The faces of personalized medicine: a framework for understanding its meaning and scope

The characteristics and role of digital literacy in an effective health protection

The evolution of modern healthcare underscores the crucial question of societal priorities in development. When distributing finite healthcare resources, decision-makers must weigh numerous factors and navigate a range of sometimes conflicting criteria, including equity, access, fairness, and effectiveness. This chapter aims to survey the social implications of digital literacy as a pivotal element for the optimal advancement of P5 medicine, with the objective of enhancing healthcare services. The untapped potential of telemedicine and other emerging P5 technologies remains substantial in terms of their integration into routine medical practice. Adequate digital literacy among both healthcare providers and users stands as a vital prerequisite for the successful adoption and further evolution of these innovations. Coupled with improved health literacy, these factors collectively should contribute to the provision of superior healthcare services and consequently to the overall well-being of the populace.

A Dive into Delivery of Oral Hygiene Advice Based on the Personalized Oral Hygiene Advice Model

Oral health's impact on overall well-being highlights the importance of preventive measures through effective oral hygiene practices. Currently, there is growing recognition of the need for customized oral hygiene advice depending on the patient's unique needs and circumstances. This narrative review addresses the gap in understanding the significance of personalized guidance through the proposal of the Personalized Oral Hygiene Advice Model (POHAM) as a comprehensive guide for oral health professionals. This model was developed to adapt to evolving patient demographics and diverse challenges, promoting a patient-centric and effective oral health approach. The POHAM comprises a flow chart of strategies from establishing a good rapport with patients, conducting comprehensive assessment through history-taking, psychosocial and technology proficiency evaluation, tailored education modules, and customized oral care product recommendations until the reassessment. These strategies aim to enhance patient engagement and adherence, as well as act as a guide for oral health professionals to use in the clinical setting before and during the course of oral treatment. Nevertheless, continued research, education, and technological advancements are needed to realize the full potential of personalized oral hygiene strategies, ensuring a transformative and sustainable oral healthcare landscape.

Awareness of the impact of sex and gender in the disease risk and outcomes in hematology and medical oncology-a survey of Swiss clinicians

BACKGROUND

Although male and female cancer patients are distinct in many ways, there is a limited understanding in the differences between male and female biology and differing pharmacokinetic responses to cancer drugs. In fact, sex and gender are currently not considered in most treatment decisions in the fields of oncology and hematology. The lack of knowledge about potential sex differences in both disciplines may lead to differences in treatment efficacy, toxicity, and the overall survival (OS) of patients.

AIM

To evaluate their awareness about sex and gender in clinical practice we surveyed Swiss hematologists and oncologists from September to November 2022.

METHODS

We collected data about the clinical knowledge, experimental research, palliative care, quality of life, as well as the participant perception of the importance of sex and gender. We identified 767 eligible clinicians, of whom 150 completed the survey (20% response rate).

RESULTS

While most participants agreed that sex and gender were relevant when treating patients, it became clear that fewer participants knew about sex and gender differences in treatment toxicity and survival, which in turn would affect the treatment of their patients. Most participants agreed that this topic should be integrated into continuing education and research.

CONCLUSION

Our findings indicate the need for more awareness and training on sex and gender in cancer research and clinical care among oncologists and hematologists. Ideally, by better educating medical students and health professionals, a demand is created for improving research policies, publications and therefore patient care.

Modeling Red Blood Cell Metabolism in the Omics Era

Red blood cells (RBCs) are abundant (more than 80% of the total cells in the human body), yet relatively simple, as they lack nuclei and organelles, including mitochondria. Since the earliest days of biochemistry, the accessibility of blood and RBCs made them an ideal matrix for the characterization of metabolism. Because of this, investigations into RBC metabolism are of extreme relevance for research and diagnostic purposes in scientific and clinical endeavors. The relative simplicity of RBCs has made them an eligible model for the development of reconstruction maps of eukaryotic cell metabolism since the early days of systems biology. Computational models hold the potential to deepen knowledge of RBC metabolism, but also and foremost to predict in silico RBC metabolic behaviors in response to environmental stimuli. Here, we review now classic concepts on RBC metabolism, prior work in systems biology of unicellular organisms, and how this work paved the way for the development of reconstruction models of RBC metabolism. Translationally, we discuss how the fields of metabolomics and systems biology have generated evidence to advance our understanding of the RBC storage lesion, a process of decline in storage quality that impacts over a hundred million blood units transfused every year.

Psychiatric mental health nurse practitioner student knowledge and perceptions of pharmacogenetic testing

Psychotropic medications are typically prescribed in a trial-and-error fashion, and some providers are beginning to utilize pharmacogenetic testing (PGx) as a supplemental prescribing tool in treatment decision making. PGx testing shows potential in enhancing provider insights into personalized prescribing for patients by examining genetic information related to drug metabolism. Literature points to providers' lack of knowledge in PGx interpretation as a main barrier, including psychiatric mental health nurse practitioners (PMHNPs). The aim of this study was to measure a difference, if any, in the knowledge and perceptions of PGx after implementation using a pre-post design. This study implemented an educational intervention on graduate nursing students (n = 15). Data were collected by using a pre- and post-interventional questionnaire. Results demonstrated a significant difference in findings related to students' knowledge (p < 0.001), students' skills related to pharmacogenetics, (p < 0.001), as well as students' perceived ability to implement pharmacogenetics into their practice, (p = 0.028). The authors propose that the knowledge gained from the study demonstrates the importance of introducing PGx education into the PMHNP curricula and to prepare future PMHNPs to confidently utilize PGx in their clinical practice.

Challenges and opportunities in building a health economic framework for personalized medicine in oncology

Personalized medicine has allowed for knowledge at an individual level for several diseases and this has led to improvements in prevention and treatment of various types of neoplasms. Despite the greater availability of tests, the costs of genomic testing and targeted therapies are still high for most patients, especially in low- and middle-income countries. Although value frameworks and health technology assessment are fundamental to allow decision-making by policymakers, there are several concerns in terms of personalized medicine pharmacoeconomics. A global effort may improve these tools in order to allow access to personalized medicine for an increasing number of patients with cancer.

3D Printed Pharmaceutical Systems for Personalized Treatment in Metabolic Syndrome

The current healthcare system is widely based on the concept of “one size fit for all”, which emphasizes treating a disease by prescribing the same drug to all patients with equivalent doses and dosing frequency. This medical treatment scenario has shown varied responses with either no or weak pharmacological effects and exaggerated adverse reactions preceded by more patient complications. The hitches to the concept of “one size fits all” have devoted the attention of many researchers to unlocking the concept of personalized medicine (PM). PM delivers customized therapy with the highest safety margin for an individual patient’s needs. PM has the potential to revolutionize the current healthcare system and pave the way to alter drug choices and doses according to a patient’s clinical responses, providing physicians with the best treatment outcomes. The 3D printing techniques is a solid-form fabrication method whereby successive layers of materials based on computer-aided designs were deposited to form 3D structures. The 3D printed formulation achieves PM goals by delivering the desired dose according to patient needs and drug release profile to achieve a patient’s personal therapeutic and nutritional needs. This pre-designed drug release profile attains optimum absorption and distribution, exhibiting maximum efficacy and safety profiles. This review aims to focus on the role of the 3D printing technique as a promising tool to design PM in metabolic syndrome (MS).

