Category: 3. Business

Elliot Deady/BBC

Elliot Deady/BBC

Treatment with adjuvant nivolumab (Opdivo) led to a sustained disease-free survival (DFS) advantage compared with placebo in patients with muscle-invasive urothelial carcinoma (MIUC) following radical radical resection, according to 5-year follow-up findings from the phase 3 CheckMate 274 trial (NCT02632409) presented at the 2025 ESMO Congress and published concurrently in Annals of Oncology.

Among all randomly assigned patients, the median DFS was 21.9 months (95% CI, 18.8-36.9) with nivolumab vs 11.0 months (95% CI, 8.3-16.6) with placebo (HR, 0.74; 95% CI, 0.61-0.90). In each respective arm, the DFS rates were 45.1% vs 35.3% at 36 months, 41.2% vs 33.0% at 48 months, and 36.4% vs 30.9% at 60 months. In patients with a PD-L1 expression of 1% or higher, the median DFS was 55.5 months (95% CI, 25.8-66.5) in the nivolumab arm and 8.4 months (95% CI, 5.6-20.0) in the placebo arm (HR, 0.58; 95% CI, 0.42-0.79). The DFS rates in the PD-L1 expression of 1% or higher population were 56.6% vs 33.1% at 36 months, 53.9% vs 32.2% at 48 months, and 46.8% vs 32.2% at 60 months in the experimental and placebo arms, respectively.

Among all randomly assigned patients with muscle-invasive bladder cancer (MIBC), the median DFS was 25.6 months (95% CI, 19.2-42.6) with nivolumab and 9.4 months (95% CI, 7.4-13.7) with placebo (HR, 0.66; 95% CI, 0.53-0.81). The 36-month, 48-month, and 60-month DFS rates were 46.8% vs 32.3%, 42.8% vs 30.2%, and 36.7% vs 28.9%, respectively. Among patients with MIBC and a PD-L1 expression of at least 1%, the median DFS in each arm was 59.4 months (95% CI, 39.5-not evaluable [NE]) and 8.3 months (95% CI, 4.7-16.6); the DFS rates were 60.3% vs 30.7% at 36 months, 57.0% vs 30.7% at 48 months, and 48.3% vs 30.7% at 60 months (HR, 0.50; 95% CI, 0.36-0.72).

In patients with MIBC and prior receipt of cisplatin, the median DFS was 19.6 months (95% CI, 15.6-48.2) with nivolumab compared with 8.3 months (95% CI, 5.6-11.2) using placebo (HR, 0.63; 95% CI, 0.47-0.84). The DFS rates in each arm were 46.8% vs 29.3% at 36 months, 42.6% vs 27.8% at 48 months, and 33.4% vs 26.2% at 60 months. Among those without prior receipt of cisplatin for MIBC, data showed a median DFS of 25.9 months (95% CI, 19.2-55.5) vs 13.7 months (95% CI, 8.2-22.1) in each respective arm (HR, 0.70; 95% CI, 0.52-0.95). The DFS rates in each arm across this population were 46.6% vs 35.6% at 36 months, 42.8% vs 32.9% at 48 months, and 39.8% vs 31.9% at 60 months.

“With 5 years [of] follow-up, adjuvant nivolumab continues to show DFS benefits vs placebo in all [randomly assigned] patients and in patients with tumors PD-L1 [expression] greater than or equal to 1%. The benefits of nivolumab extended to the secondary and exploratory end points,” presenting investigator Matthew Galsky, MD, professor of Medicine (Hematology and Medical Oncology), director of Genitourinary Medical Oncology, co-director of the Center of Excellence for Bladder Cancer, and associate director for Translational Research at The Tisch Cancer Institute, stated in the presentation. “Overall, these results provide additional support for adjuvant nivolumab as a standard treatment for patients with high-risk MIUC after radical surgery.”

In the double-blind, multicenter phase 3 CheckMate 274 trial, 709 patients with high-risk MIUC were randomly assigned 1:1 to receive nivolumab at 240 mg intravenously every 2 weeks (n = 353) or matched placebo (n = 356). Investigators stratified patients by tumor PD-L1 expression status, receipt of prior neoadjuvant cisplatin-containing chemotherapy, and nodal status.

