# DrugWatch: A Comprehensive Multi-Source Data Visualisation Platform for Drug Safety Information

arXiv: https://arxiv.org/abs/2407.01585 · HTML: https://mlsanity.com/paper/2407.01585/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 22 references that are in the map.
- First posted on arXiv 18 Jun 2024.

## Builds on (most cited first, 5 of 5)

- [Scaling Instruction-Finetuned Language Models](https://mlsanity.com/paper/2210.11416/) (2022)
- [SciBERT: A Pretrained Language Model for Scientific Text](https://mlsanity.com/paper/1903.10676/) (2019)
- [Unified Structure Generation for Universal Information Extraction](https://mlsanity.com/paper/2203.12277/) (2022)
- [PHEE: A Dataset for Pharmacovigilance Event Extraction from Text](https://mlsanity.com/paper/2210.12560/) (2022)
- [Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Study](https://mlsanity.com/paper/2402.15663/) (2024)

## Built on by (most cited first, 2 of 2)

- [VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning](https://mlsanity.com/paper/2503.15438/) (2025)
- [DrugClaw and DrugAudit: A Primary-Source-Grounded Agent and Authority-Aware Benchmark for Drug-Information Question Answering](https://mlsanity.com/paper/2606.01434/) (2026)

## Abstract (arXiv)

Drug safety research is crucial for maintaining public health, often requiring comprehensive data support. However, the resources currently available to the public are limited and fail to provide a comprehensive understanding of the relationship between drugs and their side effects. This paper introduces DrugWatch, an easy-to-use and interactive multi-source information visualisation platform for drug safety study. It allows users to understand common side effects of drugs and their statistical information, flexibly retrieve relevant medical reports, or annotate their own medical texts with our automated annotation tool. Supported by NLP technology and enriched with interactive visual components, we are committed to providing researchers and practitioners with a one-stop information analysis, retrieval, and annotation service. The demonstration video is available at https://www.youtube.com/watch?v=RTqDgxzETjw. We also deployed an online demonstration system at https://drugwatch.net/.