EC Pharmacology and Toxicology

Background: Clinical drug development suffers from high attrition rates, often due to limited translational predictability and the inability of classical computational pipelines to capture electronic-scale phenomena relevant to drug-target recognition, reactivity, and resistance [1,35].

Objective: This perspective formally establishes Quantum Pharmacology (QP) as a foundational discipline integrating quantum-level modeling, artificial intelligence, and pharmacometrics to mechanistically link electronic-scale drug properties with clinical outcomes. In parallel, Smart Protein Therapeutics (SPT) is introduced as a distinct therapeutic paradigm based on programmable and functionally adaptive protein entities. Their integration defines Quantum Smart Protein Therapeutics (QSPT) as an applied framework for quantum-informed precision therapeutics [2-4,36].

Methods: We propose a Quantum Pharmacological Optimization Workflow encompassing: (i) molecular pre-processing and protonation control [18]; (ii) hierarchical quantum calculations (semi-empirical → DFT → correlated methods) including solvent and frequency corrections [4-7]; (iii) quantum-informed docking, molecular dynamics (MD), and free-energy estimation [15-17]; (iv) quantum-aware ADME/Tox prediction [6,27]; and (v) integration into PK/PD and PopPK models with AI-guided refinement [35-40].

Applications: Case studies-gentamicin optimization against resistant K. pneumoniae [37-40], stabilization of oral insulin/GLP-1 analogues [24-26], vancomycin binding to resistant ligase targets [27-29], and cisplatin selectivity in tumor vs renal tissue [30-33]-illustrate QP’s capacity to enhance binding, reduce toxicity, and improve translational predictability.

Impact and Roadmap: We outline a five-stage translational pathway (conceptual → preclinical → pharmacometric integration → clinical translation → implementation) and highlight the role of quantum optimization in reducing misfolding, improving molecular selectivity, and aligning with regulatory model-informed drug development (MIDD) [36,38-40].

 Keywords: Quantum Pharmacology; Quantum-Informed PK/PD; Smart Protein Therapeutics; Quantum Drug Design; Precision Medicine

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