The trial’s primary end point was DFS in all randomly assigned patients and among those with a PD-L1 expression status of at least 1%. Secondary end points included overall survival (OS) and disease-specific survival (DSS). Safety was an exploratory end point.

Interim OS data showed that among all randomly assigned patients, the median OS was 75.0 months (95% CI, 56.7-NE) with nivolumab and 50.1 months (95% CI, 38.0-72.1) with placebo (HR, 0.83; 95% CI, 0.67-1.02). The 36-month, 48-month, and 60-month OS rates in each arm were 65.3% vs 57.7%, 59.5% vs 51.3%, and 54.6% vs 47.1%, respectively. Among those with PD-L1 expression of 1% or higher, the median OS was not reached (NR; 95% CI, 70.0-NE) vs 59.4 months (95% CI, 29.1-NE), with respective rates of 73.8% vs 56.5% at 36 months, 69.6% vs 51.6% at 48 months, and 64.3% vs 49.9% at 60 months (HR, 0.63; 95% CI, 0.44-0.90).

Among all randomly assigned patients with MIBC, interim data showed a median OS of 61.2 months (95% CI, 48.2-NE) with nivolumab and 38.2 months (95% CI, 29.8-50.3) with placebo (HR, 0.73; 95% CI, 0.58-0.91). The OS rates in this population were 63.8% vs 53.1% at 36 months, 56.6% vs 45.9% at 48 months, and 51.3% vs 41.8% at 60 months. Among those with MIBC and PD-L1 expression in at least 1% of tumor cells, the median OS was NR (95% CI, 75.0-NE) vs 38.2 months (95% CI, 27.8-72.1) in the nivolumab and placebo arms, respectively (HR, 0.51; 95% CI, 0.35-0.76). The OS rates were 75.0% vs 53.3% at 36 months, 70.0% vs 47.4% at 48 months, and 64.8% vs 45.3% at 60 months.

In the overall population, the median DSS was NR (95% CI, 91.9-NE) with nivolumab and NR (95% CI, 52.1-NE) with placebo (HR, 0.79; 95% CI, 0.62-1.00). Data showed DSS rates of 71.7% vs 63.1% at 36 months, 66.7% vs 57.5% 48 months, and 63.0% vs 54.1% at 60 months. In patients with PD-L1 expression of 1% or higher, the median DSS in each arm was NR (95% CI, NE-NE) vs 92.1 months (95% CI, 54.4-NE); the DSS rates in each arm were 79.8% vs 64.3% at 36 months, 77.0% vs 59.6% at 48 months, and 74.0% vs 57.6% at 60 months (HR, 0.57; 95% CI, 0.37-0.87).

Among 709 randomly assigned patients, 133 (18.8%) underwent circulating tumor DNA (ctDNA) analysis; of these patients, 54 (40.6%) had evaluable ctDNA. The median DFS was 52.1 months (95% CI, 19.4-NE) in patients with undetectable ctDNA (n = 79) vs 5.0 months (95% CI, 2.8-6.5) among those with detectable ctDNA (n = 54; HR, 0.30; 95% CI, 0.18-0.48). Additionally, the median OS was NR (95% CI, 62.0-NE) and 28.2 months (95% CI, 19.4-36.1) among patients with undetectable and detectable ctDNA, respectively (HR, 0.44; 95% CI, 0.25-0.76).

Among patients with detectable ctDNA, nivolumab conferred improvements in DFS (HR, 0.35; 95% CI, 0.18-0.66) and OS compared with placebo (HR, 0.41; 95% CI, 0.20-0.83). In those with undetectable ctDNA, numerical improvements occurred with nivolumab for DFS (HR, 0.99; 95% CI, 0.51-1.93) and OS (HR, 0.87; 95% CI, 0.41-1.84). Galsky noted that conclusions in exploratory post hoc ctDNA analyses were limited due to a small sample size.

