Friday, November 6 Single-Day Event
|Presentation (click for abstract)
|Presenter (click for bio)
|Collection, Analysis, Visualization, and Sharing for COVID-19 Insights: Cloud-based Data-driven Approach
|Naoki Mashiko, Amazon Web Services
|Slides (PDF, 45.8MB)
|COVID-19 Update – Emerging Trends and Data about SARS-CoV-2 Epidemiology and Genetics from a Data Analytics Perspective, Practical Guidance and Insights from PerkinElmer and TIBCO® *
|Dan Weaver, PerkinElmer Bioinformatics
Michael O’Connell, TIBCO
|Slides (PDF, 6.4MB)
|Responding to COVID-19 Leveraging Analytics
|Toru Tsunoda, SAS Institute Japan
|Slides (PDF, 2.8MB)
|CDISC Response to COVID-19 *
|Bess LeRoy, CDISC
|Slides (PDF, 3.1MB)
|Skill Building of Modeling & Simulation and its Applications
|Takamichi Baba, Shogo Miyazawa, Satoki Fujita and Yoshitake Kitanishi, Shionogi & Co., Ltd.
|Slides (PDF, 2.7MB)
Seminar and Presentation AbstractsCollection, Analysis, Visualization, and Sharing for COVID-19 Insights: Cloud-based Data-driven Approach
Naoki Mashiko, Amazon Web Services
Healthcare and life sciences organizations are accelerating global COVID-19 response from research, development, clinical care, and prevention. In order to find and share important insights in real-time, a data-driven approach - collecting, analyzing, and visualizing broad and large-scale data – is essential to be more agile, innovative, and effective.
AWS, among others, collaborate such organizations to host open data for COVID-19 response; anyone can experiment and analyze curated COVID-19 related data and share results and insights with other collaborators. In this session, we will share data-driven use cases and how the cloud solved and contributed the current issues with reference architectures and best practices.
COVID-19 Update – Emerging Trends and Data about SARS-CoV-2 Epidemiology and Genetics from a Data Analytics Perspective, Practical Guidance and Insights from PerkinElmer and TIBCO®
Dan Weaver, PerkinElmer Bioinformatics
Michael O’Connell, TIBCO
The COVID-19 situation continues to evolve with new and expanded data sets becoming available every day. The PerkinElmer and TIBCO teams continue to analyze this data to provide additional insights for the research community. Our Experts show how the TIBCO Spotfire platform and Lead Discovery Premium solution can help us to gain a better understanding of COVID-19. Topics include the history of Coronavirus (MERS, SARS and COVID-19) and what we currently know about its genetics, sequence and structure analysis. In addition analyses of COVID-19 associated proteins via Lead Discovery Premium will focus on how the disease has evolved as it has spread, and exploration of preliminary insights on human genetic factors that drive severity of COVID19 symptoms will be discussed.
Responding to COVID-19 Leveraging Analytics
Toru Tsunoda, SAS Institute Japan
SAS believe many social issues can be resolved leveraging analytics and is proud to be part of the Data for Good movement, which encourages using data in meaningful ways to solve humanitarian issues around poverty, health, human rights, education and the environment. To effectively mitigate the disruptions caused by COVID-19, various global and local initiatives have been taken within SAS. They include support to COVID-19 researches, prediction of patients and contact tracing. In this session, SAS’ belief and some initiatives / use cases will be shared.
CDISC Response to COVID-19
Bess LeRoy, Head of Standards Development, CDISC
In late March 2020, CDISC convened a Task Force to address challenges around standardizing COVID-19 data. Members of the Task Force included industry stakeholders, regulators, academia, and key CDISC data standards staff. The Task Force worked over a period of four weeks and on April 21st, 2020 published guidance on three areas of focus: a CDISC Interim User Guide for COVID-19 for studies developing treatments and vaccines for COVID-19, guidance for ongoing studies disrupted by the COVID-19 Pandemic, and resources for public health researches which included annotated case report forms and mapping spreadsheet for a tool developed by the World Health Organization (WHO) and the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC). This presentation will describe the development process that was followed and the lessons since publication.
Skill Building of Modeling & Simulation and its Applications
Takamichi Baba, Biostatistics2 Group, Biostatistics Center, Global Development Division, Shionogi & Co., Ltd.
Shogo Miyazawa, Data Science Office, Integrated Disease Care Division, Shionogi & Co., Ltd.
Satoki Fujita, Data Science Office, Integrated Disease Care Division, Shionogi & Co., Ltd.
Yoshitake Kitanishi, Head of Data Science Office, Integrated Disease Care Division, Shionogi & Co., Ltd.
Modeling and simulation (M&S), which aims to predict future realities and make experimental inferences in a virtual setting from various and complex data, is not only used for evaluating pharmacokinetics but also for economics, hygiene and so on. The SIR model categorized under M&S, which has been used internationally due to the current Covid-19 epidemics, is highly contributory to decision making. Therefore, M&S is attracting more and more attention on a global scale. Shionogi has accumulated data on how to efficiently apply M&S in various critical decision making situations In this presentation, we would like to introduce our efforts by focusing on M&S in the field of infectious diseases. Through M&S, we have been promoting the understanding of the transmission of infectious diseases and the assessment of the impact of infectious diseases on society and the treatment there of. In order to carry out the evaluation efficiently, we have established an organization to utilize various analyses software including Open Source Software such as SAS, MATLAB, R, Python, Berkeley Madonna, etc. We have applied M&S not only to respiratory infections but also to infections transmitted sexually or through mosquitoes. We have also been promoting discussions with each value chain. Throughout this talk, we will introduce our way of construction of organization for these analyses, and concrete and situational analysis examples. In addition, there are some cases in which the transmission of diseases is not limited to infectious diseases but is also applicable to other diseases, and the use of M&S is rapidly expanding. With that, we would like to share the latest cases.