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Research papers on Personalized medicine and genomics

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  3. Precision Medicine, AI, and the Future of Personalized Health Care

    Kevin B. Johnson, Wei‐Qi Wei, Dilhan Weeraratne, et al. · 2020 · Clinical and Translational Science · 1,753 citations

    The convergence of artificial intelligence (AI) and precision medicine promises to revolutionize health care. Precision medicine methods identify phenotypes of patients with less-common responses to treatment or unique healthcare needs. AI leverages sophisticated computation and inference to generate insights, enables the system to reason and learn, and empowers clinician decision making through augmented intelligence. Recent literature suggests that translational research exploring this convergence will help solve the most difficult challenges facing precision medicine, especially those in which nongenomic and genomic determinants, combined with information from patient symptoms, clinical h

  6. Personalized <i>In Vitro</i> and <i>In Vivo</i> Cancer Models to Guide Precision Medicine

    Chantal Pauli, Benjamin D. Hopkins, Davide Prandi, et al. · 2017 · Cancer Discovery · 958 citations

    Abstract Precision medicine is an approach that takes into account the influence of individuals' genes, environment, and lifestyle exposures to tailor interventions. Here, we describe the development of a robust precision cancer care platform that integrates whole-exome sequencing with a living biobank that enables high-throughput drug screens on patient-derived tumor organoids. To date, 56 tumor-derived organoid cultures and 19 patient-derived xenograft (PDX) models have been established from the 769 patients enrolled in an Institutional Review Board–approved clinical trial. Because genomics alone was insufficient to identify therapeutic options for the majority of patients with advanced di

  9. Precision and Personalized Medicine: How Genomic Approach Improves the Management of Cardiovascular and Neurodegenerative Disease

    Oriana Strianese, Francesca Rizzo, Michele Ciccarelli, et al. · 2020 · Genes · 235 citations

    Life expectancy has gradually grown over the last century. This has deeply affected healthcare costs, since the growth of an aging population is correlated to the increasing burden of chronic diseases. This represents the interesting challenge of how to manage patients with chronic diseases in order to improve health care budgets. Effective primary prevention could represent a promising route. To this end, precision, together with personalized medicine, are useful instruments in order to investigate pathological processes before the appearance of clinical symptoms and to guide physicians to choose a targeted therapy to manage the patient. Cardiovascular and neurodegenerative diseases represe

  10. From “Personalized” to “Precision” Medicine: The Ethical and Social Implications of Rhetorical Reform in Genomic Medicine

    Eric T. Juengst, Michelle L. McGowan, Jennifer R. Fishman, et al. · 2016 · The Hastings Center Report · 211 citations

    Since the late 1980s, the human genetics and genomics research community has been promising to usher in a "new paradigm for health care"-one that uses molecular profiling to identify human genetic variants implicated in multifactorial health risks. After the completion of the Human Genome Project in 2003, a wide range of stakeholders became committed to this "paradigm shift," creating a confluence of investment, advocacy, and enthusiasm that bears all the marks of a "scientific/intellectual social movement" within biomedicine. Proponents of this movement usually offer four ways in which their approach to medical diagnosis and health care improves upon current practices, arguing that it is mo

  11. The Penn Medicine BioBank: Towards a Genomics-Enabled Learning Healthcare System to Accelerate Precision Medicine in a Diverse Population

    A. Verma, S. Damrauer, Nawar Naseer, et al. · 2022 · Journal of Personalized Medicine · 124 citations

    The Penn Medicine BioBank (PMBB) is an electronic health record (EHR)-linked biobank at the University of Pennsylvania (Penn Medicine). A large variety of health-related information, ranging from diagnosis codes to laboratory measurements, imaging data and lifestyle information, is integrated with genomic and biomarker data in the PMBB to facilitate discoveries and translational science. To date, 174,712 participants have been enrolled into the PMBB, including approximately 30% of participants of non-European ancestry, making it one of the most diverse medical biobanks. There is a median of seven years of longitudinal data in the EHR available on participants, who also consent to permission