Investigators observed no new safety signals in the latest analysis for CheckMate 274. Any-grade treatment-related adverse effects (TRAEs) occurred in 79% and 56% of the nivolumab and placebo arms, respectively; grade 3 or higher toxicities affected 18% vs 7%. The most common any-grade TRAEs in each arm included pruritus (23% vs 11%), fatigue (17% vs 12%), diarrhea (17% vs 11%), rash (15% vs 6%), and lipase increases (10% vs 6%).

Disclosures: Galsky noted advisory board/consul associations with AbbVie, Alligator Bioscience, Analog Devices, ARS Pharmaceuticals, Asieris Pharmaceuticals, AstraZeneca, Basilea Pharmaceutica, Bicycle Therapeutics, Bristol Myers Squibb, Curis, Daiichi Sankyo, Dragonfly Therapeutics, EMD Serono, Fujifilm, Genentech, Gilead Sciences, GlaxoSmithKline, Janssen, Merck, Numab Therapeutics, Pfizer, Rappta Therapeutics, Seagen, UroGen Pharma, and Veracyte.

Reference

Galsky MD, Gschwend JE, Milowsky MI, et al. Adjuvant nivolumab versus placebo for high-risk muscle-invasive urothelial carcinoma: 5-year efficacy and ctDNA results from CheckMate 274. Ann Oncol. Published online October 17, 2025. doi:10.1016/j.annonc.2025.09.139

The windy city of Chicago, Illinois, is set to host the CHEST: American College of Chest Physicians Annual Meeting from October 19 to October 22, 2025, highlighting innovative research and discussions surrounding pulmonary and critical care specialties. The conference will feature multiple sessions concerning the use of artificial intelligence (AI) in medicine, the use of glucagon-like peptide 1 inhibitors to address issues in sleep medicine, and late-breaking abstracts in its 4-day schedule.

The main conference events kick off on October 19, with the keynote address coming from inspirational speaker Sean Swarner, who has 1 functioning lung after 2 bouts with cancer. The power of pulmonary medicine, allowing those with lower lung function to lead normal lives, highlights the reason that many of the doctors practice: to improve the prognosis for those with major pulmonary challenges. After this demonstration of what progress in pulmonary medicine can do for the average person, the core of the conference will get underway.

New coverage guidelines will be debated on Monday morning, specifically on noninvasive ventilation in chronic obstructive pulmonary disease (COPD). The panel aims to review the National Coverage Determination guidelines, identify challenges that will arise due to the guidelines, and discuss how to implement the guidelines into practice.

AI is a topic of conversation at multiple panels, including at the opening session on Tuesday, October 21, where the use of AI will be discussed in both pulmonary and critical care medicine. Experts on the panel plan to highlight 3 AI applications that are affecting medicine in the pulmonary, critical care, and sleep specialties and teach the audience how to use these AI tools to help documentation and clinical decisions. Ethical challenges and implementation pitfalls of AI will also be covered as the practical use of AI is questioned.

Also on Tuesday, the conference will focus on the past, present, and future of respiratory vaccines. COVID-19 vaccines, influenza, and pneumococcal disease vaccines have previously been shown to be helpful in avoiding unnecessary death due to these viruses, and the future development of vaccines in this space could further reduce morbidity in vulnerable populations. The goal of the panel, according to the description, is to “encourage[e] pulmonary and critical care clinicians to continue their work as advocates of vaccination” by going over current science and recommendations for respiratory vaccines.

The conference’s Wednesday events kick off with a panel about the new federal policies in the US that have changed the priorities affecting multiple areas of health. The National Medical Association will be offering insight into what these changes mean for medical education and research across the country, including highlighting both legislation and executive orders that affect health care and discussing methods of reducing the harm that could come from these actions. Aaron Baugh, MD, and Marilyn Foreman, MD, MS, of UCSF Department of Medicine and Indiana University School of Medicine, respectively, will be the moderators for this panel.

The conference is set to conclude on October 22. After 4 full days of panels, discussions, and abstract presentations, CHEST will draw to a close on Wednesday evening, after providing pulmonologists and other specialists across the country with updated research, information, and guidelines to better serve their patients when they return to their practices.

