- Automated ADR monitoring process leading to improving the overall healthcare of patients
- Reduced time and effort in identifying and validating adverse events
- Increased efficiency by providing access to vast amounts of textual data to identify potential adverse drug reaction signals
- Support for compliance monitoring, adhering to both regulatory agencies and healthcare needs
- Improved user experience throughout the entire drug development lifecycle
The Goal
A global Pharma company needed a more efficient solution that could provide systematic and comprehensive approaches to monitoring Adverse Drug Reactions (ADR) in scientific literature. Regulatory agencies such as the FDA and European Medicinal Agency’s pharmacovigilance guidelines require Pharma companies to provide a strict ‘signal detection’ process for identifying new adverse events. Also, depending on the severity of the ADR, they have to quickly assess such signals and promptly notify the regulatory bodies.
The Challenge
ADR monitoring (or pharmacovigilance) requires constant monitoring for undesirable effects medical drugs can have on the body post licensing for use. For this to happen efficiently, it is critical to receive the necessary information from patients and healthcare providers via Individual Case Safety Reports (ICSRs) and other sources such as scientific literature where the information is far less structured than in ICSR.
The Pharma company’s existing process of monitoring and screening for reported ADR in scientific literature was not only time and effort-consuming but generally struggled to meet its goal. The main challenges were:
- handling the exponentially growing safety information in diverse data sources and different formats that needs to be scanned
- full coverage of all important ADRs data elements
- ambiguity of using generic and brand drug names interchangeably
- capturing the complexity of the causal relations between different entities involved in a case report in a consistent way
The Solution: Knowldge Graph Based Scientific Literature Monitoring for Adverse Events
The solution for monitoring adverse events implemented by Ontotext is based on semantic text analysis and knowledge graphs. It is highly configurable and flexible, going beyond the standard deep indexing of content.
Now the Pharma company can processes in real time publications feed from multiple sources like NCBI PubMed and Elsevier EMBASE and can identify reported potential drug adverse events. The solution handles both article content and associated publications meta data, like MeSH terms, and recogizes data elements relevant to the ICSR schema. These inlude patient, gender, age, drug name, active ingredient, co-treatment drug and route of administration. It uses both established reference datasets, like UMLS and RxNorm, but also proprietary terminologies created for each individual client of the platform.
The extracted data is complemented with structured ADR knowledge from a public Adverse Event Reporting system (FAERS from US FDA, EudraVigilance, VigiBase from WHO). The information in it is normalized to established medical and drug terminologies like MedDRA, SNOMED CT, MeSH, and more. The automatic ADR extraction significantly speeds up the overall process as it provides already normalized and structured data that only needs to be validated by the SMEs.
Business Benefits
- Utilizing publicly available safety information to build a comprehensive and up-to-date drug safety knowledge graph, assisting in causality assessment
- Connecting knowledge locked in their proprietary safety data with large public repositories of semi-structured drug adverse reaction data
- Tracing safety information throughout the entire drug development lifecycle in a single intelligent system
- Automatically detecting new safety signals as new data is ingested in the knowledge graph
- Enabling decreased time and effort to identify and validate adverse events
Why Choose Ontotext?
With Ontotext’s scientific literature monitoring solution, the Pharma company can sift through vast amounts of textual data, such as medical records and clinical notes, and efficiently identify reported potential ADR signals. This also facilitates compliance monitoring, adhering to both regulatory agencies and healthcare needs. All in all, the Pharma company gained an integrated drug safety signals detection process that helps them identify and validate ADR signals timely and efficiently.
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