BACKGROUND: n-of-1 trials are undertaken to optimise the evaluation of health technologies in individual patients. They involve a single patient receiving treatments, both interventional and control, consecutively over set periods of time, the order of which is decided at random. Although n-of-1 trials are undertaken in medical research it could be argued they have the utility to be undertaken more frequently. We undertook the National Institute for Health Research (NIHR) commissioned DIAMOND (Development of generalisable methodology for n-of-1 trials delivery for very low volume treatments) project to develop key points to assist clinicians and researchers in designing and conducting n-of-1 trials.
METHODS: The key points were developed by undertaking a stakeholder workshop, followed by a discussion within the study team and then a stakeholder dissemination and feedback event. The stakeholder workshop sought to gain the perspectives of a variety of stakeholders (including clinicians, researchers and patient representatives) on the design and use of n-of-1 trials. A discussion between the study team was held to reflect on the workshop and draft the key points. Lastly, the stakeholders from the workshop were invited to a dissemination and feedback session where the proposed key points were presented and their feedback gained.
RESULTS: A set of 22 key points were developed based on the insights from the workshop and subsequent discussions. They provide guidance on when an n-of-1 trial might be a viable or appropriate study design and discuss key decisions involved in the design of n-of-1 trials, including determining an appropriate number of treatment periods and cycles, the choice of comparator, recommended approaches to randomisation and blinding, the use of washout periods and approaches to analysis.
CONCLUSIONS: The key points developed in the project will support clinical researchers to understand key considerations when designing n-of-1 trials. It is hoped they will support the wider implementation of the study design.

Objectives: The objective of this narrative review is to explore the advantages and limitations of VHs in delivering healthcare, including access to specialized professionals, streamlined communication, efficient scheduling, integration of electronic health records, ongoing monitoring, and support, transcending geographical boundaries, and resource optimization. Methods: Review of literature. Results: The national healthcare systems are facing an alarming rise in pressure due to global shifts. Virtual hospitals (VH) offer a practical solution to numerous systemic challenges, including rising costs and increased workloads for healthcare providers. VH also facilitate the delivery of personalized services and enable the monitoring of patients beyond the conventional confines of healthcare settings, reducing the reliance on waiting medicine carried out in doctors\' offices or hospitals. Conclusion: VH can mirror the conventional healthcare referral system.

The relatively recent adoption of Endoscopic Sleeve Gastroplasty (ESG) amongst obese patients has gained approval within the surgical community due to its notable benefits, including significant weight loss, safety, feasibility, repeatability, and potential reversibility. However, despite its promising clinical outcomes and reduced invasiveness, there is still a lack of standardised procedures for performing ESG. Multiple suture patterns and stitching methods have been proposed over time, yet rational tools to quantify and compare their effects on gastric tissues are absent. To address this gap, this study proposed a computational approach. The research involved a case study analyzing three distinct suture patterns (C-shaped, U-shaped and Z-shaped) using a patient-specific computational stomach model generated from magnetic resonance imaging. Simulations mimicked food intake by placing wire features in the intragastric cavity to replicate sutures, followed by applying a linearly increasing internal pressure up to 15 mmHg. The outcomes facilitated comparisons between suture configurations based on pressure-volume behaviours and the distribution of maximum stress on biological tissues, revealing the U-shaped as the more effective in terms of volume reduction, even if with reduced elongation strains and increased tissues stresses, whereas the Z-shaped is responsible of the greatest stomach shortness after ESG. In summary, computational biomechanics methods serve as potent tools in clinical and surgical settings, offering insights into aspects that are challenging to explore in vivo, such as tissue elongation and stress. These methods allow for mechanical comparisons between different configurations, although they might not encompass crucial clinical outcomes.

OBJECTIVE: Personalised medicine is seen as an exciting opportunity to improve the health outcomes of people with obesity. As research on phenotyping and personalised treatment for obesity rapidly advances, this study sought to understand patient preferences and perspectives on personalised medicine for obesity.
METHODS: A participatory world café methodology was used to garner the perspectives of people living with obesity on the potential opportunities and limitations associated with a personalised approach to obesity risk identification and treatment. Data were recorded by participants on tablemats and analysed thematically using thematic analysis.
RESULTS: Patients expressed the hope that personalised medicine for obesity would reduce stigma, support understanding of obesity as a disease, and improve treatment outcomes and acceptance. They also expressed concern about the accuracy of personalised medicine for obesity, its implications for insurance and that further advances in individual, personalised medicine, would detract attention from social, environmental, economic and psychological drivers of obesity.
CONCLUSIONS: This study highlights how patients are generally very optimistic about the potential for personalised obesity medicine but also raise a number of legitimate concerns that will be of interest to clinicians, industry, and policy makers.

