Biotechnology is advancing rapidly, driven by innovations in genomics, gene editing, synthetic biology, and more. The exponential growth of biological data has necessitated scalable cloud-based capabilities for storage, analysis, and global collaboration. In this article, we first provide an overview of groundbreaking biotechnologies.
We then examine how cloud platforms are enabling researchers to leverage these technologies for impactful applications. Finally, we look at real-world examples of cloud-based tools driving progress in genomics and beyond.
Introduction to Cutting-Edge Biotechnologies
Genomics: Studying the genome has revealed invaluable insights into health, disease, and life itself.
Next-generation sequencing technologies can rapidly sequence whole genomes, transcriptomes, and more to understand genetic drivers.
CRISPR
This revolutionary gene-editing tool based on bacterial immune systems enables precise manipulation of DNA sequences. It provides unprecedented control over genomes for creating targeted changes.
Synthetic Biology
This applies engineering principles to design and construct novel biological components like synthetic genes, proteins, and microbes not found in nature. It enables customized biological solutions. These technologies are transforming areas like medicine, agriculture, conservation and more by providing fine-grained understanding and control over biological systems. However, realizing their immense potential requires advanced computational capabilities.
Powering Biotechnology with Cloud Computing
Genomics and beyond generate massive datasets requiring extensive storage, computing power, and analytics. The cloud offers on-demand access with benefits like:
Storage and Big Data Analytics: Petabyte-scale cloud data lakes allow storing enormous genomic, proteomic, and other omic datasets cost-effectively while providing big data analytics capabilities through services like AWS Glue, Google BigQuery, etc.
Scalable Compute: On-demand high-performance cloud computing resources like virtual servers and GPUs accelerate complex tasks like genome assembly, RNA sequencing analysis, and molecular simulations.
Global Collaboration
Cloud platforms enable seamless data sharing and collaboration between cross-functional teams across different geographic locations and organizations.
Machine Learning
Automated analysis of massive biomedical datasets using cloud-based ML tools provides insights at a scale not feasible manually.
Security
Cloud infrastructure offers enterprise-grade security and access controls to safeguard sensitive health data while enabling controlled sharing between researchers.
Agility and Efficiency
Cloud eliminates the need for upfront infrastructure investments and lengthy setup times. Biotech teams can provision resources instantly and only pay for what they use.
By providing virtually unlimited scale and cutting-edge capabilities, the cloud becomes the foundation for leveraging biotechnologies. Let us look at how the cloud is powering innovation across genomics, gene editing, synthetic biology, and more.
Cloud-Based Platforms Advancing Biotechnology
Here are some examples of cloud platforms enabling researchers to push boundaries in genomics, bioengineering, and drug discovery:
Seven Bridges Platform: This cloud ecosystem simplifies genomics analysis on AWS for tasks like processing sequencing data, and identifying biomarkers and drug targets using machine learning algorithms.
BaseCamp by Benchling: Researchers use this cloud laboratory information management platform to improve collaboration on projects leveraging synthetic biology, genome editing, and more.
Microsoft Genomics Service
This Azure cloud service accelerates sequencing analysis pipelines using scalable processing power to gain insights faster.
DNAnexus Cloud Workflows
These automate complex genomics workflows for studies like clinical trials centralizing data and analysis on a compliant cloud platform.
AWS Cloud9
This cloud IDE helps developers code, run, test, and debug bioinformatics programs on AWS without environment setup overheads.
Google Cloud Life Sciences API
Researchers can run workflows for analysis like genome sequence alignment and variant calling using Google Cloud capabilities.
Innovative Biotech Projects Powered by the Cloud
Here are some cutting-edge projects using cloud services to drive breakthroughs:
Svante Biotech CO2 Capture
This company leverages cloud computing to model enzymatic processes that capture CO2 emissions for making industrial processes greener.
Ginkgo Bioworks
Using AWS capabilities for security, scale and automation, Gingko is able to engineer high-throughput yeast foundries to rapidly prototype synthetic biology designs.
Handl Therapeutics Antibiotic Discovery – Handl’s cloud platform profiles soil microbes at scale to identify promising antibiotic compounds through big data analytics and machine learning.
10X Genomics Single Cell Sequencing
Compute capabilities of Google Cloud enable 10x to process huge amounts of data from single-cell genomics experiments to advance precision medicine.
Rapid Medical Diagnostics on Azure
This startup combines IoT sample collection devices, cloud-orchestrated workflows, and ML tools hosted on Azure to enable faster infectious disease diagnosis.
The Road Ahead
Cloud-based environments will continue fueling biotechnology progress through democratized access to computation, big data capabilities, global collaboration platforms, and more. As genomic and biodata grow exponentially, integrating advanced analytics like artificial intelligence with cloud infrastructure will become indispensable to harnessing these richest datasets for both understanding life and improving it.