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Baker McKenzie advised Lotus Pharmaceutical Co. Ltd. in its agreement to acquire 100% equity interests in New Alvogen Group Holdings, Inc., which owns Alvogen US, a fully integrated specialty pharmaceutical company based in New Jersey. The transaction includes a mix of cash, preferred shares, and contingent earnout. Closing is subject to customary regulatory approvals.

Led by Lawrence Lee, the multijurisdictional Baker McKenzie team includes attorneys from nine offices across three countries, and is comprised of the following attorneys:

• M&A: Lawrence Lee (Partner, Palo Alto), Hao-Ray Hu (Partner, Taipei), Alex Chiang (Partner, Taipei), Jean-François Findling (Partner, Luxembourg), Emery Mitchell (Partner, San Francisco), Fang-Yi Jen (Partner, Taipei), Louis Hsieh (Partner, Taipei), Nicolas Clément (Counsel, Luxembourg), Natasia Dumitru (Counsel, Luxembourg), Gwen Karanadze (Associate, New York), Devin Muntz (Associate, Chicago), James Tenrai (Associate, Palo Alto), Alyssa Dickinson (Associate, San Francisco), Caroline Shih (Associate, San Francisco), Aubrey Kelley (Associate, New York), Bretton Stephenson (Associate, Los Angeles), Elena Apopei (Associate, Luxembourg), Jane Wu (Associate, Taiwan)

• Antitrust: John Fedele (Partner, Washington D.C.), Sylwia Lis (Partner, Washington D.C.), Andrew Black (Counsel, Washington D.C.), Evan Harris (Associate, Washington D.C.)

• Benefits: Thomas Asmar (Partner, Palo Alto), Sesen Hailemichael (Associate, San Francisco)

• Banking and Finance: Miju Damodar (Partner, New York), Yanshu Zhang (Associate, New York), Bee Leay Teo (Senior Consultant, Taipei), Yuci Hung (Associate, Taiwan)

• IP: Cynthia Cole (Partner, Palo Alto), Mackenzie Martin (Partner, Dallas), DJ Lee (Associate, Dallas), Richard Yang (Associate, Palo Alto)

• Litigation: Mark Goodman (Partner, San Francisco), Barry Thompson (Partner, Los Angeles), Tom Tysowsky (Associate, Los Angeles), Henna Bhandal (Associate, Los Angeles), Ina Jheng (Associate, Taipei)

• Employment: Amanda Cohen (Partner, San Francisco)

• FDA Regulation: Xin Tao (Partner, Washington D.C.), Lois Sheng Liu (Associate, Washington D.C.), Roberta Lynn Turner (Associate, Dallas)

• Tax: Lane Morgan (Partner, Dallas)

• Environmental: Jessica Wicha (Counsel, Chicago)

• Real Estate: Sarah Swain (Associate, San Francisco)

Commenting on the transaction, Lawrence Lee said, “This was a truly global undertaking, demanding seamless collaboration across numerous time zones to serve a client team dispersed throughout Asia and Europe. The complexity of the matter required our team to operate with precision and dedication around the clock.”

This matter is representative of the breadth and depth of Baker McKenzie’s experience advising life sciences companies on their most business critical issues. As one of the first law firms to advise life sciences corporates on their global expansion over 60 years ago, the Firm’s knowledge is rooted in its DNA.

Baker McKenzie is a transactional powerhouse, with more than 2,500 deal practitioners in more than 40 countries offering leading expertise in the areas most critical for clients. The Firm excels in complex transactions and cross-border deals, and has been steadfast in solving clients’ problems – wherever they are in the world – by providing a unique blend of local strength and global excellence .

Learn more on Lotus Pharmaceutical’s website https://www.lotuspharm.com/newsroom/lotus-acquires-avolgen-us.

