What Is the Future of Pharmacovigilance? - PowerPoint PPT Presentation

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What Is the Future of Pharmacovigilance?

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With the regulatory environment changing almost daily, the challenges of maintaining complex pharmacovigilance systems, is becoming increasingly tough, and the future of PV is set to rely upon AI and other automaton tools. Not only are the public becoming more aware of the issues surrounding pharmacovigilance, but with the frequent use of social media platforms, and intense scrutiny from the media, companies involved in the pharmaceutical industry need to act more diligently than ever before. – PowerPoint PPT presentation

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Title: What Is the Future of Pharmacovigilance?


1
What Is the Future of Pharmacovigilance?
2
  • With the regulatory environment changing almost
    daily, the challenges of maintaining complex
    pharmacovigilance systems, is becoming
    increasingly tough, and the future of PV is set
    to rely upon AI and other automaton tools. Not
    only are the public becoming more aware of the
    issues surrounding pharmacovigilance, but with
    the frequent use of social media platforms, and
    intense scrutiny from the media, companies
    involved in the pharmaceutical industry need to
    act more diligently than ever before.
  • The need to rethink PV strategies
  • With the introduction of AI and other PV
    automaton tools, technology solutions that
    already exist, such as safety databases, must
    work alongside more modern, innovative methods in
    order to be successful.

3
  • How regulatory authorities are using modern tech
  • Collecting and evaluating adverse events for
    therapies is already underway by many regulatory
    authorities, with the use of the U.S. FDA
    Sentinel System, for example and electronic
    system used to monitor the safety of medical
    products available on the market today, and which
    works alongside the FDA Adverse Event Reporting
    System, or FAERS. There are also apps for mobile
    devices that enable users to report adverse drug
    reactions to the relevant authorities.

4
  • Improving end-to-end safety processes
  • In order for PV systems to be truly effective,
    the people managing the system must be properly
    trained, and the system itself must be able to
    receive and manage data from global sources while
    delivering automaton efficiencies. End-to-end
    safety processes must be made more effective, and
    the first step to achieving this process mapping
    to encourage and drive forward improvements.
  • How to achieve full pharmacovigilance
    transformation
  • Involving many levels of automation, the basic
    procedure for automating a process workflow
    involves the tracking and monitoring of tasks
    with the collection of continuous metrics.

5
  • Resulting in automatic entry, processing and
    analysis in a safety database, robotic process
    automation, or RPA, can help to significantly
    reduce manual tasks. Often combined with RPA,
    natural language processing can help humans to
    make more informed decisions, and cognitive
    computing has humans at its heart, driving the
    decisions that provide the required outcome. This
    is in contrast to AI, which naturally involves
    little, or no human interaction.
  • Machine learning and pharmacovigilance
  • A subset of AI, machine learning allows analyst
    and data scientists to build algorithms that,
    based upon data, can learn and make effective
    predictions. Trained to identify patterns in big
    data, the algorithms improve over time.

6
  • Automation is expected to have significant
    benefits for PV, such as improved regulatory
    compliance and enhanced productivity, among
    others.
  • The future of pharmacovigilance
  • With the effective use of the appropriate
    technology, the following 3 safety areas can be
    significantly improved upon
  • Efficiency, quality and compliance can be
    enhanced with the standardization and automation
    of PV processes and safety data management.

7
  • Through the mining of data, emerging safety
    signals can be better identified and predicted.
  • AI gives a much clearer view of safety issues,
    while advanced cognitive solutions extract code
    and process AE data for greater transparency and
    trust.
  • Building a roadmap for the successful future of
    pharmacovigilance
  • A clear vision, robust strategies, milestone
    initiatives and strong partners with proven track
    records in PV delivery, safety technology and
    regulatory reporting, are essential elements for
    any pharmaceutical company wanting to guarantee
    the success of PV for the future.

8
  • Making efficient and proper use of such
    technologies as mobile apps tech for big data
    analytics and cloud-based solutions, are set to
    help companies progress towards end-to-end
    automation right across the spectrum of
    pharmacovigilance.
  • For all companies wanting to meet the many and
    varied challenges that PV throws at them daily,
    and to ensure that they can play a role in its
    future, they must embrace advanced technology
    solutions and automation.

9
  • Agile Scientific is a life sciences organization
    that brings decades of industry knowledge,
    expertise, processes, best practices, and systems
    to companies. Agile Scientifics clinical
    services function to accelerate all facets of
    drug development, ensure compliance at a global
    level and optimize pipeline value / ROI. Agile
    Scientific Group LLC is fortunate to partner with
    smaller virtual organizations and Fortune 500
    Life Sciences companies alike. We have extensive
    experience providing focused, pragmatic clinical
    solutions to our sponsor Life Science
    organizations and CROs across all areas of Drug
    Safety, Regulatory Affairs, HEOR /
    Pharmacoepidemiology, Quality Assurance.
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