  12. Genomic Medicine, Precision Medicine, Personalized Medicine: What’s in a Name?

    D M Roden, Rachel F. Tyndale · 2013 · Clinical Pharmacology & Therapeutics · 74 citations

    This issue of Clinical Pharmacology & Therapeutics is devoted to genomic medicine, and a reader may reasonably ask what we mean when we use those words. In the initial issue of the journal Genomics in 1987, McKusick and Ruddle pointed out that the descriptor "genome" had been coined in 1920 as a hybrid of "gene" and "chromosome," and that their new journal would focus on the "newly-developing discipline of mapping/sequencing (including analysis of the information)." A key milestone in the field was the generation of the first draft of a human genome in 2000, but this success really represents only one of many milestones in the journey from Mendel to MiSeq.

  15. Unsupervised Learning in Precision Medicine: Unlocking Personalized Healthcare through AI

    A. Trezza, Anna Visibelli, B. Roncaglia, et al. · 2024 · Applied Sciences · 35 citations

    Integrating Artificial Intelligence (AI) into Precision Medicine (PM) is redefining healthcare, enabling personalized treatments tailored to individual patients based on their genetic code, environment, and lifestyle. AI’s ability to analyze vast and complex datasets, including genomics and medical records, facilitates the identification of hidden patterns and correlations, which are critical for developing personalized treatment plans. Unsupervised Learning (UL) is particularly valuable in PM as it can analyze unstructured and unlabeled data to uncover novel disease subtypes, biomarkers, and patient stratifications. By revealing patterns that are not explicitly labeled, unsupervised algorit

  16. Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors

    Shiyue Zeng, Qi Qing, Wei Xu, et al. · 2024 · Frontiers in Medicine · 33 citations

    Precision medicine, characterized by the personalized integration of a patient’s genetic blueprint and clinical history, represents a dynamic paradigm in healthcare evolution. The emerging field of personalized anesthesia is at the intersection of genetics and anesthesiology, where anesthetic care will be tailored to an individual’s genetic make-up, comorbidities and patient-specific factors. Genomics and biomarkers can provide more accurate anesthetic protocols, while artificial intelligence can simplify anesthetic procedures and reduce anesthetic risks, and real-time monitoring tools can improve perioperative safety and efficacy. The aim of this paper is to present and summarize the applic

  17. PRECISION MEDICINE AND GENOMICS: A COMPREHENSIVE REVIEW OF IT-ENABLED APPROACHES

    Francisca Chibugo Udegbe, Ogochukwu Roseline Ebulue, Charles Chukwudalu Ebulue, et al. · 2024 · International Medical Science Research Journal · 29 citations

     This review delves into Information Technology's (IT) transformative impact on precision medicine and genomics, spotlighting the pivotal role of bioinformatics, data mining, machine learning, and blockchain technologies in advancing personalized healthcare. A comprehensive analysis outlines how these IT-enabled approaches facilitate the analysis, interpretation, and application of vast genomic data sets, thereby enhancing disease prediction, diagnosis, and treatment on an individual level. Despite the promising advancements, the review also addresses significant challenges, including data complexity, interoperability, ethical considerations, and the digital divide, underscoring the necessit

  18. Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine

    P. Ahluwalia, Kalyani Ballur, Tiffanie Leeman, et al. · 2024 · Cancers · 20 citations

    Simple Summary Cancer affects millions of individuals every year, with colorectal cancer being among the most common. There is an increased need to identify new biomarkers that can not only diagnose patients early, but also stratify them so the best treatment can be initiated for each patient. Every human has a unique genetic makeup that causes them to respond differently to cancer. In recent years, new technologies have provided unprecedented access to tumor samples from patients. Through these analyses, we can not only diagnose and classify patients based on their comparative risk, but also monitor their response to emerging therapies. Continued progress using these methods will transform

  19. UltraAIGenomics: Artificial Intelligence-Based Cardiovascular Disease Risk Assessment by Fusion of Ultrasound-Based Radiomics and Genomics Features for Preventive, Personalized and Precision Medicine: A Narrative Review