The intelligent hospital logistics management system is comprised of five distinct platforms: an energy management platform, an intelligent lighting control platform, a one-stop service platform, a power operation and maintenance monitoring platform, and a visualization platform for the BIM O&M platform. The platform exhibits substantial expandability and forward-thinking characteristics, ensuring its adaptability to novel business models over time while concurrently reducing logistics input costs. The Internet of Things (IoT) and intelligent logistics management systems represent two pivotal areas of interest within the domain of healthcare. The integration of the Internet of Things (IoT) and High-Integrity Logistics Management (HILIMP) through the utilization of state-of-the-art information technology (IT) applications, including cloud computing, big data, and spatial geographic information, has the potential to transform the manner in which hospitals oversee their logistics operations. The sharing of information resources and the optimisation of their allocation can facilitate the streamlining of hospital operations, the improvement of efficiency, and the realisation of lean and efficient management. The integrated management platform for hospital intelligent logistics, which incorporates the Internet of Things, comprises a business module that encompasses a multitude of terminals, including web, mobile, handheld, and large-screen devices. The aforementioned terminals facilitate access to a diverse array of applications, which are currently constrained by their limited accessibility.

An intelligent logistics management system has been developed to enhance energy efficiency in hospitals through five core mechanisms. The first mechanism is territorial monitoring, which involves the deployment of multi-mode sensors in high energy-consuming equipment to collect real-time data. These sensors are designed to identify anomalies with an energy efficiency deviation greater than 20%. The first method is based on the dynamic energy consumption baseline, and it involves the realization of second-level interception (e.g., charging the pile at full power during non-working hours) through the LSTM anomaly detection model. The second method is prediction-driven dynamic tuning, which integrates outpatient volume and environmental data to predict regional load demand (e.g., The operating room air conditioning system is preheated to achieve on-demand regulation of HVAC and self-adaptation of logistics equipment. The pneumatic pipeline air pressure is dynamically adjusted according to the transport load. The third component is equipment health—energy-efficiency linkage. This is achieved through analysis of over 200 dimensional characteristics of early warning of energy-efficiency deterioration equipment, priority maintenance of high-energy-consumption failure points, and reduction of sudden energy consumption loss by 67%. The fourth component is process re-engineering—system synergy. Intelligent path planning has been demonstrated to reduce handling mileage by 22%. Batch removal of medical waste has been shown to reduce cold chain energy consumption by 19%. Furthermore, cross-system energy savings can be achieved through fresh air, air-conditioning residual cooling recovery, lighting, and logistics linkage. The fifth component is the digital twin, which is continuously optimized. The establishment of a three-dimensional baseline, encompassing the interrelationships among buildings, equipment, and temporal periods, is imperative. This baseline should be subject to automatic refinement, informed by historical data. A case in point is the adjustment of the air-conditioning set temperature by 0.5 °C in a given season, a strategy that is dynamically adapted through the analysis of past data. The technological closed loop (data collection → AI diagnosis → demand prediction → automatic execution → system synergy) has been demonstrated to reduce the ineffective energy consumption of equipment by 42%, the air conditioning power by 35%, and the overall energy consumption of the hospital by 25–32%. Furthermore, it has been shown to promote the transformation of energy management from experience-driven to AI-driven.

System components

In order to circumvent the inherent limitations of the Internet + Hospital Intelligent Logistics Comprehensive Management Platform and give full play to its potential, the Internet + Hospital Intelligent Logistics Comprehensive Management Platform is constructed using the microservice architecture, as shown in Fig. 3. The characteristics of the hospital intelligent logistics platform with multi-terminal access (Web/mobile/handheld devices/large screen), multi-business modules (equipment monitoring/materials scheduling/energy management), and large fluctuations in the amount of access are addressed by this system, which adopts Spring Cloud microservices architecture (Spring Boot 3.0 + Nacos 2.2 Service Governance + Sentinel 1.8 Fusion Limit Flow). Achieving technical decoupling is contingent upon the following core value: The first component of interest is the medical-level high availability, which is characterized by the independent deployment of microservices and rolling upgrades. This ensures that the core business of power equipment monitoring and other 7 × 24 h of uninterrupted operation is supported. The K8s elastic scalability is also of note, as it can support emergency scheduling emergencies (> 500 QPS). The second component of interest is the non-functional depth of the adaptation. Redis caching through the Redis + library table is employed to ensure that the response time to the application of the hospital district is less than 200 milliseconds. The integration of Spring Security OAuth2 + State Secrets SM4 and GitLab CI/CD is achieved to facilitate a single-service upgrade with zero interruption. The architecture design primarily emphasizes non-functional requirements, encompassing performance, security, usability, ease of use, and maintainability. The overarching design concept constitutes the platform that provides support for the system. The overarching design concept underpinning the development of this system is the establishment of a unified platform capable of supporting all applications. The overarching design concept entails the establishment of a cohesive platform capable of supporting all applications. The architectural design features of this product are enumerated below:

