Using AI to calculate trial risk

Clinical Trial Risk Tool

We have developed a machine learning and rule based tool called the Clinical Trial Risk Tool using natural language processing. The Clinical Trial Risk Tool allows a user to upload a trial protocol and which categorises the protocol as high, medium, or low risk of ending uninformatively.

When a pharmaceutical company develops a drug, it needs to pass through several phases of clinical trials before it can be approved by regulators.

Before the trial is run, the drug developer writes a document called a protocol. This contains key information about how long the trial will run for, what is the risk to participants, what kind of treatment is being investigated, etc.

The tool is open-source under MIT licence and it does not save any of your data.

The problem is that each protocol is up to 200 pages long and the structure can vary.

Currently, professionals at a funding organisation read the protocols and perform a subjective assessment of the trial’s cost, complexity, and risk of ending uninformatively.

One of the most common causes of a trial ending uninformatively is underpowering. There are several indicators of high risk of uninformativeness which can be identified in a protocol, such as a lack of and or an inadequate statistical analysis plan, use of non-standard endpoints, or the use of cluster randomisation. Low-risk trials are often run by well-known institutions with external funding and an international or intercontinental array of sites. These indicators can be referred to as features or parameters.

ThIS PROJECT SHOWS what is possible with natural language processing. THE TOOL MAY BE EXTENDED IN FUTURE TO identify a more complete set of cost, complexity, or uninformativeness risk factors.

Benefits or details include:

The risk factors which the tool identifies are:

The features are then passed into a scoring formula which scores the protocol from 0 to 100, and then the protocol is flagged as HIGH, MEDIUM or LOW risk

How to cite the Clinical Trial Risk Tool?

If you would like to cite the tool alone, you can cite:

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 doi: 10.12688/gatesopenres.14416.1.

A BibTeX entry for LaTeX users is

	doi = {10.12688/gatesopenres.14416.1},
	url = {},
	year = 2023,
	month = {apr},
	publisher = {F1000 Research Ltd},
	volume = {7},
	pages = {56},
	author = {Thomas A Wood and Douglas McNair},
	title = {Clinical Trial Risk Tool: software application using natural language processing to identify the risk of trial uninformativeness},
	journal = {Gates Open Research}