Open-Source Retrieval Augmented Generation Framework for Retrieving Accurate Medication Insights from Formularies for African Healthcare Workers
On the map: Retrieval-augmented generation → Medical and biomedical RAG
Abstract (arXiv)
Accessing accurate medication insights is vital for enhancing patient safety, minimizing errors, and supporting clinical decision-making. However, healthcare professionals in Africa often rely on manual and time-consuming processes to retrieve drug information, exacerbated by limited access to pharmacists due to brain drain and healthcare disparities. This paper presents "Drug Insights," an open-source Retrieval-Augmented Generation (RAG) chatbot designed to streamline medication lookup for healthcare workers in Africa. By leveraging a corpus of Nigerian pharmaceutical data and advanced AI technologies, including Pinecone databases and GPT models, the system delivers accurate, context-specific responses with minimal hallucination. The chatbot integrates prompt engineering and S-BERT evaluation to optimize retrieval and response generation. Preliminary tests, including pharmacist feedback, affirm the tool's potential to improve drug information access while highlighting areas for enhancement, such as UI/UX refinement and extended corpus integration.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 5 of its 14 references that are in the map. First posted on arXiv 28 Jan 2025.
Builds on
5 of 14 references.
References · 5
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
- 2022BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Miningcited by 531
- 2023Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Healthcited by 118
- 2023A Study on the Implementation of Generative AI Services Using an Enterprise Data-Based LLM Application Architecturecited by 28
- 2024Enhancing Multilingual Information Retrieval in Mixed Human Resources Environments: A RAG Model Implementation for Multicultural Enterprisecited by 7
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- 2025Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations
- 2025Rethinking Retrieval-Augmented Generation for Medicine: A Large-Scale, Systematic Expert Evaluation and Practical Insights
- 2025DrugRAG: Enhancing Pharmacy LLM Performance Through A Novel Retrieval-Augmented Generation Pipeline
- 2024Tool Calling: Enhancing Medication Consultation via Retrieval-Augmented Large Language Models
- 2025RAG-based Architectures for Drug Side Effect Retrieval in LLMs