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At least 19 recordsLinked to original sources
PubMed2025

Acoustic ejection mass spectrometry: the potential for personalized medicine.

INTRODUCTION: The emergence of personalized medicine (PM) has shifted the focus of healthcare from the traditional 'one-size-fits-all' approach to strategies tailored to individual patients, accounting for genetic, environmental, and lifestyle factors. Acoustic ejection mass spectrometry (AEMS) is a novel technology that offers a robust and scalable platform for high-throughput MS readout. AEMS achieves analytical speeds of one sample per second while maintaining high data quality, broad compound coverage, and minimal sample preparation, making it an invaluable tool for PM. AREAS COVERED: This article explores the potential of AEMS in critical PM applications, including therapeutic drug monitoring (TDM), proteomics, metabolomics, and mass spectrometry imaging. AEMS simplifies conventional workflows by minimizing sample preparation, enhancing automation compatibility, and enabling direct analysis of complex biological matrices. EXPERT OPINION: Integrating AEMS with orthogonal separation techniques such as differential mobility spectrometry (DMS) further addresses challenges in isomer discrimination, expanding the platform's analytical capabilities. Additionally, the development of high-throughput data processing tools could further enable AEMS to accelerate the development of personalized medicine.

Humans↗
PubMed2026

Evolution of Precision Oncology, Personalized Medicine, and Molecular Tumor Boards.

With multiple molecular targeted therapies available for patients with cancer that correspond to a specific genetic alteration, the selection of the best treatment is essential to ensure therapeutic efficacy. Molecular tumor boards (MTBs) play a key role in this process to deliver personalized medicine to patients with cancer in a multidisciplinary manner. Historically, personalized medicine has been offered to patients with advanced cancer, but the incorporation of molecular targeted therapies and immunotherapy into the perioperative setting requires clinicians to understand the role of the MTB. Evidence is accumulating to support feasibility and survival benefit in patients treated with matched therapy.

Humans↗
PubMed2025

The Use of Next-Generation Sequencing in Personalized Medicine.

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Humans↗
PubMed2024

The use of next-generation sequencing in personalized medicine.

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

High-throughput sequencing↗
PubMed2026

CAUSAL artificial intelligence and data-driven decision intelligence in personalized medicine: a review of healthcare informatics systems.

This review examines the integration of causal artificial intelligence (AI) and data-driven decision intelligence within healthcare informatics systems to advance personalized medicine and clinical decision-making. A narrative review methodology was employed, synthesizing interdisciplinary literature from major databases, including PubMed, Scopus, Web of Science, IEEE Xplore, and ScienceDirect. Studies focusing on causal inference, decision intelligence, and healthcare informatics applications in personalized medicine were included. Data were extracted on methodological approaches, healthcare settings, analytical techniques, and clinical applications, followed by thematic synthesis. Findings indicate that causal AI enhances clinical decision support by enabling estimation of treatment effects and simulation of intervention outcomes at the individual patient level. Integration of multimodal health data such as electronic health records, genomic data, and real-time monitoring improves prediction accuracy and supports tailored treatment strategies. Additionally, causal models improve interpretability, fostering clinician trust and facilitating transparent decision-making. Robust healthcare informatics infrastructures, including interoperable systems and data warehouses, were identified as critical enablers of causal analytics. Overall, causal AI represents a transformative advancement in healthcare analytics, supporting more informed, individualized, and evidence-based clinical decisions. Its integration within healthcare informatics systems has significant potential to improve patient outcomes and guide the future of intelligent, personalized healthcare delivery.

Precision Medicine↗
PubMed2026

Advances in organoids for personalized medicine: from technological development to clinical application.

Organoids, three-dimensional cell culture models derived from patient tissues or stem cells, have emerged as a cutting-edge technology in personalized medicine, owing to their remarkable ability to closely recapitulate in vivo tissue architecture and function. This review provides a comprehensive overview of the technological evolution and construction methodologies of organoids, highlighting their significant applications in oncology, genetic disorders, infectious diseases, and drug screening. This review examines how organoids enable precision medicine by preserving genomic fidelity, predicting drug sensitivity, and creating disease models via gene editing. Despite these advances, organoid technology faces several technical challenges that impede its full clinical translation. Addressing these obstacles is critical for realizing the potential of organoids in individualized therapeutic strategies. This article aims to delineate current progress and future directions in organoid research, furnishing a theoretical foundation and guiding future investigations towards enhancing personalized treatment paradigms.

disease modeling↗
PubMed2026

Establishing a Multicenter Personalized Medicine Program in Childhood, Adolescent, and Young Adult Cancer in Spain: The SEHOP-PENCIL Project.

