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临床数据管理2020年度大会
CLINICAL DATA MANAGEMENT 2020 CHINA VIRTUAL CONFERENCE

10月12 - 18日 | OCTOBER 12 - 18

聚焦规范 落实标准 直面挑战
FOCUSING COMPLIANCE, IMPLEMENTING STANDARDS, RISING TO CHALLENGES

临床数据管理2020年度大会将于2020年10月12-18日在线举办。本届大会主题为“聚焦规范 落实标准 直面挑战”，届时国内外临床数据管理专家将分享新药申请和审批的国际监管要求。大会还将就现实世界数据中数据管理的最新方案、智能化临床试验的数据管理以及在紧急突发情况下对临床数据管理的探索和实践等热点话题进行分享，与参会者共同讨论学习，共同推进中国的临床试验数据管理水平。

Clinical Data Management 2020 China Virtual Conference will be held on October 12-18. The conference theme is: Focusing Compliance, Implementing Standards, Rising to Challenges, this virtual conference will invite domestic and international regulatory and clinical data management experts, aiming to share regulatory requirements for new drug applications and approvals. Participants will learn about recent programs of data management in real world data, in decentralized clinical trials, exploration and practice of clinical data management under urgent situation. We sincerely hope that you will be able to join us for driving development of clinical data management profession.

会议亮点 | CONFERENCE HIGHLIGHTS：

  1. 分享国际国内双递交临床研究数据监管要求与策略
    To share International and Domestic NDA Submission Regulatory Requirements and Strategy
  2. 介绍新药政法规要求下的数据管理和质量要求
    To introduce the data management and quality expectation in compliance with the new Chinese GCP regulations
  3. 探讨现实世界数据中的数据管理
    To discussion about data management in Real World Data
  4. 对紧急状态下临床数据管理的探索和实践
    To exploration and practice of Clinical Data Management under Urgent Situation

目标受众 | TARGETED AUDIENCE:

  • 制药企业研发决策管理人员
    Managerial staff in R&D department
  • 临床试验数据管理员
    Clinical trial data managers
  • 临床试验项目经理
    Clinical trial project managers
  • 临床试验项目管理员
    Clinical trial project administrators
  • 临床监查员
    Clinical trial monitors
  • 临床试验质量保证和质量控制人员
    Clinical trial quality assurance and quality control professionals
  • 临床试验稽查员
    Clinical trial auditors
  • 临床研究专业人员
    Clinical development professionals
  • 临床注册专业人员
    Clinical regulatory affairs professionals
  • 研究者和研究协调员
    Clinical researchers and study coordinator

议程委员会和专题主席 | PROGRAM COMMITTEE & SESSION CHAIR:
(按姓氏首字母顺序排列)

  • 程书彦，SCDM 中国指导委员会委员
    勃林格殷格翰（中国）投资有限公司
    Shuyan Cheng, SCDM China Steering Committee Member
    Boehringer Ingelheim (China) Investment Co., Ltd.
  • 邓亚中，SCDM 中国指导委员会委员
    北京信立达医药科技有限公司
    Yazhong Deng, SCDM China Steering Committee Member
    Beijing Trust Medical Consulting Co. Ltd
  • 刘川，SCDM 中国指导委员会委员
    北京科林利康医学研究有限公司
    Daniel Liu, SCDM China Steering Committee Member
    Beijing Clinical Service Center
  • 黎婉珊，SCDM 中国指导委员会委员
    默沙东研发（中国）有限公司
    Joyce Lai, SCDM China Steering Committee Member
    MSD R&D (China) Ltd
  • Anita Shen，SCDM 中国指导委员会副主席
    辉瑞（中国）研究开发有限公司
    Anita Shen, SCDM China Steering Committee Vice Chair
    Pfizer (China) Research and Development Co., Ltd
  • 孙华龙，大会专题主席
    美达临床数据技术有限公司
    Hualong Sun, CDM Conference Session Chair
    Meta Clinical Technology
  • 田正隆，SCDM 中国指导委员会委员
    精鼎医药研究开发（上海）有限公司
    Zhenglong Tian, SCDM China Steering Committee Member
    PAREXEL China Co., Ltd
  • 颜崇超，SCDM 中国指导委员会委员
    上海盛迪医药有限公司
    Charles Yan, SCDM China Steering Committee Member
    Shanghai Shengdi Medicine Co., Ltd
  • 张玥，SCDM 理事会顾问委员
    SCDM 中国指导委员会主席
    上海复宏汉霖生物技术股份有限公司
    Carrie Zhang, SCDM Board Advisory
    SCDM China Steering Committee
    ChairShanghai Henlius Biotech, Inc.
  • 张薇，SCDM 中国指导委员会委员
    葛兰素史克(中国)医药研发有限公司
    Wei Zhang, SCDM China Steering Committee Member
    GSK Shanghai R&D

