Improving Processor Usage In InterpolateSolution from the PDE Toolbox Via Parallel Computing?

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I have a set of ~50 saved results structures from the PDE Toolbox, at roughly 7GB each, on which I need to interpolate to different coordinates. Keeping the code simple, this looks something like:
for index = 1:50
filename=([f1(index),f2,'.mat']);
presaved_results = load(filename,'results');
A = interpolateSolution(presaved_results.results,X,Y,Z,[1,2,3]);
A = reshape(A,size(X,1),size(X,2),3);
end
The aim is to integrate this into an optimisation proceedure using MATLAB's GA, meaning this interpolation step is called many times.
This function seems to just use just 1/4 cores available on my processer, sitting at roughly 30% cpu usage for around 60 seconds per file, so I wondered if it's possible to use the Parallel Computing Toolbox, or anything similar to use more of my processor to speed this up? If not, I assume hardware improvements maybe my only option?
Happy to look into undocumentated solutions, this is currently the biggest bottleneck in my code by some significant margin, it's only a factor of 2 slower to solve the whole FEM model from scatch vs just interpolating to the points of interest because the actual solver utilises my CPU(s) better.

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