A mathematical model with fractional-order dynamics for the combined treatment of metastatic colorectal cancer

Amilo, David; Sadri, Khadijeh; Kaymakamzade, Bilgen; Hincal, Evren

doi:10.1016/j.cnsns.2023.107756

Cited by 15 publications

(2 citation statements)

References 50 publications

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“…These technologies can decipher intricate patterns within genomic and proteomic information, facilitating the identification of subtle correlations and predictive biomarkers. AI-driven algorithms hold the potential to enhance the accuracy of patient stratification, predict treatment responses, and uncover previously unrecognized molecular subtypes of colorectal cancer, thereby guiding clinicians toward more effective therapeutic interventions. , Despite these optimiztic prospects, challenges persist on the path to realizing the full potential of precision medicine in colorectal cancer. One notable hurdle involves the need for robust and standardized methodologies for biomarker discovery and validation.…”

Section: Future Progression and Challengesmentioning

confidence: 99%

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Kiran,

Yashaswini,

Maheshwari

et al. 2024

ACS Pharmacol. Transl. Sci.

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Precision medicine is transforming colorectal cancer treatment through the integration of advanced technologies and biomarkers, enhancing personalized and effective disease management. Identification of key driver mutations and molecular profiling have deepened our comprehension of the genetic alterations in colorectal cancer, facilitating targeted therapy and immunotherapy selection. Biomarkers such as microsatellite instability (MSI) and DNA mismatch repair deficiency (dMMR) guide treatment decisions, opening avenues for immunotherapy. Emerging technologies such as liquid biopsies, artificial intelligence, and machine learning promise to revolutionize early detection, monitoring, and treatment selection in precision medicine. Despite these advancements, ethical and regulatory challenges, including equitable access and data privacy, emphasize the importance of responsible implementation. The dynamic nature of colorectal cancer, with its tumor heterogeneity and clonal evolution, underscores the necessity for adaptive and personalized treatment strategies. The future of precision medicine in colorectal cancer lies in its potential to enhance patient care, clinical outcomes, and our understanding of this intricate disease, marked by ongoing evolution in the field. The current reviews focus on providing in-depth knowledge on the various and diverse approaches utilized for precision medicine against colorectal cancer, at both molecular and biochemical levels.

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Section: Future Progression and Challengesmentioning

confidence: 99%

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Kiran,

Yashaswini,

Maheshwari

et al. 2024

ACS Pharmacol. Transl. Sci.

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“…This is more sensible, which is one fact that FC is becoming more common. The theory of fractional derivatives was found to be more appropriate for modeling real-world problems than ordinary ones (Rossikhin and Shitikova, 2012;Łabedzki and Pawlikowski, 2023;Amilo et al, 2024).…”

Section: Introductionmentioning

confidence: 99%

Approximation of Two-Dimensional Time-Fractional Navier-Stokes Equations involving Atangana-Baleanu Derivative

Singh,

Tamsir,

El Saman

et al. 2024

Int. j. math. eng. manag. sci.

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This article addresses the two analytical methods, i.e., the new iterative transform method (NITM) and the homotopy perturbation transform method (HPTM), along with an Aboodh transform (AT), to approximate the nonlinear system of two-dimensional (2D) time-fractional Navier-Stokes (TFNS) equations. We take the time-fractional derivative in the form of Atangana-Baleanu (AB). The article's suggested examples examine the accuracy and efficacy of the proposed methods, while the graphs demonstrate their potential and effectiveness. The article also provides demonstrations of uniqueness and convergence. The aforementioned techniques are straightforward and support a high rate of convergence, which helps in understanding the dynamics of fractional nonlinear systems.

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An optimal solution for tumor growth model using generalized Bessel polynomials

Saeidi,

Dahaghin,

Mehrabi

et al. 2024

Math Methods in App Sciences

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In this paper, a mathematical model is given that depicts the interactions between cancer cells and viruses in the setting of oncolytic virotherapy. The model is separated into three classes, namely, concentrations of uninfected tumor cells in the population “ ”, free virus “ ”, and cancerous cells infected “ ”. Applying Caputo fractional derivative, the model is fractionalized, and using generalized Bessel polynomials, an optimal problem is solved utilizing Lagrange multipliers method. The results show that the presented method has high accuracy and is suitable for solving the nonlinear systems based on partial differential equations especially tumors models.

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A mathematical model with fractional-order dynamics for the combined treatment of metastatic colorectal cancer

Cited by 15 publications

References 50 publications

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Approximation of Two-Dimensional Time-Fractional Navier-Stokes Equations involving Atangana-Baleanu Derivative

An optimal solution for tumor growth model using generalized Bessel polynomials

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