Drug Optimization
Identify a chemical compound that potentially interacts with the desired target.
Identify the mechanism of action of a compound by massive genomic analysis, functional analysis and evaluation of protein-protein interaction, using big data at a glance.
Discover key resistant genes or biomarkers of sensibility.
Link genomic information with our drug bank datasets to identify synthetic lethality interactions.
Exploit that information with patient data to translate your key findings to the clinic.
Step 1 - Drug of interest.
Select the compound of interest from our databank list, or provide the cell line sensibility of your proprietary compound.
Step 2 - Match the uploaded data with our databases.
We use proprietary algorithms to match drug sensibility to genomic data.
Step 3 - Match the generated results with therapeutic opportunities and clinical efficacy.
Biomarkers of response and resistance can be generated and matched with potential therapeutic options, patient survival and clinical efficacy of the identified compounds.
Step 4: Generate your report
We provide a comprehensive report that contains a biomarker list, potential combinations and options for clinical development.
Objective
Optimize your compound in a matrix environment by linking genomic data with clinical efficacy using big data.
How
Our platform with its built-in proprietary algorithms matches drug sensibility, genomic data, functional analysis, drug-bank data and clinical outcomes.
We provide molecular biology-drug information and patient data at a global scale.
Process
We apply artificial intelligence and big data analysis to de-risk and accelerate the processes of drug discovery and development.
"CancerAppy helps you to think outside the box. With our integration of big data and artificial intelligence we provide you novel hypotheses to optimize your compound."
– CancerAppy Team-