Using Quantitative Systems Pharmacology for supporting rationally designed multi-target discovery projects in CNS R&D
Hugo Geerts,
Chief Scientific Officer,
In Silico Biosciences Inc
Despite heavy investment in CNS R&D and an increased understanding of the neurobiology, the clinical failure rate remains above 90%, likely due to the limited translation from animal models to the human brain and the lack of efficacy of very selective one-target drugs on complex neuronal network.
Quantitative Systems Pharmacology, an approach that uses computer-based mechanistic modeling based upon the physiology of (human) brain networks, functional imaging of genetics and pharmacology of drug-receptor interaction and parametrized with clinical data is a possible powerful and valuable tool for drug discovery. By using mathematics as a common language to develop prototypes of the ‘virtual’ human brain, we will present a strategy for a rationally designed multi-target discovery platform to identify clinical candidates for which we can better predict better clinical outcomes in Alzheimer’s disease and schizophrenia. Similar to other ‘engineering’ industries, the platform can also serve also as a knowledge repository that conserves and expand ‘tacit’ corporate scientific knowledge.
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