At NextGen Omics US 2026, Deepak Veeregowda, CEO and co-founder of QT Sense, challenges the current boundaries of multi-omics, arguing that while traditional approaches provide valuable molecular snapshots, they fall short in explaining the underlying drivers of cellular behavior.

Conventional omics technologies—genomics, proteomics, and transcriptomics—primarily capture static end states, revealing what has occurred within a cell. However, they often lack the ability to uncover causality—why a process started, where it originated, and how it evolved over time. This limitation is especially critical in areas like drug toxicity, where understanding the trigger and progression of cellular stress is essential.

QT Sense addresses this gap by introducing real-time, non-destructive cellular sensing, offering a direct window into the functional state of living cells. Their approach adds a crucial dynamic, functional layer to existing omics data, enabling researchers to observe biological processes as they unfold rather than reconstructing them retrospectively.

A key innovation underpinning this capability is quantum sensing, which allows high-resolution, live-cell imaging at the subcellular level without altering the cell’s natural state. This technology enables continuous monitoring of processes such as cellular metabolism, oxidative stress, and free radical activity, delivering insights that were previously inaccessible.

Importantly, QT Sense’s platform addresses three major gaps in traditional omics:

  • Temporal resolution – tracking how biological processes evolve over time
  • Spatial resolution – pinpointing where events occur within cellular structures like mitochondria
  • Physiological relevance – preserving the natural state of living cells without destructive sample preparation

By combining these dimensions, researchers can build causal relationships rather than correlations—an essential step toward more predictive and effective drug development.

The implications for the life sciences are significant. Real-time cellular insight can enhance drug target identification, enable more robust and relevant biomarker discovery, and improve understanding of patient heterogeneity, ultimately supporting the development of more precise and personalized therapies.

Looking ahead, Veeregowda envisions a future where real-time functional data seamlessly integrates with traditional multi-omics, creating a comprehensive, systems-level understanding of biology. In this paradigm, drug discovery will no longer rely solely on static datasets but will be driven by continuous, high-resolution insights into cellular function.

As the field evolves, one message is clear: omics alone is no longer enough. The next wave of innovation will come from technologies that can capture biology in motion—bringing us closer to truly understanding and treating complex diseases.