A Conceptual Framework for Real-Time Quantum Emulation on Classical Hardware: Towards Precision Oncology through Accurate Molecular Simulations

Quantum simulations are pivotal for modeling complex molecular interactions in cancer drug discovery, yet hardware limitations hinder real-time applications. This manuscript presents a conceptual and theoretical framework for a classical computer with quantum emulation capabilities, achieving high fidelity approaching chemical accuracy in real-time particle and quantum behavior reporting. All data, simulations, and codes are contained within this manuscript.The framework integrates advanced tensor network states (TNS) and hybrid quantum-classical algorithms, supported by rigorous mathematical derivations, QuTiP-based simulations, sensitivity analyses, Bayesian inference for uncertainty quantification, and Python implementations. Applications focus on KRAS G12C-inhibitor design for oncology (PDB ID: 6OIM for sotorasib), using B3LYP/6-31G(d,p) basis set and AMBER ff14SB force field, linking quantum expectation values to binding free energies via QM/MM coupling.Simulations of the KRAS G12C-sotorasib complex (40 qubits, bond dimension $D=16$) replicate quantum dynamics within 1 kcal/mol accuracy, with posterior uncertainty below 0.05 for key parameters. Falsifiability criteria are established via Popperian benchmarks for systems up to $n>40$ qubits.This emulation paradigm bridges classical and quantum computing, enabling transformative advancements in precision medicine for cancer therapy.