LAUSR

Translational model-based approaches have played a role in increasing success in the development of novel anti-cancer treatments. However, despite this, significant translational uncertainty remains from animal models to patients. Optimisation of dose and scheduling (regimen) of drugs to maximise the therapeutic utility (maximise efficacy while avoiding limiting toxicities) is still predominately driven by clinical investigations. Here we argue that utilising pragmatic mechanism based translational modelling of nonclinical data can further inform this optimisation. Consequently, a prototype model is demonstrated that addresses the required fundamental mechanisms.