Vial’s Post

Love it! Evidence-based decision-making in clinical trials needs to become the standard. Too many delays in clinical development and operations can be overcome with this approach! 🧬🧪🧑🔬 #vial #datainsights

This AI evolution in the medical industry has already begun, and its progress hinges on four main pillars: risk-based methodologies, AI, complex protocol designs, and DCTs. Read more about how data science is changing the face of healthcare at Clinical Leader https://lnkd.in/eSjBfUAC

Is artificial intelligence the future of clinical trials? According to Clinical Leader, there is no doubt about it! In fact, “AI could be useful from recruitment to post-study data management, and could also create study plans, read protocols, and suggest insights”. It could therefore “automate or radically transform the processes to improve study timelines.” Do you resonate with this statement? If so, exploring Protocol AI's capabilities could be a game-changer for you! Protocol AI is the first-in-class AI software revolutionizing clinical trial protocol development, empowering experts to conduct faster, cheaper, and safer trials. Curious? Contact us and start developing clinical trial protocols of the future. https://lnkd.in/eSjBfUAC #ArtificialIntelligence #ClinicalTrials #ClinicalInnovation #AIHealthcare #DigitalHealth #HealthTech #AIinMedicine #ProtocolAI #ClinicalTrialInnovation #FutureOfHealthcare #AIForGood #MedTech #DataScienceInHealthcare #SmartHealthcare #AIResearch #HealthcareTransformation

Seeing more and more articles like this one about the utilization of AI for CDM in clinical trials. I've actually spoken with a number of CDM's about this recently and the resounding feedback has been "the technology's not there yet, but it will be". While this may come off as ominous for those whose livelihoods are in CDM (like myself, to an extent), I think the bigger picture we're missing is that CDM AI platforms aren't capable of pooling data from various EDC's. While there are EDC's which have automated (AI) functionality, their intelligence and ultimately their decision-making ability is limited to the data from other trials which use that specific EDC. For laypeople (again, like myself) what this can be compared to is if, for example, I knew every publicly available piece of information about oranges, but you wanted me to make a decision/prediction about all fruit in general, you wouldn't be able to get an accurate answer out of me. The same goes for EDC's like RAVE, which has an AI functionality, but this can only make decisions based on trial data from groups who use RAVE. That's pretty limiting when you consider how many EDC's there are in use today. I'm very interested in hearing from my network about where you think AI's impact in CDM is headed. Feel free to comment below or let me know if you'd like to hop on a call! https://lnkd.in/gp8exVve

The unification of systems requires an actionable cloud-based foundation that can break down silos, unite systems, and perform actions in accordance with specific requirements and controls to optimize processes and accommodate the various complex workflows of all stakeholders in the ecosystem. For ultimate customization capabilities, check out REDCap Cloud

AI IS NOT COMING - AI IS HERE. Eisai will use Medidata's Clinical Data Studio to streamline trials and improve patient experience, giving the Sponor control over clinical data, the ability to execute scalable and complex trials, and enhancement of the overall patient experience. The future is now! #AI #clinicaltrials #datamanagement #collaboration #research #development #data #patientoutcomes #discovery https://lnkd.in/e7dFTAMR

Healthcare and Life-sciences is being transformed by Data and AI. Paul Rankin shares his expert perspective on how data and the clinical trial value chain is rapidly evolving in step with these advances to deliver better patient outcomes. #datasecurity

AI has become ubiquitous across virtually every industry, and life sciences organizations are certainly not the exception. Its benefit is felt across various phases of a trial life cycle, from improving efficiency in clinical research with vast data handling and analysis capabilities, to enhancing the patient experience through remote health assessments and progress trackers. Read more about how AI is revolutionizing clinical work streams here: https://bit.ly/49Bw6tv #AI #IndustryInsights #Clinical

One possible use of AI in pharm is automated data management, which can help small companies speed up the process. Do you think automated data management will become the norm? #AI #Biopharma #Efficiency

Data-Driven Development: How Real-World Data and AI Are Transforming Clinical Trials