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 Clinical Trial Risk Tool is online at https://clinical.fastdatascience.com.
Artificial Intelligence and Deep Learning for Enterprise is a meetup group in London dedicated to talks from people in the industry using developments in AI for exciting real world applications.
We initially developed the Clinical Trial Risk Tool to identify risk factors in HIV and TB protocols. Version 2 is coming soon, which will also make cost predictions (i.e. predict the cost of running a trial in dollars), and which will also cover further disease areas, such as Enteric and diarrheal diseases, Influenza, Motor neurone disease, Multiple sclerosis, Neglected tropical diseases, Oncology, COVID, Cystic fibrosis, Malaria, and Polio.
The project has been funded by the Bill and Melinda Gates Foundation and we have published a technical paper in the journal Gates Open Research:
The software is under MIT License, meaning that it is open source, and can be freely used for other purposes, both commercial and non-commercial, with no restrictions attached. The source code is on Github at https://github.com/fastdatascience/clinical_trial_risk.
[Fast Data Science]](https://fastdatascience.com/) is a leading data science consultancy firm providing bespoke machine learning solutions for businesses of all sizes across the globe, with a concentration on the pharmaceutical and healthcare industries.
The Clinical Trial Risk Tool has been featured in a guest column in Clinical Leader, titled A Tool To Tackle The Risk Of Uninformative Trials, in cooperation with Abby Proch, Executive Editor at Clinical Leader. In the article, Thomas Wood of Fast Data Science highlights the problem of “uninformative” clinical trials – those that don’t provide meaningful results, even if the drug being tested is effective or ineffective. He distinguishes these from simply “failed” trials and emphasises the ethical and financial waste they represent.
Shining a Light on Clinical Trial Risk: Exploring Clinical Trial Protocol Analysis Software 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.
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.