Principles Of Precision Medicine Research Articles

Translational risk-adapted approaches to de-escalated radiation for human papillomavirus-positive oropharyngeal cancer: Past, present, and future

Interest in the use of de-escalated radiation to treat patients with newly diagnosed human papillomavirus (HPV)-positive oropharyngeal cancer has grown dramatically with the publication of prospective trials demonstrating the efficacy of such an approach. While the rationale for de-escalation--- namely to decrease treatment-related toxicity while maintaining the excellent rates of disease control historically observed in patients with this disease—is inherently obvious, uncertainty exists regarding how to best select patients for de-escalation. Consequently, risk-adapted strategies using a variety of translational and clinical platforms have been increasingly popularized to better refine treatment. These have integrated contemporary methods of mid-treatment response assessment using advanced technologies and molecular assays to customize the radiation dose. By monitoring the response as patients actively proceed through treatment, risk-adapted protocols have the potential to provide insight into the biological behavior of tumors and make individualized therapy possible. The purpose of this review is to summarize the evidence to date on risk-adapted approaches to de-escalated radiation-- highlighting the clinical, radiological, and biological data which may ultimately help usher the principles of precision medicine into practice for patients with HPV-positive oropharyngeal cancer.

Evaluating osteogenic potential of a 3D-printed bioceramic-based scaffold for critical-sized defect treatment: an in vivo and in vitro investigation.

The integration of precision medicine principles into bone tissue engineering has ignited a wave of research focused on customizing intricate scaffolds through advanced 3D printing techniques. Bioceramics, known for their exceptional biocompatibility and osteoconductivity, have emerged as a promising material in this field. This article aims to evaluate the regenerative capabilities of a composite scaffold composed of 3D-printed gelatin combined with hydroxyapatite/tricalcium phosphate bioceramics (G/HA/TCP), incorporating human dental pulp-derived stem cells (hDPSCs). Using 3D powder printing, we created cross-shaped biphasic calcium phosphate scaffolds with a gelatin layer. The bone-regenerating potential of these scaffolds, along with hDPSCs, was assessed through in vitro analyses and in vivo studies with 60 rats and critical-sized calvarial defects. The assessment included analyzing cellular proliferation, differentiation, and alkaline phosphatase activity (ALP), and concluded with a detailed histological evaluation of bone regeneration. Our study revealed a highly favorable scenario, displaying not only desirable cellular attachment and proliferation on the scaffolds but also a notable enhancement in the ALP activity of hDPSCs, underscoring their pivotal role in bone regeneration. However, the histological examination of calvarial defects at the 12-wk mark yielded a rather modest level of bone regeneration across all experimental groups. The test and cell group exhibited significant bone formation compared to all other groups except the control and cell group. This underscores the complexity of the regenerative process and paves the way for further in-depth investigations aimed at improving the potential of the composite scaffolds.

Liquid biomarkers in prostate cancer: recent advancements and future directions.

Traditional diagnostic approaches of prostate cancer like PSA are limited by high false-positive rates and insufficient capture of tumour heterogeneity, necessitating the development of more precise tools. This review examines the latest advancements in liquid biomarkers for prostate cancer, focusing on their potential to refine diagnostic accuracy and monitor disease progression. Liquid biomarkers have gained prominence because of their minimally invasive nature and ability to reflect the molecular characteristics of prostate cancer. Circulating tumour cells provide insight into tumour cell dissemination and are indicative of aggressive disease phenotypes, with single-cell analyses revealing genomic instability and treatment resistance. Circulating tumour DNA offers real-time tumour genomic information, aiding in treatment decision-making in advanced prostate cancer, where it has been associated with clinical progression. MicroRNAs act as oncogenes or tumour suppressors and exhibit diagnostic and prognostic potential; however, their clinical utility is constrained by the lack of consistent validation. Extracellular vesicles contain tumour-derived biomolecules, with specific proteins demonstrating prognostic relevance. Applications of these markers to urinary testing have been demonstrated. Liquid biomarkers show potential in refining prostate cancer management. Future research should aim to integrate these biomarkers into a cohesive framework in line with precision medicine principles.