注册方式 | REGISTRATION

注册费 | REGISTRATION FEE:

三人及三人以上报名，可享团队注册优惠价格，详情请洽咨询热线。
For group registration, please contact registration hotline

注册方式 | REGISTRATION:

请扫描以下二维码在线报名，或登陆 https://www.wenjuan.com/s/R7rAjeu/ 报名。

Please register by clicking the link above or scanning the QR code

注册截止日期为2020年10月11日
Please pay attention that the registration deadline is Oct 11, 2020

咨询热线 | Registration Hotline：021-32798627

邮箱 | Email: [email protected]

 

*迈氏管理咨询（上海）有限公司负责大会的组织和管理
*The conference will be organized and managed by MCI

大会日程 | Agenda

Download Agenda CN
Download Agenda EN
日期
Date		 时间
Time		 专题名称
Session Topic		 专题主席
Session Chair
10月12日，周一
October 12，Monday		 09:00-11:30 主旨演讲 Keynote

国际国内双递交临床研究数据监管要求与策略
International and Domestic NDA Submission Regulatory Requirements and Strategy

 Carrie Zhang
10月13日，周二
October 13，Tuesday		 13:00-14:30 新药政法规要求下的数据管理和质量要求
Data management and quality expectation in compliance with the new Chinese GCP regulations		 Daniel Liu
10月14日，周三
October 14，Wednesday		 9:30-11:00 真实世界数据中数据管理探讨
Discussion about data management in Real World Data		 Zhenglong Tian
10月15日，周四
October 15，Thursday		 9:00-11:00 FDA推动的新要求
New requirements driven by FDA		 Joyce Lai
10月16日，周五
October 16，Friday		 13:00-14:30 紧急状态下临床数据管理的探索和实践
Exploration and practice of Clinical Data Management under Urgent Situation		 Hualong Sun
10月17日，周六
October 17，Saturday		 10:30-12:00 临床试验数据的可视化管理
Data Management from Visualization		 Yazhong Deng
10月17日，周六
October 17，Saturday		 14:00-15:30 智能化临床试验的数据管理
Data Management in Decentralized Clinical Trials		 Wei Zhang
Enjoy the CLINICAL DATA MANAGEMENT 2020 CHINA VIRTUAL CONFERENCE with your colleagues.
REGISTER NOW

