Catalog Advanced Search

Search by Category
Search by Format
Sort By
Search by Category
Search by Format
Search by Date Range
Products are filtered by different dates, depending on the combination of live and on-demand components that they contain, and on whether any live components are over or not.
Start
End
Search by Keyword
Sort By
  • Contains 1 Component(s)

    The simultaneous rise in demand for global RWD and proliferation of potential data sources and analytic tools require pharmacoepidemiologists to understand and collaborate on data strategy.

    The simultaneous rise in demand for global RWD and proliferation of potential data sources and analytic tools require pharmacoepidemiologists to understand and collaborate on data strategy. This four-part video series on data strategy, including governance, quality management, architecture, and asset planning was co-developed by ISPE members and Donna Burbank of Global Data Strategy.


  • Contains 1 Component(s)

    This webinar aims to provide an in-depth understanding of the electronic health records (EHR) ‎databases in Hong Kong, Japan, Taiwan, and South Korea‎.

    Presented by 

    Dr. Celine Chui (Hong Kong), Dr. Masao Iwagami (Japan), Prof Edward Lai (Taiwan), Dr. Judy Shin (South Korea)

    This webinar aims to provide an in-depth understanding of the electronic health records (EHR) databases in Hong Kong, Japan, Taiwan, and South Korea. Participants will gain valuable insights into the unique features of each database, including Hong Kong's CDARS (Clinical Data Analysis and Reporting System), Japan's MDV (Hospital-based database provided by Medical Data Vision Co., Ltd) and JMDC (claims data provided by JMDC Inc.), South Korea's HIRA (Health Insurance Review and Assessment Service) and NHID (The National Health Information Database), and Taiwan's NHIRD (National Health Insurance Research Database) and CGRD (Chang Gung Research Database). Presenters from each region will introduce these databases and showcase research done using these databases.

    Learning Objectives:

    1. Provide an overview of electronic health record databases in Asia with potential for international collaboration.

    2. Foster cross-continental international collaboration.



  • Contains 1 Component(s)

    The simultaneous rise in demand for global RWD and proliferation of potential data sources and analytic tools require pharmacoepidemiologists to understand and collaborate on data strategy.

    The simultaneous rise in demand for global RWD and proliferation of potential data sources and analytic tools require pharmacoepidemiologists to understand and collaborate on data strategy. This four-part video series on data strategy, including governance, quality management, architecture, and asset planning was co-developed by ISPE members and Donna Burbank of Global Data Strategy.


  • Contains 1 Component(s)

    This session aims to help attendees focus on challenges and insights into how operationalizing barriers can be overcome.

    Presented by Andrew Bate, VP, Head of Safety Innovation & Analytics, GSK

    Despite the hype, AI/ML is not new: it’s been used routinely in elements of Pharmacoepidemiology and Safety for decades. For all the talk of experimentation and related methodological publications, the biggest challenges are often operationalizing these activities into routine use. This webinar will focus on challenges and insights into how operationalizing barriers can be overcome, and will include examples of how AI/ML has been or is being incorporated to support routine safety surveillance activities. 

    Learning Objectives:

    • Recognize what AI is and the opportunities it affords for pharmacoepidemiology and routine safety surveillance activities
    • Understand how AI is impacting safety now and how it may do so in the future
    • Appreciate some of the implications of AI on the field


  • Contains 1 Component(s)

    This tutorial aims to give a practical introduction tailored for pharmacoepidemiologists on how to set up, structure, and implement analytic workflows using Git, the most frequently used distributed version-control system to date.

    Presented by Janick Weberpals, Transparency and reproducibility in pharmacoepidemiology research 

    Transparency and reproducibility in conducting healthcare database studies in pharmacoepidemiology are critical scientific requirements for meaningful research. While many advances have been made in the documentation and reporting of study protocols and results, the principles for version control and sharing of analytic code in real-world evidence are not yet as established as in other quantitative disciplines like computational biology and health informatics. 

    This tutorial aims to give a practical introduction tailored for pharmacoepidemiologists on how to set up, structure, and implement analytic workflows using Git, the most frequently used distributed version-control system to date. 


  • Contains 1 Component(s)

    Presented by Kathryn Rough, IQVIA - This webinar will discuss what it means for machine learning algorithms to be fair, explore potential issues, and share concrete steps for creating fair algorithms, as part of our larger goal of promoting equity in health systems.

    Machine learning has the potential to transform aspects of how healthcare and medicine are delivered, yet we know these technologies have the capacity to exacerbate existing inequalities (or introduce new ones). 

    This webinar will discuss what it means for machine learning algorithms to be fair, explore potential issues, and share concrete steps for creating fair algorithms, as part of our larger goal of promoting equity in health systems. Special attention will be paid to fairness and bias considerations for large language models (e.g., ChatGPT/GPT-4, Bard/LaMDA). 


  • Contains 1 Component(s)

    This webinar was presented on behalf of the ISPE Vaccines Special Interest Group (SIG) and the ISPE Student Council (SISPE).

    This webinar was presented on behalf of the ISPE Vaccines Special Interest Group (SIG) and the ISPE Student Council (SISPE). Event highlights included: engaging with top professionals from pharmaceuticals, consulting, academia, and government; exploring various career paths within the vaccine industry; and participating in a dynamic agenda that included panelist introductions, a moderated Q&A session, and an open Q&A forum. This is an excellent platform for professionals and students alike to gain insights and network with industry leaders.