1. (1)

   The microservice architectural style is readily adaptable to accommodate growth and expansion. The partitioning of services into discrete units, or microservices, represents a means of reducing the overall size of a service while increasing its precision. This approach entails concentrating on a relatively autonomous domain with the objective of mitigating risk and facilitating the reuse of combinations. Furthermore, it enables the expansion of the service, which is frequently a constraint. In contrast to the necessity of simultaneous upgrades for all services, optimisation and expansion can be achieved in an incremental manner. The process of data slicing may be conducted by user organisations, data centres and service area clusters according to geographic location, with each entity having the capacity to perform this process independently.

2. (2)

   Protocol adaptation represents a more flexible approach. The adaptation of communication protocols is achieved through the protocol adapter of the device management module, which is capable of supporting a variety of communication protocols, including MQTT, ModbusTCP, OPC UA, and BACnet, among others.

3. (3)

   The provision of an open interface allows for seamless integration. The platform offers an open application programming interface (API) based on Hypertext Transfer Protocol (HTTP) or Hypertext Transfer Protocol Secure (HTTPS), which permits third-party applications to access the data.

4. (4)

   The implementation of encryption ensures an elevated level of security. The application layer is secured through the utilisation of the HTTPS protocol in conjunction with digital certificates, thereby preventing any potential data tampering or denial of information interaction. The application layer’s sensitive data is encrypted through the utilisation of symmetric encryption algorithms, thereby ensuring the confidentiality and integrity of the data. The server-side interface processing serves to prevent both SQL injection attacks and cross-site XSS attacks.

Function introduction

Figure 4 illustrates the system function diagram. The IoT + Hospital Intelligent Logistics Comprehensive Management Platform’s product system represents a business architecture of N + 1 + 5, comprising N applications, one center, and five centers. The system can be described as an N + 1 + 5 business architecture, consisting of N applications, one center, and five centers. The N applications encompass four business sections: a one-stop service; safety, operations, and maintenance; energy consumption management; and BIM + FM visualization and big data DSS. The one-stop service section incorporates various business subsystems, including a unified scheduling desk, maintenance and repair reports, medical waste management, meal ordering systems, inspection management tools, warehouse management platforms, satisfaction surveys, and more. This section is made up of several business subsystems, including a unified dispatching desk, maintenance and repair, medical waste management, food ordering, inspection management, warehouse management, vehicle management, and satisfaction surveys. The Safety Operations and Maintenance and Energy Consumption Management section is responsible for monitoring safety operations, issuing alerts in the event of malfunctions, administering operations and maintenance, and compiling statistical analyses related to water, electricity, gas, and specialized equipment consumption in the context of hospital logistics.

One centre makes reference to the Internet of Things (IoT) + hospital intelligent logistics centre, which is capable of carrying out a multitude of applications. Such applications include unified user management, unified resource management, unified process management, unified payment management, unified report management, and open unified login and access interfaces. The open and unified login and access interface serves to dismantle information silos, integrate third-party applications, and provide a unified management portal. This has the effect of further improving the efficiency of management and business flow, while also facilitating a deeper exploration of the potential value of data to support logistics management decisions. The aforementioned five centres are the process centre, the report centre, the user centre, the resource centre, and the payment centre.

