Programs

Four programs

The first is SNOW, the reader, and a clinic can use it today. We are building the company around the next two, our own assays for infectious disease and for cancer, which are still in development. The fourth, the data layer, is built on what the reader keeps.

Reading commercial tests today

The reader and the record

The software reads the lateral-flow tests clinics already run, whether they develop bands or spots, and keeps each reading.

Those tests are made by other companies, so the reader can be useful in a clinic now, before any of our own assays are finished.

It does not promise a better call than a technician can make. The first thing it adds is a record. A faint line called by eye leaves nothing to look back at, but with SNOW the photo and its measurement stay on file next to the clinician's call.

A negative test. Only the control spot has developed, and the four test positions are blank.
Assay development and validation

Tick-borne and infectious disease

Vector-borne diseases are spreading, and guidelines call for annual screening, but a clinic can test only for the targets on the cassettes it buys.

Canine tick-borne screening is among the highest-volume point-of-care testing in veterinary medicine. All that volume makes tick-borne panels the best place to evaluate SNOW, and tick-borne disease is also a clinical target for our own assays.

We design our assays to be multiplex, testing one sample for several targets. A panel can add targets without changes to SNOW, which reads each zone wherever a new design or format puts it. That matters most for pathogens spreading into regions where clinics do not currently test for them.

Targets

  • Anaplasma
  • Borrelia
  • Ehrlichia
  • Dirofilaria (heartworm)
  • Leptospira
  • Leishmania
  • Feline retroviruses (FeLV/FIV)
  • Bovine respiratory syncytial virus

In development. Nothing on this list is a cleared or approved test.

Targets identified; engineering underway

Oncology and liquid biopsy

We are developing rapid blood tests for cancers that are currently diagnosed late, at high cost, or both.

In dogs, cancer diagnosis runs through imaging, biopsy and referral, a route that is slow and costly and often ends only after the dog shows clinical signs. Circulating protein biomarkers offer another, a blood panel that could be read at the first visit.

The biological targets came out of peer-reviewed research at The Ohio State University. Now that they are identified, the rest is engineering, from conjugation and strip optimization to multiplexing and validation. A company is better placed than an academic lab to do it.

The blood-panel approach depends on multiplexing, because a single marker is rarely specific enough. Telling which cancer a dog has, and how far it has advanced, takes a panel of markers read together.

Targets

  • Canine urothelial carcinoma (bladder cancer)
  • Canine osteosarcoma
  • Pan-cancer marker panel

In development. Nothing on this list is a cleared or approved test.

Built; awaiting coverage

The data layer

Every reading carries a place and a time, and enough of them together can show where a disease is moving.

Clinics run rapid tests all day, but almost none of the results are kept as data. A one-word entry in a chart cannot be counted across clinics.

With signalment and location attached, results kept in SNOW can help answer questions no single clinic can, such as where a pathogen is emerging, which breeds and ages carry the risk, and how prevalence changes with the season.

Until enough clinics in an area use SNOW, the counts describe who happened to be testing. The software works in rates rather than raw counts, scales the number of positives it expects to the number of tests run, and leaves areas with too little testing blank instead of reading them as a signal. It cannot yet tell a real rise from a change in who is being tested.

raw countswhere SNOW is usedshare positivegray = too few tests
This example region is drawn two ways. On the left, raw counts mostly show where SNOW is used. On the right, each cell shows the share of its tests that came back positive, and cells with too few tests are left gray.