Hyper-responsiveness to warfarin in a young patient with the VKORC1 -1639GA/CYP2C9*1*46 genotype: a case report

BACKGROUND

Warfarin is the most widely used oral anticoagulant; nevertheless, dosing of warfarin is problematic for clinicians worldwide. Inter-individual variability in response to warfarin is attributed to genetic as well as non-genetic factors. Pharmacogenomics studies have identified variants in CYP2C9 and VKORC1 genes as significant predictors of warfarin dose, however, phenotypes of rare variants are not well characterized.

CASE PRESENTATION

We report a case of hyper-responsiveness to warfarin in a 22-year-old outpatient with Crohn's disease who presented with a swollen, red, and painful left calf. Deep venous thrombosis (DVT) in the left lower extremity was confirmed via ultrasonography, and hence, anticoagulation therapy of heparin and concomitant warfarin was initiated. Warfarin dose of 7.5 mg/day was estimated by the physician based on clinical factors. Higher than the expected international normalized ratio (INR) value of 4.5 necessitated the reduction of the warfarin dose to 5 and eventually to 2.5 mg/day to reach a therapeutic INR value of 2.6. Pharmacogenetic profiling of the VKORC1 -1639G > A and CYP2C9 *2, *3, *4, *5, *8, *14, *20, *24, *26, *33, *40, *41, *42, *43, *45, *46, *55, *62, *63, *66, *68, *72, *73 and *78 revealed a VKORC1-1639GA/CYP2C9*1*46 genotype. The lower catalytic activity of the CYP2C9*46 (A149T) variant was previously reported in in vitro settings.

CONCLUSIONS

This is the first report on a case of warfarin hyper-responsive phenotype of a patient with the heterozygous CYP2C9*1*46 polymorphism.

Fabrication of Hydroxypropyl Methylcellulose Orodispersible Film Loaded Mirtazapine Using a Syringe Extrusion 3D Printer

Depression is a mental illness causing a continuous negative feeling and loss of interest and affects physical and mental health. Mirtazapine (MTZ) is an effective medicine for treating depression, but patients lack compliance. However, transforming a pharmaceutical dosage form to an orodispersible film (ODF) could resolve this issue. This study aims to fabricate ODF-loading mirtazapine, using a syringe extrusion 3D printer, and compare its properties with the solvent-casting method. The ODFs were prepared by dissolving the mirtazapine in a hydroxypropyl methylcellulose E15 solution, and then fabricated by a 3D printer or casting. The 3D printing was accurate and precise in fabricating the ODFs. The SEM micrographs showed that the mirtazapine-printed ODF (3D-MTZ) was porous, with crystals of mirtazapine on the film’s surface. The 3D-MTZ exhibited better mechanical properties than the mirtazapine-casted ODF (C-MTZ), due to the 3D-printing process. The disintegration time of the 3D-MTZ in a simulated salivary fluid, pH 6.8 at 37 °C, was 24.38 s, which is faster than the C-MTZ (46.75 s). The in vitro dissolution study, in 0.1 N HCl at 37 °C, found the 3D-MTZ quickly released the drug by more than 80% in 5 min. This study manifested that 3D-printing technology can potentially be applied for the fabrication of ODF-containing mirtazapine.

Tools for the Economic Evaluation of Precision Medicine: A Scoping Review of Frameworks for Valuing Heterogeneity-Informed Decisions

BACKGROUND AND OBJECTIVE

Precision medicine highlights the importance of exploring heterogeneity in the effectiveness and costs of interventions. Our objective was to identify and compare frameworks for valuing heterogeneity-informed decisions, and consider their strengths and weaknesses for application to precision medicine.

METHODS

We conducted a scoping review to identify papers that proposed an analytical framework to place a value, in terms of costs and health benefits, on using heterogeneity to inform treatment selection. The search included English-language papers indexed in MEDLINE, Embase or EconLit, and a manual review of references and citations. We compared the frameworks qualitatively considering: the purpose and setting of the analysis; the types of precision medicine interventions where the framework could be applied; and the framework's ability to address the methodological challenges of evaluating precision medicine.

RESULTS

Four analytical frameworks were identified: value of stratification, value of heterogeneity, expected value of individualised care and loss with respect to efficient diffusion. Each framework is suited to slightly different settings and research questions. All focus on maximising net benefit, and quantify the opportunity cost of ignoring heterogeneity by comparing individualised or stratified decisions to a means-based population-wide decision. Where the frameworks differ is in their approaches to uncertainty, and in the additional metrics they consider.

CONCLUSIONS

Identifying and utilising heterogeneity is at the core of precision medicine, and the ability to quantify the value of heterogeneity-informed decisions is critical. Using an analytical framework to value heterogeneity will help provide evidence to inform investment in precision medicine interventions, appropriately capturing the value of targeted health interventions.

Formulation and characterization of immediate-release oral dosage forms with zolpidem tartrate fabricated by digital light processing (DLP) 3D printing technique

The introduction of three-dimensional (3D) printing in the pharmaceutical field has made great strides towards innovations in the way drugs are designed and manufactured. In this study, digital light processing (DLP) technique was used to fabricate oral dosage forms of different shapes with zolpidem tartrate (ZT), incorporated within its therapeutic range. Formulation factors, such as poly(ethylene glycol) diacrylate (PEGDA) and poly(ethylene glycol) 400 (PEG 400) ratio, as well as water content, were varied in combination with the surface area/volume (SA/V) ratio to achieve immediate drug release. Hypromellose (HPMC) was used as a stabilizing agent of photoreactive suspensions in an attempt to prevent drug sedimentation and subsequent variations in drug content uniformity. Oral dosage forms with doses in the range from 0.15 mg to 6.37 mg, showing very rapid and rapid drug dissolution, were successfully fabricated, confirming the potential of this technique in drug manufacturing with the ability to provide flexible dose adjustments and desirable release profiles by varying formulation factors and geometry of 3D models. DSC (differential scanning calorimetry), XRPD (X-ray powder diffraction) and scanning electron microscopy (SEM) showed that ZT remained in a crystalline form within printed dosage forms and no interactions were found between ZT and polymers.

Curcuminoids for Metabolic Syndrome: Meta-Analysis Evidences Toward Personalized Prevention and Treatment Management

The metabolic syndrome (MS) is a multifactorial syndrome associated with a significant economic burden and healthcare costs. MS management often requires multiple treatments (polydrug) to ameliorate conditions such as diabetes mellitus, insulin resistance, obesity, cardiovascular diseases, hypertension, and non-alcoholic fatty liver disease (NAFLD). However, various therapeutics and possible drug-drug interactions may also increase the risk of MS by altering lipid and glucose metabolism and promoting weight gain. In addition, the medications cause side effects such as nausea, flatulence, bloating, insomnia, restlessness, asthenia, palpitations, cardiac arrhythmias, dizziness, and blurred vision. Therefore, is important to identify and develop new safe and effective agents based on a multi-target approach to treat and manage MS. Natural products, such as curcumin, have multi-modalities to simultaneously target several factors involved in the development of MS. This review discusses the recent preclinical and clinical findings, and up-to-date meta-analysis from Randomized Controlled Trials regarding the effects of curcumin on MS, as well as the metabonomics and a pharma-metabolomics outlook considering curcumin metabolites, the gut microbiome, and environment for a complementary personalized prevention and treatment for MS management.

