Cost-effectiveness comparison between blood biomarkers and conventional tests in Alzheimer's disease diagnosis.

Dementia management has evolved with drugs such as lecanemab, shifting management from palliative care to early diagnosis and intervention. However, the administration of these drugs presents challenges owing to the invasiveness, high cost and limited availability of amyloid-PET and cerebrospinal fluid tests for guiding drug administration. Our manuscript explores the potential of less invasive blood biomarkers as a diagnostic method, with a cost-effectiveness analysis and a comparison with traditional tests. Our findings suggest that blood biomarkers are a cost-effective alternative, but with lower accuracy, indicating the need for multiple specific biomarkers for precision. This underscores the importance of future research on new blood biomarkers and their clinical efficacy.

Innovation Process and Industrial System of US Food and Drug Administration-Approved Software as a Medical Device: Review and Content Analysis.

BACKGROUND: There has been a surge in academic and business interest in software as a medical device (SaMD). SaMD enables medical professionals to streamline existing medical practices and make innovative medical processes such as digital therapeutics a reality. Furthermore, SaMD is a billion-dollar market. However, SaMD is not clearly understood as a technological change and emerging industry. OBJECTIVE: This study aims to review the landscape of SaMD in response to increasing interest in SaMD within health systems and regulation. The objectives of the study are to (1) clarify the innovation process of SaMD, (2) identify the prevailing typology of such innovation, and (3) elucidate the underlying mechanisms driving the SaMD innovation process. METHODS: We collected product information on 581 US Food and Drug Administration-approved SaMDs from the OpenFDA website and 268 company profiles of the corresponding manufacturers from Crunchbase, Bloomberg, PichBook.com, and other company websites. In addition to assessing the metadata of SaMD, we used correspondence and business process analysis to assess the distribution of intended use and how SaMDs interact with other devices in the medical process. RESULTS: The current SaMD industry is highly concentrated in medical image processing and radiological analysis. Incumbents in the medical device industry currently lead the market and focus on incremental innovation, whereas new entrants, particularly startups, produce more disruptive innovation. We found that hardware medical device functions as a complementary asset for SaMD, whereas how SaMD interacts with the complementary asset differs according to its intended use. Based on these findings, we propose a regime map that illustrates the SaMD innovation process. CONCLUSIONS: SaMD, as an industry, is nascent and dominated by incremental innovation. The innovation process of the present SaMD industry is shaped by data accessibility, which is key to building disruptive innovation.

Increasing orphan drug loss in Japan: Trends and R&D strategy for rare diseases.

Rare disease (RD) patients face significant unmet therapeutic needs worldwide. However, orphan drugs approved in the United States, but not approved or developed in Japan, have increased rapidly with recently increasing US approvals, indicating greater RD drug loss in Japan. US/EU-based startups have become key players in RD drug R&D, significantly contributing to this drug loss trend. They successfully develop drugs in the United States by combining in-licensing with in-house drug discovery. Out-licensing to Japanese companies or large pharma is critical for expansion into Japan, with successes attributed to drug innovation, target indications, and transactional capabilities. These findings highlight the need to foster partnerships with startups and cultivate an ecosystem in Japan that nurtures local startups, to address drug loss and ensure access to promising drugs.

Global biomarker trends in Alzheimer's research: A bibliometric analysis.

Alzheimer's disease (AD) has no effective treatment, although antibody drugs targeting beta-amyloid, mainly aducanumab, have produced useful clinical results. Biomarkers can be used to determine drug regimens effectively and to monitor the effects of drugs. A concept in which biomarkers reflect disease states is emerging. Although several AD biomarker studies have been reported, measurement methods and target molecules are still being validated, and various biomarkers are being explored. This study analyzed trends in research on AD biomarkers using bibliometric methods, revealing an exponential increase in research reports in this field, with the US most active in research. Analysis of the 'Burst' biomarkers using CiteSpace revealed that networks centered on authors, rather than networks among countries, drive new research trends in this area.