Nuclear Cardiology in the Era of Precision Medicine: Tailoring Treatment to the Individual Patient.

Nuclear cardiology, employing advanced imaging technologies like positron emission tomography (PET) and single photon emission computed tomography (SPECT), is instrumental in diagnosing, risk stratifying, and managing heart diseases. Concurrently, precision medicine advocates for treatments tailored to each patient's genetic, environmental, and lifestyle specificities, promising a revolution in personalized cardiovascular care. This review explores the synergy between nuclear cardiology and precision medicine, highlighting advancements, potential enhancements in patient outcomes, and the challenges and opportunities of this integration. We examined the evolution of nuclear cardiology technologies, including PET and SPECT, and their role in cardiovascular diagnostics. We also delved into the principles of precision medicine, focusing on genetic and molecular profiling, data analytics, and individualized treatment strategies. The integration of these domains aims to optimize diagnostic accuracy, therapeutic interventions, and prognostic evaluations in cardiovascular care. Advancements in molecular imaging and the application of artificial intelligence in nuclear cardiology have significantly improved the precision of diagnostics and treatment plans. The adoption of precision medicine principles in nuclear cardiology enables the customization of patient care, leveraging genetic information and biomarkers for enhanced therapeutic outcomes. However, challenges such as data integration, accessibility, cost, and the need for specialized expertise persist. The confluence of nuclear cardiology and precision medicine offers a promising pathway toward revolutionizing cardiovascular healthcare, providing more accurate, effective, and personalized patient care. Addressing existing challenges and fostering interdisciplinary collaboration is crucial for realizing the full potential of this integration in improving patient outcomes.

In Situ Bioprinting: Process, Bioinks, and Applications.

Traditional tissue engineering methods face challenges, such as fabrication, implantation of irregularly shaped scaffolds, and limited accessibility for immediate healthcare providers. In situ bioprinting, an alternate strategy, involves direct deposition of biomaterials, cells, and bioactive factors at the site, facilitating on-site fabrication of intricate tissue, which can offer a patient-specific personalized approach and align with the principles of precision medicine. It can be applied using a handled device and robotic arms to various tissues, including skin, bone, cartilage, muscle, and composite tissues. Bioinks, the critical components of bioprinting that support cell viability and tissue development, play a crucial role in the success of in situ bioprinting. This review discusses in situ bioprinting techniques, the materials used for bioinks, and their critical properties for successful applications. Finally, we discuss the challenges and future trends in accelerating in situ printing to translate this technology in a clinical settings for personalized regenerative medicine.

Abstract IA011: The epigenetic-based liquid biopsy odyssey of bedside pancreatic cancer diagnostics

Abstract Pancreatic cancer (PC), often diagnosed at an advanced stage, urgently requires innovative early detection methods to improve patient outcomes. Presently, there is no approved screening method for pancreas cancer and its high-risk individuals (HRIs), as existing techniques rely on costly and invasive imaging modalities, which face challenges in detecting interval cancers. This study presents an innovative approach that utilizes liquid biopsy technology combined with blood-based DNA methylation biomarkers—ADAMTS1, BNC1, and LRFN5. These biomarkers demonstrate a remarkable 94% diagnostic accuracy for early-stage PC detection, providing a transformative strategy in precision medicine. In line with precision medicine principles, the potential application of this liquid biopsy-based DNA methylation panel for monitoring HRIs offers a promising path toward personalized surveillance. The creation of an affordable bedside test with exceptional diagnostic accuracy has the potential to revolutionize early detection strategies for PCs. Identifying early curable stage PC through this liquid biopsy technique aligns perfectly with precision medicine, promising increased patient survival. If successfully integrated into routine healthcare, early detection could significantly advance the fight against pancreatic cancer, paving the way for more effective and patient-centric diagnostic approaches. Citation Format: Nita Ahuja. The epigenetic-based liquid biopsy odyssey of bedside pancreatic cancer diagnostics [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA011.

