Scientific

Due to genetic and environmental differences, people bearing the same disease, respond differently to the same Standard  of care (SOC) treatment (and a substantial percentage do not respond at all). Accordingly, several treatment mechanisms (each, a ‘drug family’) are developed, to offer solutions for the same disease, in order to accommodate these genetic differences.
However, currently, physicians do not have any tools to choose the right drug family for a patient. Trial and error method is used until the effective treatment is identified. In chronic autoimmune diseases, such as Rheumatoid arthritis (RA) Multiple sclerosis (MS) addressed by Genefron, diagnosing response takes months to years.
The lack of response to a drug family results in:

  • Disease progression – patient condition deterioration, unnecessary suffering & low satisfaction
  • May worsening symptoms increasing long term care costs
  • Unnecessary treatment costs: $15,000-$50,000  per treatment which is ineffective for the patient

Genefron has developed a breakthrough technology platform, which enables it to develop a personal diagnostic kit (PDk) which can predict autoimmune disease patient’s clinical response to a specific drug family. This platform technology has been applied to acute viral diseases outcome successfully and (see CMV results below).
Using big data analysis,  novel machine learning algorithms combined with biological knowledge and bioinformatics tools, Genefron can detect a small set of biomarkers (genes), specific to each set of disease / drug family, representing a personal gene expression signature (PGES). Measuring the PGES, i.e., predicting patient’s response, is done rapidly (72h) by a simple manipulation on a standard blood sample.
Genefron initiated its research by comparing genetic expression micro-arrays profile of sick to normal patients as well as clinical  designated “responders” to clinical designated “non-responders” patients during a specific treatment. We have identified a small set of   biomarkers (genes), specific to each disease/treatment which predicts the treatment outcome prior to its administration. This group of biomarkers are unique for disease and treatment and termed personal gene expression signature (PGES). Measuring the biomarkers is conducted by using qRT-PCR machine in PBMC separated from a simple blood sample.
The PGES enabled Genefron to develop a personal diagnostic kit (PDK) that can serve the physician as an aiding tool to determine the ultimate outcome for the individual patient.
Predict a personal response to drugs before commencing treatment and enable the:

  1. Tailoring the type and dosage to the individual,
  2. May reduce costly inefficient treatments and  may prevent unnecessary suffering caused by ineffective drugs, short and long supporting term treatments.
  3. Serve as a companion diagnostics for existing drugs and new drugs currently under development.

Publications

For RA test:
https://www.tandfonline.com/doi/full/10.1080/03007995.2018.1443581    (peer review)
http://acrabstracts.org/abstract/expression-levels-of-selected-genes-may-predict-response-to-tnf-alpha-blockers-or-rituximab-in-the-individual-rheumatoid-arthritis-patient/
For RA (EULAR):
https://b-com.mci-group.com/Abstract/Statistics/AbstractStatisticsViewPage.aspx?AbstractID=357864
For CMV test:
Correlation between interferon signaling genes (ISG) expression and CMV intrauterine transmission
See below


Correlation Between Interferon Isgnaling Genes (ISG’s)

genefron-infographic