BACKGROUND: The advent of Personalized Medicine (PM) holds significant promise in revolutionizing healthcare by tailoring treatments to individual patients based on their data. However, its successful implementation requires the seamless integration of innovative technologies and presents formidable challenges in terms of sustainability. To tackle these challenges head-on, the International Consortium for Personalized Medicine (ICPerMed) was established, and the IC2PerMed project, as part of this consortium, seeks to foster collaboration between the European Union (EU) and China in the field of Personalized Medicine. Based on the results collected by the project, the objective of this study is to discern the key priorities for the implementation of Personalised Medicine concerning Information and Communication Technologies (ICT) and Big Data and digital solutions, with a particular emphasis on data management and protection.
METHODS: A Delphi survey was conducted to gather expert\'s consensus on the main priorities for actions on Information and Communication Technologies (ICT) and Big Data and digital solutions in the field of Personalized Medicine.
RESULTS: The survey identified seven priorities in the area of Big Data and digital solutions, including data interoperability, standards, security measures, and international partnerships. Additionally, twelve priorities were identified for the innovation-to-market process, emphasizing cost-effectiveness, need assessment, and value definition in resource allocation.
CONCLUSIONS: The effective implementation of new technologies in Personalized Medicine research and practice is essential for the advancement of healthcare systems in both the European and Chinese contexts. The identified priorities play a pivotal role in promoting the sustainability of health systems and driving innovation in the implementation of Personalized Medicine. Addressing challenges related to data interoperability, standards, security, international collaboration, cost-effectiveness, and value assessment is of utmost importance in order to propel the progress of Personalized Medicine in healthcare systems.

BACKGROUND: Personalised medicine (PM) has been fostered by technological and medical advances, but all stakeholders, including healthcare professionals, citizens and policy makers, should achieve adequate health literacy to promote PM implementation. The \"Integrating China in the International Consortium for Personalised Medicine\" (IC2PerMed) project, funded by the International Consortium for Personalised Medicine, focuses on this issue by highlighting the need to educate healthcare professionals and empower citizens. Within the aforementioned project, building on a mapping of European and Chinese policies in PM, experts in the field of PM participated in an online workshop and a following two-round Delphi survey, in order to identify the priority areas of intervention for healthcare professionals\' education and curricula, engagement and empowerment of citizens and patients.
RESULTS: Nine experts completed the survey and reached a consensus on seventeen priorities: seven were related to health professionals\' education and curricula, whereas ten on citizen and patients\' awareness and empowerment.
CONCLUSIONS: These priorities emphasized the importance of education and health literacy, multidisciplinary and international collaboration, public trust, and consideration of ethical, legal, and social issues. The present experience highlights the relevance of the involvement of stakeholders in informing decision-makers, developing appropriate national plans, strategies, and policies, and ensuring the adequate implementation of PM in health systems.

This study focuses on the application of nurse-led multidisciplinary collaborative therapy (MDT) management model for calciphylaxis prevention of patients with terminal renal disease. Through the establishment of a multidisciplinary management team spanning nephrology department, blood purification center, dermatology department, burn and plastic surgery department, infection department, stem cell platform, nutrition department, pain department, cardiology department, hydrotherapy group, dermatology group, and outpatient treatment room, the distribution of duties among team members were clarified to bring out the best advantages of a multidisciplinary teamwork during treatment and nursing. For patients with calciphylaxis symptoms in terminal renal disease, a case-by-case management model was carried out with the focus on personalised problem. We emphasised on personalised wound care, precise medication care, active pain management, psychological intervention and palliative care, the amelioration of calcium and phosphorus metabolism disorder, nutritional supplementation, and the therapeutic intervention based on human amniotic mesenchymal stem cell regeneration. The MDT model effectively compensates for traditional nursing mode and could serve as a novel clinical management modality for calciphylaxis prevention in patients with terminal renal disease.

