Kaohsiung Medical University

China Medical University Hospital in Taichung, Taiwan has been recently validated for three HIMSS Digital Maturity Models: Stage 7 for the Infrastructure Adoption Model (INFRAM), revalidation of Stage 7 for the Electronic Medical Record Adoption Model (EMRAM), and Stage 6 for the Adoption Model for Analytics Maturity (AMAM). The INFRAM measures an organisation's maturity in infrastructure and associated technology capabilities. The EMRAM measures their clinical outcomes, patient engagement, and clinician use of EMR technology, while the AMAM gauges their analytics capabilities. WHY IT MATTERS CMUH is the first hospital in Taiwan to be validated for Stage 7 INFRAM. It was able to achieve this feat in just four months after achieving Stage 6. It attributed its achievement to its infrastructure strategy which took inspiration from the Chinese Zodiac. The hospital is also the first in the country to be validated for Stage 6 AMAM. It was able to demonstrate some mature applications of analytics, including the analysis of medication expenses that helped it realise an annual cost savings of approximately NT$ 200 million ($6.2 million). Another example is its ARDiTeX (ARDS Technology System) visualisation panel that is used in the Respiratory ICU. It enabled the reduction in 28-day mortality among diagnosed patients with ARDS (Acute Respiratory Distress Syndrome). Additionally, CMUH was revalidated for Stage 7 of the EMRAM. To meet the requirements of this stage, the hospital introduced major changes in its EMR system. These include the implementation of the Electronic Medication Administration Record, integration of records across multidisciplinary teams, and establishing interoperability with the Med-cloud database of Taiwan's National Health Insurance. HIMSS also recognised its antimicrobial AI platform, the Intelligent Anti-Microbial System ( i.A.M.S. ), as a noteworthy use of the EMR. It is a four-in-one AI-driven platform that identifies drug-resistant strains and predicts and monitors the risk of infectious sepsis and mortality. It also makes smart drug dosage recommendations and automatic comparisons of drug-drug interactions and allergy history. In just three months after its implementation in June 2021, i.A.M.S. helped cut the mortality rate due to sepsis by 7.1%, compared to 13.4% in the same period in the previous year. To date, CMUH has developed 16 AI-driven services and 50 dashboards based on the Microsoft Power Business Intelligence platform, which are all implemented broadly across clinical and operational areas. THE LARGER TREND CMUH joins a growing group of Taiwanese healthcare providers that have been validated for the EMRAM. Its revalidation follows Changhua Christian Hospital which was also validated for Stage 7 EMRAM a few months ago. The Kaohsiung Medical University Chung-Ho Memorial Hospital is the latest hospital in Taiwan to be validated at Stage 6, followed by Far Eastern Memorial Hospital last year. Taichung Veterans General Hospital and Tungs' Taichung MetroHarbor Hospital have also achieved Stage 6 for this model. CMUH’s AMAM and INFRAM validations also follow those of Samsung Medical Center, the first healthcare provider in Asia-Pacific to achieve Stage 6 AMAM and Stage 7 INFRAM . ON THE RECORD Dr Wei-Cheng Chen, chief secretary of CMUH, shared that they turned to international standards and models for inspiration and validation in their efforts towards digital transformation. "During these years – without any role models of smart hospitals in Taiwan – we observed and learned to figure out what a smart AI hospital is. We found that HIMSS provides a systematic approach and clear criteria to achieve this goal. That’s why CMUH strongly endorses HIMSS to guide our directions and find out our weaknesses," Dr Chen shared. Further explaining their vision of becoming a smart AI hospital, CMUH Superintendent Dr Der-Yang Cho said: "At CMUH, our smart healthcare vision is anchored in a patient-centred approach, aiming to refine clinical processes and elevate care quality through data analytics and AI. This approach, continuously evolving with our digital transformation journey, integrates advanced AI and BI to deliver more precise, efficient, and reliable medical solutions like the i.A.M.S." "Superintendent Dr. Cho underscores our commitment to 'useful, practical, and favoured' tools and projects that enhance patient care and quality of life. Through these efforts, we aspire to make our healthcare services not only effective and efficient but also preferred and valued by our patients," Vice Superintendent and CMUH professor Oscar K. Lee added.