The Internet of Things (IoT) has become the cornerstone of the perception layer of the smart hospital logistics system, stemming from the rigid needs of medical scenarios. The necessity of full-domain perception is paramount in hospitals, where equipment status must be monitored in real time. The magnetic resonance imaging (MRI) temperature rise of ± 0.5 °C, the direction of energy flow (sub-metering), and the traditional supervisory control and data acquisition (SCADA) system’s support for point collection are limitations that the Internet of Things (IoT) distributed sensing network (temperature/vibration/current sensors) overcomes by meeting the needs of hospitals simultaneously. The IoT distributed sensing network can provide a building’s whole chain of dynamic sensing. The present study explores the phenomenon of real-time control dependency. The deployment of IoT actuators, such as smart valves and inverters, has been shown to be 60% more cost-effective than traditional PLC systems. These actuators facilitate wireless remote regulation, a feature that enhances their functionality and versatility. The following essay will explore the core benefits and synergistic value of big data technology.

The utilization of big data technology has become an inevitable choice due to the inherent characteristics of medical data, which can be defined by three key elements: volume, speed, and variety. The first element, volume, refers to the substantial quantity of data generated on a daily basis, which can exceed 50 gigabytes. The second element, speed, refers to the rapid rate at which updates to the second-level data are executed, typically within a span of less than one second. The third element, variety, refers to the diverse range of data types and formats that are present. The utilization of BIM (Building Information Modeling) models and video streaming in this context underscores the necessity of meticulous analysis for intelligent decision-making. Predictive maintenance, in particular, necessitates the integration of vibration spectra (time series data), maintenance records (text), and infrared images (unstructured). The utilization of infrared images (unstructured) necessitates the implementation of Hadoop + MLlib and other big data platforms to facilitate multimodal analysis. The process of energy consumption optimization entails the extraction of data spanning a decade, incorporating historical meteorological information and outpatient visit records. Conventional relational databases, such as Oracle, are susceptible to failure during petabyte-scale data processing operations. The integration of technological systems fosters the creation of exclusive value in the medical field. The Internet of Things (IoT) has been demonstrated to collect current harmonics and large volumes of data, thereby warning of bearing wear and reducing the need for excessive maintenance. The integration of IoT with big data has been shown to reduce operational and maintenance (O&M) costs and energy expenditure, thus establishing itself as the optimal solution for the digital transformation of medical logistics.

Security system

Data security system

In the context of hospital logistics management systems, data security emerges as a paramount concern. The implementation of a robust data security framework entails the integration of three core components: storage encryption, local disaster recovery, and off-site disaster recovery. This triad of mechanisms constitutes the foundation of a comprehensive data security system.

The storage layer employs a hierarchical encryption strategy, utilizing AES-256 for database field encryption to defend against drag database attacks, BitLocker full disk encryption to prevent physical theft, eDrive protocol to block the loss of mobile media hardware-level encryption leakage, and a unified key management platform to ensure that even if the data is misdirected, it remains unreadable ciphertext.

The local disaster recovery system is predicated on the zero-trust principle, which is to say that it is based on continuous data protection (CDP) technology. This system generates anti-pollution snapshots at 15-minute intervals. Furthermore, it utilizes write-once-read-many (WORM) locks to operate logs, thereby preventing tampering. In addition, all transmission channels are encrypted by TLS 1.3 + SM4 to meet the relevant audit requirements.

Thirdly, off-site disaster recovery employs blockchain-verified replicas in at least 200 km geographically isolated nodes (RPO < 5 min) and facilitates 10-second fusion switching (RTO < 30 s). These mechanisms ensure the comprehensive and traceable management of first aid material dispatch records during extreme disasters. The system has passed the Equal Protection Level 3 certification (GB/T 22239 − 2019), thereby achieving military-grade protection for the entire life cycle of core data. The system has been designed to ensure that backup points are independently backed up, with multiple backups stored in different locations. This enhances the system’s disaster-tolerance capability and ensures the integrity of data.

Network security system

The network security system is founded upon four fundamental principles.

