CLIC News Round up – September 8, 2020


News Roundup
September 8, 2020

Updates from CLIC

Improving Standards, Practices, and Processes

New York University’s (NYU) Clinical and Translational Science Institute has developed a strategy to conduct pre-reviews of studies before they are submitted to a full convened IRB. This new process was implemented in response to improving its scientific review standards and practices, as well as a means to maximize the resources at their institution. To learn more about how NYU’s new process enabled the rapid review of study proposals during the COVID-19 crisis, read their story here.

Virginia Commonwealth University (VCU) recognized the need for a database that enables performance data to be shared openly, improves transparency, and eases the administration burden on principal investigators and study teams. This new database was the result of an effort that was initiated to better define key performance indicators. Read how VCU’s new database enabled improved teamwork to respond to studies submitted during COVID-19.


Registration is Open!

The CLIC hosted NCATS responsive Un-Meeting has refocused and rescheduled to a ½ day virtual Un-Meeting Wednesday, September 30th, 2020. This new “rapid-response” topic will encourage discussions around the changes resulting from the COVID pandemic. Potential themes include

    • Identifying clinical research trial design opportunities as a unified network in the post-COVID clinical era
    • What is the impact on recruitment?
    • What is the role of the CTSA Program in clinical research post-COVID?
    • New uses of technology in research?

Other topics to be defined, because, like all of Un-Meetings, the attendees make the agenda!  To keep conversations meaningful, attendance will be limited, so register soon, we are filling up fast! We look forward to seeing you in the ether!

  • What does training look like?
  • What do remote trials look like?

    News from around the CTSA Program Consortium

    UPitt Virologist addresses questions raised by a man who reportedly was reinfected with COVID-19

    A 33-year old man was found to have a second SARS-CoV-2 infection some four-and-a-half months after he was diagnosed with his first, from which he recovered. The man, who showed no symptoms, was diagnosed when he returned to Hong Kong after a trip to Spain.


    OHSU Invent-a-thon
    Brainstorm – Build-Make Healthcare Better!

    Oregon Health & Science University is joining forces with MIT Hacking Medicine, creative problem solvers, and academic and industry partners from across the region to build innovative MedTech and digital health/health IT solutions to pressing healthcare challenges. Hear from inspiring keynote speakers, join an interdisciplinary team of fellow innovation enthusiasts, brainstorm and build a prototype, attend workshops, receive coaching from mentors, speak with our sponsors, and pitch a solution to investor judges to compete for up to $40,000 in team prizes.


    ICYMI: News from the Science & Research World

    npj Digital Medicine volume 3, Article number: 107 (2020)

    Stanford researchers are developing a delivery science for artificial intelligence in healthcare

    Artificial Intelligence (AI) has generated a large amount of excitement in healthcare, mostly driven by the emergence of increasingly accurate machine learning models. However, the promise of AI delivering scalable and sustained value for patient care in the real world setting has yet to be realized. In order to safely and effectively bring AI into use in healthcare, there needs to be a concerted effort around not just the creation, but also the delivery of AI. This AI “delivery science” will require a broader set of tools, such as design thinking, process improvement, and implementation science, as well as a broader definition of what AI will look like in practice, which includes not just machine learning models and their predictions, but also the new systems for care delivery that they enable. The careful design, implementation, and evaluation of these AI-enabled systems will be important in the effort to understand how AI can improve healthcare.

     

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