Designing anti-cancer drugs and directing anti-cancer therapy

TL;DR

This paper presents a web application prototype that helps clinicians design personalized anti-cancer therapies by visualizing patient-specific metabolic pathways and identifying key enzymatic targets for drug intervention.

Contribution

It introduces a novel interactive tool that integrates biological data and graph algorithms to assist in personalized cancer drug design.

Findings

The application effectively visualizes patient-specific metabolic pathways.

It ranks and highlights key enzymatic sites for targeted therapy.

The tool supports clinicians in making informed drug therapy decisions.

Abstract

A prototype for a web application was designed and implemented as a guide to be used by clinicians when designing the best drug therapy for a specific cancer patient, given biological data derived from the patients tumor tissue biopsy. A representation of the patients metabolic pathways is displayed as a graph in the application, with nodes as substrates and products and edges as enzymes. The top metabolically active sub- paths in the pathway, ranked using an algorithm based on both the patients biological data and the graph topology, are also displayed and can be individually highlighted to examine potential enzymatic sites to be disrupted by a drug.