Applying precision medicine principles to the management of multimorbidity: the utility of comorbidity networks, graph machine learning, and knowledge graphs.

The current management of patients with multimorbidity is suboptimal, with either a single-disease approach to care or treatment guideline adaptations that result in poor adherence due to their complexity. Although this has resulted in calls for more holistic and personalized approaches to prescribing, progress toward these goals has remained slow. With the rapid advancement of machine learning (ML) methods, promising approaches now also exist to accelerate the advance of precision medicine in multimorbidity. These include analyzing disease comorbidity networks, using knowledge graphs that integrate knowledge from different medical domains, and applying network analysis and graph ML. Multimorbidity disease networks have been used to improve disease diagnosis, treatment recommendations, and patient prognosis. Knowledge graphs that combine different medical entities connected by multiple relationship types integrate data from different sources, allowing for complex interactions and creating a continuous flow of information. Network analysis and graph ML can then extract the topology and structure of networks and reveal hidden properties, including disease phenotypes, network hubs, and pathways; predict drugs for repurposing; and determine safe and more holistic treatments. In this article, we describe the basic concepts of creating bipartite and unipartite disease and patient networks and review the use of knowledge graphs, graph algorithms, graph embedding methods, and graph ML within the context of multimorbidity. Specifically, we provide an overview of the application of graph theory for studying multimorbidity, the methods employed to extract knowledge from graphs, and examples of the application of disease networks for determining the structure and pathways of multimorbidity, identifying disease phenotypes, predicting health outcomes, and selecting safe and effective treatments. In today's modern data-hungry, ML-focused world, such network-based techniques are likely to be at the forefront of developing robust clinical decision support tools for safer and more holistic approaches to treating older patients with multimorbidity.

Transitioning from Subtyping to Precision Medicine in Parkinson's Disease: A Purpose-Driven Approach.

The International Parkinson and Movement Disorder Society (MDS) created a task force (TF) to provide a critical overview of the Parkinson's disease (PD) subtyping field and develop a guidance on future research in PD subtypes. Based on a literature review, we previously concluded that PD subtyping requires an ultimate alignment with principles of precision medicine, and consequently novel approaches were needed to describe heterogeneity at the individual patient level. In this manuscript, we present a novel purpose-driven framework for subtype research as a guidance to clinicians and researchers when proposing to develop, evaluate, or use PD subtypes. Using a formal consensus methodology, we determined that the key purposes of PD subtyping are: (1) to predict disease progression, for both the development of therapies (use in clinical trials) and prognosis counseling, (2) to predict response to treatments, and (3) to identify therapeutic targets for disease modification. For each purpose, we describe the desired product and the research required for its development. Given the current state of knowledge and data resources, we see purpose-driven subtyping as a pragmatic and necessary step on the way to precision medicine. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Pediatric contributions and lessons learned from the NEPTUNE cohort study.

Primary glomerular diseases are rare entities. This has hampered efforts to better understand the underlying pathobiology and to develop novel safe and effective therapies. NEPTUNE is a rare disease network that is focused on patients of all ages with minimal change disease, focal segmental glomerulosclerosis, and membranous nephropathy. It is a longitudinal cohort study that collects detailed demographic, clinical, histopathologic, genomic, transcriptomic, and metabolomic data. The goal is to develop a molecular classification for these disorders that supersedes the traditional pathological features-based schema. Pediatric patients are important contributors to this ongoing project. In this review, we provide a snapshot of the children and adolescents enrolled in NEPTUNE and summarize some key observations that have been made based on the data accumulated during the study. In addition, we describe the development of NEPTUNE Match, a program that aims to leverage the multi-scalar information gathered for each individual patient to provide guidance about potential clinical trial participation based on the molecular characterization and non-invasive biomarker profile. This represents the first organized effort to apply principles of precision medicine to the treatment of patients with primary glomerular disease. NEPTUNE has proven to be an invaluable asset in the study of glomerular diseases in patients of all ages including children and adolescents.

