Abstract
Experimental studies on the cellular uptake of nanoparticles (NPs), useful for the investigation of NP-based drug delivery systems,are often difficult to interpret due to the large number of parameters that can contribute to the phenomenon. It is therefore of greatinterest to identify unsignificant parameters to reduce the number of variables used for the design of experiments. In this work,a model of the wrapping of elliptical NPs by the cell membrane is used to compare the influence of the aspect ratio of the NP,the membrane tension, the NP-membrane adhesion, and its variation during the interaction with the NP, on the equilibrium stateof the wrapping process. Several surrogate models, such as Kriging, Polynomial Chaos Expansion (PCE), and Artificial NeuralNetworks (ANN) have been built and compared in order to emulate the computationally expensive model. Only the ANN-basedmodel outperformed the other approaches by providing much better predictivity metrics and could therefore be used to compute thesensitivity indices. Our results showed that the NP’s aspect ratio, the initial NP-membrane adhesion, the membrane tension and thedelay for the increase of the NP-membrane adhesion after receptor dynamics are the main contributors to the cellular internalizationof the NP, while the influence of other parameters is negligible