Genomic medicine on the frontier of precision medicine

Another large prospective cohort study is underway in Europe to characterize the human exposomes in working life.71 The Exposome Project for Health and Occupational Research aims to develop detection and analytical platforms with high-throughput technologies to enable future research in this domain. The emerging field of exposomes holds excellent promise but currently lags behind other omics technologies.61 Hu et al. recently proposed a novel workflow to analyze and quantify human exposomes using an untargeted approach using gas chromatography high-resolution mass spectrometry.62 Exposomes are an aggregate of environmental, dietary, behavioral, and microbial exposures in a person’s life combined with the biological responses to such exposures.60 The systematic study of exposomes can be considered an extension of metabolomics, including chemicals in the environment and diet and those produced in the body as a response to sleep, regular exercise, or a lack thereof. Developing pediatric cohorts and expanding the recruitment of the pediatric population into the existing cohorts will be crucial in understanding the genetic epidemiology of diseases in children, including infants and newborns. The other omics technologies, including transcriptomics, proteomics, epigenomics, metabolomics, and microbiomics, have emerged, enhancing the knowledge necessary for maximizing the applicability of genomics data for better health outcomes.
Genomic research is unlocking unprecedented insights into the human genome, transforming the landscape of healthcare. This will facilitate earlier diagnosis, personalised treatment plans, and better management of chronic conditions. Addressing disparities in access to genetic testing and personalised treatments is crucial to ensure equitable healthcare outcomes. For instance, genetic testing for BRCA mutations informs decisions on preventive measures, such as prophylactic surgery, for breast and ovarian cancer.
A road map to AI-based integrative multiomics approach for precision medicine in pediatric healthcare and research. Through faster and cost-effective genomics data, next-generation sequencing provided the impetus to understand the nuances of complex interactions between genes, diet, and lifestyle that are heterogeneous across the population. It is common sense that no two individuals are the same, and so they should not get the same healthcare. Precision medicine or precision healthcare is medical care that takes advantage of large data sets of individuals such as their genome or their entire electronic health record to tailor their healthcare to their unique attributes. The goal of precision medicine is to provide more a precise approach for the prevention, diagnosis and treatment of disease.
Further research is needed to fully understand these genetic impacts and to optimize individual treatment plans. Pharmacogenomics leverages genomic biomarkers to predict individual responses to drug efficacy and toxicity. It is going to be the therapy of choice for rare genetic diseases in the next 15–20 years.
Denosumab targeted against nuclear factor κ-B ligand RANK-L, inhibits osteoclastic activation and prevents further growth in giant cell bone tumor. In advanced melanoma, Ipilimumab, a monoclonal antibody directed against cytotoxic T-lymphocyte antigen (CTLA-4) has improved survival. Osmertinib targeted against EGFR-mutated non-small cell lung cancer has drastically improved disease-free survival.
Partnering with populations historically absent from biomedical research to improve diversity and equity of epidemiological knowledge (Northwest-Alaska Pharmacogenetics Research Network) This timeline maps key developments in EMR, indicated in red, alongside seminal advances in genomics, marked in blue, and post-genomic fields, highlighted in yellow. Looking toward post-genomic clinical translation in modern healthcare, a parallel commitment to reducing disparities that hinder equal access is essential. Genetic testing not only informs the current risk of a specific disease, but also reveals health predispositions, ancestral histories, and intricate biological information that could resonate across a lifetime and even influence future generations91,92,93. As EMR and -omics data converge, a complex ethical landscape emerges.
The unauthorized embryo editing for Human Immunodeficiency Virus (HIV) resistance in China prompted global ethical debates, leading to the international governance frameworks from the World Health Organization (WHO) and the Nuffield Council on Bioethics . Ongoing debates focus on balancing expanded reproductive choice with ethical concerns about screening scope, incidental findings, and equity of access. Integrated multiomic approaches combining single cell RNA-seq and epigenomics further elucidate resistance, transcriptional heterogeneity, and lineage plasticity underlying immune evasion [51, 114]. Sequencing of cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA) enables noninvasive profiling and real-time monitoring of resistance mutations, minimal residual disease, and treatment response [40, 73].
To truly harness the power of these longitudinal models, a significant shift in patient care strategy is required. Integrative longitudinal multi-omic analyses are also not without their complexities. Solid red lines represent health trajectories with -omics monitoring, showing improved outcomes due to timely interventions, while dashed red lines reflect trajectories without -omics monitoring, highlighting delayed interventions. These steps culminate in biomarker discovery, ultimately enabling clinical translation. Starting with patient enrollment, the cycle progresses through clinical visits, biosample collection, electronic medical record (EMR) integration, and -omics data generation. This circular flow diagram represents the sequential stages of post-genomic research leading to clinical translation.
