Cortical.io Case Studies How a biopharmaceutical company evaluated social media to monitor off-label drug use

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	How a biopharmaceutical company evaluated social media to monitor off-label drug use Cortical.io

How a biopharmaceutical company evaluated social media to monitor off-label drug use

Cortical.io

Technology Category	Analytics & Modeling - Natural Language Processing (NLP)
Applicable Industries	Pharmaceuticals
Applicable Functions	Product Research & Development Quality Assurance
Use Cases	Chatbots Regulatory Compliance Monitoring
Services	Data Science Services
Challenge	The biopharmaceutical company was facing a challenge in tracking off-label usage of their medications. Off-label usage refers to the prescribing of medications in a manner not specified by the FDA and accounts for 10 to 20 percent of all prescriptions written. However, its exact extent is difficult to measure because pharmaceutical companies have no direct feedback mechanism to track what medical conditions their products are prescribed for. The company had no means to monitor how their medications are used as patient records are subject to privacy restrictions and do not allow the company to reconstruct which medication was prescribed for which condition. The company decided to use social media, particularly Reddit, as a source of knowledge about medication usage. Read More
About Customer	The customer is a global biopharmaceutical company. The company does not sell directly to consumers and therefore has no means to monitor how their medications are used. Patient records are subject to privacy restrictions and when available they do not allow the company to reconstruct which medication was prescribed for which condition. The company wanted to gather intelligence about off-label drug usage by screening patient comments in social media. Read More
Solution	The company turned to Cortical.io for their expertise in developing Natural Language Understanding (NLU) based-solutions to develop a tool able to overcome the hurdle of ambiguity and vague wording inherent to social media posts and to correctly interpret them despite the limited number of posts available for training. During the initial phase of the project, Cortical.io created a prototype based on SemanticPro Classify & Automate to identify mentions of on- and off-label medication usage in a static set of Reddit posts. Leveraging Cortical.io meaning-based algorithms, the application automatically and accurately filters and classifies Reddit messages and summarizes the results. Cortical.io trained classifiers for each of the example drugs specified by the company using publicly available information. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Natural Language Processing (NLP)

Applicable Industries

Pharmaceuticals

Applicable Functions

Product Research & Development

Quality Assurance

Use Cases

Chatbots

Regulatory Compliance Monitoring

Services

Data Science Services

Challenge

The biopharmaceutical company was facing a challenge in tracking off-label usage of their medications. Off-label usage refers to the prescribing of medications in a manner not specified by the FDA and accounts for 10 to 20 percent of all prescriptions written. However, its exact extent is difficult to measure because pharmaceutical companies have no direct feedback mechanism to track what medical conditions their products are prescribed for. The company had no means to monitor how their medications are used as patient records are subject to privacy restrictions and do not allow the company to reconstruct which medication was prescribed for which condition. The company decided to use social media, particularly Reddit, as a source of knowledge about medication usage.

About Customer

The customer is a global biopharmaceutical company. The company does not sell directly to consumers and therefore has no means to monitor how their medications are used. Patient records are subject to privacy restrictions and when available they do not allow the company to reconstruct which medication was prescribed for which condition. The company wanted to gather intelligence about off-label drug usage by screening patient comments in social media.

Solution

The company turned to Cortical.io for their expertise in developing Natural Language Understanding (NLU) based-solutions to develop a tool able to overcome the hurdle of ambiguity and vague wording inherent to social media posts and to correctly interpret them despite the limited number of posts available for training. During the initial phase of the project, Cortical.io created a prototype based on SemanticPro Classify & Automate to identify mentions of on- and off-label medication usage in a static set of Reddit posts. Leveraging Cortical.io meaning-based algorithms, the application automatically and accurately filters and classifies Reddit messages and summarizes the results. Cortical.io trained classifiers for each of the example drugs specified by the company using publicly available information.

Impact #1	The company was able to review over 2.2 million Reddit posts mentioning medications.
Impact #2	The company was able to filter for trade or generic names of medication.
Impact #3	The company was able to filter out off-topic posts based on the semantic meaning of the post.

Impact #1

The company was able to review over 2.2 million Reddit posts mentioning medications.

Impact #2

The company was able to filter for trade or generic names of medication.

Impact #3

The company was able to filter out off-topic posts based on the semantic meaning of the post.

Benefit #1	The Cortical.io application achieved a very high level of accuracy based on standard NLU metrics (92-100%) in classifying on-label vs. off-label usage.

Benefit #1

The Cortical.io application achieved a very high level of accuracy based on standard NLU metrics (92-100%) in classifying on-label vs. off-label usage.

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Overview

How a biopharmaceutical company evaluated social media to monitor off-label drug use

Operational Impact

Quantitative Benefit