Kaohsiung Medical University to build $300M smart hospital in Taiwan Kaohsiung Medical University has announced its NT$10 billion ($320 million) investment to build a smart hospital in the Taoyuan Aerotropolis. The hospital, which will initially have a bed capacity of 515, will "introduce the latest medical technologies, develop telemedicine capabilities, and utilise AI and big data research outcomes to… enhance the quality of healthcare." Based on a press release, the upcoming hospital will focus on cancer treatment, critical care, and integrated care for chronic diseases. It will also provide preventive medicine, community healthcare, clinical medicine, and home healthcare, as well as offer comprehensive outpatient, emergency, and inpatient services. Additionally, it will have 39 medical sub-specialties, including internal medicine, surgery, obstetrics and gynaecology, and paediatrics, among others. KMU has signed a BOT contract with the National Tsing Hua University, to which the operation and ownership of the hospital will be transferred after 50 years. The first phase of the hospital's construction will begin next year and is expected to be completed by 2028. In the future, its bed capacity will be raised by close to a thousand. The smart hospital is being constructed as part of the 7.2-hectare NTHU Taoyuan Medical and Educational R&D Park project. AIIMS Delhi rolls out state-developed Sandes internal comms app The All India Institute Of Medical Sciences in New Delhi has implemented a government-developed messaging platform to streamline communication among hospital staff. Called Sandes, the app will be used primarily for internal communications at AIIMS Delhi, including the secure and fast exchange of patient records, a news report noted. Through Sandes, the hospital seeks to achieve better connectivity, quicker information sharing, and seamless collaboration among departments and staff. The app was developed by the National Informatics Centre for government offices. Metropolis Healthcare launches WhatsApp chatbot for doctors Metropolis Healthcare, a chain of pathology labs and diagnostic centres in India, has developed a WhatsApp chatbot for doctors. Aiming to enhance doctor-provider communication, Metropolis introduced the said chatbot to allow doctors to conveniently access medical information, such as test availability, methodology, sample transport guidelines, turnaround time, sensitivity, specificity and cost. They can also upload patient prescriptions and receive prompt guidance from Metropolis for testing processes. The chatbot also includes CME modules to help doctors keep abreast of industry updates. Metropolis targets to reach over 100,000 doctors in the first year of the rollout of the chatbot, according to a news report .