Radiotranscriptomics of non-small cell lung carcinoma for assessing high-level clinical outcomes using a machine learning-derived multi-modal signature

BackgroundMulti-omics research has the potential to holistically capture intra-tumor variability, thereby improving therapeutic decisions by incorporating the key principles of precision medicine. The purpose of this study is to identify a robust method of integrating features from different sources, such as imaging, transcriptomics, and clinical data, to predict the survival and therapy response of non-small cell lung cancer patients.Methods2996 radiomics, 5268 transcriptomics, and 8 clinical features were extracted from the NSCLC Radiogenomics dataset. Radiomics and deep features were calculated based on the volume of interest in pre-treatment, routine CT examinations, and then combined with RNA-seq and clinical data. Several machine learning classifiers were used to perform survival analysis and assess the patient’s response to adjuvant chemotherapy. The proposed analysis was evaluated on an unseen testing set in a k-fold cross-validation scheme. Score- and concatenation-based multi-omics were used as feature integration techniques.ResultsSix radiomics (elongation, cluster shade, entropy, variance, gray-level non-uniformity, and maximal correlation coefficient), six deep features (NasNet-based activations), and three transcriptomics (OTUD3, SUCGL2, and RQCD1) were found to be significant for therapy response. The examined score-based multi-omic improved the AUC up to 0.10 on the unseen testing set (0.74 ± 0.06) and the balance between sensitivity and specificity for predicting therapy response for 106 patients, resulting in less biased models and improving upon the either highly sensitive or highly specific single-source models. Six radiomics (kurtosis, GLRLM- and GLSZM-based non-uniformity from images with no filtering, biorthogonal, and daubechies wavelets), seven deep features (ResNet-based activations), and seven transcriptomics (ELP3, ZZZ3, PGRMC2, TRAK1, ATIC, USP7, and PNPLA2) were found to be significant for the survival analysis. Accordingly, the survival analysis for 115 patients was also enhanced up to 0.20 by the proposed score-based multi-omics in terms of the C-index (0.79 ± 0.03).ConclusionsCompared to single-source models, multi-omics integration has the potential to improve prediction performance, increase model stability, and reduce bias for both treatment response and survival analysis.

A serum metabolomics study of vascular cognitive impairment patients based on Traditional Chinese medicine syndrome differentiation.

