Personalized and Precision Medicine Journal

Abstract Background and Objective: Gene therapy can be employed to treat several disorders, including cancer. Globally, women are more frequently diagnosed with breast cancer than any other cancer type, underscoring the necessity for innovative strategies. Algorithms driven by artificial intelligence can enhance the gene therapy process for breast cancer by analyzing vast data sets, identifying intricate patterns, and classifying those patterns. This project aims to perform a literature evaluation focusing on the therapeutic uses of artificial intelligence in gene therapy for breast cancer.

Materials and Methods: For the aim of this study, data was gathered by reading previously published articles and searching the PubMed database for phrases that were relevant to the question being investigated.
Findings: The AI-driven algorithm analyzes complex molecular pathways in the human body, replicates the knowledge of scientists and physicians in clinical research, and simulates biological processes related to gene regulation, thereby improving the effectiveness of gene vectors, managing gene and drug delivery parameters, and modeling cellular behavior. This method diminishes medical errors and promotes early disease identification and drug efficacy forecasting, thereby providing patients with optimal results from advanced treatments like gene therapy with minimal side effects.
Conclusion: Over the period of the past decade, a multitude of efforts have been made to deploy various gene therapy procedures for breast cancer patients, to achieve the highest possible level of efficacy while minimizing the risk of adverse consequences. As a result, artificial intelligence is considered to be a powerful tool for improving early diagnosis and efficient gene therapy for breast cancer.

Abstract Spinal muscular atrophy (SMA) is a prevalent autosomal recessive disorder characterized by gradual weakening of the skeletal and respiratory muscles, resulting in substantial impairment. The illness is a result of genetic abnormalities in the survival motor neuron 1 (SMN1) gene, which leads to a reduction in the SMN protein and subsequently causes the degeneration of lower motor neurons. Gene therapy is a method that has the potential to cure or prevent uncommon monogenic illnesses by substituting a defective gene with a functional one. Gene therapy is particularly suitable for monogenic illnesses since it has the ability to correct abnormalities in a single gene. Currently, Nusinersen, risdiplam, and onasemnogene abeparvovec are the only officially sanctioned treatments for SMA that have the ability to influence the course of the illness. The purpose of this analysis is to examine and analyze their mechanisms of action, impacts, and potential safety issues. Nusinersen and risdiplam function by altering the SMN2 gene product, whereas onasemnogene abeparvovec operates by introducing copies of the SMN1 gene into cells. In this article, we briefly describe the pathogenesis and treatment strate, gies of SMA.

Abstract Gene therapy, as an experimental therapy, is applied for the treatment of diseases through modification of genes. Gene therapy corrects the mutated genes. Somatic and germline gene therapy are two main types of gene therapy. In germline editing, normal genes are inserted into the human’s eggs or sperm, zygote, or early embryo. Therefore, the gene is transmitted to the next generation, but in somatic gene therapy, a normal gene is inserted into somatic cells and corrects the defective gene without transmission to children. Personalized medicine is a novel therapeutic protocol for the prevention and treatment of diseases that considers individuals’ responding differences to medications.  So, it raises ethical issues. Ethical concerns regarding gene therapy and personalized medicine are as follows: safety, accessibility, cost-efficiency, genetic enhancement, dignity, autonomy, identity, and social discrimination.