Senior Director Computational Biology

About Acadia Pharmaceuticals

Acadia is advancing breakthroughs in neuroscience to elevate life. Since our founding, we have been working at the forefront of healthcare to bring vital solutions to people who need them most. We developed and commercialized the first and only FDA-approved drug to treat hallucinations and delusions associated with Parkinson’s disease psychosis, and the first and only approved drug in the United States and Canada for the treatment of Rett syndrome. Our clinical-stage development efforts are focused on Prader-Willi syndrome, Alzheimer’s disease psychosis, and multiple other programs targeting neuro-psychiatric and neuro-rare diseases. For more information, visit Acadia.com and follow us on LinkedIn and X.

 

Position Summary

The Sr. Director, Computational Biology will be responsible for the integrated analysis of complex, multidimensional preclinical and clinical datasets to provide clarifying knowledge that enables critical decision-making at the program and leadership levels.  The role will contribute to and drive bioinformatics, statistics and general data analysis and visualization of pre-clinical, translational and clinical research data including, where appropriate: the acquisition and management of multi-omic data from internal research and public databases in cloud-based computing environments; the application of externally- and internally-developed algorithms to process and analyze data and; the development and deployment of data applications to visualize multivariate data in interactive tools, to facilitate hypothesis generation and testing by team members.

The Sr. Director, Computational Biology demonstrates an understanding of the drug development process and comprehensive working knowledge of the technical and theoretical aspects of sequencing technology, biostatistics, machine learning, biology, bioinformatics, target discovery, biomarker development and computational biology.

Primary Responsibilities

• Provide computational support for pre-clinical, translational and clinical scientists in the efforts of discovery biology, translational research and clinical biomarker studies.
• Develop and implement bioinformatic algorithms for integrative analysis and visualization of multi-omics data from various sources and data modalities such as bulk or single-cell RNA-Seq, targeted exome and whole genome sequencing, proteomics and other biomarker signals from cell culture, in vivo studies, and clinical serum, blood and tissue biopsies.
• Develop interactive and secure web applications in R Shiny and/or Python Streamlit to make complex analysis pipelines and database queries accessible to non-bioinformatic scientists.
• Support research scientists in the analysis and visualization of multivariate data for internal and external presentations to key opinion leaders, at scientific conferences and to external stakeholders throughout the process of developing strategic partnerships.
• Provide oral presentations to internal and external audiences on research results across all stages of drug development in formal settings and at regular company meetings.
• Where appropriate, support the translational/clinical research/medical affairs teams in conducting analyses and providing visualizations for investor presentations, investigator brochures, site initiation visits and safety review boards.
• Perform other duties as assigned.

Education/Experience/Skills

PhD in Bioinformatics, Computational Biology, Genomics, Computer Science or related field. Targeting 8 years of experience, including a minimum of 4 years in the pharmaceutical or biotech industry.  An equivalent combination of relevant education and experience may be considered.

Key Skills:

• Experience leading teams of biostatisticians/data scientists and integrating with teams across research departments to provide computational support where needed.
• Extensive experience analyzing and integrating large, multivariate data sets, planning NGS experiments and analysis pipelines.
• Experience in target discovery, predictive/response biomarker identification and translational research with applications in patient datasets and/or clinical trials.
• Secure management of sensitive internal data and protected health information in cloud-based computing environments.
• Secure deployment of web-based applications in cloud servers. Strict adherence to regulatory requirements under 21 CFR Part 11, the EU’s GDPR and the principle of least privilege.
• Proficiency in machine learning alg