大会专题介绍 | SESSION INTRODUCTION

  • 主旨演讲：国际国内双递交临床研究数据监管要求与策略
    Keynote：International and Domestic NDA Submission Regulatory Requirements and Strategy    聚焦临床试验数据监管要求与规范，已邀请国际国内药监部门领导、国际药厂全球数据管理负责人等，分享监管与核查要求，探讨全球递交临床试验数据管理策略与运营关注。Focusing on clinical trial data regulatory requirements and submission standards, invite international agency officers and global clinical data management leader in top international pharmaceutical company, share most recent regulatory requirements and inspection focus, discuss global submission strategy and best operation practices.
  • 新药政法规要求下的数据管理和质量要求
    Data management and quality expectation in compliance with the new Chinese GCP regulations近来，NMPA发布了新版药物临床试验质量管理规范，其中对临床数据标准和规范管理的要求与国际ICH GCP要求更加趋于一致，使得中国临床试验数据用于未来全球药政申报，和采用海外临床试验数据用于NMPA药政申报成为可能。随着这个新版中国GCP的进一步落实，NMPA 会进一步强化临床试验数据结果的质量和可信性监督管理。本分会场主题将概述中国新版GCP对临床试验数据的质量要求，数据管理员如何在新的药政规范环境下发挥更大的作用，和数据质量规范管理体系的建设等。
    Recently, NMPA published a new version of Chinese GCP.  The Chinese GCP is officially adopting ICH requirements regarding data quality and integrity, which makes it possible directly to utilize global trial data to submit NDA NMPA, and Chinese trial data may be possible for the acceptance by oversea authorities.  With the further implementation of data standards, NMPA is also enhancing inspective forces on the quality and integrity of clinical trial outcomes, including data from oversea trials. This theme will outline the requirements of Chinese GCP on data quality, changeable DM role and responsibilities in the new regulatory environments, and sound system of data QMS.
  • 真实世界数据中数据管理探讨
    Discussion about data management in Real World Data    国家药监局2020年1月发布了《真实世界证据支持药物研发与审评的指导原则（试行）》。目前关于全球在真实世界证据具体应用于药物研发上缺乏实操的指导方案，因此该指导原则对国际国内都受到很高的重视。真实世界证据又很多的重要的应用场景（如：适应症拓展、罕见病治疗药物、等等），而真实世界数据（Real World Data, RWD）是RWE的基础，因此与之相关的数据管理和统计分析思路也随之提上日程。
    研究者通过真实世界研究获取的数据被称为“真实世界数据”（Real World Data，RWD）。真实世界数据可以来源于多种渠道，如日常所收集的各种与患者健康状况和/或诊疗及保健有关的数据。但真实世界数据的标准性和质量也是一个老问题，目前RWD普遍存在数据的记录、采集、存储等流程缺乏严格的质量控制，数据不完整，数据标准和数据模型不统一等问题。我们在此主要针对真实世界数据的收集，治理，及可能数据递交等相关的数据管理问题进行探讨，为未来RWD能够成为能够成为满足临床研究目的RWE做好准备。In January 2020, NMPA promulgate “Guiding Principles of Real World Evidence supporting Drug Development and Review (Trial). At present, globally, there are lack of practical guidance on the application of real-world evidence to drug research and development, and therefore NMPA Guiding Principles are highly valued both in China and globally. Real-world evidence could important application in many areas (e.g. indication expansion, rare disease treatment, etc.), and here Real World Data (Real World Data, RWD) is the foundation of RWE, so data management and statistical analysis ideas associated with RWD will be discussed here.
    The data obtained by the investigators/researchers through real-world research is called “Real World Data” (RWD). Real-world data can come from various sources, for example, data collected on daily base related to the patient’s health status and/or diagnosis and health care. However, the standard and quality of real-world data has also been an existing problem. At present, RWD generally has problems such as lack of strict quality control, incomplete data, and inconsistent data standards and data models, etc. Thus, we are here to discuss data management related to the collection, curation, and possibly data submission of real-world data, and well prepare how to have RWD to be able to become RWE for clinical research purposes.
  • 智能化临床试验的数据管理
    Data Management in Decentralized Clinical Trials智能化临床试验是一种应用智能设备及远程通讯技术、以受试者为中心的新型临床研究模式。在信息化的基础上，利用大数据、云计算、人工智能等新技术，临床试验智能化可实现临床试验远程管理与监督，改善受试者可及性，提高试验质量与效率。智能化临床试验需解决各种电子源数据存在的数据标准、系统分割与信息系统孤岛问题，实现电子源数据的跨机构、跨区域、跨领域的临床数据资源互联互通，该场景下的数据管理具有一定独特性，给数据管理带来新的机会，也提出新的挑战。Telemedicine and mobile healthcare providers have been used extensively in healthcare delivery，but have yet to be widely incorporated into clinical trials. With the use of digital health technologies for data capture, Remote or Decentralized Clinical Trials which allow trial participants to take part in clinical research from anywhere has the potential to transform clinical trials. The decentralized setting is operationally feasible, potentially results in accelerated enrollment, improves data quality and study efficiency. Unified data standards and elimination of information island will greatly help realize data interconnection from different eSource. Data management in DCTs need new approach and risk mitigation strategies, which brings new challenges for data managers.
  • 紧急状态下临床数据管理的探索和实践
    Exploration and practice of Clinical Data Management under Urgent Situation自2020年1月下旬以来新冠肺炎在全球范围内大流行，医疗资源集中于抗疫情造成临床试验的研究者不足，因为人员移动受限受试者无法在规定访视节点如期到研究机构接受检查和治疗，临床研究协调员无法进医院协助数据录入，而临床监查员无法进入研究机构进行源文件核查，所有这些因素造成临床试验进展严重滞后，临床数据缺失，数据真实可靠性得不到保障，这对临床数据管理工作带来巨大的挑战，本Session将就疫情、自然灾害等紧急状态下临床数据管理工作的措施和实践进行讨论，并就实际案例进行分享。Since the late of January 2020, there is a COVID-19 pandemic around the world. Because medical resource has to focus on anti – COVID-19 pandemic, there is lack of investigators to conduct clinical trials. Because of the limitation of people movement, subjects cannot enter to investigational sites getting test and treatment as scheduled visiting, Clinical Research Coordinators (CRC) cannot enter to investigational sites performing data entry, and Clinical Research Associates (CRA) cannot enter to investigational sites performing source document verification (SDV). Those factors lead to a big delay of clinical trials, clinical data missing, and issues of data integrity, and bring big challenges to clinical data management activities. In this session, we will discuss the measures and practices of clinical data management activities under urgent situations such epidemic and natural disaster, etc, and share case study.
  • 临床试验数据的可视化管理
    Data Management from Visualization临床试验数据量巨大，可视化技术是国际最新发展趋势。针对临床数据管理和分析的不同阶段，应用可视化手段，呈现数据之间的关联和趋势, 直观理解数据信息, 快速发现异常数据, 了解试验数据的质量和风险，使数据管理过程更加主动直观, 提高试验效率。The clinical trial data are relatively large, and the correlation between the data is strong. In order to better present the correlation between the data, the latest international development trend is to use more visualization technology. Visualization means can be applied to present the correlation and trend of data at different stages of clinical data management and analysis, intuitively understand data information, quickly find abnormal data, and understand the quality and risk of experimental data, so as to make the data management process more active and intuitive and improve the experimental efficiency.
  • FDA推动的新要求
    New requirements driven by FDA

