Natural language processing is becoming ever more important in research. The explosion in interest in LLMs is sparking many opportunities to analyse text data in healthcare, social sciences, and other areas.
We’re proud to announce that 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 community.
Funded by the Bill and Melinda Gates Foundation, this app uses natural language processing, Plotly Dash, and the spaCy and Scikit-Learn libraries to calculate the risk of a clinical trial failing to deliver informative results. It reads the trial protocol and identifies key features from the text which are fed into a risk model.
Join Plotly’s webinar to see the tool in action! https://tinyurl.com/4zd3emkr
You can try the new version of the app at: https://clinicaltrialrisk.org/tool
You can try version 1.0 of the app (using Plotly Dash) at: https://clinicaltrialrisk.org/tool/login?guest=true/.
Wood TA and McNair D. Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness. Gates Open Res 2023, 7:56 (https://doi.org/10.12688/gatesopenres.14416.1).
Guest post by Safeer Khan, Lecturer at Department of Pharmaceutical Sciences, Government College University, Lahore, Pakistan Introduction The success of clinical studies relies heavily on proper financial planning and budgeting. These processes directly impact key factors such as project timelines, resource allocation, and compliance with regulatory requirements. The accurate forecasting of costs for clinical trials, however, is a highly complex and resource-intensive process. A study by the Tufts Center for the Study of Drug Development found that the average cost of developing a new drug is approximately $2.
Guest post by Safeer Khan, Lecturer at Department of Pharmaceutical Sciences, Government College University, Lahore, Pakistan Introduction Recent years have seen a substantial rise in oncology clinical trials, with annual growth exceeding 260 studies on average [1]. Despite this increase, these studies continue to be some of the most demanding and resource-intensive in clinical research. The combination of intensive monitoring, detailed assessment schedules, and highly specific eligibility criteria creates substantial operational challenges.
Guest post by Safeer Khan, Lecturer at Department of Pharmaceutical Sciences, Government College University, Lahore, Pakistan Introduction In recent years, the cost of conducting clinical trials has risen dramatically. This increase has posed a significant challenge for pharmaceutical companies, researchers, and healthcare innovators. According to a study published in Nature Reviews in 2017, the median cost of conducting a study was $3.4 million for phase I trials, $8.6 million for phase II trials, and $21.