Objective: Vascular cognitive impairment (VCI) accounts for approximately 50%-70% of all dementia cases and poses a significant burden on existing medical systems. Identifying an optimal strategy for preventing VCI and developing efficient symptomatic treatments remains a significant challenge. Syndrome differentiation represents a fundamental approach for personalized diagnosis and treatment in Traditional Chinese Medicine (TCM) and aligns with the principles of precision medicine. The objective of this study was to elucidate the metabolic characteristics of VCI based on TCM syndrome differentiation, thus providing novel insights into the diagnosis and treatment of VCI. Methods: A 2-year cross-sectional cognitive survey was conducted in four communities in Beijing between September 2020 and November 2022. The syndrome differentiation of participants was based on the Kidney-Yang Deficiency Syndrome Scale (KYDSS), which was originally developed by Delphi expert consultation. The identification of serum metabolites was performed by Ultra performance liquid chromatography (UPLC) analysis coupled with an electrospray ionization quadruple time-of-flight mass spectrometer (ESI-QTOF MS). Multivariate, univariate, and pathway analyses were used to investigate metabolic changes. Logistic regression models were also used to construct metabolite panels that were capable of discerning distinct groups. Phospholipase A2 (PLA2) levels were measured by a commercial ELISA kit. Results: A total of 2,337 residents completed the survey, and the prevalence of VCI was 9.84%. Of the patients with VCI, those with Kidney-Yang deficiency syndrome (VCIS) accounted for 70.87% of cases and exhibited more severe cognitive impairments. A total of 80 participants were included in metabolomics study, including 30 with VCIS, 20 without Kidney-Yang deficiency syndrome (VCINS), and 30 healthy control participants (C). Ultimately, 45 differential metabolites were identified when comparing the VCIS group with group C, 65 differential metabolites between the VCINS group and group C, and 27 differential metabolites between the VCIS group and the VCINS group. The downregulation of phosphatidylethanolamine (PE), and phosphatidylcholine (PC) along with the upregulation of lysophosphatidylethanolamine (LPE), lysophosphatidylcholine (LPC), phosphatidic acid (PA) and phospholipase A2 (PLA2) can be considered as the general metabolic characteristics associated with VCI. Dysfunction of glycerophospholipids, particularly LPEs and PCs, was identified as a key metabolic characteristic of VCIS. In particular Glycerophospho-N-Arachidonoyl Ethanolamine (GP-NArE) was discovered for the first time in VCI patients and is considered to represent a potential biomarker for VCIS. The upregulation of PLA2 expression was implicated in the induction of alterations in glycerophospholipid metabolism in both VCIS and VCINS. Moreover, robust diagnostic models were established based on these metabolites, achieving high AUC values of 0.9322, 0.9550, and 0.9450, respectively. Conclusion: These findings contribute valuable information relating to the intricate relationship between metabolic disorders in VCI, neurodegeneration and vascular/neuroinflammation. Our findings also provide a TCM perspective for the precise diagnosis and treatment of VCI in the context of precision medicine.

Microbial Dysbiosis and Male Infertility: Understanding the Impact and Exploring Therapeutic Interventions.

The human microbiota in the genital tract is pivotal for maintaining fertility, but its disruption can lead to male infertility. This study examines the relationship between microbial dysbiosis and male infertility, underscoring the promise of precision medicine in this field. Through a comprehensive review, this research indicates microbial signatures associated with male infertility, such as altered bacterial diversity, the dominance of pathogenic species, and imbalances in the genital microbiome. Key mechanisms linking microbial dysbiosis to infertility include inflammation, oxidative stress, and sperm structural deterioration. Emerging strategies like targeted antimicrobial therapies, probiotics, prebiotics, and fecal microbiota transplantation have shown potential in adjusting the genital microbiota to enhance male fertility. Notably, the application of precision medicine, which customizes treatments based on individual microbial profiles and specific causes of infertility, emerges as a promising approach to enhance treatment outcomes. Ultimately, microbial dysbiosis is intricately linked to male infertility, and embracing personalized treatment strategies rooted in precision medicine principles could be the way forward in addressing infertility associated with microbial factors.

Precision medicine: Vinpocetine as a potential treatment for GABRG2-related epilepsy.

Pathogenic variants of the GABRG2 gene, encoding a GABAA receptor subunit, have been associated with various epileptic syndromes and drug-resistant epilepsy. Vinpocetine has been previously reported efficacious in a patient harboring a GABRB3 pathogenic variant, encoding another GABAA receptor subunit. We describe a patient with GABRG2-related drug-resistant epilepsy who improved after vinpocetine treatment. An 8-year-old boy with a family history of epilepsy was diagnosed with early onset absence epilepsy at 6 months of age and was treated unsuccessfully with sodium valproate and ethosuximide. At 6 years of age, he developed generalized tonic-clonic seizures and increasing absences despite lamotrigine add-on as well as learning difficulties. Brain MRI was normal and video-EEG telemetry showed multiple myoclonic absences. An epilepsy gene panel analysis showed a GABRG2 pathogenic variant, c.254 T > A p.(Ile85Lys) (NM_198903.2), inherited from the proband's father. Seizures were resistant to several medications. After treatment with vinpocetine add-on, the patient showed a dramatic initial response, further reduction of seizures, and improvement of his cognitive functions. This case illustrates that vinpocetine could be considered in drug-resistant epilepsies related to GABRG2 in accordance with the principles of precision medicine.

