Multiomics Platform Integration Advances Cancer Treatment Predictions
By Bio-IT World Staff
July 24, 2025 | A groundbreaking biotech collaboration in Switzerland has successfully integrated nine molecular analysis platforms to create a comprehensive tumor profiling system that predicts optimal cancer treatments—showcasing how next-generation sequencing can be enhanced through multiomics approaches for transformative clinical outcomes.
The Tumor Profiler research consortium, involving academic institutions and Roche, has developed a technology-agnostic platform that processes 43,000 data points per tumor sample within a two-week technical turnaround time. Published in Nature Medicine, the study demonstrates how biotech innovation can bridge the gap between laboratory capabilities and clinical implementation.
The multiomics approach builds upon the NGS foundation that Swiss university hospitals implemented around 2015. Recognizing the limitations of single-platform analysis, researchers developed an integrated system combining single-cell genomics and transcriptomics, targeted spatial proteomics, cytometry by time of flight, mass spectrometry proteotyping, drug phenotyping platforms, iterative indirect immunofluorescence imaging, targeted next-generation DNA sequencing, and digital pathology systems.
"We're basically technology-agnostic," explained Dr. Andreas Wicki from the University of Zurich. The platform accepts any technology meeting specific criteria, including the critical requirement for rapid results processing—a key factor for biotech companies developing diagnostic solutions.
Biotech Cost Optimization
The project reveals dramatic cost reduction potential for multiomics biotechnology. Initial per-patient costs of approximately $140,000 in 2018 have dropped to roughly $14,000 today—a 90% reduction that makes commercial deployment increasingly viable.
This cost trajectory mirrors typical biotech scaling patterns, where initial research-grade implementations become commercially accessible through optimization and automation. The researchers demonstrated that not all nine technologies are necessary for every patient, with simulation exercises showing that two to four platforms could suffice for most cases—further reducing implementation costs for biotech companies.
NGS Evolution and Enhancement
While NGS remains a cornerstone technology, the study highlights how next-generation sequencing can be enhanced through complementary platforms. Traditional NGS and digital pathology represent the only current diagnostic standards among the nine technologies used, positioning additional platforms as next-generation enhancements to existing workflows.
The research demonstrates that NGS data become significantly more powerful when combined with functional genomics, proteomics, and imaging technologies. This integration approach offers biotech companies a pathway to enhance existing NGS platforms rather than replacing them entirely.
Data Processing and Machine Learning Integration
The platform generates massive datasets requiring sophisticated bioinformatics processing. From 43,000 data points per sample, researchers currently use only 54 individual markers for treatment recommendations—highlighting both the potential and the challenge for biotech companies developing analysis software.
Machine learning models will be essential for leveraging complete datasets, representing a significant opportunity for biotech firms specializing in artificial intelligence and data analytics. The consortium plans to focus on developing these predictive models to fully use the multiomics data generated by their platform.
For complete technical details and clinical outcomes data, read Deborah Borfitz’s full article in Clinical Research News.