PharmKDD 2025 Call For Papers



Description
Pharmaceutical research and development (PRD) refers to the process of discovering and developing medicines and treatments. It is an expensive ($1-2.6 billion on average) and time consuming (10-15 years on average) process. Despite the time and monetary investments, historical data shows that the success rate of a new drug from discovery to final approval from the Food and Drug Administration is only around 10%. This fact highlights the urgent need for innovative methods to improve the efficiency and success rate of the PRD process.

There are many steps in the PRD pipeline, which includes target identification, molecule design and synthesis, pre-clinical development, human clinical trials, and post-marketing surveillance. Over the years, large volumes of data have been accumulated from these different steps, which encode evidence and insights of the PRD process. This provides an unprecedented opportunity for developing effective data mining and knowledge discovery (KDD) methods to extract insights from those data to improve the PRD process. Furthermore, advances in deep phenotyping using AI have greatly expanded the disease landscape, capturing a richer spectrum of disease attributes and patient subtypes, which in turn elevates drug discovery efforts by refining target identification and validation—effectively transforming the other side of the therapeutic equation into a more precise, data-driven realm of innovation.

There are lots of examples of recent research developing KDD methods for PRD. However, the existing research has been mostly isolated into different communities focusing on a particular intermediate step, while we cannot have any of these steps fail in order to successfully develop a drug. Therefore, there is an urgent need for a forum to bring together researchers and practitioners from both academia and industry working on different aspects of KDD for PRD, discuss the state-of-the-art research and technologies, and chart the future agenda.

Topics of Interests
All topics on KDD for pharmaceutical research and development are welcome to submit, including but not limited to the following Submission Guidelines

Timeline

© Fei Wang