This post originally appeared on Fast Data Science’s blog on LinkedIn.
Clinical trials, the backbone of medical science advancement, often grapple with high costs, complexity, and lengthy timelines. Fast Data Science presents Fast Clinical AI, a game-changing solution that harnesses the power of Natural Language Processing (NLP) and predictive modelling to tackle these challenges head-on.
Fast Clinical AI automates the extraction of critical information from trial protocols, significantly reducing manual efforts. This tool identifies risk factors and predicts costs and enrolment criteria, ensuring efficient trial planning and execution.
By identifying potential risks early in the trial process, Fast Clinical AI allows researchers to take proactive measures, minimising the chances of trial delays or failures. This proactive approach ensures that trials are faster and more reliable.
Fast Clinical AI helps predict and manage the costs associated with clinical trials, ensuring better resource allocation. Reducing manual efforts and streamlining processes significantly reduces the time required to bring new treatments to market.
Explore how Fast Clinical AI can revolutionise your clinical trials. Visit here for more details. Learn more about clinical trial cost modelling with NLP and AI here. Connect with us today to see how we can support your clinical trial efforts. Let’s innovate together!
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Creating clinical trial budgets from protocols Creating a clinical trial budget is a fiddly and time consuming process. The playbook for running the clinical trial is a document called the protocol. You can find examples of protocols here. The protocol states how many participants will take part in the trial and also what visits and procedures will take place. Above: a protocol. Source: NCT04128579 A clinical trial manager must read the protocol and look for all pieces of information in the protocol that is relevant to the budget, in particular the Schedule of Events (also called Schedule of Assessments or Schedule of Activities), which is a table or series of tables which indicate which procedures and assessments will take place on which the visits.
We have improved the Clinical Trial Risk Tool in the last 6 months, making it more user friendly and taking on board the feedback that we’ve received. We’ve improved the accuracy of the machine learning components too. The tool now outputs its key figures such as risk levels and estimated cost in easily readable cards, so you can see at a glance the key takeaways from your protocol: The risk factors are now organised into collapsible categories, so you can explore them easily without an information overload.
Guest post by Safeer Khan, Lecturer at Department of Pharmaceutical Sciences, Government College University, Lahore, Pakistan Introduction The success of a clinical trial is strongly dependent on the structure and coordination of the teams managing it. Given the high stakes and significant impact of every decision made during the trial, it is essential for each team member to collaborate efficiently in order to meet strict deadlines, comply with regulations, and ensure reliable results.