The Biological and Molecular Action of Ozone and Its Derivatives: State-of-the-Art, Enhanced Scenarios, and Quality Insights.

The ultimate objective of this review is to encourage a multi-disciplinary and integrated methodological approach that, starting from the recognition of some current uncertainties, helps to deepen the molecular bases of ozone treatment effects on human and animal well-being and to optimize their performance in terms of reproducibility of results, quality, and safety. In fact, the common therapeutic treatments are normally documented by healthcare professionals' prescriptions. The same applies to medicinal gases (whose uses are based on their pharmacological effects) that are intended for patients for treatment, diagnostic, or preventive purposes and that have been produced and inspected in accordance with good manufacturing practices and pharmacopoeia monographs. On the contrary, it is the responsibility of healthcare professionals, who thoughtfully choose to use ozone as a medicinal product, to achieve the following objectives: (i) to understand the molecular basis of the mechanism of action; (ii) to adjust the treatment according to the clinical responses obtained in accordance with the principles of precision medicine and personalized therapy; (iii) to ensure all quality standards.

Precision Medicine as a New Frontier in Speech-Language Pathology: How Applying Insights From Behavior Genomics Can Improve Outcomes in Communication Disorders.

Precision medicine is an emerging intervention paradigm that leverages knowledge of risk factors such as genotypes, lifestyle, and environment toward proactive and personalized interventions. Regarding genetic risk factors, examples of interventions informed by the field of medical genomics are pharmacological interventions tailored to an individual's genotype and anticipatory guidance for children whose hearing impairment is predicted to be progressive. Here, we show how principles of precision medicine and insights from behavior genomics have relevance for novel management strategies of behaviorally expressed disorders, especially disorders of spoken language. This tutorial presents an overview of precision medicine, medical genomics, and behavior genomics; case examples of improved outcomes; and strategic goals toward enhancing clinical practice. Speech-language pathologists (SLPs) see individuals with various communication disorders due to genetic variants. Ways of using insights from behavior genomics and implementing principles of precision medicine include recognizing early signs of undiagnosed genetic disorders in an individual's communication patterns, making appropriate referrals to genetics professionals, and incorporating genetic findings into management plans. Patients benefit from a genetics diagnosis by gaining a deeper and more prognostic understanding of their condition, obtaining more precisely targeted interventions, and learning about their recurrence risks. SLPs can achieve improved outcomes by expanding their purview to include genetics. To drive this new interdisciplinary framework forward, goals should include systematic training in clinical genetics for SLPs, enhanced understanding of genotype-phenotype associations, leveraging insights from animal models, optimizing interprofessional team efforts, and developing novel proactive and personalized interventions.

Handgrip strength conditional tolerance regions suggest the need for personalized sarcopenia definition: an analysis of the American NHANES database.

Handgrip strength (HGS) is a well-established clinical biomarker that assesses functional capacity in older populations. In addition, HGS is a diagnostic tool that forecasts aging health conditions, such as sarcopenia. This paper provides HGS statistical tolerance regions and presents the need to establish HGS reference values according to patients' characteristics. For this purpose, we used a conditional tolerance algorithm for HGS, and we observed the tolerances regions in different age strata and sex of non-sarcopenic individuals from the National Health and Nutrition Examination Survey (NHANES, wave 2011-2012). Our results have critical implications for sarcopenia, since conventional and available HGS cut-offs do not consider age range. This paper offers new perspectives on the evolution of traditional definitions of sarcopenia according to the principles of precision medicine.

Care for Patients with Type-2 Chronic Rhinosinusitis.