3D Tissue-Engineered Vascular Drug Screening Platforms: Promise and Considerations

Despite the efforts devoted to drug discovery and development, the number of new drug approvals have been decreasing. Specifically, cardiovascular developments have been showing amongst the lowest levels of approvals. In addition, concerns over the adverse effects of drugs to the cardiovascular system have been increasing and resulting in failure at the preclinical level as well as withdrawal of drugs post-marketing. Besides factors such as the increased cost of clinical trials and increases in the requirements and the complexity of the regulatory processes, there is also a gap between the currently existing pre-clinical screening methods and the clinical studies in humans. This gap is mainly caused by the lack of complexity in the currently used 2D cell culture-based screening systems, which do not accurately reflect human physiological conditions. Cell-based drug screening is widely accepted and extensively used and can provide an initial indication of the drugs' therapeutic efficacy and potential cytotoxicity. However, in vitro cell-based evaluation could in many instances provide contradictory findings to the in vivo testing in animal models and clinical trials. This drawback is related to the failure of these 2D cell culture systems to recapitulate the human physiological microenvironment in which the cells reside. In the body, cells reside within a complex physiological setting, where they interact with and respond to neighboring cells, extracellular matrix, mechanical stress, blood shear stress, and many other factors. These factors in sum affect the cellular response and the specific pathways that regulate variable vital functions such as proliferation, apoptosis, and differentiation. Although pre-clinical in vivo animal models provide this level of complexity, cross species differences can also cause contradictory results from that seen when the drug enters clinical trials. Thus, there is a need to better mimic human physiological conditions in pre-clinical studies to improve the efficiency of drug screening. A novel approach is to develop 3D tissue engineered miniaturized constructs in vitro that are based on human cells. In this review, we discuss the factors that should be considered to produce a successful vascular construct that is derived from human cells and is both reliable and reproducible.

Public R&D Projects-Based Investment and Collaboration Framework for an Overarching South Korean National Strategy of Personalized Medicine

Since the South Korean government designated personalized medicine (PM) as a national strategic task in 2016, it has spared no investment to achieve its goals, which were recently accelerated by the COVID-19 pandemic. This study analyzed investment trends in 17 regions and eight technology clusters related to PM, consisting of 5727 public R&D projects worth USD 148.5 million, from 2015 to 2020. We also illustrated the level of investment for different PM-related technology clusters in each region; various research organizations explicitly verified comparable innovation capabilities for all eight technology fields in 17 regions, showing individual differences in technology areas per region. Our framework provided information to allow implementation of two goals: administering successful PM and improving regional equality in public health and healthcare according to technical and organizational levels. This study empirically demonstrates that it can provide a precise overarching innovation scheme with regional, technical, and organizational dimensions to establish collaboration among different stakeholders, thereby creating a foundation for an overarching national PM strategy.

Toward Overcoming Treatment Failure in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an autoimmune disorder characterized by inflammation and bone erosion. The exact mechanism of RA is still unknown, but various immune cytokines, signaling pathways and effector cells are involved. Disease-modifying antirheumatic drugs (DMARDs) are commonly used in RA treatment and classified into different categories. Nevertheless, RA treatment is based on a "trial-and-error" approach, and a substantial proportion of patients show failed therapy for each DMARD. Over the past decades, great efforts have been made to overcome treatment failure, including identification of biomarkers, exploration of the reasons for loss of efficacy, development of sequential or combinational DMARDs strategies and approval of new DMARDs. Here, we summarize these efforts, which would provide valuable insights for accurate RA clinical medication. While gratifying, researchers realize that these efforts are still far from enough to recommend specific DMARDs for individual patients. Precision medicine is an emerging medical model that proposes a highly individualized and tailored approach for disease management. In this review, we also discuss the potential of precision medicine for overcoming RA treatment failure, with the introduction of various cutting-edge technologies and big data.

Metabolomic Profiles of Men and Women Ischemic Stroke Patients

Background: Stroke is known to affect both men and women; however, incidence and outcomes differ between them. Therefore, the discovery of novel, sex-specific, blood-based biomarkers for acute ischemic stroke (AIS) patients has the potential to enhance the understanding of the etiology of this deadly disease in the content of sex. The objective of this study was to identify serum metabolites associated with male and female AIS patients. Methods: Metabolites were measured with the use of untargeted, reverse-phase ultra-performance liquid chromatography-tandem mass spectrometry quantification from blood specimens collected from AIS patients. Samples were collected from 36 patients comprising each of 18 men and women with matched controls. Metabolic pathway analysis and principal component analysis (PCA) was used to differentiate metabolite profiles for male and female AIS patients from the control, while logistic regression was used to determine differences in metabolites between male and female AIS patients. Results: In female AIS patients, 14 distinct altered metabolic pathways and 49 corresponding metabolites were identified, while 39 metabolites and 5 metabolic pathways were identified in male patients. Metabolites that are predictive of ischemic stroke in female patients were 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC (P-16:0/20:4) (AUC = 0.914, 0.765–1.000), 1-(1-enyl-palmitoyl)-2-palmitoyl-GPC (P-16:0/16:0) (AUC = 0.840, 0.656–1.000), and 5,6-dihydrouracil (P-16:0/20:2) (AUC = 0.815, 0.601–1.000). Significant metabolites that were predictive of stroke in male patients were 5alpha-androstan-3alpha,17beta-diol disulfate (AUC = 0.951, 0.857–1.000), alpha-hydroxyisocaproate (AUC = 0.938, 0.832–1.000), threonate (AUC = 0.877, 0.716–1.000), and bilirubin (AUC = 0.817, 0.746–1.000). Conclusions: In the current study, the untargeted serum metabolomics platform identified multiple pathways and metabolites associated with male and female AIS patients. Further research is necessary to characterize how these metabolites are associated with the pathophysiology in male and female AIS patients.

Advanced therapeutic modalities in hepatocellular carcinoma: Novel insights

Hepatocellular carcinoma (HCC), the most common type of liver cancer, is usually a latent and asymptomatic malignancy caused by different aetiologies, which is a result of various aberrant molecular heterogeneity and often diagnosed at advanced stages. The incidence and prevalence have significantly increased because of sedentary lifestyle, diabetes, chronic infection with hepatotropic viruses and exposure to aflatoxins. Due to advanced intra‐ or extrahepatic metastasis, recurrence is very common even after radical resection. In this paper, we highlighted novel therapeutic modalities, such as molecular‐targeted therapies, targeted radionuclide therapies and epigenetic modification‐based therapies. These topics are trending headlines and their combination with cell‐based immunotherapies, and gene therapy has provided promising prospects for the future of HCC treatment. Moreover, a comprehensive overview of current and advanced therapeutic approaches is discussed and the advantages and limitations of each strategy are described. Finally, very recent and approved novel combined therapies and their promising results in HCC treatment have been introduced.

