The overall survival of patients with advanced malignancies remains unsatisfactory low although the treatment of few cancer types has improved. Current therapeutics are effective in a limited number of patients and are associated with side effects and the development of resistance. The discovery of more efficient and less toxic cancer therapies remains a major challenge.

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Each year research institutes and pharma industry produce thousands of new compounds with potential antitumor potency. Unfortunately, most of them will fail during clinical trials due to inappropriate preclinical investigation, mainly using too weak cut-off for efficacy and lack of predictive biomarkers for proper patient selection. Improving preclinical drug development is therefore strongly needed. 

 

Recent technology breakthroughs reveal cancer molecular alterations in details. Genetic analysis of thousands of tumors worldwide led to the accumulation of tremendous amounts of information. It confirms the huge heterogeneity of tumors: not a single cancer is exactly identical to another. The development of computational tools to analyse these data offers unprecedented alternatives for drug discovery.

 

4HF Biotec uses data mining-based strategies for cancer drug discovery. We believe our approaches will improve evaluation of novel anticancer drugs at the preclinical stage and the analyses of cancer molecular features contained in our databases permit discovery of novel targets. Together, it should result in more efficient treatments for cancer patients.