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Welcome to SPARC

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Systems Pharmacology AI Research Center (SPARC) aims to advance the use of artificial intelligence (AI), patient digital twins and systems pharmacology in drug discovery through research innovation and multi-disciplinary collaborations.

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Revolutionize the future of precision drug development by making it PErsonalized, ACcelerated, and Economically accessible for all.


  • Curate AI-ready open data sets for drug discovery​

  • Develop digital twins models for drug perturbation experiments​

  • Design, implement, and evaluate programmable drug development platform​

  • Nurture an ecosystem great for AI drug discovery partnerships among stakeholders​

  • Educate and train next-generation AI drug discovery researchers


Annual Translational and Transformative Informatics Symposium (ATTIS) 2024


The 8th Annual Translational and Transformative Informatics Symposium (ATTIS), an event that stands as a cornerstone in the development of biomedical informatics and translational medicine, celebrating the inception of the Systems Pharmacology AI Research Center (SPARC) and the Department of Biomedical Informatics and Data Science (DBIDS) at UAB. Scheduled for Friday, May 3rd, 2024, ATTIS 2024 promises to be an exceptional gathering for professionals and trainees alike.

New Informatics Research Center to Focus on Artificial Intelligence


The University of Alabama System Board of Trustees approved the creation of the UAB Systems Pharmacology Artificial Intelligence (AI) Research Center (SPARC). SPARC, in partnership with the Heersink School of Medicine (HSOM) and the Center for Clinical and Translational Sciences (CCTS), will advance the use of AI, systems biology, and quantitative pharmacology in drug discovery through research innovation and interdisciplinary collaborations.

Birmingham Biotechnology Hub


By leveraging AI in tandem with representative data, the Hub will become a global center of excellence in drug, vaccine, and diagnostics development. It will address the unique needs of underrepresented patient segments, improve diagnostic accuracy and drug efficacy, reduce
timelines to develop new drugs and vaccines, enable rapid response to emerging health threats, and improve health outcomes of diverse patients at home and abroad.


Center Resources


The AI.MED lab uses translational bioinformatics to develop innovative techniques and create new databases and discover novel biomedical information to improve clinical care, diagnosis and treatment. The Bioinformatics Lab provides services to manage and analyze next-generation sequencing data. The team includes individuals with skills in bioinformatics, computer science, and statistics.

U-BRITE (UAB Biomedical Research Information Technology Enhancement) assembles new and existing HIPAA-compliant, high-performance informatics tools to provide researchers with a means to better manage and analyze clinical and genomic data sets and implements a “translational research commons” to facilitate and enable interdisciplinary team science across geographical locations.

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i2b2 (Informatics for Integrating Biology and the Bedside) is an NIH-funded National Center for Biomedical Computing based at Partners HealthCare System. i2b2 was developed as a scalable informatics framework designed for translational research. i2b2 was designed primarily for cohort identification, allowing users to perform an enterprise-wide search on a de-identified repository of health information to determine the existence of a set of patients meeting certain inclusion or exclusion criteria.


Our Impact


AI-based Drug Design Projects


Invited Talks




Team Projects



Our Partners


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Current Openings at SPARC

Scientist I (T210750)

SPARC is seeking qualified candidates to apply for a leading Academic Scientist position. The role is specifically designed for an individual with an extensive post-doctoral background ten plus (10+) years in chemistry, pharmacology, entrepreneurship, and drug discovery. The selected candidate will be central to advancing and guiding multidisciplinary research in AI/ML-enabled drug discovery, pharmacology, genomics, structural genomics, molecular dynamics, docking simulations, and chemical screenings. 

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