Scientific Developer; Chemical Biology Resources

About the team/job

Safety and toxicology concerns remain one of the most persistent challenges in drug discovery. This is an exciting opportunity to join a multi-disciplinary team on a project to develop a comprehensive open source side effect resource for the scientific and pharmaceutical community, and provide structured and standardised training sets for AI/ML applications to improve early identification of safety liabilities.

You will harness modern machine learning techniques to extract data from a range of relevant resources, such as clinical trials, publications and drug labels. You will work closely with team members to ensure development of automated pipelines and effective integration into the ChEMBL database () and Open Targets Platform (https://platform.opentargets.org/), to assist users in the selection of safe and efficacious drug targets.

The Chemical Biology Resources team at EMBL-EBI provides world-leading chemogenomics resources to the scientific community including ChEMBL, a database of quantitative small-molecule bioactivity data curated primarily from the scientific literature widely used to support drug discovery projects in industry and academia. The Safety 2.0 project is funded by Open Targets, a unique public-private partnership working to deliver experimental data and informatics resources that enable scientists to make more informed decisions about target selection for developing safer and more effective drugs.

You will interact with safety scientists from Open Targets pharmaceutical partners MSD, Genentech, GSK, Pfizer, and Sanofi to understand requirements and how to help contribute to evaluating drug and target safety. You will be embedded at the world-leading EMBL-EBI, and will work collaboratively across the Chemical Biology Resources and Open Targets groups, benefit ting from a range of multi-disciplinary expertise and technologies.

We are looking for an enthusiastic and talented scientific developer in the area of cheminformatics or bioinformatics with an interest in biomedical knowledge extraction to join the Open Targets Safety 2.0 project. You should enjoy addressing challenges in knowledge extraction and data standardisation, and want to contribute to open source code and resources.

The project will develop a new side effect resource for drug discovery based on the extraction of side effect data from a range of documents. Your role will focus on developing and implementing machine learning and data processing pipelines for the extraction of safety data. The position provides a real opportunity to make a significant impact on a critical problem in drug discovery for the many users of the Open Targets Platform and ChEMBL.

This position will be situated within the Chemical Biology Resources team (). You will work closely with other Safety 2.0 project team members to ensure effective delivery of work packages, and collaboratively with the Chemical Biology Resources team and Open Targets Core teams to ensure effective integration and longevity of pipelines and resources.

• To work closely as part of a team across Chemical Biology Resources and Open Targets to deliver a drug side-effect resource

• Develop machine learning pipelines for extracting drug side effects from drug labels, clinical trials, publications and other documents, and mapping to biomedical ontologies

• Integrate project workflows with existing infrastructures in the EBI Chemical Biology Resources and Open Targets teams

• Assist with data curation to prepare clean and reliable training sets

• Collaborate with the Open Targets pharmaceutical partners to assess, prioritise, validate and refine the developed methods

• Disseminate the outcomes of the project to the scientific…