Daniel Hübschmann, Jennifer Wischhusen, Andreas Trumpp. Developing a real-world clinical genomic platform to deliver precision oncology in underrepresented populations abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1306.
Sood et al. (Fri,) studied this question.