Abdelhalim Habiba, Berber Asude, Lodi Mudassir, Jain Rihi, Nair Achuth, Pappu Anirudh, Patel Kush, Venkat Vignesh, Venkatesan Cynthia, Wable Raghu, Dinatale Matthew, Fu Allyson, Iyer Vikram, Kalove Ishan, Kleyman Marc, Koutsoutis Joseph, Menna David, Paliwal Mayank, Patel Nishi, Patel Thirth, Rafique Zara, Samadi Rothela, Varadhan Roshan, Bolla Shreyas, Vadapalli Sreya, Ahmed Zeeshan
Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States.
Department of Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers Biomedical and Health Sciences, New Brunswick, NJ, United States.
Front Genet. 2022 Jul 6;13:929736. doi: 10.3389/fgene.2022.929736. eCollection 2022.
Precision medicine has greatly aided in improving health outcomes using earlier diagnosis and better prognosis for chronic diseases. It makes use of clinical data associated with the patient as well as their multi-omics/genomic data to reach a conclusion regarding how a physician should proceed with a specific treatment. Compared to the symptom-driven approach in medicine, precision medicine considers the critical fact that all patients do not react to the same treatment or medication in the same way. When considering the intersection of traditionally distinct arenas of medicine, that is, artificial intelligence, healthcare, clinical genomics, and pharmacogenomics-what ties them together is their impact on the development of precision medicine as a field and how they each contribute to patient-specific, rather than symptom-specific patient outcomes. This study discusses the impact and integration of these different fields in the scope of precision medicine and how they can be used in preventing and predicting acute or chronic diseases. Additionally, this study also discusses the advantages as well as the current challenges associated with artificial intelligence, healthcare, clinical genomics, and pharmacogenomics.
精准医学通过对慢性病进行早期诊断和改善预后，极大地有助于提高健康水平。它利用与患者相关的临床数据以及他们的多组学/基因组数据，以得出医生应如何进行特定治疗的结论。与医学中基于症状的方法相比，精准医学考虑到一个关键事实，即所有患者对相同治疗或药物的反应并不相同。当考虑传统上不同的医学领域（即人工智能、医疗保健、临床基因组学和药物基因组学）的交叉点时，将它们联系在一起的是它们对精准医学这一领域发展的影响，以及它们各自如何为针对患者个体而非症状的治疗结果做出贡献。本研究讨论了这些不同领域在精准医学范围内的影响和整合，以及它们如何用于预防和预测急性或慢性疾病。此外，本研究还讨论了与人工智能、医疗保健、临床基因组学和药物基因组学相关的优势以及当前面临的挑战。