Pediatric cancer care in Spain lacked a national personalized medicine program. The SEHOP-PENCIL initiative, established by the SEHOP, was designed to address this gap. A national survey identified the genomic sequencing needs of hospitals treating pediatric patients with cancer. Results showed improved access to targeted next-generation sequencing panels but revealed persistent variability in implementation, limited availability of advanced sequencing (whole-exome sequencing, whole-genome sequencing, RNA sequencing, and DNA methylation profiling), and gaps in cancer predisposition clinics and molecular tumor boards (MTBs). SEHOP-PENCIL is organized as a network of 10 specialized genomic centers serving 45 hospitals through a centralized inclusion system. The program standardizes patient eligibility, genomic workflows, and result interpretation, supported by a national MTB. This framework enables informed clinical decision making, ensures access to molecular diagnosis and innovative therapies, and supports systematic data collection to advance pediatric cancer research and personalized care. SEHOP-PENCIL represents a pioneering national model for integrating precision oncology into pediatric cancer care in Spain. By fostering collaboration, standardizing genomic practices, and promoting equitable access, it aims to reduce disparities and improve outcomes, offering a scalable example for other decentralized health care systems.

Humans↗
PubMed2026

Personalized medicine strategy for MPNSTs: using precision oncology on PDOX models to inform tumor boards.

BACKGROUND: Malignant peripheral nerve sheath tumors (MPNSTs) are a heterogeneous group of aggressive soft tissue sarcomas with poor prognosis. Currently there is a lack of effective treatments for MPNSTs. Here, we propose a personalized medicine approach that integrates a precision oncology strategy guided by MPNST genomic analysis, with a functional validation of treatment response in an orthotopic xenograft model (PDOX) derived from the same MPNST. METHODS: Comprehensive whole genome sequencing analysis was performed in primary MPNSTs, relapses and (in one case) metastases, following disease progression in two independent individuals. Matched MPNST PDOX models were generated by orthotopically implanting tumor fragments near the sciatic nerve of immunodeficient mice. Candidate targeted combination therapies were prioritized based on genomic alterations and tested in vivo in the PDOX models. RESULTS: The feasibility of the developed strategy is illustrated for two MPNST patients, one Neurofibromatosis type 1 (NF1) individual that developed two independent MPNSTs and another sporadic MPNST case with multiple metastatic relapses. Genomic analysis revealed a remarkable degree of genomic stability across primary MPNSTs and their successive relapses in each patient, and even metastases in one individual. While based on a small number of cases requiring additional analyses, this finding aligns with previous evidence suggesting a fair genomic conservation throughout tumor evolution. This stability supports the identification of consistent therapeutic vulnerabilities throughout disease progression. Among the therapies tested, co-treatment of MEK inhibitor (MEKi) plus bromodomain inhibitor (BETi) elicited the highest antitumor activity, resulting in approximately 60% tumor volume reduction in the sporadic MPNST PDX model, whose patient has been receiving this therapy for eight months with sustained remission. CONCLUSIONS: This study demonstrates the feasibility and clinical utility of integrating genomic-driven precision oncology with PDOX-based functional testing for MPNSTs. This strategy may support molecular tumor boards (MTBs) in their treatment decisions. The observed genomic stability supports the use of longitudinal tumor profiling to guide treatment, and the success of MEKi+BETi highlights its potential as a combination therapy for MPNSTs.

Precision Medicine↗
PubMed1976

Whole-person medicine and psychiatry for medical students.

Doctors predominantly going to work in the community are taught technologically advanced medicine in specialised hospitals. The subject-matter has to be fragmented in order to be teachable, but somebody has to put the whole person together again. The task is taken on by university departments of psychiatry and mental health. A teaching programme has been evolved in Bristol to meet these needs and to teach clinical psychiatry.

Attitude of Health Personnel↗
PubMed2025

Advancing translational exposomics: bridging genome, exposome and personalized medicine.

Understanding the interplay between genetic predisposition and environmental and lifestyle exposures is essential for advancing precision medicine and public health. The exposome, defined as the sum of all environmental exposures an individual encounters throughout their lifetime, complements genomic data by elucidating how external and internal exposure factors influence health outcomes. This treatise highlights the emerging discipline of translational exposomics that integrates exposomics and genomics, offering a comprehensive approach to decipher the complex relationships between environmental and lifestyle exposures, genetic variability, and disease phenotypes. We highlight cutting-edge methodologies, including multi-omics technologies, exposome-wide association studies (EWAS), physiology-based biokinetic modeling, and advanced bioinformatics approaches. These tools enable precise characterization of both the external and the internal exposome, facilitating the identification of biomarkers, exposure-response relationships, and disease prediction and mechanisms. We also consider the importance of addressing socio-economic, demographic, and gender disparities in environmental health research. We emphasize how exposome data can contextualize genomic variation and enhance causal inference, especially in studies of vulnerable populations and complex diseases. By showcasing concrete examples and proposing integrative platforms for translational exposomics, this work underscores the critical need to bridge genomics and exposomics to enable precision prevention, risk stratification, and public health decision-making. This integrative approach offers a new paradigm for understanding health and disease beyond genetics alone.