Strategic trends of pharmaceutical companies: A growth model through regional focus and inter-regional alliances.

Pharmaceutical companies face challenges in business continuity resulting from declining research and development productivity. This study examines the relationship between two strategic pillars: region and therapeutic area, while considering company size. The results indicate that a therapeutic area focus is an effective strategy for small/medium-sized companies, whereas a regional focus is effective for larger companies. These findings highlight the limitations of the traditional global pharmaceutical model from 2004 to 2018 and aim to contribute to the future corporate strategic planning of these companies.

Optimizing the Relationship between Regulation and Innovation in Dietary Supplements: A Case Study of Food with Function Claims in Japan.

Regulation has long been a counterpart of innovation in the health care industry, and recent cases have demonstrated that appropriately designed regulations can both coexist with and promote innovation. This study is the first study to explore how the regulatory environment affected the innovation process during the transition of the regulations for functional foods in Japan by examining quantitatively the impact of the foods with function claims (FFC) system on industry, companies, and products. Based on a dataset of Japanese dietary supplement manufacturing companies (n = 169) and their products (n = 731) in 2019, we found that companies that have newly entered the FFC system are smaller in scale than existing companies (p < 0.01, Wilcoxon rank sum test). We also found that companies with FFC products have larger revenue growth (p = 0.01). A multiple regression analysis revealed that FFC product sales increased with in-house clinical testing (coefficient: 26.8, p < 0.0001), diverse active ingredients (coefficient: 7.6, p < 0.001), and the claim of new functions (coefficient: 10.2, p < 0.05). These results suggested that the FFC system facilitated the market entry of small and mid-size enterprises and promoted the creation of high-value products through innovative company efforts.

Recent trends in interorganizational deal networks in pharmaceutical and biotechnology industries.

While there have been trends in drug discovery from small molecules to new chemical modalities since the large mergers and acquisitions (M&A) of pharmaceutical companies in the late 2000s, trends in interorganizational deal networks have not been well addressed. We investigated the changing trends in interorganizational deals in the pharmaceutical and biotechnology industries. The results demonstrated that there have been changing trends, including a growing number of spinouts from academia and M&A in the United States and Europe. These findings indicates that the traditional network in which large pharmaceutical companies drove drug discovery output has changed, and interorganizational deals among diverse players have become more active.

The gap between development and manufacturing in gene therapy: Strategic options for overcoming traps.

Gene therapy has been one of the most promising therapeutic approaches in recent years. This study analyzed a research and development (R&D) system for adeno-associated virus (AAV)-based gene therapies, and confirmed that there was a gap between the development and manufacturing capabilities. Although a start-up company that has no academic or manufacturing facilities can begin the clinical development process, it cannot successfully continue development activities without forming alliances and capital investment or, at a certain stage, without appropriate manufacturing and marketing strategies. We reviewed a series of case studies to categorize the acquisition patterns of pharmaceutical companies that are engaged in AAV gene therapy. These results provide insights into the R&D structures for AAV gene therapies from a technological management perspective.

Determination of Waste Management Workers' Physical and Psychological Load: A Cross-Sectional Study Using Biometric Data.

Waste management workers experience high stress and physical strain in their work environment, but very little empirical evidence supports effective health management practices for waste management workers. Hence, this study investigated the effects of worker characteristics and biometric indices on workers' physical and psychological loads during waste-handling operations. A biometric measurement system was installed in an industrial waste management facility in Japan to understand the actual working conditions of 29 workers in the facility. It comprised sensing wear for data collection and biometric sensors to measure heart rate (HR) and physical activity (PA) based on electrocardiogram signals. Multiple regression analysis was performed to evaluate significant relationships between the parameters. Although stress level is indicated by the ratio of low frequency (LF) to high frequency (HF) or high LF power in HR, the results showed that compared with workers who did not handle waste, those who did had lower PA and body surface temperature, higher stress, and lower HR variability parameters associated with higher psychological load. There were no significant differences in HR, heart rate interval (RRI), and workload. The psychological load of workers dealing directly with waste was high, regardless of their PA, whereas others had a low psychological load even with high PA. These findings suggest the need to promote sustainable work relationships and a quantitative understanding of harsh working conditions to improve work quality and reduce health hazards.

