Can fractional calculus help improve tumor growth models?

ODE-based population models remain viable tools to investigate tumor growth and support clinical evidence. By following a fractional approach, this study derives analytical solutions for five of these models, whose parameters are best-fitted against extant clinical data. In terms of tumor growth prediction, results show that fractional models not only have better performance, which is mostly wanted for decision-making in oncology, but also reveal interesting characteristics to be further explored. •Analytical solutions for five different ODE-based tumor growth models are derived.•Fractional power series method for investigating tumor growth dynamics is adopted.•Clinical data are used to best-fit free model parameters, including fractional order.•Numerical simulations are implemented for both fractional and classical models.•Results indicate that fractional models are better predictors, among other features.