    L. Saba, M. Maindarkar, A. Johri, et al. · 2024 · Reviews in Cardiovascular Medicine · 19 citations

    Cardiovascular disease (CVD) diagnosis and treatment are challenging since symptoms appear late in the disease’s progression. Despite clinical risk scores, cardiac event prediction is inadequate, and many at-risk patients are not adequately categorised by conventional risk factors alone. Integrating genomic-based biomarkers (GBBM), specifically those found in plasma and/or serum samples, along with novel non-invasive radiomic-based biomarkers (RBBM) such as plaque area and plaque burden can improve the overall specificity of CVD risk. This review proposes two hypotheses: (i) RBBM and GBBM biomarkers have a strong correlation and can be used to detect the severity of CVD and stroke precisely,

  20. Large Language Models in Genomics—A Perspective on Personalized Medicine

    Shahid Ali, Yazdan Ahmad Qadri, Khursheed Ahmad, et al. · 2025 · Bioengineering · 19 citations

    Integrating artificial intelligence (AI), particularly large language models (LLMs), into the healthcare industry is revolutionizing the field of medicine. LLMs possess the capability to analyze the scientific literature and genomic data by comprehending and producing human-like text. This enhances the accuracy, precision, and efficiency of extensive genomic analyses through contextualization. LLMs have made significant advancements in their ability to understand complex genetic terminology and accurately predict medical outcomes. These capabilities allow for a more thorough understanding of genetic influences on health issues and the creation of more effective therapies. This review emphasi

  21. Applications of Green Carbon Dots in Personalized Diagnostics for Precision Medicine

    H. Etefa, F. B. Dejene · 2025 · International Journal of Molecular Sciences · 17 citations

    Green carbon dots (GCDs) have emerged as a revolutionary tool in precision medicine, offering transformative capabilities for personalized diagnostics and therapeutic strategies. Their unique optical and biocompatible properties make them ideal for non-invasive imaging, real-time monitoring, and integration with genomics, proteomics, and bioinformatics, enabling accurate diagnosis and tailored treatments based on patients’ genetic and molecular profiles. This study explores the potential of GCDs in advancing individualized patient care by examining their applications in precision medicine. It evaluates their utility in non-invasive diagnostic imaging, targeted therapy delivery, and the formu

  22. From Genomics to AI: Revolutionizing Precision Medicine in Oncology

    Giulia Calvino, Juliette Farro, S. Zampatti, et al. · 2025 · Applied Sciences · 14 citations

    The increasing burden of cancer globally necessitates innovative approaches for diagnosis, prognosis, and treatment. This article explores the transformative impact of genomics and artificial intelligence (AI) in precision oncology, addressing how their convergence is reshaping cancer care and its challenges. Methods: This review synthesizes current research on the applications of genomics, including next-generation sequencing, and AI, such as machine learning and deep learning, across the cancer care continuum. It examines their roles in identifying genetic variants, assessing cancer risk, guiding targeted therapies and immunotherapy, predicting treatment response, and enabling early detect

  23. Multi-Omics Integration in Personalized Medicine: Advancing Laboratory Diagnostics and Precision Therapeutics in the Era of Individualized Healthcare

    T. Ikwelle, Augustine Chinedu Ihim, D. Ozuruoke, et al. · 2025 · Journal of Drug Delivery and Therapeutics · 12 citations

    Personalized medicine is revolutionizing healthcare by shifting from a one-size-fits-all model to a tailored approach that considers individual genetic, molecular, environmental, and lifestyle factors. This review comprehensively explores the role of personalized medicine in laboratory diagnostics and patient management through the lens of emerging omics technologies such as genomics, transcriptomics, proteomics, metabolomics, and pharmacogenomics. Each omics domain offers unique insights into disease mechanisms, drug response, and biomarker discovery, enabling more accurate diagnoses, targeted therapies, and improved treatment outcomes. While genomics and pharmacogenomics focus on the genet

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