Clinical Pharmacology – Chemical
Less than a century after discovery of double helix routine sequencing of patient’s DNA and RNA as well as individual tumour genomes and transcriptomes is becoming reality. However, our understanding of how to fully capitalise on this unprecedented measurement capability in pharmacology, medicine and healthcare is lagging behind. In particular, there is a gap between the scope of available genomics data and the scope of quantitative mechanistic models well established in pharmacology. I will discuss approaches from Systems Biology field that aim at closing this gap with genome-scale mechanistic models of molecular cell biology. In particular, steady state models covering whole set of metabolic enzymes encoded in human genome can be constrained by individual genomics data and applied to mechanistic modelling of the effect of genetic polymorphism on the response to pharmacological perturbation. I will show examples of prototype Quantitative Systems Pharmacology models using genome scale metabolic networks informed by individual genomics data.