Clinical trials are the backbone of medical progress, but navigating their design and execution can be complex. Fast Data Science is dedicated to helping researchers by analysing clinical trial protocols through the power of Natural Language Processing (NLP).
We are presenting a selection of software which can be used for clinical trial protocol analysis or clinical trial cost prediction and risk assessment.
Fast Data Science’s Clinical Trial Risk Tool (https://app.clinicaltrialrisk.org/) allows researchers to upload a protocol as a PDF, and it uses an AI model to estimate the risk of the trial ending uninformatively.
The Clinical Trial Risk Tool is free to use for pathologies in an international development context such as HIV and TB, Enteric and diarrheal diseases, Influenza, Neglected tropical diseases, COVID, Malaria, and Polio. For trials in Oncology, Motor neurone disease, Multiple sclerosis, Cystic fibrosis, and other pathologies, it will be available on a subscription basis.
You can read more on our website about how the Clinical Trial Risk Tool works. The tool was a winner of the Plotly Dash Apps Challenge and has been published and peer-reviewed in Gates Open Research.
This web-based platform facilitates the creation, management, and registration of high-quality protocols, particularly beneficial for researchers in low-resource settings (access through The Global Health Network: https://edctpknowledgehub.tghn.org/protocol-development/septre-protocol-tool/)
This SaaS platform targets the financial aspects of clinical trials, assisting biopharmaceutical companies, CROs, and service providers with budgeting, proposal development, and vendor management (https://strategikonpharma.com/clinical-maestro-2/)
SoftFormance provides tools for planning, managing, and tracking clinical study data, promoting efficiency and transparency throughout the research process (https://www.softformance.com/industries/software-for-clinical-trials/).
The best protocol analysis software for your research depends on your specific goals. Whether it’s risk assessment, or financial and capacity planning, a dedicated tool can significantly streamline your workflow.
Fast Data Science is committed to expanding our NLP capabilities beyond HIV and TB. Stay tuned for future updates as we strive to empower researchers across a wider range of clinical trials!
On 8 October, Thomas Wood of Fast Data Science presented the Clinical Trial Risk Tool, along with the Harmony project, at the AI and Deep Learning for Enterprise (AI|DL) meetup sponsored by Daemon. You can now watch the recording of the live stream on AI|DL’s YouTube channel below: The Clinical Trial Risk Tool leverages natural language processing to identify risk factors in clinical trial protocols. The initial prototype Clinical Trial Risk Tool is online at https://app.
Understand your clinical trials Are your clinical trials risky? Are costs running away? It’s very tricky to estimate clinical trial costs before a trial is run. Try our free cost calculator. This is a regression model, trained on real clinical trial data. Trial is for condition HIV Tuberculosis COVID Influenza Malaria Enteric and diarrheal diseases Neglected tropical diseases Polio Diabetes Pneumonia Hypertension (see full product) Motor neurone disease (see full product) Multiple sclerosis (see full product) Obesity (see full product) Sickle cell anemia (see full product) Stroke (see full product) Cystic fibrosis (see full product) Cancer (see full product) Other (see full product) Phase Early Phase 1 1 1.
This month, I presented the Clinical Trial Risk Tool at the Plotly Dash in Action webinar. I was interviewed by Plotly’s Community Manager Adam Schroeder. You can watch the relevant part of the webinar below. The Clinical Trial Risk Tool was one of four interactive apps presented as part of the webinar. The speakers at the webinar were: Matteo Trachsel, Head of Sustainability at Thermoplan AG, Switzerland, who presented his Product Environmental Report Dash App, which calculates the carbon footprint of coffee machine usage.