An iterative, interdisciplinary, collaborative framework for developing and evaluating digital behavior change interventions

The rapid expansion of technology promises to transform the behavior science field by revolutionizing the ways in which individuals can monitor and improve their health behaviors. To fully live into this promise, the behavior science field must address distinct challenges, including: building interventions that are not only scientifically sound but also engaging; using evaluation methods to precisely assess intervention components for intervention optimization; and building personalized interventions that acknowledge and adapt to the dynamic ecosystem of individual and contextual variables that impact behavior change. The purpose of this paper is to provide a framework to address these challenges by leveraging behavior science, human-centered design, and data science expertise throughout the cycle of developing and evaluating digital behavior change interventions (DBCIs). To define this framework, we reviewed current models and practices for intervention development and evaluation, as well as technology industry models for product development. The framework promotes an iterative process, aiming to maximize outcomes by incorporating faster and more frequent testing cycles into the lifecycle of a DBCI. Within the framework provided, we describe each phase, from development to evaluation, to discuss the optimal practices, necessary stakeholders, and proposed evaluation methods. The proposed framework may inform practices in both academia and industry, as well as highlight the need to offer collaborative platforms to ensure successful partnerships that can lead to more effective DBCIs that reach broad and diverse populations.

Personalized Cancer Medicine in the Media: Sensationalism or Realistic Reporting?

BACKGROUND

Given that media coverage can shape healthcare expectations, it is essential that we understand how the media frames "personalized medicine" (PM) in oncology, and whether information about unproven technologies is widely disseminated.

METHODS

We conducted a content analysis of 396 news reports related to cancer and PM published between 1 January 1998 and 31 December 2011. Two coders independently coded all the reports using a pre-defined framework. Determination of coverage of "standard" and "non-standard" therapies and tests was made by comparing the media print/broadcast date to the date of Federal Drug Administration approval or incorporation into clinical guidelines.

RESULTS

Although the term "personalized medicine" appeared in all reports, it was clearly defined only 27% of the time. Stories more frequently reported PM benefits than challenges (96% vs. 48%, p < 0.001). Commonly reported benefits included improved treatment (89%), prediction of side effects (30%), disease risk prediction (33%), and lower cost (19%). Commonly reported challenges included high cost (28%), potential for discrimination (29%), and concerns over privacy and regulation (21%). Coverage of inherited DNA testing was more common than coverage of tumor testing (79% vs. 25%, p < 0.001). Media reports of standard tests and treatments were common; however, 8% included information about non-standard technologies, such as experimental medications and gene therapy.

CONCLUSION

Confusion about personalized cancer medicine may be exacerbated by media reports that fail to clearly define the term. While most media stories reported on standard tests and treatments, an emphasis on the benefits of PM may lead to unrealistic expectations for cancer genomic care.

The personalized medicine discourse: archaeology and genealogy

Personalized Medicine (PM) is an evolving and often missinterpreted concept and no agreement of personalization exist. We examined the PM discourse towards foucauldian archeological and genealogical analysis to understand the meaning of "personalization" in medicine. In the archaeological analysis, the historical evolution is characterized by the coexistence of two epistemologies: the holistic vision and the omic sciences. The genealogical analysis shows how these epistemologies may affect the meaning of "person" and, consequently, the ontology of patients. Additionally, substitutions/confusions of the term PM are related to continuously evolving medical knowledge and new technologies; different etymological roots of "personalization" and "person"; and cultural differences. In conclusion, if the definition of "personalization" in medicine is not clear, patients might get wrong expectations about what is achievable for their health. Therefore, epistemological trends should not be separated as they drive same goals: providing accurate diagnosis and treatments based on large data to predict disease progression.

Shape memory materials and 4D printing in pharmaceutics

Shape memory materials (SMMs), including alloys and polymers, can be programmed into a temporary configuration and then recover the original shape in which they were processed in response to a triggering external stimulus (e.g. change in temperature or pH, contact with water). For this behavior, SMMs are currently raising a lot of attention in the pharmaceutical field where they could bring about important innovations in the current treatments. 4D printing involves processing of SMMs by 3D printing, thus adding shape evolution over time to the already numerous customization possibilities of this new manufacturing technology. SMM-based drug delivery systems (DDSs) proposed in the scientific literature were here reviewed and classified according to the target pursued through the shape recovery process. Administration route, therapeutic goal, temporary and original shape, triggering stimulus, main innovation features and possible room for improvement of the DDSs were especially highlighted.

Leveraging proteomics in orphan disease research: pitfalls and potential

Introduction: The term 'orphan diseases' includes conditions meeting prevalence-based or commercial viability criteria: they affect a small number of individuals and are considered an unviable market for drug development. Proteomics is an important technology to study them, providing information on mechanisms and evolution, biomarkers, and effects of therapeutic interventions.Areas covered: Herein, we review how proteomics and bioinformatic tools could be applied to the study of rare diseases and discuss pitfalls and potential.Expert opinion: Research in the field of rare diseases has to face many challenges, and implementation plans should foresee highly specialized collaborative consortia to create multidisciplinary frameworks for data sharing, advancing research, supporting clinical studies, and accelerating drug development. The integration of different technologies will allow better knowledge of disease pathophysiology, and the inclusion of proteomics and other omics technologies in this context will be pivotal to this aim.Several aspects of rare diseases, often perceived as limiting factors, might actually be advantages for a precision medicine approach: the limited number of patients, the collaboration with patient societies, and the availability of curated clinical registries could allow the development of homogeneous clinical databases and ultimately a better control over the data to be analyzed.

Practicality of 3D Printed Personalized Medicines in Therapeutics

Technological advances in science over the past century have paved the way for remedial treatment outcomes in various diseases. Pharmacogenomic predispositions, the emergence of multidrug resistance, medication and formulation errors contribute significantly to patient mortality. The concept of "personalized" or "precision" medicines provides a window to addressing these issues and hence reducing mortality. The emergence of three-dimensional printing of medicines over the past decades has generated interests in therapeutics and dispensing, whereby the provisions of personalized medicines can be built within the framework of producing medicines at dispensaries or pharmacies. This plan is a good replacement of the fit-for-all modality in conventional therapeutics, where clinicians are constrained to prescribe pre-formulated dose units available on the market. However, three-dimension printing of personalized medicines faces several hurdles, but these are not insurmountable. In this review, we explore the relevance of personalized medicines in therapeutics and how three-dimensional printing makes a good fit in current gaps within conventional therapeutics in order to secure an effective implementation of personalized medicines. We also explore the deployment of three-dimensional printing of personalized medicines based on practical, legal and regulatory provisions.

Personalized Clinical Phenotyping through Systems Medicine and Artificial Intelligence

Personalized Medicine (PM) has shifted the traditional top-down approach to medicine based on the identification of single etiological factors to explain diseases, which was not suitable for explaining complex conditions. The concept of PM assumes several interpretations in the literature, with particular regards to Genetic and Genomic Medicine. Despite the fact that some disease-modifying genes affect disease expression and progression, many complex conditions cannot be understood through only this lens, especially when other lifestyle factors can play a crucial role (such as the environment, emotions, nutrition, etc.). Personalizing clinical phenotyping becomes a challenge when different pathophysiological mechanisms underlie the same manifestation. Brain disorders, cardiovascular and gastroenterological diseases can be paradigmatic examples. Experiences on the field of Fondazione Policlinico Gemelli in Rome (a research hospital recognized by the Italian Ministry of Health as national leader in "Personalized Medicine" and "Innovative Biomedical Technologies") could help understanding which techniques and tools are the most performing to develop potential clinical phenotypes personalization. The connection between practical experiences and scientific literature highlights how this potential can be reached towards Systems Medicine using Artificial Intelligence tools.

