Analyze Cells As You Would Molecules

Transformational method for retrieval of single cell data that breaks from 60 years of brute force dogma.

It is standard practice to analyze molecules (proteins, DNA) with molecules (antibodies, enzymes). This is incredibly efficient. Yet when it comes to cells, the standard practice is to use large instruments that sort through cells one at a time. PHENO-IMMUNO COMPUTING (PIC) is the first method that uses cells to analyze cells.

PIC

PhenoImmuno Computer

Instrument free technology for deep single cell analysis.

PIC is an information technology that is grown. And more than that, it is grown using the most widely used industrial organism, baker’s yeast. This enables unparalleled diagnostic power with incredible cost effectivity.

Sample Collection

Sample Collection

Blood, urine, saliva, tissue, and other sample forms available in liquid formats.

Immunolabeling

Immunolabeling

Biomarkers of interest are defined using effective immunolabels.

PIC clustering

PIC clustering

Immunolabels are associated with living microbial computational units.

Computing

Computing

Molecular profiles are processed and presence of target cells is indicated.

Tube

PIC operating system

Machine supervised learning of single cell biomarkers.

The TUBE is an automated operating system that deploys PIC for the purpose of learning highly specific single cell biomarkers. By the distributed power of biology, the TUBE is able to screen through an unprecedented number of cells in record time.

biobank system

biobank system

A diverse set of samples is uploaded to the TUBE. Proprietary preservation enables high-throughput analysis by PIC.

single cell query

single cell query

Depth of single cell knowledge is greatly increased with unsupervised learning of many more patients and many more cells.

Single cell biomarker discovery is today made infeasible by the bottleneck of phenotypic analysis.

There exists no facility today that can perform meaningful phenome-wide analysis of semi-rare diseases like leukemia in a reasonable amount of time. A 100K sample study performed in a reasonable amount of time would require more instruments than companies sell in a year (see below, figure on the right). And while 100K samples is a lot, chemical analysis of the same lot is easily accomplished with routine laboratory instruments. The problem is that the current approach dedicates 99.999% of the resources to process material that is informationally uninteresting. PIC provides a biological solution that works in a distributed way extracting only essential information, much like our own immune system. Biological analysis has an unparalleled potential to scale (see below, figure on the left).

biology vs silicon

biology vs silicon

An elephant is healthier than a mouse despite having many more cells it must maintain. This is known as Peto’s paradox, and it speaks to the potential of biological systems to scale up information processing.

cost of brute force

cost of brute force

To validate early biomarkers of rare diseases, large studies are necessary. This is the challenge of preventive healthcare. Even the most effective instruments fall short. Costs of single cell biomarker discovery facilities are plotted above.