We are pleased to announce our Special Presentations.

  • Unveiling Estimand----Estimand X Data Scientist
    by Leslie Meng, Director of Biostatistics, Boehringer-Ingelheim

    Leslie Meng, BI, China

    ICH E9(R1) is an addendum on Estimands and Sensitivity Analysis in Clinical Trials to the guideline on Statistical Principles for Clinical Trials (ICH E9). ICH E9(R1) proposed a structured framework to strengthen the dialogue between disciplines involved in the formulation of clinical trial objectives, design, conduct, analysis and interpretation, as well as between sponsor and regulator regarding the clinical question of interest that a clinical trial should address. ICH E9(R1) was finalized in Dec 2019, and now it's at step 5 for adoption by each country's health authority. In January 2021, NMPA announced that the adoption of ICH E9(R1) will start in Jan 2022 which means every clinical trial will implement Estimand in the protocol as well as statistical analysis plan. In this talk, the mystery of Estimand will be unveiled, a case sharing will show how the Estimand concept is implemented in the clinical trial and how this impacts on the analyses from statistical programmers' perspective.

    • Data FAIRification: a foundation for accelerating insight generation
      by Shuang Li, Data Scientist, Product Development Data Sciences, Roche

      Shuang Li, Roche

      The reign of data is beginning. To maximize the value of the data that we own, we should pay attention to where we put these data, or the context in which it was generated or acquired, or how it is managed – we are faced with immense time and resource challenges when we try to reuse these data, for filings or for combining into large-scale datasets needed to enable insight generation. We’d like to talk about how we build an E2E engine from FAIRification activities to use of data sets and how to instill a culture of data citizenship to adopt new practices. With the learning-by-doing approach, we develop a fit-for-purpose framework to support the teams to FAIRify incoming data. FAIR data mindset is becoming the new norm to the business from early study planning through Phase III and beyond. FAIR Data Shared becomes the foundation for accelerating and innovating the discovery, development and delivery of more personalized treatments for our patients.

      • An Brief Introduction to Natural Language Processing in Healthcare
        by Xiaohua Li, Lead of science team, Zuoyi Tech

        Xiaohua Li, Zuoyi Tech

        Recently, Natural language processing(NLP) technology which analyzes and represents language has been experiencing a rapid progress due to deep learning and transformer models. Many NLP models and applications have been developed and showed promising achievements in many areas. This talk will start by short introduction to NLP, NLP history and progress in recent years and will expound our research and products in healthcare industry, including medical knowledge graph construction, EHR document understanding, clinical desicion support models, doctor-patient dialogue process optimization and how we apply NLP technology to support top-tier hospitals and clients in China.