Innovation of Obstinate and Ferocious Pharmacochemical Molecules for Selective Targeting and Eradication of Cancer Cells: A Conceptual, Normative, and Computationally Validated Framework with Rigorous Mathematical Modeling, Sensitivity Analysis, Bayesian Inference, and Translational Roadmap

Current targeted cancer therapies, including antibody-drug conjugates (ADCs) and proteolysis-targeting chimeras (PROTACs), achieve meaningful but limited clinical responses due to off-target toxicity, rapid resistance via efflux pumps, and incomplete tumor eradication. Here we introduce a novel class of obstinate and ferocious pharmacochemical molecules (OFPAs) — multi-modal, small-molecule chimeras engineered for unprecedented selectivity, catalytic potency, and resistance evasion. OFPAs integrate (i) cancer-specific targeting ligands, (ii) a catalytic ROS-generating domain for fierce apoptotic amplification, (iii) an efflux-pump inhibitory moiety conferring obstinacy against multidrug resistance, and (iv) a PROTAC-like ubiquitin-recruiting warhead for oncoprotein degradation.We deepen the modeling of heterogeneous cancer-cell dynamics through a multi-scale framework that explicitly incorporates (i) macroscopic extended Gompertz tumor growth, (ii) mesoscopic subpopulation heterogeneity with three clones (sensitive, efflux-resistant, hypoxia-driven resistant), explicit per-cell ABC-transporter (P-gp) dynamics with mass-action turnover, stochastic mutational transitions via Poisson-process approximation, and (iii) microscopic intracellular ROS/apoptosis cascades coupled to hypoxia-dependent fitness. Furthermore, we extend the OFPA paradigm to chronic viral diseases (HIV latent reservoirs and HBV cccDNA) by adapting the modular architecture and deriving disease-specific PK/PD models, demonstrating conceptual versatility with projected superior efficacy.Using extended Gompertzian tumor-growth dynamics coupled with compartmental pharmacokinetics/pharmacodynamics (PK/PD) including full target-mediated drug disposition (TMDD), Latin-hypercube Monte Carlo sensitivity analysis (n=1000), variance-based Sobol indices, and Bayesian uncertainty quantification, we demonstrate that OFPAs achieve 79% superior tumor-volume reduction and near-complete eradication within 60 days compared with conventional targeted agents in simulated heterogeneous tumors. All code, derivations, parameter tables (with exact literature sources and units), and data are self-contained within this conceptual manuscript, rendering the framework fully reproducible and falsifiable.This work provides the first rigorous, non-precedented theoretical blueprint for next-generation pharmacochemical oncology (and beyond), with a detailed translational roadmap, ethical declarations, and explicit pathways for empirical refutation.