Because Response to Interferon is Personal

1. Genefron Personalized Medicine Diagnostic July 2013 Because Response to Interferon is Personal

2. Genefron LTD Team • Genefron Ltd. is an Israeli based, privately held company company that specializes in the development of in-vitro diagnostic kits for personalized medicine. • Our Team: • CEO Yaniv Kotler, MSC, LLB • Bioinformatics Management – Yoav Smith, PhD(Genomic Data Analysis Unit, Hebrew University, Jerusalem) • Business Development – Jack Lahav, Livingston NJ. • CFO - Orit Kotler, MBA. • Project Manager - Shlomo Pundak, PhD • Clinical trials – conducted at : Sheba Medical Center, Tel Aviv, and Shaare Zedek Medical center, Jerusalem.

3. Hepatitis C virus (HCV) INF treatment INF signal Direct Antiviral Agents Pi’s, Pol-i. INF induced genes personal gene expression Innate immune response: RNAase, Ubiquitin etc

4. INF induced genes - PGE (personal gene expression) INF signal Nucleus Personal gene expression signature mRNA Proteins – virus degradation

5. The Problem and the Technology 1.5% of WW population is infected with HCV. Currently only about 50% of the Caucasians, 30% of Asians and 80% of the Afro-Americans a HCV patients are non responders to the PEGylatedIFNa treatment. Non-responders and relapsed patients report severe adverse effectsand incur long and expensive treatments with minimal clinical results. Genefron’ s qRT PCR Diagnostic kit, IFR10, from liver tissue or blood samples measuring INF personal gene expression (PGE) signature can identify responders /non responders with ~ 96% accuracy will have an immediate and profound influence on MDs' decision of a specific patient optimal treatment, feasible outcome and cost.

6. IFR10 Diagnostics kit

7. Massive Data-Methylation, DNA, RNA,MICRO-ARRAY, SNP …It’s for Giants

8. Bioinformatics • Genefron’s breakthrough discovery is a verifiable and highly accurate platform algorithm for scanning extremely large databases that can be applied into various fields. This algorithm is designed to find mathematical connections and characters allowing identifying the desired group within the tested large databases. • Using our algorithm, we examined results from microarray data experiments by comparing responders to non responders and searching for a small list of genes and their particular importance within the liver tissue to the IFN responsiveness and consequently the treatment’s ultimate outcome.

9. Team Race

10. Algorithm outcome Top 10 genes Gene race

11. Results of gene expression analysis • 3 situations: • Healthy - No infection = no Personal Gene Signature (PGE) • After Infection = “natural” PGE: • non responders = high genes expression • Responders = low gene expression • After Infection + INF treatment = max PGE

12. HCV Test Validation & Verification 95% 89% 95% 95%

13. HCV Responders vs. Non respondersIdentification using PGE Example 1: We have used our algorithm on published RT PCR data (Dill et. al. Lausanne SW, 2011) which included 27 patients (X axis), RT-PCR – liver tissue, HCV Type 1 prior to PEG INF treatment. The patients presents various PGE signature (Y axis). The results identified 2 major groups responders (red) and non responders (blue) in 96% accuracy.

14. Personal Gene Expression . Example 1: Dill et.al. Lausanne SW, 2011. data after analysis ROC curve

15. Genefron invention in HCV treatment – Liver Biopsy • Identified PGE signature by qRT PCR about 95% accuracy + cost efficiency • Diagnosed HCV patient • Genefron Diagnosis test II for non responders for Treatment prediction with a defined treatment

16. Personal Treatment Adjustment • Personal Treatment AdjustmentUsing the PGE of a patient and a second novel algorithm we are developing a new method for adjustment of Personal Treatment (PT) including Interferon with/without combination of the new DAA medications. This approach will give the physician a new tool to tailor a specific treatment course base on the genomic information of the patient.

17. Cost efficiency – Israel (example) • SOC in Israel: • IFN treatment (estimated 2000- 2500 patient per year), Budget ~$30M • If negative IFN+DAA (512 patient per year), Budget ~$12M • Potential saving: • We estimate that at least 96% of the non responders can skip IFN treatment . ~ 1200 patients X $15K =$18M • Test cost ~$600. ($1.5M). Saving of $16.5M

18. Global market • $2.9 B is INFα (mostly for HCV) WW market. • $1.3 B saving today • USA +EU can save today ~$1B$. • $20B global market for hepatitis C therapies expected to be by the end of the decade – meaning $17.3B expense on DAA (nature) • Using our technology can reduce dramatically the market to ~$11B.

19. More PGE Signature Implications • Multiple sclerosis (MS) patients may be treated by IFN-b. We have identified the responders and non-responders patient populations correlates to MD diagnosis. • WW market $5.6B. • Estimated saving: $1.2B MS patients- the graph represent 15 patients (X axis) PGE Signature Genes (Y axis) before and 24h after IFN-b treatment. Notice the expression “shutdown” in the non responders:

20. Algorithm implications Dengue Healthy volunteers • Boxplot of 3 genes (g1-g3, X axis) expression (QRT-PCR units) in PBMC samples of 9 patients, 4 days post infection comparing uncomplicated cases vs. Dengue syndrome shock patients. The red line resemble the average expression of the group • 7 healthy volunteers (X- axis) donated PBMC samples before treatment with Poly C adjuvant and PBMC samples were taken 24 h post treatment. The change (delta E) in expression (Y axis) was measured in 4 genes (g1-g4). Note i307, i308 as non responders for future IFN treatment.

21. Genefron LTD overview