Cloud Computing in Healthcare and Biomedical Science

This blog post explores a real cloud application in biomedicine, based on the article “Unraveling the role of cloud computing in health care system and biomedical sciences” by Sachdeva et al. (2024), and connects it with a real biomedical cloud platform: Terra.

Introduction

The healthcare sector is undergoing a major digital transformation. Biomedical research now generates huge amounts of data from electronic health records, medical imaging, genomics, transcriptomics, and clinical monitoring systems. Managing and analysing these datasets requires scalable and efficient computational infrastructure.

Cloud computing offers a solution by providing computing resources, storage, and software through the internet. Instead of relying only on local servers or institutional clusters, researchers and healthcare organisations can use remote cloud infrastructure on demand.

Sachdeva et al. (2024) describe cloud computing as an important tool for improving healthcare delivery, biomedical research, data accessibility, and collaboration.

What is cloud computing in healthcare?

Cloud computing allows users to access computing resources such as storage, databases, servers, networking, and software without directly managing the physical infrastructure.

In healthcare and biomedical science, this is especially useful because data can be:

• stored securely,
• accessed from different locations,
• processed using scalable computing resources,
• shared between researchers and institutions,
• integrated with artificial intelligence and machine learning tools.

Note: In high-performance and distributed computing, cloud platforms are important because they distribute workloads across multiple servers and data centres, allowing large biomedical analyses to scale beyond a single local computer.

Key applications in biomedicine

Electronic Health Records

Cloud platforms can store and manage electronic health records, making patient information accessible to authorised healthcare professionals across different institutions.

Telemedicine

Cloud computing supports telemedicine by enabling remote consultations, real-time data sharing, and continuous patient monitoring.

Biomedical research and genomics

Modern biomedical research produces very large datasets. For example, sequencing experiments such as RNA-seq or whole-genome sequencing can generate gigabytes or terabytes of data. Cloud platforms allow researchers to run computational workflows without downloading all the data locally.

Real-world example: Terra

A real example of a biomedical cloud platform is Terra, developed by the Broad Institute in collaboration with Google Cloud and Microsoft.

Terra is designed for large-scale biomedical and genomic data analysis. It allows researchers to:

• store large biomedical datasets,
• run reproducible workflows,
• analyse genomic and clinical data,
• collaborate with other researchers,
• scale computational resources depending on the analysis.

Why Terra is useful

Instead of moving massive datasets to a local computer, Terra follows the idea of bringing computation to the data. This is very useful in genomics, where datasets are often too large to download and process locally.

For example, a researcher could use Terra to run a variant calling or RNA-seq workflow directly in the cloud.

# Example idea of a cloud-based workflow
Upload sequencing data → Select workflow → Run analysis in the cloud → Download results

This approach reflects distributed computing principles, where computations are performed across multiple remote machines.

Advantages of Cloud Computing in Healthcare

Challenges and Limitations

Data Security and Privacy

Healthcare data is sensitive and must comply with regulations such as GDPR.

Ethical and Legal Concerns

Cross-border data sharing raises issues related to governance and ethical use.

Technical Integration

Migrating from existing systems to cloud infrastructure can be complex.

Warning: Cloud computing requires careful planning to ensure data security, cost control, and compliance with regulations.

Connection with HPC and Distributed Computing

Cloud computing is closely related to high-performance and distributed computing:

• Workloads are distributed across multiple servers
• Resources are allocated dynamically (elastic computing)
• Large-scale analyses can run in parallel

Unlike traditional HPC clusters, cloud platforms provide more flexibility and accessibility.

Conclusion

Cloud computing is transforming healthcare and biomedical science by enabling scalable, efficient, and collaborative data analysis.

The study by Sachdeva et al. (2024) highlights its importance in modern healthcare systems, while platforms like Terra demonstrate its real-world application in biomedical research.

As biomedical data continues to grow, cloud computing will become increasingly important for enabling innovation in healthcare, genomics, and data-driven medicine.

References

1. Sachdeva, S., et al. (2024). Unraveling the role of cloud computing in health care system and biomedical sciences. Heliyon.
   https://pmc.ncbi.nlm.nih.gov/articles/PMC11004887/

2. Terra Platform.
   https://terra.bio/

3. Google Cloud – Healthcare & Life Sciences.
   https://cloud.google.com/solutions/healthcare-life-sciences

4. Microsoft Azure for Healthcare.
   https://azure.microsoft.com/en-us/industries/healthcare/