In the last 20 years, growing interest in chronic rhinosinusitis (CRS) has become evident in medical literature; nevertheless, it is still difficult to identify the real prevalence of the disease. Epidemiological studies are few and focused on heterogeneous populations and diagnostic methods. Recent research has contributed to identifying CRS as a disease characterized by heterogeneous clinical scenarios, high impact on quality of life, and elevated social costs. Patient stratification with phenotypes and identification of the pathobiological mechanism at the origin of the disease (endotype) and its comorbidities are pivotal in the diagnostic process, and they should be addressed in order to properly tailor treatment. A multidisciplinary approach, shared diagnostic and therapeutic data, and follow-up processes are therefore necessary. Oncological multidisciplinary boards offer models to imitate in accordance with the principles of precision medicine: tracing a diagnostic pathway with the purpose of identifying the patient's immunological profile, monitoring therapeutical processes, abstaining from having only a single specialist involved in treatment, and placing the patient at the center of the therapeutic plan. Awareness and participation from the patient's perspective are fundamental steps to optimize the clinical course, improve quality of life, and reduce the socioeconomic burden.

Abstract IA014: Precision public health approaches to health equity

Abstract Since President Barack Obama announced the “Precision Medicine Initiative” during his state of the union address in January 2015, the sciences of precision medicine and health equity have largely grown in parallel, though there have been some efforts to bring the two together. As research on health equity has evolved to name and consider structural racism, the penultimate goal of research in this area also as moved from efforts to identify and describe gaps between racial and ethnic groups to characterizing the context creates and perpetuates racial inequities and how best to mitigate them. In this presentation, I will briefly describe how syndemics, intersectionality, and individual tailoring may complement downstream efforts to characterize epigenetic and genomic efforts to develop biomedical interventions to achieve healthcare equity and health equity. After noting how the principles of precision medicine may be applied more broadly than the most common way it is operationalized through genomic medicine, I argue that that creating racial justice in health will require defining health equity more clearly and precisely. Consequently, I utilize the example of Black men and the context of COVID-19 to highlight how more precisely defining the structural context of the population of interest by using tools such as intersectionality and syndemics is fundamental to achieving equity. I highlight how achieving health equity will require creating, resisting, undoing, and mitigating structural racism and note what that means for cancer research. Precision medicine may help to mitigate the health effects of structural racism, and it will remain an important tool to promote population health; however, efforts to achieve health equity and racial justice will require interventions that change the contexts and conditions that create, exacerbate, and perpetuate structural inequities and the racial inequities in health outcomes that they produce and maintain. Citation Format: Derek M. Griffith. Precision public health approaches to health equity. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr IA014.

Advancing Precision Medicine in Paediatrics: Past, present and future.

Precision Medicine is an approach to disease treatment and prevention taking into account individual genetic, environmental, therapeutic and lifestyle variability for each person. This holistic approach to therapeutics is intended to enhance drug efficacy and safety not only across healthcare systems but for individual patients. While weight and to some extent gestational age have been considered in determining drug dosing in children, historically other factors including genetic variability have not been factored into therapeutic decision making. As our knowledge of the role of ontogeny and genetics in determining drug efficacy and safety has expanded, these insights have provided new opportunities to apply principles of Precision Medicine to the care of infants, children and youth. These opportunities are most likely to be achieved first in select sub-groups of children. While there are many challenges to the successful implementation of Precision Medicine in children including the need to ensure that Precision Medicine enhances rather than reduces equity in children's health care rather, there are many more opportunities. Research, advocacy, planning and teamwork are required to move Precision Medicine forward in children in pursuit of the common goal of safe and effective drug therapy.

COVID-19 Vaccines Adverse Effects and the need for more focused, if not individualized approach in COVID-19 vaccination programs

Aim of this review is to discuss the need for more focused, if not individualized COVID-19 vaccination approach with a goal to prevent serious adverse effects and to establish high quality vaccination programs according to the principles of precision medicine.