#SysBio4CancerResearch: Mathematical modeling has made a significant recent impact in the design of treatment scheduling protocols that are evolution-based strategies to mitigate the evolution of resistance. But there is still many unanswered questions, and #MathOnco or #SysBio approaches will be key to future work. We’ve outline open questions in the field here: elifesciences.org/articles/8…

#SysBio4CancerResearch: Another important future direction is the integration of AI/ML approaches with mechanistic modeling. Combining highly predictive black-box approaches with parameterized math models to gain mechanistic insight into that black-box: frontiersin.org/journals/imm…

#SysBio4CancerResearch: The best way to bring preclinical data to bear on clinical translation is the integration of mathematical models to interpolate or extrapolate these data, and to test & generate hypotheses about underlying biological mechanisms. A great example of this model iteration process from Paras Jain & @mkjolly15: sciencedirect.com/science/ar…

#SysBio4CancerResearch: The best way to bring preclinical data to bear on clinical translation is the integration of mathematical models to interpolate or extrapolate these data, and to test & generate hypotheses about underlying biological mechanisms. A recent great example of model iteration is @stroblmar’s paper on PARP inhibitors in ovarian cancer: cell.com/cell-systems/abstra…