Extracting Knowledge from Documents: Enabling Semantic Search for Pharmaceutical Research and Development

The Challenge A major pharmaceutical research and development company faced difficulty creating regulatory reports and files based on years of drug experimentation data. Their regulatory intelligence teams and drug development chemists spent dozens of hours searching through hundreds of thousands of documents to find past experiments and their results in order to fill out regulatory compliance documentation. The company’s internal search platform enabled users to look for documents, but required exact matches on specific keywords to surface relevant results, and lacked useful search filters. Additionally, due to the nature of chemistry and drug development, many documents were difficult to understand at a glance and required scientists to read through them in order to determine if they were relevant or not. The Solution EK collaborated with the company to improve their internal search platform by enhancing Electronic Lab Notebook (ELN) metadata, thereby increasing the searchability and findability of critical research documents, and created a strategy for leveraging ELNs in AI-powered services such as chatbots and LLM-generated document summaries.