Newsletter January 2020
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Newsletter January 2020 |
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Risk based monitoringRisk-based monitoring refers to a series of monitoring processes that include the presumed risks that could affect the quality or safety of a study, advised by Health Authorities (ICH GCP Guideline E6[R2]) for responding better to trials’ main challenges and priorities. CROs accept that each study demands its own risk-based monitoring processes, which is why they emphasize on the preliminary steps (trial, protocol and database design) before the study conduction for identifying possible risks and putting in place an adapted monitoring. Traditionally, the sponsor got data gathered from different sites, and it was 100% verified. RBM strategies are changing traditional clinical study conduction. Thanks to the availability of sources off-site and telecommunication technologies, the study coordinator is not only able to remotely monitor subjects and sites’ data but also to deeply analyze, remotely, the alerts and to manage them. It encourages and allows the decision making "as soon as possible". Among the different RBM strategies recommended by the FDA and EMA, we can retain 4:
Different tools need to be used to implement RBM within a trial such as: statistics, strong predictive and advanced analytics and it can also integrate AI and MLArtificial Intelligence and Machine Learning in RBMAI and ML have impacted the way of conceiving Human tasks and roles. Many consider that new technologies are helping professionals to focus on what really matters by providing them powerful analytics tools. In Clinical trials and RBM, new technologies are not only helping reduce the source data verification time but to also quickly identify risks on subject exposure, level of AE risks on sites, protocol risks, false positive/negatives… This helps protect patients’ safety and enhance their quality of life. The use of AI and ML in RBM relies, among others, on the use of smart risk dashboards (created at study-design phase) whose alerts integrate data mining, smart and predictive graphs and other data science tools to indicate situations that need further investigation. Although we might be aware of new and evolving technologies' power, can we say that in some years, studies will be fully conducted by machines?Gregg Larson, VP of Clinical Operations at Ultragenyx Pharmaceuticals Inc., was interviewed by the DIA's forum on November 2019, and he stressed on the importance of Human critical thinking when using new technologies for RBM. He said that "fully relying on algorithms can be misleading" and declared that the role of new technologies is mainly take the "checklist" tasks’ place, thanks to its ability of fast processing. The role of Clinical research associates is mainly evolving to the climax of its capacity on being judgemental when facing data for critical decision-making. The interviewee insisted on the skill of staying "vigilant on focusing on what matters the most". As AI and ML, along with new technologies, are still evolving, we can expect changes and greater integration of these technologies within RBM on Clinical trials. And you, what do you think about new technologies being used for RBM on Clinical trials? Sources: |
Save-the-date, conferences and events to comeDIA Europe 2020
ACDM Annual Conference 2020
9ème Journée de la Recherche Clinique
SCDM Interesting White Paper
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