The low bioavailability of orally administered drugs as a result of the instability in the gastrointestinal tract environment creates significant challenges to developing site-targeted drug delivery systems. This study proposes a novel hydrogel drug carrier using pH-responsive materials assisted with semi-solid extrusion 3D printing technology, enabling site-targeted drug release and customisation of temporal release profiles. The effects of material parameters on the pH-responsive behaviours of printed tablets were analysed thoroughly by investigating the swelling properties under both artificial gastric and intestinal fluids. It has been shown that high swelling rates at either acidic or alkaline conditions can be achieved by adjusting the mass ratio between sodium alginate and carboxymethyl chitosan, enabling site-targeted release. The drug release experiments reveal that gastric drug release can be achieved with a mass ratio of 1:3, whilst a ratio of 3:1 allows for intestinal release. Furthermore, controlled release is realised by tuning the infill density of the printing process. The method proposed in this study can not only significantly improve the bioavailability of oral drugs, but also offer the potential that each component of a compound drug tablet can be released in a controlled manner at a target location.

BACKGROUND: Respiratory diseases are the 2nd leading cause of death globally. The current treatments for chronic lung diseases are only supportive. Very few new classes of therapeutics have been introduced for lung diseases in the last 40 years, due to the lack of reliable lung models that enable rapid, cost-effective, and high-throughput testing. To accelerate the development of new therapeutics for lung diseases, we established two classes of lung-mimicking models: (i) healthy, and (ii) diseased lungs - COPD.
METHODS: To establish models that mimic the lung complexity to different extents, we used five design components: (i) cell type, (ii) membrane structure/constitution, (iii) environmental conditions, (iv) cellular arrangement, (v) substrate, matrix structure and composition. To determine whether the lung models are reproducible and reliable, we developed a quality control (QC) strategy, which integrated the real-time and end-point quantitative and qualitative measurements of cellular barrier function, permeability, tight junctions, tissue structure, tissue composition, and cytokine secretion.
RESULTS: The healthy model is characterised by (i) continuous tight junctions, (ii) physiological cellular barrier function, (iii) a full thickness epithelium composed of multiple cell layers, and (iv) the presence of ciliated cells and goblet cells. Meanwhile, the disease model emulates human COPD disease: (i) dysfunctional cellular barrier function, (ii) depletion of ciliated cells, and (ii) overproduction of goblet cells. The models developed here have multiple competitive advantages when compared with existing in vitro lung models: (i) the macroscale enables multimodal and correlative characterisation of the same model system, (ii) the use of cells derived from patients that enables the creation of individual models for each patient for personalised medicine, (iii) the use of an extracellular matrix proteins interface, which promotes physiological cell adhesion and differentiation, (iv) media microcirculation that mimics the dynamic conditions in human lungs.
CONCLUSIONS: Our model can be utilised to test safety, efficacy, and superiority of new therapeutics as well as to test toxicity and injury induced by inhaled pollution or pathogens. It is envisaged that these models can also be used to test the protective function of new therapeutics for high-risk patients or workers exposed to occupational hazards.

Personalised medicine is a medical model that aims to provide tailor-made prevention and treatment strategies for defined groups of individuals. The concept brings new challenges to the translational step, both in clinical relevance and validity of models. We have developed a set of recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine.
These recommendations have been developed following four main steps: (1) a scoping review of the literature with a gap analysis, (2) working sessions with a wide range of experts in the field, (3) a consensus workshop, and (4) preparation of the final set of recommendations.
Despite the progress in developing innovative and complex preclinical model systems, to date there are fundamental deficits in translational methods that prevent the further development of personalised medicine. The literature review highlighted five main gaps, relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. We identified five points of focus for the recommendations, based on the consensus reached during the consultation meetings: (1) clinically relevant translational research, (2) robust model development, (3) transparency and education, (4) revised regulation, and (5) interaction with clinical research and patient engagement. Here, we present a set of 15 recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine.
Appropriate preclinical models should be an integral contributor to interventional clinical trial success rates, and predictive translational models are a fundamental requirement to realise the dream of personalised medicine. The implementation of these guidelines is ambitious, and it is only through the active involvement of all relevant stakeholders in this field that we will be able to make an impact and effectuate a change which will facilitate improved translation of personalised medicine in the future.

Personalised medicine (PM) presents a great opportunity to improve the future of individualised healthcare. Recent advances in -omics technologies have led to unprecedented efforts characterising the biology and molecular mechanisms that underlie the development and progression of a wide array of complex human diseases, supporting further development of PM. This article reflects the outcome of the 2021 EATRIS-Plus Multi-omics Stakeholder Group workshop organised to 1) outline a global overview of common promises and challenges that key European stakeholders are facing in the field of multi-omics research, 2) assess the potential of new technologies, such as artificial intelligence (AI), and 3) establish an initial dialogue between key initiatives in this space. Our focus is on the alignment of agendas of European initiatives in multi-omics research and the centrality of patients in designing solutions that have the potential to advance PM in long-term healthcare strategies.

Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer has remained dismal over the past 30 years. Henceforth, reliable preclinical model systems are warranted to bridge the gap between laboratory experiments and clinical practice. In this review, we discuss the status quo of ovarian cancer preclinical models which includes conventional cell line models, patient-derived xenografts (PDXs), patient-derived organoids (PDOs), patient-derived explants (PDEs), and genetically engineered mouse models (GEMMs). Each model has its own strengths and drawbacks. We focus on the potentials and challenges of using these valuable tools, either alone or in combination, to interrogate critical issues with OC.

Quantitative measurement of plasma Epstein-Barr virus (EBV) DNA by real-time PCR at the end of primary treatment is a robust prognostic marker for nasopharyngeal carcinoma (NPC) patients. However, up to 40% of patients who would later develop disease recurrence had undetectable post-treatment plasma EBV DNA. Targeted sequencing for the entire EBV genome potentially allows a more comprehensive and unbiased detection of plasma EBV DNA and enables the use of other parameters such as fragment size as biomarkers. Hence, we explored if plasma EBV DNA sequencing might allow more accurate prognostication of NPC patients.
Plasma samples collected from 769 patients with stage IIB-IVB NPC at 6-8 weeks after radiotherapy were analysed using targeted sequencing for EBV DNA.
The sensitivities of the PCR-based analysis, at a cut-off of any detectable levels of plasma EBV DNA, for prediction of local and distant recurrences were 42.3% and 85.3%, respectively. The sequencing-based analysis (involving quantitation and size profiling) achieved better performance for both local and distant recurrences than PCR. Using a cut-off of the proportion of plasma EBV DNA deduced by sequencing at 0.01%, the sensitivities of the sequencing-based analysis for local and distant recurrences were 88.5% and 97.1%, with the resultant negative predictive values of 99.1% and 99.4%, respectively. Among patients with undetectable EBV DNA on quantitative PCR, sequencing could further define a subgroup that enjoyed superior survival outcomes based on the proportion of plasma EBV DNA, with a 5-year progression-free survival (PFS) approaching 90%. On multivariate analysis, sequencing-based quantitative level of plasma EBV DNA was the independent prognostic factor with the highest hazard ratio for prediction of overall survival and PFS.
NPC prognostication using post-treatment plasma EBV DNA could be enhanced through sequencing.

BACKGROUND: Heterogeneity in oral potentially malignant disorder (OPMD) poses a problem for accurate prognosis that impacts on treatment strategy and patient outcome. A holistic assessment based on gene expression signatures from both the tumour cells and their microenvironment is necessary to provide a more precise prognostic assessment than just tumour cell signatures alone.
METHODS: We reformulated our previously established multigene qPCR test, quantitative Malignancy Index Diagnostic System (qMIDS) with new genes involved in matrix/stroma and immune modulation of the tumour microenvironment. An algorithm calculates and converts a panel of 16 gene mRNA expression levels into a qMIDS index to quantify risk of malignancy for each sample.
RESULTS: The new qMIDSV2 assay was validated in a UK oral squamous cell carcinoma (OSCC) cohort (n = 282) of margin and tumour core samples demonstrating significantly better diagnostic performance (AUC = 0.945) compared to previous qMIDSV1 (AUC = 0.759). Performance of qMIDSV2 were independently validated in Chinese (n = 35; AUC = 0.928) and Indian (n = 95; AUC = 0.932) OSCC cohorts. Further, 5-year retrospective analysis on an Indian dysplastic lesion cohort (n = 30) showed that qMIDSV2 was able to significantly differentiate between lesions without transformation and those with malignant transformation.
CONCLUSIONS: This study validated a novel multi-gene qPCR test on a total of 535 tissue specimens from UK, China and India, demonstrating a rapid minimally invasive method that has a potential application for dysplasia risk stratification. Further study is required to establish if qMIDSV2 could be used to improve OPMD patient management, guide treatment strategy and reduce oral cancer burden.