Precision Medicine in Hematology 2021: Definitions, Tools, Perspectives, and Open Questions

During the past few years, our understanding of molecular mechanisms and cellular interactions relevant to malignant blood cell disorders has improved substantially. New insights include a detailed knowledge about disease-initiating exogenous factors, endogenous (genetic, somatic, epigenetic) elicitors or facilitators of disease evolution, and drug actions and interactions that underlie efficacy and adverse event profiles in defined cohorts of patients. As a result, precision medicine and personalized medicine are rapidly growing new disciplines that support the clinician in making the correct diagnosis, in predicting outcomes, and in optimally selecting patients for interventional therapies. In addition, precision medicine tools are greatly facilitating the development of new drugs, therapeutic approaches, and new multiparametric prognostic scoring models. However, although the emerging roles of precision medicine and personalized medicine in hematology and oncology are clearly visible, several questions remain. For example, it remains unknown how precision medicine tools can be implemented in healthcare systems and whether all possible approaches are also affordable. In addition, there is a need to define terminologies and to relate these to specific and context-related tools and strategies in basic and applied science. To discuss these issues, a working conference was organized in September 2019. The outcomes of this conference are summarized herein and include a proposal for definitions, terminologies, and applications of precision and personalized medicine concepts and tools in hematologic neoplasms. We also provide proposals aimed at reducing costs, thereby making these applications affordable in daily practice.

My Data, My Choice? - German Patient Organizations' Attitudes towards Big Data-Driven Approaches in Personalized Medicine. An Empirical-Ethical Study

Personalized medicine (PM) operates with biological data to optimize therapy or prevention and to achieve cost reduction. Associated data may consist of large variations of informational subtypes e.g. genetic characteristics and their epigenetic modifications, biomarkers or even individual lifestyle factors. Present innovations in the field of information technology have already enabled the procession of increasingly large amounts of such data (‘volume’) from various sources (‘variety’) and varying quality in terms of data accuracy (‘veracity’) to facilitate the generation and analyzation of messy data sets within a short and highly efficient time period (‘velocity’) to provide insights into previously unknown connections and correlations between different items (‘value’). As such developments are characteristics of Big Data approaches, Big Data itself has become an important catchphrase that is closely linked to the emerging foundations and approaches of PM. However, as ethical concerns have been pointed out by experts in the debate already, moral concerns by stakeholders such as patient organizations (POs) need to be reflected in this context as well. We used an empirical-ethical approach including a website-analysis and 27 telephone-interviews for gaining in-depth insight into German POs’ perspectives on PM and Big Data. Our results show that not all POs are stakeholders in the same way. Comparing the perspectives and political engagement of the minority of POs that is currently actively involved in research around PM and Big Data-driven research led to four stakeholder sub-classifications: ‘mediators’ support research projects through facilitating researcher’s access to the patient community while simultaneously selecting projects they preferably support while ‘cooperators’ tend to contribute more directly to research projects by providing and implemeting patient perspectives. ‘Financers’ provide financial resources. ‘Independents’ keep control over their collected samples and associated patient-related information with a strong interest in making autonomous decisions about its scientific use. A more detailed terminology for the involvement of POs as stakeholders facilitates the adressing of their aims and goals. Based on our results, the ‘independents’ subgroup is a promising candidate for future collaborations in scientific research. Additionally, we identified gaps in PO’s knowledge about PM and Big Data. Based on these findings, approaches can be developed to increase data and statistical literacy. This way, the full potential of stakeholder involvement of POs can be made accessible in discourses around PM and Big Data.

Empowering individual trait prediction using interactions for precision medicine

Background

One component of precision medicine is to construct prediction models with their predicitve ability as high as possible, e.g. to enable individual risk prediction. In genetic epidemiology, complex diseases like coronary artery disease, rheumatoid arthritis, and type 2 diabetes, have a polygenic basis and a common assumption is that biological and genetic features affect the outcome under consideration via interactions. In the case of omics data, the use of standard approaches such as generalized linear models may be suboptimal and machine learning methods are appealing to make individual predictions. However, most of these algorithms focus mostly on main or marginal effects of the single features in a dataset. On the other hand, the detection of interacting features is an active area of research in the realm of genetic epidemiology. One big class of algorithms to detect interacting features is based on the multifactor dimensionality reduction (MDR). Here, we further develop the model-based MDR (MB-MDR), a powerful extension of the original MDR algorithm, to enable interaction empowered individual prediction.

Results

Using a comprehensive simulation study we show that our new algorithm (median AUC: 0.66) can use information hidden in interactions and outperforms two other state-of-the-art algorithms, namely the Random Forest (median AUC: 0.54) and Elastic Net (median AUC: 0.50), if interactions are present in a scenario of two pairs of two features having small effects. The performance of these algorithms is comparable if no interactions are present. Further, we show that our new algorithm is applicable to real data by comparing the performance of the three algorithms on a dataset of rheumatoid arthritis cases and healthy controls. As our new algorithm is not only applicable to biological/genetic data but to all datasets with discrete features, it may have practical implications in other research fields where interactions between features have to be considered as well, and we made our method available as an R package (https://github.com/imbs-hl/MBMDRClassifieR).

Conclusions

The explicit use of interactions between features can improve the prediction performance and thus should be included in further attempts to move precision medicine forward.

Tailoring Atomoxetine Release Rate from DLP 3D-Printed Tablets Using Artificial Neural Networks: Influence of Tablet Thickness and Drug Loading

Various three-dimensional printing (3DP) technologies have been investigated so far in relation to their potential to produce customizable medicines and medical devices. The aim of this study was to examine the possibility of tailoring drug release rates from immediate to prolonged release by varying the tablet thickness and the drug loading, as well as to develop artificial neural network (ANN) predictive models for atomoxetine (ATH) release rate from DLP 3D-printed tablets. Photoreactive mixtures were comprised of poly(ethylene glycol) diacrylate (PEGDA) and poly(ethylene glycol) 400 in a constant ratio of 3:1, water, photoinitiator and ATH as a model drug whose content was varied from 5% to 20% (w/w). Designed 3D models of cylindrical shape tablets were of constant diameter, but different thickness. A series of tablets with doses ranging from 2.06 mg to 37.48 mg, exhibiting immediate- and modified-release profiles were successfully fabricated, confirming the potential of this technology in manufacturing dosage forms on demand, with the possibility to adjust the dose and release behavior by varying drug loading and dimensions of tablets. DSC (differential scanning calorimetry), XRPD (X-ray powder diffraction) and microscopic analysis showed that ATH remained in a crystalline form in tablets, while FTIR spectroscopy confirmed that no interactions occurred between ATH and polymers.

