Dinesh Barupal, PhD
Director, Integrated Data Science Laboratory for Metabolomics and Exposomics (IDSL-ME)
Associate Professor, Department of Environmental Medicine (EM)
Dinesh Barupal, PhD, serves as the Director of the Integrated Data Science Laboratory for Metabolomics and Exposomics (www.idsl.me) at the Icahn School of Medicine at Mount Sinai, where he leads the first NIH-funded laboratory dedicated specifically to exposomics data science. As an Associate Professor in the Department of Environmental Medicine and Public Health, Dr. Barupal has established a premier research hub that bridges the critical gap between complex analytical chemistry and large-scale epidemiological studies through the development of next-generation computational frameworks. His research program is anchored by the creation of the IDSL software ecosystem, a comprehensive suite of R and Python packages including IDSL.IPA, IDSL.UFA, and IDSL.CSA, IDSL.GOA and ChemRICH, that automates the annotation and interpretation of high-resolution mass spectrometry data to move beyond individual metabolite identification toward holistic pathway analysis. A central pillar of his contribution to the field is the development of major community resources such as the Blood Exposome Database (www.bloodexposome.org), which catalogs chemicals detected in human blood with curated metabolic and toxicological data, and the Exposome Correlation and Interpretation Database (www.ecidbase.org), a NIEHS U24-funded resource designed to map inter-chemical correlations and interpret the dark matter in untargeted datasets. His laboratory is also at the forefront of integrating emerging technologies into biomonitoring, utilizing deep learning frameworks and quantum chemistry simulations to predict molecular fingerprints and identify novel biomarkers without physical standards.
Beyond his work on software and databases, Dr. Barupal serves as a Principal Investigator for multiple significant NIH grants, including a GeoSpace NIEHS R24 project to create a geospatial knowledgebase and an R01 investigation into prenatal risk factors for sleep development, while also holding significant roles in the Neuro and Cancer Exposome initiatives. His expertise extends to global public health policy through a long-standing collaboration with the International Agency for Research on Cancer, where he has advanced the prioritization of chemical agents for carcinogenicity evaluation using deep text-mining and database fusion methodologies. He is a dedicated advocate for open science who ensures the reproducibility of his computational workflows by freely disseminating all software codes and comprehensive documentation through public repositories. With over 70 peer-reviewed publications and a strong commitment to education through his leadership of the Computational Metabolomics Course, Dr. Barupal continues to drive the advancement of exposomics and precision environmental health.
We asked Dr. Barupal to elaborate on his work.
What inspired you to take on your current role here at Mount Sinai?
I was inspired by the opportunity to lead a pioneering research program at the intersection of computational biology and environmental health. My research goal has been to uncover the environmental drivers of chronic disease, and Mount Sinai provided the ideal environment to establish the Integrated Data Science Laboratory for Metabolomics and Exposomics (IDSL.ME). I wanted to create a world-class bioinformatic infrastructure capable of translating complex exposomic data into actionable biological insights.
What impact do you hope to make through your work?
My primary objective is to map all the chemicals that are hazardous to our health. By developing next-generation computational frameworks and resources like the Blood Exposome Database and the Exposome Correlation and Interpretation Database, I hope to enable the global research community to access and interpret the chemical exposome. Ultimately, I want to provide a holistic understanding of how the exposome influences the progression of chronic diseases, which is essential for identifying hazardous chemical exposures and informing public health.
Is there any specific message that you would like to share with our readers?
To truly advance precision medicine, we must scale up our efforts to map the human exposome with the same rigor and depth as the human genome. Genetics alone cannot explain the rising rates of chronic conditions; we need a comprehensive, high-throughput capability to monitor the complex chemical environment we live in. By leveraging AI and large-scale knowledgebases to decode these environmental exposures, we can move beyond reactive healthcare to proactive hazard identification. Scaling up exposomics is not just a technical challenge, it is a public health imperative that will allow us to pinpoint the environmental roots of diseases like cancer, diabetes, and neurodegeneration, leading to better prevention strategies for everyone.
ConduITS is supported by NCATS of the NIH’s CTSA Program. Any use of CTSA-supported resources requires citation of grant number UL1TR004419 awarded to ISMMS in the acknowledgment section of every publication resulting from this support. Adherence to the NIH Public Access Policy is also required.