    1. 组合产品)的上市后安全报告Combination Product
    2. 逻辑观察标识符名称和代码LOINC（Logical Observation Identifiers Names and Codes)
  • 我们将介绍两个 FDA 推动的新需求的相关背景、 对数据管理经理带来的挑战和经验分享。
    1. FDA宣布组合产品（Combination Product/ CP）上市后安全报告（ Post-marketing Safety Reporting / PMSR）的最终规则。如果产品在 2019 年起根据新药申请 （NDA） 或abbreviated NDA 获得营销授权，则 CP 和零部件申请人必须遵守 PMSR 要求。为了在新出台的 FDA 和欧盟法规中调整投诉流程/政策，我们在将现有的独立不良事件和产品质量投诉 （AE_PQC） 跨部门流程转变为集成流程方面, 在构建新的流程以在临床试验中收集数据, 都会面临一些挑战。
    2. 监管临床研究在多个行业进行和支持，包括学术医疗中心、生物制药公司、生物技术公司、临床研究组织、信息技术供应商等。FDA开始要求列入一个医学实验室和观察术语编码系统，逻辑观察标识符名称和代码（ Logical Observation Identifiers Names and Codes / LOINC®）。虽然这一要求有助于调整医疗保健和受管制临床研究之间的语义，但满足此要求的准备情况和对 LOINC 的理解在这些行业中可能有很大差异。
  • In this session, we will share background, challenges and experiences on below new requirements driven by FDA which impacts Data Managers.
    1. FDA declared the Final Rule on Post-marketing Safety Reporting (PMSR) for Combination Products (CPs). CPs and constituent part applicants must comply with the PMSR requirements if the product received marketing authorization under a new drug application (NDA) or abbreviated NDA from 2019. To align complaint processes/policies in the upcoming FDA and EU Regulations, not only are we facing some challenges on transforming the existing independent Adverse Event & Product Quality Complaint (AE&PQC) cross-divisional processes to an integrated process, but also building up new models/process to collect data in clinical trial.
    2. Regulated clinical research is carried out and supported across multiple sectors including academic medical centers, biopharmaceutical companies, biotechnology companies, clinical research organizations, information technology vendors and others. The FDA began requiring the inclusion of a medical laboratory and observation terminology coding system, Logical Observation Identifiers Names and Codes (LOINC®). While this requirement will help align semantics between healthcare and regulated clinical research, readiness for this requirement and understanding of LOINC can vary dramatically across these sectors.

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