Hydroxypropyl Methylcellulose E15: A Hydrophilic Polymer for Fabrication of Orodispersible Film Using Syringe Extrusion 3D Printer

Extrusion-based 3D printing technology is a relatively new technique that has a potential for fabricating pharmaceutical products in various dosage forms. It offers many advantages over conventional manufacturing methods, including more accurate drug dosing, which is especially important for the drugs that require exact tailoring (e.g., narrow therapeutic index drugs). In this work, we have successfully fabricated phenytoin-loaded orodispersible films (ODFs) through a syringe extrusion 3D printing technique. Two different grades of hydroxypropyl methylcellulose (HPMC E5 and HPMC E15) were used as the film-forming polymers, and glycerin and propylene glycol were used as plasticizers. The 3D-printed ODFs were physicochemically characterized and evaluated for their mechanical properties and in vitro disintegration time. Then, the optimum printed ODFs showing good mechanical properties and the fastest disintegration time were selected to evaluate their drug content and dissolution profiles. The results showed that phenytoin-loaded E15 ODFs demonstrated superior properties when compared to E5 films. It demonstrated a fast disintegration time in less than 5 s and rapidly dissolved and reached up to 80% of drug release within 10 min. In addition, it also exhibited drug content uniformity within United States Pharmacopeia (USP) acceptable range and exhibited good mechanical properties and flexibility with low puncture strength, low Young’s modulus and high elongation, which allows ease of handling and application. Furthermore, the HPMC E15 printing dispersions with suitable concentrations at 10% w/v exhibited a non-Newtonian (shear-thinning) pseudoplastic behavior along with good extrudability characteristics through the extrusion nozzle. Thus, HPMC E15 can be applied as a 3D printing polymer for a syringe extrusion 3D printer.

Patient-derived tumour models for personalized therapeutics in urological cancers

Preclinical knowledge of dysregulated pathways and potential biomarkers for urological cancers has undergone limited translation into the clinic. Moreover, the low approval rate of new anticancer drugs and the heterogeneous drug responses in patients indicate that current preclinical models do not always reflect the complexity of malignant disease. Patient-derived tumour models used in preclinical uro-oncology research include 3D culture systems, organotypic tissue slices and patient-derived xenograft models. Technological innovations have enabled major improvements in the capacity of these tumour models to reproduce the clinical complexity of urological cancers. Each type of patient-derived model has inherent advantages and limitations that can be exploited, either alone or in combination, to gather specific knowledge on clinical challenges and address unmet clinical needs. Nevertheless, few opportunities exist for patients with urological cancers to benefit from personalized therapeutic approaches. Clinical validation of experimental data is needed to facilitate the translation and implementation of preclinical knowledge into treatment decision making.

A Flexible, Microfluidic, Dispensing System for Screening Drug Combinations

It is known that in many cases a combination of drugs is more effective than single-drug treatments both for reducing toxicity and increasing efficacy. With the advent of organoid screens, personalised medicine has become possible for many diseases. Automated pipetting to well plates is the pharmaceutical industry standard for drug screening, but this is relatively expensive and slow. Here, a rotary microfluidic system is presented that can test all possible drug combinations at speed with the use of droplets. For large numbers of combinations, it is shown how the experimental scale is reduced by considering drug dilutions and machine learning. As an example, two cases are considered; the first is a three-ring and three radii configuration and the second is a four ring and forty-eight radii configuration. Between these two, all other cases are shown to be possible. The proposed commercial instrument is shown to be flexible, the user choosing which wells to fill and which driver-computational sub-routine to select. The major issues addressed here are the programming theory of the instrument and the reduction of droplets to be generated by drug dilutions and machine learning.

Clinical Decision Support May Link Multiple Domains to Improve Patient Care: Viewpoint

Integrating clinical decision support (CDS) across the continuum of population-, encounter-, and precision-level care domains may improve hospital and clinic workflow efficiency. Due to the diversity and volume of electronic health record data, complexity of medical and operational knowledge, and specifics of target user workflows, the development and implementation of comprehensive CDS is challenging. Additionally, many providers have an incomplete understanding of the full capabilities of current CDS to potentially improve the quality and efficiency of care delivery. These varied requirements necessitate a multidisciplinary team approach to CDS development for successful integration. Here, we present a practical overview of current and evolving applications of CDS approaches in a large academic setting and discuss the successes and challenges. We demonstrate that implementing CDS tools in the context of linked population-, encounter-, and precision-level care provides an opportunity to integrate complex algorithms at each level into a unified mechanism to improve patient management.

Movement behaviour patterns in patients with hip and/or knee osteoarthritis in the physical therapy setting: a cross-sectional study

Background

Osteoarthritis is one of the most common chronic joint diseases, mostly affecting the knee or hip through pain, joint stiffness and decreased physical functioning in daily life. Regular physical activity (PA) can help preserve and improve physical functioning and reduce pain in patients with osteoarthritis. Interventions aiming to improve movement behaviour can be optimized by tailoring them to a patients’ starting point; their current movement behaviour. Movement behaviour needs to be assessed in its full complexity, and therefore a multidimensional description is needed.

Objectives

The aim of this study was to identify subgroups based on movement behaviour patterns in patients with hip and/or knee osteoarthritis who are eligible for a PA intervention. Second, differences between subgroups regarding Body Mass Index, sex, age, physical functioning, comorbidities, fatigue and pain were determined between subgroups.

Methods

Baseline data of the clinical trial ‘e-Exercise Osteoarthritis’, collected in Dutch primary care physical therapy practices were analysed. Movement behaviour was assessed with ActiGraph GT3X and GT3X+ accelerometers. Groups with similar patterns were identified using a hierarchical cluster analysis, including six clustering variables indicating total time in and distribution of PA and sedentary behaviours. Differences in clinical characteristics between groups were assessed via Kruskall Wallis and Chi² tests.

Results

Accelerometer data, including all daily activities during 3 to 5 subsequent days, of 182 patients (average age 63 years) with hip and/or knee osteoarthritis were analysed. Four patterns were identified: inactive & sedentary, prolonged sedentary, light active and active. Physical functioning was less impaired in the group with the active pattern compared to the inactive & sedentary pattern. The group with the prolonged sedentary pattern experienced lower levels of pain and fatigue and higher levels of physical functioning compared to the light active and compared to the inactive & sedentary.

Conclusions

Four subgroups with substantially different movement behaviour patterns and clinical characteristics can be identified in patients with osteoarthritis of the hip and/or knee. Knowledge about these subgroups can be used to personalize future movement behaviour interventions for this population.

Trial registration

Dutch clinical trial registration number of e-Exercise Osteoarthritis: NTR4224.

3D Printing of Solid Oral Dosage Forms: Numerous Challenges With Unique Opportunities

Since the FDA approval of Spritam, there has been a growing interest in the application of 3D printing in pharmaceutical science. 3D printing is a method of manufacturing involving the layer-by-layer deposition of materials to create a final product according to a digital model. There are various techniques used to achieve this method of printing including the SLS, SLA, FDM, SSE and PB-inkjet printing. In biomanufacturing, bone and tissue engineering involving 3D printing to create scaffolds, while in pharmaceutics, 3D printing was applied in drug development, and the fabrication of drug delivery devices. This paper aims to review the use of some 3D printing techniques in the fabrication of oral solid dosage forms. FDM, SLA SLS, and PB-Inkjet printing processes were found suitable for the fabrication of oral solid dosage forms, though a great deal of the available research was focused on fused deposition modelling due to its availability and flexibility. Process parameters as well as strategies to control the characteristics of printed dosage forms are analysed and discussed. The review also presents the advantages and possible limitations of 3D printing of medicines.

'Precision' or 'personalized' psychiatry: different terms - same content?

