Can decision analytic modelling promote clinical translation of personalised medicine markers for oncology drugs?

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Personalised medicine is an approach that has great potential to improve healthcare. There has been limited success to date, however, in utilising proposed tests in the clinical. It is proposed that use of mathematical models early in the development of personalised medicine tests will allow early understanding of the value that the test will have for patients and society. Such insight will help build a strong case to undertake the research required before personalised medicine can be more widely used to improve treatment for cancer.