Magic Targets
for Magic Bullets

120 years ago, Nobel Prize laureate Paul Ehrlich laid out his theory for “magic bullets” in medicine: therapeutics that would kill a specific pathogen and leave the body unharmed. Dr Ehrlich acknowledged then that even a magic bullet needs a target. We pick up where Dr Ehrlich left off, finding magic targets for magic bullets.

Our RNA-based technology reveals the underlying causes of immune system imbalance and thereby new therapeutic targets.

AACC Annual Scientific Meeting & Clinical Lab Expo 2020

FBB Biomed Technology Featured at AACC Annual Meeting

Immune System & Disease

To understand disease, we must look beyond the pathogen.

Just as a balanced immune system is the body’s mightiest defense, an imbalanced immune system can become the agent of disease. Decoding the language of the immune system holds the key to pinpointing which patient is going to progress to severe disease.

The Role of RNA

The language of the immune system is ribonucleic acid (RNA). Immunological intelligence is gathered in the form of RNA and then decisions are made and executed through RNA.

We use RNA biomarkers because they are the earliest indicator of disease and hold valuable immune regulatory information.

Biomarkers as Targets

As RNA encodes immunological decision making and regulation, immune system-related RNA biomarkers also are therapeutic targets. Based on the latest sequencing techniques and bioinformatics, we have found a way to automate the discovery of RNA biomarkers – and thus of “magic targets”.

In 2019, we stated the urgent need for applying artificial intelligence to RNA virology. Now we are using machine learning for our research and discovering biomarkers that have been overlooked.

We have already validated our prototype
in several diseases

Proof-of-Concept Studies

Background: Using the differential expression of biomarkers between relapses and remissions to determine if blood RNA can be correlated with clinically reported relapses (flares)

Publication: Abstract peer-reviewed and published by the ACTRIMS Forum in February 2020

Severity biomarkers over-expressed: Yes

Potential drug targets detected: Yes

Background: Using the differential expression of biomarkers between Alzheimer’s samples and apparently healthy controls to determine if blood RNA can be correlated with clinical Alzheimer’s diagnoses

Publication: Unpublished

Severity biomarkers over-expressed: Yes

Potential drug targets detected: Yes

Background: Using the differential expression of biomarkers between Parkinson’s samples and apparently healthy controls to determine if blood RNA can be correlated with clinical Parkinson’s diagnoses

Publication: Unpublished

Severity biomarkers over-expressed: Yes

Potential drug targets detected: Yes

Background: Using the differential expression of biomarkers between ALS samples and apparently healthy controls to determine if blood RNA can be correlated with clinical ALS diagnoses

Publication: Unpublished

Severity biomarkers over-expressed: Yes

Potential drug targets detected: Yes

Background: Blinded study that succeeded in accurately segmenting randomized “dengue” samples into three distinct clinically diagnosed groups: severe dengue, uncomplicated dengue and apparently healthy

Publication: Unpublished

Severity biomarkers over-expressed: Yes

Potential drug targets detected: Yes

Background: Using the differential expression of biomarkers between COVID-19 samples and apparently healthy controls to determine if blood RNA can be correlated with clinical COVID-19 diagnoses

Publication: Unpublished

Severity biomarkers over-expressed: Yes

Potential drug targets detected: Yes