Due to the increased lifetime prevalence and personal, social, and economic burden of mental disorders, psychiatry is in need of a significant change in several aspects of its clinical and research approaches. Over the last few decades, the development of personalized / precision medicine in psychiatry focusing on tailored therapies that fit each patient's unique individual, physiological, and genetic profile has not achieved the same results as those obtained in other branches, such as oncology. The long-awaited revolution has not yet surfaced. There are various explanations for this including imprecise diagnostic criteria, incomplete understanding of the molecular pathology involved, absence of available clinical tools and, finally, the characteristics of the patient. Since then, the co-existence of the two terms has sparked a great deal of discussion around the definition and differentiation between the two types of psychiatry, as they often seem similar or even superimposable. Generally, the two terminologies are used indiscriminately, alternatively, and / or separately, within the same scientific works. In this paper, an overview is provided on the overlap between the application and meaning of the terms 'precision psychiatry' and 'personalized psychiatry'.

Gender-associated differences in oral microbiota and salivary biochemical parameters in response to feeding

Saliva plays a key role in food absorption and digestion mainly due to both its enzymes and microbiota. The main objective of this study was to compare the oral microbiota and salivary parameters between men and women in response to feeding. To answer this question, we set up a pilot study on 10 male and 10 female subjects to examine the role of saliva in glycaemia physiology. Biological parameters and the microbiotal composition of saliva were analyzed in fasted and fed states. The results show that the level of blood glucose was not different between men and women in the fasted state (88.00 mg/dL ± 6.38 vs 87.00 mg/dL ±8.07, p = 0.9149) or in the fed state (102.44 mg/dL ± 14.03 vs 116.9 mg/dL ± 25, p = 0.1362). Free fatty acids (FFA 0.15 mmol/L ± 0.15 vs 0.07 mmol/L ± 0.07, p = 0,0078), cholesterol (0.53 mmol/L ± 0.30 vs 0.15 mmol/L ± 0.14, p < 0.0001), and total saliva proteins (13.2 g/L ± 4.31 vs 9.02 g/L ± 6.98, p = 0.0168) were decreased after feeding, as well as the saliva lipase (27.89 U/L ± 25.7 vs 12.28 U/L ± 4.85, p = 0.0126). A very significant increase in the relative abundance of Streptococcaceae (24.56 ± 9.32 vs 13.53 ± 7.47, p = 0.00055) and a decrease in Prevotellaceae (34.45 ± 9.30 vs 17.43 ± 9.03, p = 0.00055) were observed in the fed condition. When investigating gender-related differences in the fasted state, men showed higher levels of cholesterol (0.71 mmol/L ± 0.26 vs 0.40 mmol/L ± 0.27, p = 0.0329), FFA (0.25 mmol/L ± 0.18 vs 0.08 mmol/L ± 0.06, p = 0.0049), and triglycerides (0.24 mmol/L ± 0.15 vs 0.09 mmol/L ± 0.04, p = 0.006) than women. Finally, differences could be observed in saliva microbiota between men and women in the fasted condition but even more in the fed condition, where Porphyromonas and Capnocytophaga were overrepresented in the male salivary samples compared with female saliva. Thus, biological parameters and microbiota in saliva could be the signatures of the feeding conditions and sex gender status.

How to Address Uncertainty in Health Economic Discrete-Event Simulation Models: An Illustration for Chronic Obstructive Pulmonary Disease

Background. Evaluation of personalized treatment options requires health economic models that include multiple patient characteristics. Patient-level discrete-event simulation (DES) models are deemed appropriate because of their ability to simulate a variety of characteristics and treatment pathways. However, DES models are scarce in the literature, and details about their methods are often missing. Methods. We describe 4 challenges associated with modeling heterogeneity and structural, stochastic, and parameter uncertainty that can be encountered during the development of DES models. We explain why these are important and how to correctly implement them. To illustrate the impact of the modeling choices discussed, we use (results of) a model for chronic obstructive pulmonary disease (COPD) as a case study. Results. The results from the case study showed that, under a correct implementation of the uncertainty in the model, a hypothetical intervention can be deemed as cost-effective. The consequences of incorrect modeling uncertainty included an increase in the incremental cost-effectiveness ratio ranging from 50% to almost a factor of 14, an extended life expectancy of approximately 1.4 years, and an enormously increased uncertainty around the model outcomes. Thus, modeling uncertainty incorrectly can have substantial implications for decision making. Conclusions. This article provides guidance on the implementation of uncertainty in DES models and improves the transparency of reporting uncertainty methods. The COPD case study illustrates the issues described in the article and helps understanding them better. The model R code shows how the uncertainty was implemented. For readers not familiar with R, the model's pseudo-code can be used to understand how the model works. By doing this, we can help other developers, who are likely to face similar challenges to those described here.

Medical applications of clustered regularly interspaced short palindromic repeats (CRISPR/Cas) tool: A comprehensive overview

Since the discovery of the double helix and the introduction of genetic engineering, the possibility to develop new strategies to manipulate the genome has fascinated scientists around the world. Currently scientists have the knowledge andabilitytoedit the genomes. Several methodologies of gene editing have been established, all of them working like "scissor", creating double strand breaks at specific spots. The introduction of a new technology, which was adapted from the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas bacterial immune system, has revolutionized the genetic therapy field, as it allows a much more precise editing of gene than the previously described tools and, therefore, to prevent and treat disease in humans. This review aims to revisit the genome editing history that led to the rediscovery of the CRISPR/Cas technology and to explore the technical aspects, applications and perspectives of this fascinating, powerful, precise, simpler and cheaper technology in different fields.

Personalising surgical treatments for glaucoma patients

Surgical treatments for glaucoma have relied for decades on traditional filtering surgery such as trabeculectomy and, in more challenging cases, tubes. Antifibrotics were introduced to improve surgical success in patients at increased risk of failure but have been shown to be linked to a greater incidence of complications, some being potentially vision-threatening. As our understanding of glaucoma and its early diagnosis have improved, a more individualised management has been suggested. Recently the term "precision medicine" has emerged as a new concept of an individualised approach to disease management incorporating a wide range of individual data in the choice of therapeutic modalities. For glaucoma surgery, this involves evaluation of the right timing, individual risk factors, targeting the correct anatomical and functional outflow pathways and appropriate prevention of scarring. As a consequence, there is an obvious need for better knowledge of anatomical and functional pathways and for more individualised surgical approaches with new, less invasive and safer techniques allowing for earlier intervention. With the recent advent of minimally invasive glaucoma surgery (MIGS) a large number of novel devices have been introduced targeting potential new sites of the outflow pathway for lowering intraocular pressure (IOP). Their popularity is growing in view of the relative surgical simplicity and apparent lack of serious side effects. However, these new surgical techniques are still in an era of early experiences, short follow-up and lack of evidence of their superiority in safety and cost-effectiveness over the traditional methods. Each year several new devices are introduced while others are withdrawn from the market. Glaucoma continues to be the primary cause of irreversible blindness worldwide and access to safe and efficacious treatment is a serious problem, particularly in the emerging world where the burden of glaucoma-related blindness is important and concerning. Early diagnosis, individualised treatment and, very importantly, safe surgical management should be the hallmarks of glaucoma treatment. However, there is still need for a better understanding of the disease, its onset and progression, the functional and structural elements of the outflow pathways in relation to the new devices as well as their long-term IOP-lowering efficacy and safety. This review discusses current knowledge and the future need for personalised glaucoma surgery.