  • Contains 1 Component(s)

    Synthetic data is a form of model generated data that shares the same patterns and characteristics as real ‎data. The applications of synthetic data in pharmacoepidemiology are still emerging, but can offer new ‎ways for us to:‎ ‎1. Enable the internal reuse of datasets and sharing data with external parties in a privacy-preserving ‎manner (i.e., it can be seen as anonymization 2.0)‎ ‎2. Augment and expand datasets that are small for training machine learning models‎ ‎3. Mitigate bias in datasets by simulating observations from the under-represented groups ‎4. Simulate patients for clinical trials that are experiencing problems, including under-recruitment Synthetic data can be created when a generative AI model is trained on source data, such as claims ‎database or an EMR database. This AI-generated data would not have a one-to-one mapping to the ‎original data, and therefore will have strong privacy preserving characteristics, and the generated data ‎can be much larger than the original data. Some of these use cases have already been applied in practice ‎and some are still in the formative stage of development. This webinar will give an overview of synthetic ‎data generation and walk through some of the above applications.‎ This webinar is sponsored by the Digital Epidemiology Special Interest Group.‎

    Methods and Applications of Synthetic Data in Pharmacoepidemiology (November 15, 2023)

    Synthetic data is a form of model generated data that shares the same patterns and characteristics as real data. The applications of synthetic data in pharmacoepidemiology are still emerging, but can offer new ways for us to:

    1. Enable the internal reuse of datasets and sharing data with external parties in a privacy-preserving manner (i.e., it can be seen as anonymization 2.0)

    2. Augment and expand datasets that are small for training machine learning models

    3. Mitigate bias in datasets by simulating observations from the under-represented groups

    4. Simulate patients for clinical trials that are experiencing problems, including under-recruitment

    Synthetic data can be created when a generative AI model is trained on source data, such as claims database or an EMR database. This AI-generated data would not have a one-to-one mapping to the original data, and therefore will have strong privacy preserving characteristics, and the generated data can be much larger than the original data. Some of these use cases have already been applied in practice and some are still in the formative stage of development. This webinar will give an overview of synthetic data generation and walk through some of the above applications.
    This webinar is sponsored by the Digital Epidemiology Special Interest Group.

    This webinar is aimed towards industry/service providers, academia, government/regulatory and students.

    .

  • Contains 1 Component(s)

    This webinar covers key concepts in designing and conducting pragmatic randomized trials in electronic ‎databases, like electronic health record systems and administrative claims databases. These designs are ‎often referred to as "database-randomized trials", which may be increasingly possible within electronic ‎databases used in pharmacoepidemiology. Content will include conceptual differences from traditional ‎pragmatic trials, advantages and disadvantages of these types of trials, and relevant examples.‎

    Designing and Conducting Pragmatic Randomized Trials in Electronic Databases in ‎Pharmacoepidemiology (October 12, 2023)

    This webinar covers key concepts in designing and conducting pragmatic randomized trials in electronic databases, like electronic health record systems and administrative claims databases. These designs are often referred to as "database-randomized trials", which may be increasingly possible within electronic databases used in pharmacoepidemiology. Content will include conceptual differences from traditional pragmatic trials, advantages and disadvantages of these types of trials, and relevant examples.

    This webinar is aimed towards industry/service providers, academia and students.

    .

  • Contains 1 Component(s)

    Pharmacoepidemiology and Drug Safety (PDS), the official journal of ISPE, presents the Ronald D. Mann ‎Best Paper Award each year to the strongest contribution within a given volume of the journal. The award ‎for 2022 is presented to Dr. Elizabeth A. Suarez and collaborators for their paper ”Novel Methods for ‎Pregnancy Drug Safety Surveillance in the FDA Sentinel System.”‎ The paper discussed the application of TreeScan™, a statistical data mining tool, within the FDA Sentinel ‎System to simultaneously identify multiple potential adverse neonatal and infant outcomes after ‎maternal medication exposure. This method could supplement existing approaches to enhance the ‎surveillance of medication safety during pregnancy.‎ In this webinar, Dr. Suarez will present findings of their study, followed by comments by PDS regional ‎editor for the Americas, Dr. Vincent Lo Re. Audience will not only have the opportunity to discuss the ‎paper with Dr. Suarez and but also ask questions regarding manuscript submission to PDS with Dr. Lo Re.‎

    Pharmacoepidemiology and Drug Safety Best Paper of 2022 --- Novel Methods for Pregnancy Drug Safety Surveillance in the FDA Sentinel System (September 15, 2023)

    Pharmacoepidemiology and Drug Safety (PDS), the official journal of ISPE, presents the Ronald D. Mann Best Paper Award each year to the strongest contribution within a given volume of the journal. The award for 2022 is presented to Dr. Elizabeth A. Suarez and collaborators for their paper ”Novel Methods for Pregnancy Drug Safety Surveillance in the FDA Sentinel System.”

    The paper discussed the application of TreeScan™, a statistical data mining tool, within the FDA Sentinel System to simultaneously identify multiple potential adverse neonatal and infant outcomes after maternal medication exposure. This method could supplement existing approaches to enhance the surveillance of medication safety during pregnancy.

    In this webinar, Dr. Suarez will present findings of their study, followed by comments by PDS regional editor for the Americas, Dr. Vincent Lo Re. Audience will not only have the opportunity to discuss the paper with Dr. Suarez and but also ask questions regarding manuscript submission to PDS with Dr. Lo Re.

    This webinar is aimed towards industry/service providers, academia, government/regulatory, and students.
    .