The Clinical Trial Risk Tool has been selected as a winner of the Plotly Dash Example Apps Challenge (2023), out of 25 amazing apps submitted by the Dash users community! The trial risk app is built on Plotly Dash, a front end graphical software package.
Thomas Wood from Fast Data Science will be presenting the tool in a webinar on 7 June 2023 which you can book here.
Thank you to all #PlotlyCommunity members who participated in the recent #Dash Example Apps Challenge, and congratulations to the winning submissions!
— Plotly (@plotlygraphs) May 22, 2023
🥇 Clinical Trial Risk Dash App by Thomas Wood
🥈 SARIMA Tuner by Gabriele Albini
🥉 Product Environmental Report Dash App by…
Meanwhile, we have an article published at Wood TA and McNair D. Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness [version 1; peer review: awaiting peer review]. Gates Open Res 2023, 7:56 (https://doi.org/10.12688/gatesopenres.14416.1).
Clinical trial designs vary considerably, impacting study execution, patient recruitment, endpoints, and treatment delivery. Here’s a brief summary of some common designs: First-In-Human (FIH) Studies These are the initial human trials for a new drug, procedure, or treatment, focusing primarily on safety. Cohort Studies These observational studies follow a group of individuals over an extended period to assess risk factors associated with developing specific conditions. Case-Control Studies These studies compare individuals with a particular disease or condition (cases) to similar individuals without the disease (controls) to identify potential risk factors.
This post originally appeared on Fast Data Science’s blog on LinkedIn. The Growing Role of AI in Clinical Trials Clinical trials are vital for advancing medicine, but managing them efficiently is a constant challenge. Traditional methods for assessing risks and estimating costs often miss the mark, leading to delays and unexpected expenses. This is where Artificial Intelligence (AI) and Natural Language Processing (NLP) come into play, offering smarter, data-driven solutions to streamline trial planning and management.
This post originally appeared on Fast Data Science’s blog on LinkedIn. Budgeting is one of the most critical steps when planning a clinical trial. Clinical trials are complex, multi-phase studies that require significant resources, and understanding the costs associated with each phase is crucial for an accurate clinical trial budget. In this post, we’ll explore the different phases of clinical trials and the key factors that influence their costs, providing insights into how to prepare a comprehensive budget that aligns with your trial’s needs.
