Dynamic Pharmacokinetic Models for Drug Repurposing Applications
Lead researchers: Professor Jennifer Martin (Health) and Professor Steve Weller (Engineering)
Associated research group: Centre for Complex Dynamic Systems and Control
Drug repurposing is a method for identifying new uses for approved drugs that are outside the scope of the original intended or approved medical use. The development of repurposed drugs is attractive both in terms of the substantial cost efficiencies it offers in comparison to drug discovery, and because therapeutic advances and new drug options for many cancer patients have been far slower than expected.
Drug repurposing reduces the time for drug development by utilising the existing knowledge of repurposing drug candidates, including pharmacokinetics (PK - the movement of drugs in the body), pharmacodynamics (PD - the biochemical and physiological effects of drugs), common and uncommon toxicities, dosing schedule, and mechanism of action.
New drugs for the treatment of cancer, for example, currently require approximately 12–16 years processing time and investment of US$1–2 billion to achieve market approval. In contrast, repurposing a drug takes only 6.5 years on average to obtain approval and investment of US$300 million. A combination of both traditional drug development and drug repurposing is therefore prudent if we are to make timely inroads into treating cancer more efficiently and deliver a significant impact on human health.
This project aims to apply system identification techniques to clinical pharmacology (PK/PD) datasets to construct dynamic pharmacokinetic models with a view to better predicting patient response to individualised dosing. We anticipate that the dynamic models so created will enable the development of new in silico screening methods for drug dosing and toxicity using machine learning.
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