PILLTOP: Multi-Material Topology Optimization of Polypills for Prescribed Drug-Release Kinetics

Polypills are single oral dosage forms that combine multiple active pharmaceutical ingredients and excipients, enabling fixed-dose combination therapies, coordinated multi-phase release, and precise customization of patient-specific treatment protocols. Recent advances in additive manufacturing facilitate the physical realization of multi-material excipients, offering superior customization of target release profiles. However, polypill formulations remain tuned by ad hoc parameter sweeps; this reliance renders current design workflows ill-suited for the systematic exploration of the high-dimensional space of shapes, compositions, and release behaviors. We present an automated design framework for polypills that leverages topology optimization to match dissolution behaviors with prescribed drug release kinetics. In particular, we employ a supershape parametrization to define geometry/phase distribution, a neural network representation to specify excipient distribution, and a coupled system of modified Allen-Cahn and Fick's diffusion equations to govern dissolution kinetics. The framework is implemented in JAX, utilizing automatic differentiation to compute sensitivities for the co-optimization of pill shape and constituent distribution. We validate the method through single-phase and multi-excipient case studies.