Applications
From molecular identity to biological function
Proteins execute biology. They catalyze reactions, transmit signals, recognize threats, respond to drugs, and interact with one another to determine cellular function.
Understanding biology therefore requires knowing which proteins are present, and what molecular forms they take, what they interact with, and how those interactions change across biological states, perturbations, and time
deSIPHR is designed to measure protein biology across multiple dimensions—from molecular identity and modification state to molecular interactions and functional state. Together, these measurements generate experimental datasets that connect what proteins are to what they do.
Biopharma
Measure the molecules drug actually act on.
Most drugs either are proteins or work on proteins. Yet drug discovery has largely relied on genomic and transcriptomic proxies - or protein measurements constrained by throughput, sensitivity, or prior knowledge.
deSIPHR enables direct measurement of protein biology from limited samples, creating new ways to discover targets, characterize drug response, and understand mechanism.
Applications include:
protein and peptide discovery
protein-small molecule interactions
biologics and antibody characterization
drug response and perturbation studies
Biosecurity
Detect biology without knowing what to look for.
The next generation of biosecurity requires measurement technologies capable of identifying biological threats that may not exist in any reference database.
deSIPHR directly reads molecular identity and state without requiring prior knowledge of what's in the sample—opening a path to identify unfamiliar proteins, chemical modifications, and potentially the molecular interactions that shape their function.
Unknown protein and biothreat detection
De novo identification of engineered or non-canonical proteins
Functional analysis and biothreat mitigation
Supply chain verification and biosurveillance
Bio-AI
Give AI access to biology’s functional data layer.
AI models of biology are advancing rapidly. But their ability to predict biological function ultimately depends on the experimental data available to train and test them.
deSIPHR is designed to generate biology’s missing experimental data layer - systematically and at scale. The result is more than larger proteomic datasets. It is linked data describing what proteins are, what they interact with, and what happens next.
Applications include:
protein function datasets
interaction maps
perturbation-response datasets
training and validation for biological models
predictive models of biological response