Srivastav Amit Kumar, Mishra Manoj Kumar, Lillard James W, Singh Rajesh
Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, 720 Westview Drive SW, Atlanta, GA 30310, USA.
Department of Biological Sciences, Alabama State University, Montgomery, AL 36104, USA.
Pharmaceutics. 2025 Apr 24;17(5):555. doi: 10.3390/pharmaceutics17050555.
: Advancements in pharmacogenomics, artificial intelligence (AI), and CRISPR gene-editing technology are revolutionizing precision medicine by enabling highly individualized therapeutic strategies. Artificial intelligence-driven computational techniques improve biomarker discovery and drug optimization while pharmacogenomics helps to identify genetic polymorphisms affecting medicine metabolism, efficacy, and toxicity. Genetically editing based on CRISPR presents a precise method for changing gene expression and repairing damaging mutations. This review explores the convergence of these three fields to enhance improved precision medicine. : A methodical study of the current literature was performed on the effects of pharmacogenomics on drug response variability, artificial intelligence, and CRISPR in predictive modeling and gene-editing applications. : Driven by artificial intelligence, pharmacogenomics allows clinicians to classify patients and select the appropriate medications depending on their DNA profiles. This reduces the side effect risk and increases the therapeutic efficacy. Precision genetic modifications made feasible by CRISPR technology improve therapy outcomes in oncology, metabolic illnesses, neurological diseases, and other fields. The integration of artificial intelligence streamlines genome-editing applications, lowers off-target effects, and increases CRISPR specificity. Notwithstanding these advances, issues including computational biases, moral dilemmas, and legal constraints still arise. : The synergy of artificial intelligence, pharmacogenomics, and CRISPR alters precision medicine by letting customized therapeutic interventions. Clinically translating, however, hinges on resolving data privacy concerns, assuring equitable access, and strengthening legal systems. Future research should focus on refining CRISPR gene-editing technologies, enhancing AI-driven pharmacogenomics, and developing moral guidelines for applying these tools in individualized medicine going forward.
药物基因组学、人工智能（AI）和CRISPR基因编辑技术的进步正在通过实现高度个性化的治疗策略，彻底改变精准医学。人工智能驱动的计算技术改善了生物标志物的发现和药物优化，而药物基因组学有助于识别影响药物代谢、疗效和毒性的基因多态性。基于CRISPR的基因编辑提供了一种改变基因表达和修复有害突变的精确方法。本综述探讨了这三个领域的融合，以加强精准医学。：对当前文献进行了系统研究，以探讨药物基因组学对药物反应变异性、人工智能以及CRISPR在预测建模和基因编辑应用中的影响。：在人工智能的推动下，药物基因组学使临床医生能够根据患者的DNA图谱对患者进行分类并选择合适的药物。这降低了副作用风险并提高了治疗效果。CRISPR技术实现的精确基因修饰改善了肿瘤学、代谢性疾病、神经疾病和其他领域的治疗效果。人工智能的整合简化了基因组编辑应用，降低了脱靶效应，并提高了CRISPR的特异性。尽管取得了这些进展，但仍存在计算偏差、道德困境和法律限制等问题。：人工智能、药物基因组学和CRISPR的协同作用通过允许定制治疗干预来改变精准医学。然而，临床转化取决于解决数据隐私问题、确保公平获取和加强法律体系。未来的研究应专注于改进CRISPR基因编辑技术、加强人工智能驱动的药物基因组学，并为今后在个性化医学中应用这些工具制定道德准则。
