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

Abstract The ψ–Hamzah model represents an innovative advancement in the treatment and simulation of complex diseases, particularly those that are resistant to conventional treatments such as glioblastoma and immune-related disorders. Combining fractional equations, fractal theory, and complex integrals, this model provides a novel approach to biologically-based simulations and therapeutic processes, incorporating advanced algorithms for optimizing vaccination and drug development. This article presents the model’s comprehensive development, from theoretical foundations to practical applications. It includes detailed Python code for simulating tumor growth, incorporating both classic and ψ–Hamzah approaches, with an emphasis on their comparative efficacy in targeting cancer cells and enhancing immune response. The model’s unique use of fractional derivatives and fractal geometry offers superior precision in predicting tumor dynamics and treatment outcomes. A thorough exploration of the vaccine and drug formulation process follows, addressing chemical composition, nanoparticle structure, and stability considerations. Furthermore, experimental and environmental conditions necessary for the successful synthesis of these therapeutics are provided, including temperature, pressure, catalysts, and bioreactor specifications. Advanced simulations of immune responses and pharmacokinetics are also conducted, allowing for the evaluation of the model’s effectiveness in real biological systems. Through these simulations, the model demonstrates its potential for triggering immune activation and efficiently distributing drugs within the body, including through optimized dosing strategies. Finally, a scientific comparison between the ψ–Hamzah model and classic treatment models is presented. The ψ–Hamzah model's superior precision, broad applicability, and potential to address emerging global health threats like COVID-19 and HIV/AIDS make it a groundbreaking tool in the medical and scientific community. Recommendations for global health organizations, including WHO and FDA, advocate for the model’s integration into modern therapeutic and research practices. In conclusion, this article highlights the immense potential of the ψ–Hamzah model in revolutionizing cancer treatment, immune disorders, and other challenging diseases, providing a comprehensive framework for future research and applications in medical, pharmaceutical, and biotechnological fields.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-18
DOI
https://doi.org/10.5281/zenodo.16070967
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Genomics and Phylogenetic Studies
article

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

article en

Abstract

Abstract The ψ–Hamzah model represents an innovative advancement in the treatment and simulation of complex diseases, particularly those that are resistant to conventional treatments such as glioblastoma and immune-related disorders. Combining fractional equations, fractal theory, and complex integrals, this model provides a novel approach to biologically-based simulations and therapeutic processes, incorporating advanced algorithms for optimizing vaccination and drug development. This article presents the model’s comprehensive development, from theoretical foundations to practical applications. It includes detailed Python code for simulating tumor growth, incorporating both classic and ψ–Hamzah approaches, with an emphasis on their comparative efficacy in targeting cancer cells and enhancing immune response. The model’s unique use of fractional derivatives and fractal geometry offers superior precision in predicting tumor dynamics and treatment outcomes. A thorough exploration of the vaccine and drug formulation process follows, addressing chemical composition, nanoparticle structure, and stability considerations. Furthermore, experimental and environmental conditions necessary for the successful synthesis of these therapeutics are provided, including temperature, pressure, catalysts, and bioreactor specifications. Advanced simulations of immune responses and pharmacokinetics are also conducted, allowing for the evaluation of the model’s effectiveness in real biological systems. Through these simulations, the model demonstrates its potential for triggering immune activation and efficiently distributing drugs within the body, including through optimized dosing strategies. Finally, a scientific comparison between the ψ–Hamzah model and classic treatment models is presented. The ψ–Hamzah model's superior precision, broad applicability, and potential to address emerging global health threats like COVID-19 and HIV/AIDS make it a groundbreaking tool in the medical and scientific community. Recommendations for global health organizations, including WHO and FDA, advocate for the model’s integration into modern therapeutic and research practices. In conclusion, this article highlights the immense potential of the ψ–Hamzah model in revolutionizing cancer treatment, immune disorders, and other challenging diseases, providing a comprehensive framework for future research and applications in medical, pharmaceutical, and biotechnological fields.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Genomics and Phylogenetic Studies
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Treatment of Brain Cancer (Glioblastoma) Using the ψ–Hamzah Model. · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS