Precision medicine is an emergent medical paradigm that uses information technology to inform the use of targeted therapies and treatments. One of the first steps of precision medicine involves acquiring the patient’s informed consent to protect their rights to autonomous medical decision-making. In pediatrics, there exists mixed recommendations and guidelines of consent-related practices designed to safeguard pediatric patient interests while protecting their autonomy. Here, we provide a high-level, clinical primer of (1) ethical informed consent frameworks widely used in clinical practice and (2) promising modern adaptations to improve informed consent practices in pediatric precision medicine. Given the rapid scientific advances and adoption of precision medicine, we highlight the dual need to both consider the clinical implementation of consent in pediatric precision medicine workflows as well as build rapport with pediatric patients and their substitute decision-makers working alongside interdisciplinary health teams.

The personalised oncology paradigm remains challenging to deliver despite technological advances in genomics-based identification of actionable variants combined with the increasing focus of drug development on these specific targets. To ensure we continue to build concerted momentum to improve outcomes across all cancer types, financial, technological and operational barriers need to be addressed. For example, complete integration and certification of the ‘molecular tumour board’ into ‘standard of care’ ensures a unified clinical decision pathway that both counteracts fragmentation and is the cornerstone of evidence-based delivery inside and outside of a research setting. Generally, integrated delivery has been restricted to specific (common) cancer types either within major cancer centres or small regional networks. Here, we focus on solutions in real-world integration of genomics, pathology, surgery, oncological treatments, data from clinical source systems and analysis of whole-body imaging as digital data that can facilitate cost-effectiveness analysis, clinical trial recruitment, and outcome assessment. This urgent imperative for cancer also extends across the early diagnosis and adjuvant treatment interventions, individualised cancer vaccines, immune cell therapies, personalised synthetic lethal therapeutics and cancer screening and prevention. Oncology care systems worldwide require proactive step-changes in solutions that include inter-operative digital working that can solve patient centred challenges to ensure inclusive, quality, sustainable, fair and cost-effective adoption and efficient delivery. Here we highlight workforce, technical, clinical, regulatory and economic challenges that prevent the implementation of precision oncology at scale, and offer a systematic roadmap of integrated solutions for standard of care based on minimal essential digital tools. These include unified decision support tools, quality control, data flows within an ethical and legal data framework, training and certification, monitoring and feedback. Bridging the technical, operational, regulatory and economic gaps demands the joint actions from public and industry stakeholders across national and global boundaries.

Precision medicine for cardiomyopathies holds great promise to improve patient outcomes costs by shifting the focus to patient-specific treatment decisions, maximising the use of therapies most likely to lead to benefit and minimising unnecessary intervention. Dilated cardiomyopathy (DCM), characterised by left ventricular dilatation and impairment, is a major cause of heart failure globally. Advances in genomic medicine have increased our understanding of the genetic architecture of DCM. Understanding the functional implications of genetic variation to reveal genotype-specific disease mechanisms is the subject of intense investigation, with advanced cardiac imaging and mutliomics approaches playing important roles. This may lead to increasing use of novel, targeted therapy. Individualised treatment and risk stratification is however made more complex by the modifying effects of common genetic variation and acquired environmental factors that help explain the variable expressivity of rare genetic variants and gene elusive disease. The next frontier must be expanding work into early disease to understand the mechanisms that drive disease expression, so that the focus can be placed on disease prevention rather than management of later symptomatic disease. Overcoming these challenges holds the key to enabling a paradigm shift in care from the management of symptomatic heart failure to prevention of disease.

Psychotropic medication efficacy and tolerability are critical treatment issues faced by individuals with psychiatric disorders and their healthcare providers. For some people, it can take months to years of a trial-and-error process to identify a medication with the ideal efficacy and tolerability profile. Current strategies (e.g. clinical practice guidelines, treatment algorithms) for addressing this issue can be useful at the population level, but often fall short at the individual level. This is, in part, attributed to interindividual variation in genes that are involved in pharmacokinetic (i.e. absorption, distribution, metabolism, elimination) and pharmacodynamic (e.g. receptors, signaling pathways) processes that in large part, determine whether a medication will be efficacious or tolerable. A precision prescribing strategy know as pharmacogenomics (PGx) assesses these genomic variations, and uses it to inform selection and dosing of certain psychotropic medications. In this review, we describe the path that led to the emergence of PGx in psychiatry, the current evidence base and implementation status of PGx in the psychiatric clinic, and finally, the future growth potential of precision psychiatry via the convergence of the PGx-guided strategy with emerging technologies and approaches (i.e. pharmacoepigenomics, pharmacomicrobiomics, pharmacotranscriptomics, pharmacoproteomics, pharmacometabolomics) to personalize treatment of psychiatric disorders.

This article aims to explore the ethical issues arising from attempts to diversify genomic data and include individuals from underserved groups in studies exploring the relationship between genomics and health. We employed a qualitative synthesis design, combining data from three sources: 1) a rapid review of empirical articles published between 2000 and 2022 with a primary or secondary focus on diversifying genomic data, or the inclusion of underserved groups and ethical issues arising from this, 2) an expert workshop and 3) a narrative review. Using these three sources we found that ethical issues are interconnected across structural factors and research practices. Structural issues include failing to engage with the politics of knowledge production, existing inequities, and their effects on how harms and benefits of genomics are distributed. Issues related to research practices include a lack of reflexivity, exploitative dynamics and the failure to prioritise meaningful co-production. Ethical issues arise from both the structure and the practice of research, which can inhibit researcher and participant opportunities to diversify data in an ethical way. Diverse data are not ethical in and of themselves, and without being attentive to the social, historical and political contexts that shape the lives of potential participants, endeavours to diversify genomic data run the risk of worsening existing inequities. Efforts to construct more representative genomic datasets need to develop ethical approaches that are situated within wider attempts to make the enterprise of genomics more equitable.

Psychiatric disorders are associated with significant social and economic burdens, many of which are related to issues with current diagnosis and treatments. The coronavirus (COVID-19) pandemic is estimated to have increased the prevalence and burden of major depressive and anxiety disorders, indicating an urgent need to strengthen mental health systems globally. To date, current approaches adopted in drug discovery and development for psychiatric disorders have been relatively unsuccessful. Precision psychiatry aims to tailor healthcare more closely to the needs of individual patients and, when informed by neuroscience, can offer the opportunity to improve the accuracy of disease classification, treatment decisions, and prevention efforts. In this review, we highlight the growing global interest in precision psychiatry and the potential for the National Institute of Health-devised Research Domain Criteria (RDoC) to facilitate the implementation of transdiagnostic and improved treatment approaches. The need for current psychiatric nosology to evolve with recent scientific advancements and increase awareness in emerging investigators/clinicians of the value of this approach is essential. Finally, we examine current challenges and future opportunities of adopting the RDoC-associated translational and transdiagnostic approaches in clinical studies, acknowledging that the strength of RDoC is that they form a dynamic framework of guiding principles that is intended to evolve continuously with scientific developments into the future. A collaborative approach that recruits expertise from multiple disciplines, while also considering the patient perspective, is needed to pave the way for precision psychiatry that can improve the prognosis and quality of life of psychiatric patients.

UK Biobank is an intensively characterised prospective cohort of 500,000 adults aged 40–69 years when recruited between 2006 and 2010. The study was established to enable researchers worldwide to undertake health-related research in the public interest. The existence of such a large, detailed prospective cohort with a high degree of participant engagement enabled its rapid repurposing for coronavirus disease-2019 (COVID-19) research. In response to the pandemic, the frequency of updates on hospitalisations and deaths among participants was immediately increased, and new data linkages were established to national severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and primary care health records to facilitate research into the determinants of severe COVID-19. UK Biobank also instigated several sub-studies on COVID-19. In 2020, monthly blood samples were collected from approximately 20,000 individuals to investigate the distribution and determinants of SARS-CoV-2 infection, and to assess the persistence of antibodies following infection with another blood sample collected after 12 months. UK Biobank also performed repeat imaging of approximately 2,000 participants (half of whom had evidence of previous SARS-CoV-2 infection and half did not) to investigate the impact of the virus on changes in measures of internal organ structure and function. In addition, approximately 200,000 UK Biobank participants took part in a self-test SARS-CoV-2 antibody sub-study (between February and November 2021) to collect objective data on previous SARS-CoV-2 infection. These studies are enabling unique research into the genetic, lifestyle and environmental determinants of SARS-CoV-2 infection and severe COVID-19, as well as their long-term health effects. UK Biobank’s contribution to the national and international response to the pandemic represents a case study for its broader value, now and in the future, to precision medicine research.

