The mechanism of action of your compound can be investigated with response parameters of cancer cell line profiling, without the need for additional experiments. For instance, we perform ANOVA analysis on IC50 values and gene mutation data to identify genomic drug response biomarkers for cancer. Case studies have confirmed patient stratification markers that have been used in the clinic (Uitdehaag et al. 2019).
Precision Medicine is about the match between drug targeting and patients’ individual responses. Early proof of concept studies on response pathways help to progress your drug candidates towards the clinic and select patients whose genetic makeup corresponds to the drug’s target.
Genetic variations occur in many capacities and only a restricted number of DNA mutations has been implicated in cancer. With the aim to identify biomarkers that have clinical relevance, the pharmacogenomics analysis at NTRC concerns mutations that have been observed in cancer patients. Clinically actionable mutations are analysed by zooming in on independently validated hotspot mutations and copy number variations.
We can help you to identify a patient stratification marker for your compound. Cancer cell line profiling data, generally IC50 data, is used as a source of input. In case your mechanism is better represented by another parameter, e.g. Area Under the Curve, we adapt the analysis accordingly.
Zaman et al. (2017) TTK inhibitors as a targeted therapy for CTNNB1 (β-catenin) mutant cancers, Molecular Cancer Therapeutics, 16 (11):2609-2617
Uitdehaag et al. (2019) Combined cellular and biochemical profiling to identify predictive drug response biomarkers for kinase inhibitors approved for clinical use between 2013 and 2017. Molecular Cancer Therapeutics, 18 (2):470-481.