A Bibliometric Analysis of Wearable Device Research Trends 2001-2022-A Study on the Reversal of Number of Publications and Research Trends in China and the USA.

In recent years, Wearable Devices have been used in a wide variety of applications and fields, but because they span so many different disciplines, it is difficult to ascertain the intellectual structure of this entire research domain. No review encompasses the whole research domain related to Wearable Devices. In this study, we collected articles on wearable devices from 2001 to 2022 and quantitatively organized them by bibliometric analysis to clarify the intellectual structure of this research domain as a whole. The cluster analysis, co-occurrence analysis, and network centrality analysis were conducted on articles collected from the Web of Science. As a result, we identified one cluster that represents applied research and two clusters that represent basic research in this research domain. Furthermore, focusing on the top two countries contributing to this research domain, China and the USA., it was confirmed that China is extremely inclined toward basic research and the USA. toward applied research, indicating that applied and basic research are in balance. The basic intellectual structure of this cross-sectional research domain was identified. The results summarize the current state of research related to Wearable Devices and provide insight into trends.

Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model.

The unprecedented development of information and communication technologies has opened up immense possibilities in the field of health care. Mobile health (mHealth) is gaining increasing attention as an important technology for solving health-related problems. Although a high rate of smartphone usage among young people in Japan has been identified, smartphone usage for health management is not high. As Japanese youth are important potential users of mHealth, it is necessary to explore theories that influence the behavioral intention of Japanese youth to adopt mHealth. This study conducted a questionnaire survey in a Japanese university and collected 233 valuable responses. This study was adapted and extended from the unified theory of acceptance and use of technology (UTAUT) model to measure eight constructs: health consciousness, social influence, facilitation conditions, perceived risk, trust, performance expectancy, effort expectancy, and behavioral intention. Structural equation modeling was used for hypothesis testing. We found that trust, performance expectancy, and effort expectancy directly influenced the behavioral intention to use mHealth. Health consciousness and social influence indirectly influence behavioral intention through trust and performance expectancy. Facilitation conditions indirectly influenced behavioral intention through effort expectancy. This study makes a vital theoretical contribution to policymakers and product developers for the further diffusion of mHealth among young people in Japan.

A Layered Adopter-Structure Model for the Download of COVID-19 Contact Tracing Apps: A System Dynamics Study for mHealth Penetration.

(1) Background: Contact tracing and notification apps for coronavirus disease 2019 (COVID-19) are installed on smartphones and are intended to detect contact with another person's device. A high installation rate is important for these apps to enable them to be effective countermeasures against the silent transmission of diseases. However, the installation rate varies among apps and regions and the penetration dynamics of these applications are unclear. (2) Methods: The download behavior of contact tracing applications was investigated using publicly available datasets. The increase in downloads was modeled using a system dynamics model derived from the product growth model. (3) Results: The imitation effects present in the traditional product growth model were not observed in COVID-19 contact tracing apps. The system dynamics model, without the imitation effect, identified the downloads of the Australian COVIDSafe app. The system dynamics model, with a layered adopter, identified the downloads of the Japanese tracing app COCOA. The spread of COVID-19 and overall anti-COVID-19 government intervention measures in response to the spread of infection seemed to result in an increase in downloads. (4) Discussion: The suggested layered structure of users implied that individualized promotion for each layer was important. Addressing the issues among users who are skeptical about adoption is pertinent for optimal penetration of the apps.

Living Lab for Citizens' Wellness: A Case of Maintaining and Improving a Healthy Diet under the COVID-19 Pandemic.

