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Related Concept Videos

Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
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PIC-SURE: an open-source platform for integrating clinical and genomic data.

Alba Gutiérrez-Sacristán1, Emily E Hughes1, Ryan Amari1

  • 1Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA, USA.

NPJ Digital Medicine
|December 30, 2025
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Summary
This summary is machine-generated.

PIC-SURE is an open-source platform for integrating and analyzing large-scale clinical and genomic data. It enables real-time cohort building and analysis across over 1.4 million participants, supporting reproducible research.

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Area of Science:

  • Bioinformatics and Computational Biology
  • Genomic Data Analysis
  • Clinical Data Integration

Background:

  • Large-scale clinical and genomic datasets are crucial for biomedical research but present integration and analysis challenges.
  • Existing platforms may lack the flexibility and scalability required for real-time analysis of diverse data types.
  • The National Institutes of Health (NIH) National Heart, Lung, and Blood Institute (NHLBI) BioData Catalyst® ecosystem aims to facilitate data sharing and analysis.

Purpose of the Study:

  • To introduce PIC-SURE, an open-source platform designed for seamless integration and analysis of large-scale clinical and genomic data.
  • To highlight PIC-SURE's capability in enabling real-time cohort building and data exploration.
  • To demonstrate how PIC-SURE lowers the barrier for researchers to conduct scalable and reproducible studies using integrated datasets.

Main Methods:

  • Utilizing an open-source platform architecture for broad accessibility and community contribution.
  • Implementing a graphical user interface (GUI) and an Application Programming Interface (API) for versatile data interaction.
  • Integrating with the NIH NHLBI BioData Catalyst® ecosystem to leverage existing data resources.

Main Results:

  • PIC-SURE provides access to and analysis capabilities for data from 273 studies, encompassing approximately 1.4 million participants (as of May 2025).
  • The platform facilitates real-time exploration and analysis of complex, integrated clinical and genomic datasets.
  • Demonstrated ability to support scalable and reproducible research workflows.

Conclusions:

  • PIC-SURE effectively addresses the challenges of integrating and analyzing large-scale clinical and genomic data.
  • The platform enhances research efficiency and reproducibility by enabling real-time cohort building and analysis.
  • PIC-SURE serves as a valuable tool within the NIH NHLBI BioData Catalyst® ecosystem, promoting data-driven biomedical discovery.