Analysis of the Efficacy of Cinnamon for Patients with Diabetes Mellitus Type II Based on Traditional Persian Medicine Syndrome Differentiation: A Randomized Controlled Trial

Background: Conflicting results have been obtained from the studies on the hypoglycemic effect of cinnamon in patients with diabetes mellitus type II (T2DM). Objectives: This research aimed at assessing the effect of applying the syndrome differentiation model based on traditional Persian medicine (TPM) to identify the patients who benefit more from cinnamon supplementation. Methods: This study was a randomized, triple-blind, placebo-controlled trial based on a parallel design. One hundred and forty eligible patients referring to the Diabetes Clinic of Yazd University of Medical Sciences, who were diagnosed with T2DM, were randomly divided into the cinnamon and placebo groups. Then, 500-mg capsules of cinnamon bark powder or placebo were administered to them twice a day for three months. All the participants completed a standard questionnaire for syndrome diagnosis in traditional Persian medicine (TPM). Fasting plasma glucose (FPG), glycated hemoglobin (HbA1C), fasting insulin (FI), and insulin resistance (IR), calorie intake, and physical activity were measured before and after the interventions. The glycemic outcomes were analyzed according to the TPM syndrome. Results: There was no statistically significant difference between the patients’ demographic and clinical features in the two groups. Glycemic indices were improved in patients receiving cinnamon supplementation compared to placebo group (-13.1 ± 1.7, -1.7 ± 1.9, P < 0.001 for change in FPG and -0.27 ± 0.039 vs. 0.001 ± 0.019, P < 0.001 for change in HbA1C respectively). All the outcomes were more improved in the patients with wet syndrome compared to dry ones, which was compatible with Persian syndrome differentiation (P < 0.05). Conclusions: Diabetic patients with wet syndrome based on TPM benefit more form cinnamon supplementation.

Genetic predisposition in type 2 diabetes: A promising approach toward a personalized management of diabetes

Diabetes mellitus, also known simply as diabetes, has been described as a chronic and complex endocrine metabolic disorder that is a leading cause of death across the globe. It is considered a key public health problem worldwide and one of four important non-communicable diseases prioritized for intervention through world health campaigns by various international foundations. Among its four categories, Type 2 diabetes (T2D) is the commonest form of diabetes accounting for over 90% of worldwide cases. Unlike monogenic inherited disorders that are passed on in a simple pattern, T2D is a multifactorial disease with a complex etiology, where a mixture of genetic and environmental factors are strong candidates for the development of the clinical condition and pathology. The genetic factors are believed to be key predisposing determinants in individual susceptibility to T2D. Therefore, identifying the predisposing genetic variants could be a crucial step in T2D management as it may ameliorate the clinical condition and preclude complications. Through an understanding the unique genetic and environmental factors that influence the development of this chronic disease individuals can benefit from personalized approaches to treatment. We searched the literature published in three electronic databases: PubMed, Scopus and ISI Web of Science for the current status of T2D and its associated genetic risk variants and discus promising approaches toward a personalized management of this chronic, non-communicable disorder.

Being Precise About Precision Medicine: What Should Value Frameworks Incorporate to Address Precision Medicine? A Report of the Personalized Precision Medicine Special Interest Group

Precision medicine is a dynamic area embracing a diverse and increasing type of approaches that allow the targeting of new medicines, screening programs or preventive healthcare strategies, which include the use of biologic markers or complex tests driven by algorithms also potentially taking account of patient preferences. The International Society for Pharmacoeconomics and Outcome Research expanded its current work around precision medicine to (1) describe the evolving paradigm of precision medicine with examples of current and evolving applications, (2) describe key stakeholders perspectives on the value of precision medicine in their respective domains, and (3) define the core factors that should be considered in a value assessment framework for precision medicine. With the ultimate goal of improving health of well-defined patient groups, precision medicine will affect all stakeholders in the healthcare system at multiple levels spanning the individual perspective to the societal perspective. For an efficient, timely and practical precision medicine value assessment framework, it will be important to address these multiple perspectives through building consensus among the stakeholders for robust procedures and measures of value aspects, including performance of precision mechanism; aligned reimbursement processes of precision mechanism and subsequent treatment; transparent expectations for evidence requirements and study designs adequately matched to the intended use of the precision mechanism and to the smaller target patient populations; recognizing the potential range of value-generation such as ruling-in and ruling-out decisions.

Artificial Intelligence in Obstetrics and Gynaecology: Is This the Way Forward?

An increasing trend in funding towards artificial intelligence (AI) research in medicine has re-animated huge expectations for future applications. Obstetrics and gynaecology remain highly litigious specialities, accounting for a large proportion of indemnity payments due to poor outcomes. Several challenges have to be faced in order to improve current clinical practice in both obstetrics and gynaecology. For instance, a complete understanding of fetal physiology and establishing accurately predictive antepartum and intrapartum monitoring are yet to be achieved. In gynaecology, the complexity of molecular biology results in a lack of understanding of gynaecological cancer, which also contributes to poor outcomes. In this review, we aim to describe some important applications of AI in obstetrics and gynaecology. We also discuss whether AI can lead to a deeper understanding of pathophysiological concepts in obstetrics and gynaecology, allowing delineation of some grey zones, leading to improved healthcare provision. We conclude that AI can be used as a promising tool in obstetrics and gynaecology, as an approach to resolve several longstanding challenges; AI may also be a means to augment knowledge and assist clinicians in decision-making in a variety of areas in obstetrics and gynaecology.

Mass spectrometry based proteomics and metabolomics in personalized oncology

Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.

Latent Profiles of Health and Reproductive Risk and Protective Factors among Women in Appalachia

Women who use opiates and are involved in the criminal justice system in Appalachia may be prone to adverse health outcomes. In this study, we performed a latent class analysis of risk and protective factors on 400 drug-using women recruited from rural, Appalachian jails. A two-profile solution best fit the data. Both profiles evinced low levels of condom use, reproductive and physical health screens, and STD history. However, the primary substantive difference between the profiles was partner risk behavior: the higher risk class had main male partners with histories of injection drug use and incarceration. Results suggest that interventions need to be tailored to unique profiles of risk and protective factors, which should include taking partner risk into consideration.

The Seated Postural & Reaching Control Test in Cerebral Palsy: A Validation Study

Aim: Children with moderate-severe cerebral palsy (CP) show postural control deficits that affect their daily activities, like reaching. The Seated Postural and Reaching Control test (SP&R-co) was developed to address the need for clinical measures that objectively identify dimensions of postural imbalance and corresponding reaching limitations in children with CP.Methods: SP&R-co documentation was designed for test validity and rater training. Rater and internal consistency were examined using Cronbach's α. Reference SP&R-co score sheets of children and rater's scores were used for absolute item-by-item, average inter-rater, and intra-rater reliability. Motor classification systems and performance tests were used for construct and concurrent validity.Results: The SP&R-co scoring showed acceptable-good consistency (α = 0.76-0.84). Interrelatedness of SP&R-co items was good-excellent (α = 0.82-0.97). The raters demonstrated fair, good, and excellent item-by-item reliability (ICC = 0.41-0.92). Inter-rater and intra-rater reliability of SP&R-co dimensions were good-excellent (ICC = 0.68-0.86 and ICC = 0.64-0.95, respectively). Construct and concurrent validity showed moderate-excellent correlations (r = 0.49-0.88).Conclusions: Results provide evidence that the SP&R-co is a reliable and valid test for therapists to objectively examine and quantify seated postural and reaching control in children with CP.