The establishment and implementation of a healthy lifestyle is fundamental to public health and is an important issue for working-aged people, as it affects not only them but also the future generations. However, due to the COVID-19 pandemic and associated behavioural restrictions, lifestyles have altered, and, in certain environments, significantly worsened. In the present study, we conducted a project to improve the intestinal environment by focussing on the dietary habits of participants, utilising the living laboratory as a social technology to explore how to adapt to this drastic environmental change. We held eight workshops for voluntary participants and implemented a self-monitoring process of recording dietary behaviours (n = 78) and testing the intestinal environment (n = 14). Through this initiative, we developed a personalised wellness enhancement programme based on collaboration with multiple stakeholders and a framework for using personal data for research and practical purposes. These results provide an approach for promoting voluntary participation and behavioural changes among people, especially under the COVID-19 pandemic, as well as a practical basis for the government, academia, and industry to intervene effectively in raising people's awareness of health and wellness.

The Significance of Alliance Networks in Research and Development of Digital Health Products for Diabetes: Observational Study.

BACKGROUND: Digital health has been advancing owing to technological progress by means of smart devices and artificial intelligence, among other developments. In the field of diabetes especially, there are many active use cases of digital technology supporting the treatment of diabetes and improving lifestyle. In the innovation ecosystem, new alliance networks are formed not only by medical device companies and pharmaceutical companies, but also by information and communications technology companies and start-ups. While understanding and utilizing the network structure is important to increase the competitive advantage of companies, there is a lack of previous research describing the structure of alliance networks and the factors that lead to their formation in digital health. OBJECTIVE: The aim of this study was to explore the significance of alliance networks, focusing on digital health for diabetes, in effectively implementing processes, from the research and development of products or services to their launch and market penetration. METHODS: First, we listed the companies and contracts related to digital health for diabetes, visualized the change in the number of companies and the connections between companies in each industry, and analyzed the overview of the network. Second, we calculated the degree, betweenness centrality, and eigenvector centrality of each company in each year. Next, we analyzed the relationship between network centrality and market competitiveness by using annual sales as a parameter of company competitiveness. We also compared the network centrality of each company by industry or headquarters location (or both) and analyzed the characteristics of companies with higher centrality. Finally, we analyzed the relationship between network centrality and the number of products certified or approved by the US Food and Drug Administration. RESULTS: We found the degree centrality of companies was correlated with an increase in their sales. The betweenness and eigenvector centralities of medical devices companies located in the United States were significantly higher than those outside the United States (P=.04 and .005, respectively). Finally, the degree, betweenness, and eigenvector centralities were correlated with an increase in the number of Class III, but not of Class I nor II, medical device products. CONCLUSIONS: These findings give rise to new insights into industry ecosystem for digital health and its requirement and expect a contribution to research and development practices in the field of digital health.

Exploring the Shift in International Trends in Mobile Health Research From 2000 to 2020: Bibliometric Analysis.

BACKGROUND: Smartphones have become an integral part of our lives with unprecedented popularity and a diverse selection of apps. The continuous upgrading of information technology has also enabled smartphones to display great potential in the field of health care. OBJECTIVE: We aimed to determine the future research direction of mobile health (mHealth) by analyzing its research trends and latest research hotspots. METHODS: This study collected mHealth-related literature published between 2000 and 2020 from the Web of Science database. Descriptive statistics of publication trends of mHealth research were determined by analyzing the annual number of publications in the literature and annual number of publications by country. We constructed visualization network maps of country (or regional) collaborations and author-provided keyword co-occurrences, as well as overlay visualization maps of the average publication year of author-provided keywords to analyze the hotspots and research trends in mHealth research. RESULTS: In total, 12,593 mHealth-related research papers published between 2000 and 2020 were found. The results showed an exponential growth trend in the number of annual publications in mHealth literature. JMIR mHealth and uHealth, the Journal of Medical Internet Research, and JMIR Research Protocols were the 3 top journals with respect to number of publications. The United States remained the leading contributor to the literature in this area (5294/12,593, 42.0%), well ahead of other countries and regions. Other countries and regions also showed a clear trend of annual increases in the number of mHealth publications. The 4 countries with the largest number of publications-the United States, the United Kingdom, Canada, and Australia-were found to cooperate more closely. The rest of the countries and regions showed a clear geographic pattern of cooperation. The keyword co-occurrence analysis of the top 100 authors demonstrated 5 clusters, namely, development of mHealth medical technology and its application to various diseases, use of mHealth technology to improve basic public health and health policy, mHealth self-health testing and management in daily life, adolescent use of mHealth, and mHealth in mental health. The research trends revealed a gradual shift in mHealth research from health policy and improving public health care to the development and social application of mHealth technologies. CONCLUSIONS: To the best of our knowledge, the most current bibliometric analysis dates back to 2016. However, the number of mHealth research published between 2017 and 2020 exceeds the previous total. The results of this study shed light on the latest hotspots and trends in mHealth research. These findings provide a useful overview of the development of the field; they may also serve as a valuable reference and provide guidance for researchers in the digital health field.

