A deeper understanding of biology has the potential to transform how health care is delivered, how patients are screened, and how clinical conditions are treated and monitored. The rapid growth of biomedical data sets in recent years has led to the identification of a enormous number of molecular signatures necessary to realize the era of personalized diagnosis and treatment. We are at a turning point where we have seen a 100,000-fold reduction in costs since the first sequencing of the human genome in 2001. Currently, the rate of growth in data volume is similar to the rate of decline in sequencing costs.
In fact, the cost of sequencing the human genome has dropped from almost $100,000 to just $200 as of September 2022. High-throughput sequencing technology, especially next-generation sequencing (NGS) platforms, has led to the multi-omics revolution. Processing terabytes and even petabytes of increasingly elaborate omics data generated by NGS platforms has required the development of omics informatics.
Vast-scale and elaborate datasets are increasingly being considered, which presents some significant challenges:
- Scale of data integration: Tens of millions of entire genomes are expected to be sequenced and recorded over the next five years. Most individual omics tools and algorithms focus on solving a specific problem, which is usually part of a enormous project. This forces organizations to integrate multiple tools into a single pipeline to serve different purposes.
- Multimodal data: omics data comes from a variety of – usually isolated – sources and in a variety of formats, from raw sequences and signals to high-resolution images and mass spectrometry.
- Analytical Requirements: Once the data is on a single platform and the tools are combined into a pipeline, computational techniques must be applied to interpret the data.
This is where the next problem lies: the analysis and interpretation of omics data, including sequence alignment, assembly and variant discovery, are computationally intensive tasks required for interpretation and other downstream analyses, and are therefore critical to guarantee overall accuracy. To meet this challenge, IBM Consulting works with partners such as Amazon Web Services (AWS) who are focused on delivering a platform and toolkit for processing omics data in a secure, scalable and cost-optimized manner.
What is Amazon Omics?
Amazon Omics is a purpose-built, HIPAA-compliant, GDPR-compliant service that helps healthcare and life sciences organizations and their software partners store, query, and analyze genomic, transcriptomic, and other omics data, and then generate insights from that data to improve health and develop scientific discoveries. Using Amazon Omics, customers scale multimodal and multi-omics analytics by generating insights from omics profile, images, medical claims, and health record data processed simultaneously using other AWS services such as Amazon Lake of Health, Amazon Understand Medicine AND Amazon Medical Transcription.
Accelerate genomic innovation
Some organizations are still debating whether moving to the cloud was right for them, and others have not yet made the business case to their leadership teams. However, the healthcare and biopharmaceutical communities agree that conducting multimodal and multi-omics studies at the population level is too pricey using conventional data center infrastructure. Challenges include massive amounts of raw data, the explosive nature of workloads, the multitude of tools used, stringent security and compliance requirements, the need for cross-industry collaboration, and time to market.
With its low price per gigabase and the ability to efficiently store, index, and secure petabytes of raw sequence data, Amazon Omics becomes the obvious solution for storing heterogeneous omics data at scale, in a pay-as-you-go model.
The next step in the data journey is to analyze the ingested data and streamline the results into interoperability-ready formats with repeatable and scalable pipelines. This specially designed service offers an automated analysis workflow so that various types of data (beyond sequencing data, images, records, claims and more) can be entered into analysis using Amazon Athena, Amazon EMR, Amazon SageMakerAND Amazon QuickSight.
Scientists can finally focus on science and let undifferentiated ponderous lifting be replaced by bright, scalable and purpose-built cloud services and solutions, eliminating the possibility of errors resulting from manual or distributed data processing. Finally, the output of sequencing analysis is genomic variants presented in the form of massive, semi-structured files (variant call files and genomic variant call files), which are then typically annotated (“assigned meaning”). To analyze annotated data at scale, a query-ready data schema is required – another benefit provided by Amazon Omics – allowing you to receive the output as Apache ice table. This process alone can save you hundreds of hours of productive time. With Amazon Omics’ knowledge of file formats such as FASTQ, BAM, and CRAM, customers can focus on the data using workflow definition tools such as WDL, and Amazon Omics will take care of the rest. Customers benefit from built-in attribute-based controls to define detailed data access policies for effective management, along with comprehensive data logging and lineage to track data availability. Together, these features lend a hand reduce time to market and develop a sheltered, scalable omics processing pipeline.
Transforming the future of genomic data analysis
IBM Consulting, a leading AWS consulting partner with over 18,000 AWS certified professionals worldwide, 16 service validations and 15 AWS competencies, is at the cutting edge of innovation, helping many life sciences clients such as ModernGenomics England, Chugai, Johnson & Johnson and others, are driving innovation across the life sciences value chain. IBM Consulting is a proven consulting partner for life sciences organizations, offering solutions in research and development, supply chain and manufacturing, as well as sustainability and quantum computing. This is one of the reasons IBM Consulting was awarded named Global Innovation Partner of the Year and GSI Latin America Partner of the Year at AWS re:Invent 2022, reinforcing customers and AWS’s confidence in IBM Consulting as the trusted partner of choice.
Leveraging its expertise in genomics, IBM published a whitepaper, Explainable AI reveals changes in skin microbiome composition associated with phenotypic differences, and invested in building an accelerator to enable scientists to predict phenotype from omics data (e.g. gene expression; microbiome data) and any tabulated data (e.g. clinical) using a range of machine learning models. By combining these resources, experience, and contemporary tools like Amazon Omics, IBM Consulting can lend a hand you accelerate the analysis of your genomic data.
As a testament to IBM Consulting’s expertise in this area, IBM Consulting was selected as a strategic technology partner for Genomics England within 18 months. Using AWS as the hyperscaler of choice, Genomics England’s services are rapidly expanding, providing researchers with access to genomic datasets, enabling scientific discoveries. IBM Consulting is helping Genomics England in areas such as improving the clinical user interface and enabling rapid access to genomic data stores, supporting the adoption of cloud capabilities to hybrid cloud, and delivering stable, supported and sustainable IT services at scale. Read how IBM is helping Genomics England UK transform and build the capabilities and technologies that enable more evidence-based diagnosis and treatment for patients.
To realize the benefits of data analytics and digital collaboration in genomics, life sciences companies must have a future-proof data strategy and delivery models, lead the biopharmaceutical and academic communities to create an ecosystem, develop a secure and resilient genomic data architecture, and a value realization agenda. . IBM delivers this to its business partners through operating model transformation, technology and data/AI strategy, artificial intelligence at scale and Genomic data architecture victims.
Apply the modern service to your advantage: have a strategy
The decision to apply Amazon Omics and other AWS analytics services is simple: it eliminates the need for data analysts, researchers, and clinicians to configure or maintain tools, workflows, and infrastructure. However, determining how to store, process, and analyze data is only one part of the answer. It’s up to management to define what modern product, modern service, modern partnership or other competitive advantage this service can open the door to. Contact the IBM Life Sciences and Enterprise Strategy teams for perspectives on integrated business and technology strategy and AWS for Health integration.
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