Description
Conduct research and build informatics solutions to support drug discovery, integrating bioinformatics, cheminformatics, computational biology, and data engineering across pharmaceuticals and biotechnology. Design databases and develop algorithms and workflows for processing and analyzing compound, assay, structural biology, and multi-omics information to enable target identification, hit finding, and lead optimization.
- • Recommend new informatics systems and workflows to accelerate drug discovery operations.
- • Keep abreast of new chem/bioinformatics methods, screening technologies, and software via literature and conferences.
- • Confer with medicinal chemistry, biology, DMPK, and program teams to coordinate discovery strategy and data needs.
- • Collaborate with software engineers to develop or extend discovery informatics platforms.
- • Test and validate new and updated cheminformatics and bioinformatics tools.
- • Provide statistical and computational tools for target identification, hit triage, and mechanism-of-action analyses.
- • Prepare summary statistics and dashboards for screening campaigns, SAR, and multi-omics datasets.
- • Train scientists in the selection and use of discovery informatics tools and workflows.
- • Improve user interfaces to compound, assay, and omics data systems.
- • Direct the work of analysts and IT staff applying informatics tools to chemogenomics, proteomics, and transcriptomics in discovery.
- • Develop or customize applications to meet project-specific discovery informatics needs.
- • Develop data models and databases for compounds, targets, assays, and project metadata.
- • Create or modify web-based tools for SAR analysis, data visualization, and workflow automation.
- • Design and apply algorithms, including machine learning/QSAR, virtual screening, and network analyses for target and lead prioritization.
- • Create novel computational approaches and analytical tools for lead optimization and translational insights.
- • Compile and integrate HTS/HCS, omics, structural biology, and ADME/PK data for decision support.
- • Communicate findings through presentations, reports, and publications to project and leadership teams.
- • Curate and integrate public and proprietary bioactivity, chemical, and omics databases (e.g., ChEMBL, PubChem, GEO).
- • Consult with project teams to analyze problems, recommend technology solutions, and define computational strategies.
- • Analyze large discovery datasets, including HTS, RNA-seq, proteomics, imaging, and cheminformatics data.
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Last reviewed: Jan 2026