Humans↗
PubMed2026

Looking to the Future: How Will Personalised Medicine Impact Facial Plastic Surgery.

AIMS AND BACKGROUNDS: The objectives of this study are to examine the emerging role of personalized medicine in facial plastic surgery and to consider how biologically, anatomically, and psychologically tailored approaches may refine both aesthetic and reconstructive care. HISTORICAL ASPECTS: Facial plastic surgery has traditionally relied on anatomical principles, surgical expertise, and population-based evidence. Personalized medicine represents a shift toward more individualized care by incorporating patient-specific biological and phenotypic variation into clinical decision-making. ANATOMY: Facial plastic surgery is uniquely dependent on subtle anatomical variation, soft tissue characteristics, wound healing behavior, and age-related change. These factors differ considerably between individuals and have a direct impact on both surgical planning and outcomes. TECHNOLOGY: Advances in genomics, pharmacogenomics, artificial intelligence, tissue engineering, and three-dimensional modelling are expanding the scope of personalized care. These technologies may improve prediction of healing, treatment response, complication risk, and reconstructive requirements. PATIENT SELECTION: Personalized medicine may support more accurate patient selection by identifying those at increased risk of adverse scarring, variable response to injectables or pharmacotherapy, or differential reconstructive needs, thereby improving counselling and expectation management. TECHNIQUES: Potential applications include tailored incision planning, individualized facial rejuvenation strategies, personalized perioperative pharmacological regimens, and patient-specific reconstructive scaffolds, grafts, and implants. POSTOPERATIVE CARE: Postoperative management may also become more individualized through better prediction of inflammatory response, scar formation, analgesic requirements, and recovery trajectory, allowing more precise surveillance and adjunctive treatment. CURRENT AND FUTURE DEVELOPMENT: Although many applications remain investigational, continued progress in regenerative medicine, molecular profiling, and predictive analytics is likely to accelerate clinical translation. Ethical challenges relating to privacy, bias, and equitable access must, however, remain central. CONCLUSION AND CLINICAL RELEVANCE: Personalized medicine has the potential to enhance precision, safety, and patient-centered care in facial plastic surgery. Its future value will depend on thoughtful integration into practice as an adjunct to, rather than a replacement for, surgical judgement and aesthetic insight.

Journal Article↗
PubMedDate not supplied

Psychoanalysis applied to medicine: a personal note.

The psychoanalyst has much to contribute to medicine, more through the teaching of observational skills and an appreciation of relationships than through the teaching of psychoanalytic technique or languate itself. The analyst can promote tolerance in the physician of the unusual, an examination of the impediments of habitual ways of working and seeing, and a facility in the patient to "be himself". Attention to the unusual, as illustrated through experience in training-cum-research seminars, can enhance the doctor's satisfaction with his professional life while offering improved care to his patients. When psychoanalyst, physician and patient interact in their roles as people, there is hope of an improved quality of human existence for all.

Attitude of Health Personnel↗
PubMed2025

Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine: Bringing next-generation precision oncology to patients.

The human genome project ushered in a genomic medicine era that was largely unimaginable three decades ago. Discoveries of druggable cancer drivers enabled biomarker-driven gene- and immune-targeted therapy and transformed cancer treatment. Minimizing treatment not expected to benefit, and toxicity-including financial and time-are important goals of modern oncology. The Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine founded by Drs. John Mendelsohn and Thomas Tursz provided a vision for innovation, collaboration and global impact in precision oncology. Through pursuit of transcriptomic signatures, artificial intelligence (AI) algorithms, global precision cancer medicine clinical trials and input from an international Molecular Tumor Board (MTB), WIN has led the way in demonstrating patient benefit from precision-therapeutics through N-of-1 molecularly-driven studies. WIN Next-Generation Precision Oncology (WINGPO) trials are being developed in the neoadjuvant, adjuvant or metastatic settings, incorporate real-world data, digital pathology, and advanced algorithms to guide MTB prioritization of therapy combinations for a diverse global population. WIN has pursued combinations that target multiple drivers/hallmarks of cancer in individual patients. WIN continues to be impactful through collaboration with industry, government, sponsors, funders, academic and community centers, patient advocates, and other stakeholders to tackle challenges including drug access, costs, regulatory barriers, and patient support. WIN's collaborative next generation of precision oncology trials will guide treatment selection for patients with advanced cancers through MTB and AI algorithms based on serial liquid and tissue biopsies and exploratory omics including transcriptomics, proteomics, metabolomics and functional precision medicine. Our vision is to accelerate the future of precision oncology care.

Humans↗