  In this work we put forward the inclusion of error mitigation routines in the
process of training Variational Quantum Circuit (VQC) models. In detail, we
define a Real Time Quantum Error Mitigation (RTQEM) algorithm to assist in
fitting functions on quantum chips with VQCs. While state-of-the-art QEM
methods cannot address the exponential loss concentration induced by noise in
current devices, we demonstrate that our RTQEM routine can enhance VQCs'
trainability by reducing the corruption of the loss function. We tested the
algorithm by simulating and deploying the fit of a monodimensional
$\textit{u}$-Quark Parton Distribution Function (PDF) on a superconducting
single-qubit device, and we further analyzed the scalability of the proposed
technique by simulating a multidimensional fit with up to 8 qubits.