药物合成工艺研发贯穿于新药开发的每个阶段，并占据重要的地位。随着新药分子不断向前推进，不同临床阶段工艺研发的关注重点也将随之发生改变。在新药临床试验申请（IND）阶段，合成工艺的主要目的是在初步工艺优化的基础上，以最为高效的方式生产出可用的API，以确保毒理实验及后续临床试验的按时顺利进行。4月18日下午3点，合全药业高级主任、API业务早期项目五部研发三部负责人郭荏耘博士将做客药明直播间，聚焦毒理批次API快速交付产生的价值及意义，以及在IND申请阶段所面临的不同的CMC挑战展开经验分享，如工艺放大可行性、安全评估、晶型控制、杂质残留等。此外，郭博士也将围绕合全药业相关真实案例展开细致介绍，欢迎注册本次直播！注册报名 本次研讨会免费对外开放，请长按下方二维码报名，快速进入直播通道。主题：加速毒理批API制备，高效助力IND申请主讲人：郭荏耘 博士  合全药业高级主任、API业务早期项目五部研发三部负责人时间：2023年4月18日，15:00 – 16:00SPEAKER PROFILE郭荏耘  博士郭荏耘博士在高雄医学大学获得药物学博士学位，之后于美国北卡罗莱大学做博士后研究。2009年起从事API合成和团队管理工作，专长于API放大工艺开发，IND 申报相关CMC研究以及GMP下的API制造生产，于2021 年加入药明康德，目前为合全药业API业务早期项目五部研发三部负责人。关于合全药业合全药业是药明康德子公司，在全球多地设有研发及生产基地。合全药业服务于生命科学行业，拥有卓越的化学创新药研发和生产的能力和技术平台。作为全球新药合同研究、开发与生产领域（CRDMO）的领军企业，合全药业致力于为全球合作伙伴提供高效、灵活、高质量的一站式解决方案，以支持包括小分子、寡核苷酸、多肽及各种复杂化学偶联药物的研发与生产。CMC系列往期直播：药明直播间| CMC系列(三十四)：PDC药物的机遇、挑战与案例分享药明直播间| CMC系列(三十三)：突破寡核苷酸药物递送技术瓶颈，开发脂质纳米颗粒(LNP)的挑战与产业化实现药明直播间|CMC系列(三十二)：一站式方案“精准制导”，高活化合物及相关偶联物的CMC关键点考量药明直播间|CMC系列(三十一)：贯穿原料药与制剂的关键一环—— 如何制定药物固态开发最优策略？药明直播间| CMC系列(三十)：全球申报下注册起始物料(RSM)的研究策略探讨药明直播间|CMC系列(二十九)：一体化CMC赋能早期临床样品快速供应，加速新药研发进程药明直播间| CMC系列(二十八)：NDA及PPQ阶段原料药分析方法开发的关注点药明直播间| CMC系列(二十七)：无定形制剂产业化的挑战与解决方案药明直播间| CMC系列(二十六)：前瞻性的原料药工艺研发方案加速临床研究用药供应药明直播间|CMC系列(二十五)：绿色化学技术——助力小分子原料药研发及生产的有力工具药明直播间|CMC系列(二十四)：突破应用瓶颈，流动化学技术如何提升原料药工艺的可持续性？药明直播间|合全药业全新推出临床供应链服务：如何基于临床需求快速提供研究用药？药明直播间|合全药业新平台发布：突破高壁垒，无菌注射剂CMC关键风险点及考量药明直播间| CMC系列(二十一)：高活原料药的CMC挑战以及与多种分子形式偶联的具体应用药明直播间|CMC系列(二十)：如何通过蛋白质设计、定向进化以及AI设计全新多酶级联反应？药明直播间|CMC系列(十九)：快速实现商业化——临床后期制剂策略加速创新药全球申报药明直播间|CMC系列(十八)：IND阶段原料药工艺研发的关键点及案例分析药明直播间|CMC系列(十七)：可快速供应早期临床用药的制剂策略分享药明直播间|CMC系列(十六)：流动化学技术助力原料药工艺研发和生产的绿色转型药明直播间| CMC系列(十五)：如何应用生物利用度预测工具优化制剂处方前研究？药明直播间| CMC系列(十四)：盐型晶型的选择及其结晶工艺的开发药明直播间| CMC系列(十三)：聚焦真实案例——如何助力一款多肽创新药在数月内完成IND申报？药明直播间| CMC系列(十二)：如何优化CMC供应链以满足创新药快速申报通道的需要？药明直播间| CMC系列(十一)：临床前新药CMC的关键风险分析与应对药明直播间|CMC系列(十)：应对挑战——ADC药物研发及生产的关键策略考量药明直播间|CMC系列(九)：创新药中美双报CMC策略分享药明直播间|CMC系列(八)：高通量酶定向进化技术在药物合成中的应用药明直播间|CMC系列(七)：泽布替尼胶囊CMC布局、挑战和策略分享药明直播间|CMC系列(六)：IND申报阶段CMC工作的关键风险点及解决方案药明直播间|CMC系列(五)：创新药引进项目的CMC工作考量药明直播间|CMC系列(四)：喷雾干燥技术在新药开发中的应用药明直播间|CMC系列(三)：处方前一体化研究——推进候选药物至临床的创新引擎药明直播间|CMC系列(二)：新药生命周期的质量要点药明直播间CMC系列（一）：创新药开发，如何搞定“盐型和晶型”关键一环？