Physical isolation

It is of paramount importance to implement external network switches in order to guarantee the segregation of data flows between the local area network (LAN), intranet and Internet. This approach permits the segregation of data flows pertaining to internal and external networks, thereby enhancing the security of network-borne information.

Firewall technology

The network system utilises high-performance and high-security firewalls, which provide comprehensive protection at both the network and application levels. It is of the utmost importance that the router is configured in a manner that enables comprehensive monitoring of all communications by the firewall. The monitoring and filtering capabilities of the firewall permit the authentication and authorisation of trusted users or information, thereby enabling them to log in to external servers or exchange information.

Access control

It is recommended that an external network switch be implemented to segregate the data flow between the internal and external networks. This approach permits the sharing of data traffic while maintaining the security of network information. Computers with internet access and data ports are connected to the external network switch in order to prevent the incursion of viruses into the internal network system and to safeguard the security of related data.

Intrusion monitoring and network audit

A system for monitoring and auditing network operations is selected for deployment on the external and internal networks of the system. This system is responsible for monitoring and recording all types of network activity. The system is capable of analysing a range of security events, external events (such as external intrusion) and internal events (such as file copying, information access, information release, resource change by internal personnel, and so forth) that occur within the network in real time. Subsequently, the system assesses the violations in accordance with the established criteria and documents them, along with any associated alarms and blocks.

System advantages

Multi-system interaction

The integration, expansion and interconnection of digital systems have historically constituted the primary challenges to the digital development of hospitals. The lack of compatibility between products from different vendors has further complicated the process of overall hospital informatisation. The IoT + Hospital Intelligent Logistics Comprehensive Management Platform offers comprehensive system integration specifications that encompass all aspects of hospital logistics, thereby providing a unified and standardised platform for data exchange and workflow collaboration. The system enables interaction between disparate business segments (e.g. maintenance and warehouse) and systems (e.g. equipment O&M and BIM visualisation) within the system. Furthermore, it enables the integration of data with external systems, including HRP, HIS, and other hospital systems.

The IoT + Hospital Intelligent Logistics Integrated Management Platform employs a layered decoupling architecture, a strategy that aims to address the systemic barriers impeding digital development in healthcare settings. The core of the system is comprised of four layers. The data layer is transmitted through the unified data exchange platform, thereby providing a standardized interface that supports JSON, XML, and HL7. This facilitates heterogeneous system data conversion, thereby breaking down the barriers to compatibility with external systems, such as HRP, HIS, and others. The service layer is responsible for the deployment of the workflow collaboration engine, which is integrated vertically through various business modules, including maintenance, warehousing, and other relevant systems. One notable feature is the automatic triggering of MRI failure by spare parts requisition, which exemplifies the system’s intelligent design. Additionally, the application layer integrates business modules such as BIM visualisation, equipment operation and maintenance, and energy consumption analysis, establishing a unified operation interface for logistics business. The interaction layer utilizes API gateway and message middleware, with Kafka ensuring latency below 200 milliseconds, to facilitate horizontal cross-system synergy, such as fire alarm linkage and video monitoring.

Multi-service integration

The IoT + Hospital Intelligent Logistics Comprehensive Management Platform has the potential to integrate a number of different hospital logistics business sections, including BIM visualisation, a one-stop service, equipment operation and maintenance, energy consumption statistics and analysis, video monitoring, fire and safety monitoring, and more. Such integration could facilitate the optimisation of hospital logistics operations, enabling the streamlining of processes and the real-time monitoring of key performance indicators. The creation of a unified logistics platform that incorporates all of the aforementioned logistics business sections has the potential to improve logistics efficiency and facilitate the development of an information management model.

German Finance Minister Lars Klingbeil criticized China’s decision to tighten export controls on rare earths and expressed hope for a de-escalation following the meeting between US President Donald Trump and Chinese President Xi Jinping.

“We have made it clear within the G-7 that we do not agree with China’s approach,” said Klingbeil, who also serves as Germany’s vice chancellor, on the sidelines of the IMF and World Bank meetings in Washington. “We are monitoring the situation closely and doing what we can politically to prevent further tensions between the US and China.”