Treatment of Brain Cancer (Glioblastoma) Using the ψ–Hamzah Model.

All Articles are Available: Orcid ID: https://orcid.org/my-orcid?orcid=0009-0009-3175-8563 Science Open ID: https://www.scienceopen.com/user/2c98a8bc-b8bb-49b3-9c91-2f2986a7e16e Safe Creative register the work titled "The Theory of Intelligent Evolution, the Hamzah Equation, and the Quantum Civilisation". Safe Creative registration #2504151474836. ............................................................................................................................................................... Introduction Glioblastoma multiforme (GBM) is the most aggressive and lethal form of primary brain tumor, characterized by rapid proliferation, high invasiveness, and resistance to conventional therapies. Despite advances in neurosurgery, chemotherapy, and radiotherapy, the prognosis for patients remains dismal, with median survival typically ranging between 12 to 18 months. The challenges lie in the tumor’s heterogeneous cell populations, genetic instability, and ability to evade both immune surveillance and drug penetration across the blood–brain barrier (BBB) . Classical treatment strategies such as Temozolomide chemotherapy and ionizing radiation offer only temporary relief, as tumors frequently develop drug resistance and recur with greater aggressiveness. Moreover, the side effects associated with systemic chemotherapy and radiation—ranging from severe fatigue and nausea to irreversible damage of surrounding healthy neural tissue—further complicate patient outcomes . The ψ–Hamzah model introduces a transformative framework for addressing glioblastoma by combining fractional calculus, fractal geometry, and complex integral dynamics to more accurately simulate tumor growth, immune interactions, and therapeutic response. Unlike linear models, this approach integrates memory-dependent behavior of tumor cells, fractal diffusion of drugs within irregular tumor microenvironments, and dynamic oscillations of immune responses, enabling a higher-resolution representation of glioblastoma pathology . Through this model, novel therapeutic pathways emerge: Nanoparticle-based vaccine formulations, engineered to penetrate deep tumor sites and present glioblastoma-specific antigens with high precision. Targeted nanodrug systems, encapsulating tumor-suppressing antibodies and growth inhibitors to bypass the BBB and deliver sustained therapeutic activity. Mathematical optimization of dosing regimens, minimizing toxicity while maximizing tumor suppression efficiency. Early simulations suggest that the ψ–Hamzah framework can reduce tumor relapse, overcome classical drug resistance, and significantly extend survival outcomes compared to traditional models. This positions ψ–Hamzah not merely as a computational curiosity but as a new paradigm in quantum–biological oncology with profound implications for glioblastoma and other resistant cancers .