Personalized medicine has emerged as a revolutionary approach to healthcare in the 21st century. By understanding a patient\'s unique genetic and biological characteristics, it aims to tailor treatments specifically to the individual. This approach takes into account factors such as an individual\'s lifestyle, genetic makeup, and environmental factors to provide targeted therapies that have the potential to be more effective and lower the risk of side reactions or ineffective treatments. It is a paradigm shift from the traditional \"one size fits all\" approach in medicine, where patients with similar symptoms or diagnoses receive the same standard treatments regardless of their differences. It leads to improved clinical outcomes and more efficient use of healthcare resources. Drug repurposing is a strategy that uses existing drugs for new indications and aims to take advantage of the known safety profiles, pharmacokinetics, and mechanisms of action of these drugs to accelerate the development process. Precision medicine may undergo a revolutionary change as a result, enabling the rapid development of novel treatment plans utilizing drugs that traditional methods would not otherwise link to. In this chapter, we have focused on a few strategies wherein drug repurposing has shown great success for precision medicine. The approach is particularly useful in oncology as there are many variations induced in the genetic material of cancer patients, so tailored treatment approaches go a long way. We have discussed the cases of breast cancer, glioblastoma and hepatocellular carcinoma. Other than that, we have also looked at drug repurposing approaches in anxiety disorders and COVID-19.

UNASSIGNED: In recent years, thanks to significant advances in basic science and biotechnologies, nephrology has witnessed a deeper understanding of the mechanisms leading to various conditions associated with or causing kidney disease, opening new perspectives for developing specific treatments. These new possibilities have brought increased challenges to physicians, who face with a new complexity in disease characterization and selection the right treatment for individual patients.
UNASSIGNED: We chose four therapeutic situations: anaemia in chronic kidney disease (CKD), heart failure in CKD, IgA nephropathy (IgAN) and membranous nephropathy (MN). The literature search was made through PubMed.
UNASSIGNED: Anaemia management remains challenging in CKD; a personalized therapeutic approach is often needed. Identifying patients who could benefit from a specific therapy is also an important goal for patients with CKD and heart failure with reduced ejection fraction. Several new treatments are under clinical development for IgAN; interestingly, they target specifically the pathogenetic mechanisms of the disease. The understanding of MN pathogenesis as an autoimmune disease and the discovery of several autoantibodies allows a better characterization of patients. High-sensible techniques for lymphocyte counting open the possibility of more personalized use of anti CD20 therapies.

Therapeutic hypothermia is now standard of care for neonates with hypoxic-ischemic encephalopathy (HIE) in high income countries (HIC). Conversely, compelling trial evidence suggests that hypothermia is ineffective, and may be deleterious, in low- and middle-income countries (LMIC), likely reflecting the lower proportion of infants who had sentinel events at birth, suggesting that injury had advanced to a stage when hypothermia is no longer effective. Although hypothermia significantly reduced the risk of death and disability in HICs, many infants survived with disability and in principle may benefit from targeted add-on neuroprotective or neurorestorative therapies. The present review will assess biomarkers that could be used to personalize treatment for babies with HIE - to determine first whether an individual infant is likely to respond to hypothermia, and second, whether additional treatments may be beneficial.

UNASSIGNED: This survey assessed psychiatry residents\'/early-career psychiatrists\' attitudes towards the utility of therapeutic drug monitoring (TDM) of antipsychotics.
UNASSIGNED: A previously developed questionnaire on attitudes on TDM utility during antipsychotic treatment was cross-sectionally disseminated by national coordinators between 01/01/2022-31/12/2023. The frequency of using TDM for antipsychotics other than clozapine was the main outcome in a linear regression analysis, including sex, clinical setting, caseload, and factors generated by an exploratory factor analysis. Comparisons between residents and early-career psychiatrists, respondents working in in- and outpatient settings, and low-/middle- and high-income countries were performed.
UNASSIGNED: Altogether, 1,237 respondents completed the survey, with 37.9% having never used TDM for antipsychotics. Seven factors explained 41% of response variance; six of them were associated with frequency of TDM use (p < 0.05). Items with highest loadings for factors included clinical benefits of TDM (factors A and E: 0.7), negative expectations for beliefs of patients towards TDM (factor B: 0.6-0.7), weak TDM scientific evidence (factor C: 0.8), and TDM availability (factor D: -0.8). Respondents from low-/middle-income countries were less likely to frequently/almost always use TDM compared to high-income countries (9.4% vs. 21.5%, p < 0.001).
UNASSIGNED: TDM use for antipsychotics was poor and associated with limited knowledge and insufficient availability.

BACKGROUND: Artificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient conditions. This has heightened the demand for access to diverse data from clinical practice and daily life for research, posing challenges due to the sensitive nature of medical information, including genetics and health conditions. Regulations like the Health Insurance Portability and Accountability Act (HIPAA) in the U.S. and the General Data Protection Regulation (GDPR) in Europe aim to strike a balance between data security, privacy, and the imperative for access.
RESULTS: We present the Gemelli Generator - Real World Data (GEN-RWD) Sandbox, a modular multi-agent platform designed for distributed analytics in healthcare. Its primary objective is to empower external researchers to leverage hospital data while upholding privacy and ownership, obviating the need for direct data sharing. Docker compatibility adds an extra layer of flexibility, and scalability is assured through modular design, facilitating combinations of Proxy and Processor modules with various graphical interfaces. Security and reliability are reinforced through components like Identity and Access Management (IAM) agent, and a Blockchain-based notarisation module. Certification processes verify the identities of information senders and receivers.
CONCLUSIONS: The GEN-RWD Sandbox architecture achieves a good level of usability while ensuring a blend of flexibility, scalability, and security. Featuring a user-friendly graphical interface catering to diverse technical expertise, its external accessibility enables personnel outside the hospital to use the platform. Overall, the GEN-RWD Sandbox emerges as a comprehensive solution for healthcare distributed analytics, maintaining a delicate equilibrium between accessibility, scalability, and security.

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