Apr 06, 2023
No image
Completed
Clinical Trial Complexity Modelling
$25,000+
7-12 months
Germany, Ingelheim am Rhein
1
Service categories
Service Lines
Big Data
Domain focus
Healthcare
Programming language
Python
Frameworks
TensorFlow
Subcategories
Big Data
Predictive Analytics
Text Analytics
Challenge
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 problem is that each protocol is up to 200 pages long and the structure can vary.
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 problem is that each protocol is up to 200 pages long and the structure can vary.
Solution
For the German pharma company Boehringer Ingelheim, we developed and trained a deep learning tool using natural language processing (NLP) to predict more than 50 output variables from a clinical trial protocol.
For the German pharma company Boehringer Ingelheim, we developed and trained a deep learning tool using natural language processing (NLP) to predict more than 50 output variables from a clinical trial protocol.
Results
Our model and front end that wraps it allow pharma companies and regulators to analyse and quantify large numbers of clinical trial protocols, allowing more accurate cost estimation.
The technique can be extended to other industries where large unstructured or semi-structured documents are the norm.
Our model and front end that wraps it allow pharma companies and regulators to analyse and quantify large numbers of clinical trial protocols, allowing more accurate cost estimation.
The technique can be extended to other industries where large unstructured or semi-structured documents are the norm.