A Biophysical Simulation Framework for Investigating Lidocaine-Induced Conduction Block in Trigeminal Aβ and Aδ Fibers

Abstract: Trigeminal neuralgia is a debilitating neuropathic disorder in which abnormal interactions between trigeminal sensory fibers lead to paroxysmal facial pain. Lidocaine, a widely used sodium channel blocker, provides symptomatic relief, yet its dose-dependent effects on distinct trigeminal fiber populations remain poorly characterized. In this study, a high-fidelity biophysical simulation framework was developed to investigate the lidocaine-induced conduction block in myelinated Aβ and Aδ fibers of the human trigeminal nerve. Using the McIntyre-Richardson-Grill model as the structural basis, fiber geometries and ion channel properties were parameterized from experimental data, and a pharmacodynamic model describing state-dependent lidocaine binding to voltage-gated sodium channels was incorporated. The baseline model was validated against established electrophysiological benchmarks, including conduction velocity, strength–duration relationships, and action potential waveforms. Thousands of simulations were then conducted across a wide range of fiber diameters and drug concentrations to systematically map conduction outcomes. Results revealed a concentration-dependent, differential susceptibility of Aδ fibers to conduction block compared with Aβ fibers, delineating a therapeutic window in which nociceptive transmission could be selectively suppressed while preserving tactile sensation. This mechanistic insight provides a quantitative rationale for optimizing lidocaine dosing strategies in trigeminal neuralgia and highlights the potential of computational “virtual laboratories” to accelerate preclinical evaluation of analgesic compounds. The framework is inherently extensible, enabling future incorporation of patient-specific anatomy, additional fiber classes, and alternative pharmacological agents. These findings demonstrate the utility of biophysical modeling as a predictive platform for precision pain therapeutics. Keywords: Trigeminal neuralgia; Lidocaine; Computational modeling; Sodium channels; Conduction block