Psychological Effects of Heart Rate and Physical Vibration on the Operation of Construction Machines: Experimental Study.

BACKGROUND: A construction method has emerged in which a camera is installed around a construction machine, and the operator remotely controls the machine while synchronizing the vibration of the machine with the images seen from the operator's seat using virtual reality (VR) technology. Indices related to changes in heart rate (HR) and physical vibration, such as heart rate variability (HRV) and multiscale entropy (MSE), can then be measured among the operators. As these indices are quantitative measures of autonomic regulation in the cardiovascular system, they can provide a useful means of assessing operational stress. OBJECTIVE: In this study, we aimed to evaluate changes in HR and body vibration of machine operators and investigate appropriate methods of machine operation while considering the psychological load. METHODS: We enrolled 9 remote operators (18-50 years old) in the experiment, which involved 42 measurements. A construction machine was driven on a test course simulating a construction site, and three patterns of operation-riding operation, remote operation using monitor images, and VR operation combining monitor images and machine vibration-were compared. The heartbeat, body vibration, and driving time of the participants were measured using sensing wear made of a woven film-like conductive material and a three-axis acceleration measurement device (WHS-2). We used HRV analysis in the time and frequency domains, MSE analysis as a measure of the complexity of heart rate changes, and the ISO (International Standards Organization) 2631 vibration index. Multiple regression analysis was conducted to model the relationship among the low frequency (LF)/high frequency (HF) HRV, MSE, vibration index, and driving time of construction equipment. Efficiency in driving time was investigated with a focus on stress reduction. RESULTS: Multiple comparisons conducted via the Bonferroni test and Kruskal-Wallis test showed statistically significant differences (P=.05) in HRV-LF/HF, the vibration index, weighted acceleration, motion sickness dose value (MSDVz), and the driving time among the three operation patterns. The riding operation was found to reduce the driving time of the machine, but the operation stress was the highest in this case; operation based on the monitor image was found to have the lowest operation stress but the longest operation time. Multiple regression analysis showed that the explanatory variables (LH/HF), RR interval, and vibration index (MSDVz by vertical oscillation at 0.5-5 Hz) had a negative effect on the driving time (adjusted coefficient of determination R2=0.449). CONCLUSIONS: A new method was developed to calculate the appropriate operating time by considering operational stress and suppressing the physical vibration within an acceptable range. By focusing on the relationship between psychological load and physical vibration, which has not been explored in previous studies, the relationship of these variables with the driving time of construction machines was clarified.

Superiority of Mild Interventions against COVID-19 on Public Health and Economic Measures.

(1) Background: During the global spread of COVID-19, Japan has been among the top countries to maintain a relatively low number of infections, despite implementing limited institutional interventions and its high population density. This study investigated how limited intervention policies have affected public health and economic conditions in the COVID-19 context and aimed to gain insight into the effective and sustainable measures against new infectious diseases in densely inhabited areas. (2) Methods: A system dynamics approach was employed. Qualitative causal loop analysis and stock and quantitative flow model analysis were performed, using a Tokyo Metropolitan area dataset. (3) Results: A causal loop analysis suggested that there were risks in prematurely terminating such interventions. Based on this result and the subsequent quantitative modeling, we found that the short-term effectiveness of a short-term pre-emptive stay-at-home request caused a resurgence in the number of positive cases, whereas an additional request provided a limited negative add-on effect for economic measures (e.g., number of electronic word-of-mouth communications and restaurant visits). (4) Conclusions: These findings suggest the superiority of a mild and continuous intervention as a long-term countermeasure under epidemic pressures when compared with strong intermittent interventions.

