Building on advances presented here, MPM's computational efficiency will enable onthe-fly evaluation of optical properties in dynamic, nanoparticle-based simulations, making possible the design of complex plasmonic assemblies with targeted near-or far-field responses using inverse methods. Computation-guided design of disordered structures with desired optical properties is particularly compelling for soft hybrid materials, e.g., plasmonic gels that can dynamically reconfigure-modulating how they interact with light-in response to stimuli. In design of hybrid materials, MPM can readily compute optical properties for networks comprising both dielectric (e.g., semiconductor) and metal nanoparticles or with hierarchical nanoparticle ordering, significantly expanding the design space where computation can enhance experimental discovery. An intriguing possibility is the creation of plasmonic materials with inhomogeneous electric fields in compositionally-specific locations within the assembly, e.g., to enhance molecular detection sensitivity, plasmon-driven chemistry, or non-linear optical effects.