Time: 6:30am PDT, 9:30am EDT, 2:30pm BST, 3:30pm CEST
Duration: 180 minutes
Join us on our final day of talks to discover how Chiesi Farmaceutici and CSL Behring are using NLP with topics such as:
- Innovating drug development with natural language processing: focus on safety
- Identification of potential targets for drug repurposing in neonatology
- NLP for MedDRA Coding: Piloting in ICSR processing at CSL Behring
- Panning for gold: Surfacing novel content to drive richer conversations
Innovating drug development with natural language processing: focus on safety - Jane Reed (IQVIA)
Life science organizations face the challenge of handling ever-increasing volumes of text information within drug safety processes. Natural Language Processing (NLP) can be applied to optimize safety platforms and lower clinical development costs. NLP transforms unstructured text into structured data that can be rapidly analyzed or visualized.
This session will explore how these capabilities can be applied for safety case processing, medical coding (e.g. to MedDRA), publication search for potential Adverse Events situations and medical review of Adverse Events, and indeed, at every stage through the safety lifecycle of a drug
Identification of potential targets for drug repurposing in neonatology - Paolo Grossi (Chiesi)
SKIR, together with members from Pre-Clinical departments, would like to investigate repurposing hypothesis to associate genes/proteins involved in a given disease towards drugs already known. Historically, such discoveries were the results of serendipity. The rapid growth in electronic clinical data and text mining tools makes it feasible to systematically obtain this kind of information. The overall process consists of two different workflows: first, we retrieved any genes related to the indication, sorting those by an internal defined Scoring System, based on descriptive and qualitative metadata.
Comparing molecules with the internal knowledge, we were able to produce a Top Tier list of genes of interest. Later, we developed a specific query by correlating genes selection and all potential drugs as pharmaceutical substances possessing definite properties. Once again, we applied an analytical Scoring System to determine which could be most interesting drugs to use as repurposing target for future developments.
NLP for MedDRA Coding: Piloting in ICSR processing at CSL Behring - Martin Menke (CSL Behring)
For processing of adverse event reports, the information provided by a reporter in natural language is transferred (coded) into a standardized format to allow database processing. For the adverse event, indication, medical history, etc. the Medical Dictionary for Regulatory Activities – MedDRA must be used. Most of the coding is manual and time consuming. Only when the verbatim exactly matches a MedDRA term, coding is automatic (currently about 30%).
Natural language processing (NLP) is programming computers to process and analyze natural language data, to recognize relevant content and act upon it in a specific way, e.g. recognize a verbatim as an adverse event and assign a respective MedDRA code.
Panning for gold: Surfacing novel content to drive richer conversations - Hywel Evans (IQVIA)
As organizations engage with key stakeholders such as physicians, key opinion leaders and digital though leaders it is vital to be able to find relevant, specific content to answer questions and drive rich discussions. Over time these rich interactions can themselves form the basis for rich datasets that inform teams about emerging topics and effectiveness of communications. Find out more about text mining can unlock valuable data in pharma for stakeholder engagement.