Regulations, Open Data and Healthcare Innovation: A Case of MSK-IMPACT and Its Implications for Better Cancer Care.

This study investigated a case of Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT), a tumor profiling test approved by the U.S. Food and Drug Administration (FDA) in 2017, to examine what factors would contribute to healthcare innovation. First, we set the following three parameters to observe cases: (i) the FDA regulatory reforms, (ii) early application of new technologies, such as next-generation sequencing (NGS), to both research and clinical settings, and (iii) accumulation of open data. Then, we performed a comparative analysis of MSK-IMPACT with FoundationOne CDx and Oncomine Dx Target Test, both of which were FDA-approved tumor profiling tests launched in 2017. As a result, we found that MSK-IMPACT secures neutrality as a non-profit organization, achieves the active incorporation of basic research results, and performs superiorly in clinical operations, such as patient enrollment. On the contrary, we confirmed that FoundationOne CDx was the most prominent case in terms of the number of new drugs and expanded indications approved in which the FDA's expedited approval programs were considerably utilized. Consequently, to uncover the full potential of MSK-IMPACT, it is suggested that more intersectoral collaborative activities between various healthcare stakeholders, in particular, pharmaceutical companies, for driving clinical development must be carried out based on an organizational framework that facilitates collaboration.

Dynamic Collaborations for the Development of Immune Checkpoint Blockade Agents.

We studied the overview of drug discovery and development to understand the recent trends and potential success factors of interorganizational collaboration by reviewing 1204 transactions performed until 2019 for 107 anticancer drugs approved by the US Food and Drug Administration (FDA) from 1999 to 2018. Immune checkpoint blockade was found to be a significantly active area in interorganizational transactions, especially the number of alliances, compared with other mechanisms of action of small molecules and biologics for cancer treatment. Furthermore, the analysis of pembrolizumab and nivolumab showed that the number of approved indications for these two drugs has been rapidly expanding since their first approval in 2014. Examination of the acquisitions and alliances regarding pembrolizumab and nivolumab showed that many combination partners were developed by US-based biotechnology or start-up companies, the majority of which were biologics. These findings suggest that immune checkpoint blockade is a paradigm for cancer treatment, resulting in huge product sales and continuous indication expansion. Additionally, interorganizational collaboration, especially trial collaboration, is a strategic approach for the development of immune checkpoint blockade agents. The translation of these empirical practices to new drug candidates is expected for the research and development of innovative drugs in the future.

Age-Dependent Influence of Intrinsic and Extrinsic Motivations on Construction Worker Performance.

The increasing sophistication and complexity of construction technology have also increased workers' physical risk and psychological stress. This study examined the relationships between health risks, work motivation, and productivity as perceived by construction workers. A hypothetical model of worker perceptions, and the psychological factors influencing these perceptions, was developed. A total of 324 construction workers at a Japanese construction company participated in the study and were divided into two groups: younger (45 years of age and below) and older adults (46 years of age and above). Data were collected using a questionnaire. The differences between the age groups were analyzed with regard to their perceptions of health risks, motivation, work skills, and productivity. Both younger and older workers were affected by intrinsic motivations and extrinsic motivations, but the effect of these motivations on work performance differed depending on age. Higher health risks are anticipated to affect the work motivation and productivity perceptions of older workers. The proposed model and findings of this study contribute to understanding worker motivations and have important implications for labor management of construction projects. By addressing construction workers' intrinsic (e.g., interest) and extrinsic (e.g., reward) motivations, it is possible to sustainably improve project productivity.