Merck has highlighted the growing role of open-source chemistry software in drug discovery as RDKit marks 20 years of development and use across the life sciences.

RDKit expands beyond small molecules

Around 300 chemists, data scientists and software developers attended the 2026 RDKit User Group Meeting in Darmstadt, Germany, with participants joining both in person and virtually.

RDKit is an open-source cheminformatics and machine learning toolkit used to represent, analyse and compare molecular structures and prepare chemical data for computational modelling.

Originally developed for work with small molecules, its applications have expanded to areas including oligonucleotides, peptides and quantum chemistry.

The software now has more than 100,000 users worldwide and is used across pharmaceutical and technology organisations. Contributions to the 2026 meeting came from companies including Novartis, Bayer, Sanofi and AbbVie, highlighting the role of shared computational tools in pharmaceutical research.

Merck chief science and technology officer Philipp Harbach said: “RDKit is a powerful example of how chemistry, data and software can come together to accelerate scientific innovation.”

Open-source tools support AI workflows

RDKit can convert molecular structures into digital representations that can be analysed by machine learning models, helping researchers compare compounds, prepare datasets and support molecular design.

This makes the toolkit relevant to a growing number of AI-enabled drug discovery workflows, where computational models are used to assess molecular properties, identify potential drug candidates and help determine which experiments to conduct.

Merck said RDKit is used across several of its digital science projects, including tools for predictive modelling, protein design and Bayesian optimisation.

The software is also used outside Merck. Google, Google DeepMind, Amazon Web Services and NVIDIA are among technology companies using RDKit alongside pharmaceutical and chemical organisations.

Arvind Rajpal, head of discovery and development technologies at Merck’s healthcare business, said: “RDKit helps our research and development scientists within our Healthcare business sector turn chemical data into AI-ready representations and actionable insights for faster, better-informed molecular design.”

The open-source approach means researchers and developers can contribute to and build on a shared set of tools rather than developing every component independently.

RDKit reaches 20 years

RDKit was first published as an open-source project in 2006 and has since developed into a widely used toolkit for computational chemistry.

Merck said the software now receives almost four million downloads each month, while Google Scholar recorded more than 4,500 results for “RDKit” in 2024.

The company has been involved with the RDKit community since its early development and hosted a user group meeting in Darmstadt in 2014.

The 2026 meeting marked the toolkit’s 20th anniversary and brought together researchers from industry, academia and the open-source community.

Jérémie Eblé, head of digital center of excellence at Merck’s life science business, said: “Hosting this community at Merck offers a valuable opportunity to exchange ideas and strengthen collaboration across industry, academia and open-source contributors.”

The continued expansion of RDKit illustrates how open-source infrastructure is becoming part of the wider computational chemistry ecosystem, as pharmaceutical research increasingly combines chemical data, machine learning and automated experimentation.