The integration of nanotechnology, AI, and real-time multiomic analytics with wearable and implantable biosensors will revolutionize disease prediction, monitoring, and prevention. Roche’s Axelios sequencer with Sequencing by Expansion (SBX) technology, 3D DNA sequencing, and Element Biosciences’ AVITI24 promise faster, more affordable, and context-aware sequencing. Collectively, these advances mark genomics’ transition from a descriptive to a predictive and integrative science, driving the next era of precision medicine.
Together, these modalities support longitudinal, minimally invasive tumor surveillance that can detect relapse or progression earlier than conventional imaging. Early detection of EGFR T790M mutations in plasma before radiographic progression exemplifies its clinical value . Together, the evolution from bulk to single cell and spatial omics marks a decisive transition from describing averaged molecular states to resolving cellular heterogeneity and microenvironmental context in situ. Looking ahead, spatial multiomic platforms under commercial development (expected on AVITI24 in 2026) aim to integrate transcriptomic, proteomic, phospho-signaling, and morphological data in a single workflow, advancing comprehensive tissue-level profiling. In oncology, spatial transcriptomics and imaging-based platforms have defined immune exclusion, stromal niches, and tertiary lymphoid structures, informing immunotherapy response and resistance mechanisms . While single cell analysis specifies which cells are present and what they express, it lacks information about where cells reside within tissues.
Targeted therapies and immunotherapies in oncology like monoclonal antibody against HER 2 which is overexpressed in HER2 positive breast cancer has revolutionized treatment. Cancer genomic profiling has shown to detect gene amplification, gene deletion mutation, gene fusion of the target genes. Intra-coronary delivery of Ad vector encoding beta2 AR percutaneously, in rabbits, has shown to improve global ventricular systolic and contractility performance.
Therefore, it is the synthesis of EMR, genomics, and post-genomic data that will ultimately provide comprehensive patient profiles to enable precision medicine. By providing more nuanced measurements of the individualized impact of environmental and lifestyle factors, post-genomic technologies offer an opportunity to complement current EMR and genomic data to fill this void. Such integration will help to establish EMR-based precision medicine as an effective tool for health practitioners’ decision-making in everyday clinical practice. We discuss the specific challenges of integrating post-genomic data with EMRs, with particular focus on the critical need to map periodic -omic profiling with asynchronous EMRs12. Technological advancements are enabling large-scale and frequent measurement of a diverse set of personalized molecular processes that may have their origin in DNA yet go far beyond this. The dawn of the 21st century heralded the promise of precision medicine equipped to radically transform patient healthcare through human genetics.
The cancer, or somatic, genome can predict therapeutic response through an understanding of the molecular implications of certain mutations. This approach holds the promise of transforming clinical care by enabling more accurate diagnoses, targeted treatments, and proactive disease prevention. As these systems become more sophisticated, understanding how they arrive at specific recommendations becomes important, but complex. Multi-modal AI systems can analyze tumor genomics alongside histopathological images, treatment history, and biomarkers to predict which patients will respond to specific immunotherapies (11, 12). Health policies at all levels including clinic, industry, health system, state, and federal will need to adapt to rapidly growing precision-based approaches in order to support the goals of precision public health. Risk-stratified screening approaches that incorporate genetic risk to improve cost-effectiveness, reduce over diagnosis and maintain the benefits of screening for those at highest risk of breast cancer.
G.D.F. received support from grant 1U24CA from the NCI. A.A.B. has been receiving support from grant R35ES from the National Institutes of Health (NIH)/National Institute of Environmental Health Sciences (NIEHS). This is a preview of subscription content, access via your institution Genomic medicine on the frontier of precision medicine. Discover the latest articles, books and news in related subjects, suggested using machine learning. This is a preview of subscription content, log in via an institution to check access.
An overview of whole genome sequencing (WGS), whole exome sequencing (WES) and static gene panel techniques. AI in genomics and precision medicine research has the capacity to revolutionise the healthcare of an individual with a rare disease or cancer by offering prompt and accurate diagnosis, risk stratification based upon genotype and the capacity for personalised treatments. While genomics remains central to our mission, the scope of precision medicine has expanded to include a broader range of tools and data sources that enhance our ability to anticipate, diagnose, and manage disease across the lifespan. Behind every published article stand expert reviewers safeguarding science.