Observational studies are notoriously susceptible to bias, and parallel-group randomized trials are important to identify the best overall treatment for eligible patients. Yet, such trials can be expected to be a misleading indicator of the best treatment for some subgroups or individual patients. In selected circumstances, patients can be treated in n-of-1 trials to address the inherent heterogeneity of treatment response in clinical populations. Such trials help to accomplish the ultimate goal of all biomedical research, to optimize the care of individual patients.

Humans operating in extreme environments often conduct their operations at the edges of the limits of human performance. Sometimes, they are required to push these limits to previously unattained levels. As a result, their margins for error in execution are much smaller than that found in the general public. These same small margins for error that impact execution may also impact risk, safety, health, and even survival. Thus, humans operating in extreme environments have a need for greater refinement in their preparation, training, fitness, and medical care. Precision medicine (PM) is uniquely suited to address the needs of those engaged in these extreme operations because of its depth of molecular analysis, derived precision countermeasures, and ability to match each individual (and his or her specific molecular phenotype) with any given operating context (environment). Herein, we present an overview of a systems approach to PM in extreme environments, which affords clinicians one method to contextualize the inputs, processes, and outputs that can form the basis of a formal practice. For the sake of brevity, this overview is focused on molecular dynamics, while providing only a brief introduction to the also important physiologic and behavioral phenotypes in PM. Moreover, rather than a full review, it highlights important concepts, while using only selected citations to illustrate those concepts. It further explores, by demonstration, the basic principles of using functionally characterized molecular networks to guide the practical application of PM in extreme environments. At its core, PM in extreme environments is about attention to incremental gains and losses in molecular network efficiency that can scale to produce notable changes in health and performance. The aim of this overview is to provide a conceptual overview of one approach to PM in extreme environments, coupled with a selected suite of practical considerations for molecular profiling and countermeasures.

What exactly is a “wicked problem”? It is a social or economic problem that is so complex and so interconnected with other issues that it is extraordinarily difficult or impossible to resolve. This is because all proposed resolutions generate equally complex, equally wicked problems. In this essay, I argue that precision medicine, especially in the context of the U.S. healthcare system, generates numerous wicked problems related to distributive justice. Further, I argue that there are no easy solutions to these wicked problems. The need for trade-offs is inescapable. Rough justice is the best outcome we can hope for, and that outcome requires a commitment to processes of public reason that are fair and inclusive.

In today’s globalized and flat world, a patient can access and seek multiple health and disease management options. A digitally enabled participatory framework that allows an evidence-based informed choice is likely to assume an immense importance in the future. In India, traditional knowledge systems, like Ayurveda, coexist with modern medicine. However, due to limited crosstalk between the clinicians of both disciplines, a patient attempts integrative medicine by seeking both options independently with limited understanding and evidence. There is a need for an integrative medicine platform with a formalized approach, which allows practitioners from the two diverse systems to crosstalk, coexist, and coevolve for an informed cross-referral that benefits the patients. To be successful, this needs frameworks that enable the bridging of disciplines through a common interface with shared ontologies. Ayurgenomics is an emerging discipline that explores the principles and practices of Ayurveda combined with genomics approaches for mainstream integration. The present review highlights how in conjunction with different disciplines and technologies this has provided frameworks for (1) the discovery of molecular correlates to build ontological links between the two systems, (2) the discovery of biomarkers and targets for early actionable interventions, (3) understanding molecular mechanisms of drug action from its usage perspective in Ayurveda with applications in repurposing, (4) understanding the network and P4 medicine perspective of Ayurveda through a common organizing principle, (5) non-invasive stratification of healthy and diseased individuals using a compendium of system-level phenotypes, and (6) developing evidence-based solutions for practice in integrative medicine settings. The concordance between the two contrasting streams has been built through extensive explorations and iterations of the concepts of Ayurveda and genomic observations using state-of-the-art technologies, computational approaches, and model system studies. These highlight the enormous potential of a trans-disciplinary approach in evolving solutions for personalized interventions in integrative medicine settings.

The overall aim of precision nutrition is to replace the ‘one size fits all’ approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more ‘precision’ dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene–diet or microbiota–diet interactions. Third, precision nutrition can be used for ‘personalised nutrition’ advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet–disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.