ProtiFi develops technologies and products for omics research.

Omics is the analysis of entire populations of biological molecules, usually of one particular class. It includes the fields of genomics, transcriptomics, proteomics, glycomics, metabolomics and lipidomics. Omics technologies yield vast details on states of health and disease and will underpin personalized medicine. However, translation of R&D omics to clinical relevance remains difficult. Specifically, progress has been hindered by poor sample processing, lack of true multiomics analyses and limitations in data analysis software. Only solutions to these problems will allow omics to produce actionable biological insights like diagnoses. 
Sample preparation has been the largest contributor to overall omics data variability. Improper sample preparation can significantly compromise sensitivity and cause large observation biases. Additionally, traditional sample preparation includes the destruction of all molecule classes except the one under study, fully precluding a true multiomics approach. However, markers of disease exist in every class of biomolecule. Thus, a comprehensive understanding of biological states requires a standard multiomics sample preparation method.

Multiomics brings its own challenges. Current computational tools are typically designed for one specific class of biomolecule. Tools frequently employ non-ideal statistics and fail to report the confidence of results. Importantly, the available tools are designed for omics experts, rather than end-users like medical and biological researchers, whose field-specific expertise is essential to maximize understanding and insights.

ProtiFi has developed multiple technologies and products to address these challenges and move omics research to clinical use:

(1) The S-Trap for fast, reproducible proteomics sample prep
(2) The Si-Trap for efficient simultaneous processing of a single sample for multiomics
(3) Tryp-N, a protease that provides clearer MS/MS spectra at a better limit of detection
(4) SimpliFi, data visualization software that empowers researchers to easily explore their data and its meaning