Accelerate Drug Development and Patient Outcomes With AWS

Sphere delivers HIPAA-compliant, GxP-ready cloud and AI solutions for life sciences and healthcare organizations – genomics analysis, clinical trial data platforms, real-world evidence analytics, and AI-powered clinical decision support – built on AWS HealthLake, SageMaker, and GovCloud.

HIPAA

Compliant Architecture

GxP Ready

21 CFR Part 11 Support

AWS HealthLake

Native Integration

50%

Faster Trial Timelines

Why This Matters Now

Life sciences and healthcare organizations sit on the most valuable data in the world – genomic sequences, patient outcomes, clinical trial results – but most of it is locked in siloed systems, expensive on-premises infrastructure, and legacy data models that prevent modern AI from accessing it. Meanwhile, cloud adoption in regulated industries requires specialized compliance expertise that most AWS partners don’t have.

1. Regulatory Complexity Paralyzes Cloud Adoption

HIPAA, 21 CFR Part 11, GDPR, and ICH E6 requirements create a compliance maze that keeps life sciences IT teams stuck on legacy infrastructure years after it should have been modernized.

2. Siloed Data Prevents AI-Driven Discovery

Genomics, clinical, claims, and real-world evidence data sitting in separate systems makes the cross-dataset AI analysis that drives the most valuable drug discovery insights impossible.

3. Clinical Trial Infrastructure Is Manual and Slow

Trial data management, EDC integration, and regulatory submission preparation is still predominantly manual – introducing errors, delays, and cost overruns into every trial.

What Sphere Delivers

Sphere’s Life Sciences practice combines deep AWS expertise with hands-on regulatory compliance experience – building HIPAA-compliant, GxP-validated cloud infrastructure that actually gets through your compliance review process. Our team includes former FDA consultants and life sciences IT leaders who speak both AWS and regulatory language fluently.

HIPAA & GxP Compliant Foundation

Pre-built AWS infrastructure templates meeting HIPAA Security Rule, 21 CFR Part 11 electronic records, GCP (ICH E6), and SOC 2 Type II requirements. Validated infrastructure with IQ/OQ/PQ documentation.
AWS HealthLake Integration

FHIR R4-compliant health data lake on AWS HealthLake – enabling unified patient data storage, NLP-powered medical record analysis, and cross-dataset AI analytics.
Clinical Trial Data Platform

EDC integration, clinical data management system (CDMS) on AWS, regulatory submission data packages, and real-time trial monitoring dashboards.
Genomics Analysis Pipeline

Scalable genomics analysis pipelines on AWS – from raw sequencing data through variant calling, annotation, and population-level analysis – using AWS Omics.
AI Clinical Decision Support

SageMaker-based ML models for clinical risk scoring, drug-drug interaction prediction, adverse event detection, and patient stratification – with full model validation documentation for regulatory submission.
CSV & Computer System Validation

Validation-ready AWS platforms with risk-based CSV methodology, requirements traceability, test scripts, deviation handling, and change control documentation.

Built On Industry-Leading Technology

Built on AWS services designed for regulated healthcare and life sciences environments, Sphere creates secure platforms for clinical data, genomics workflows, medical NLP, and AI-driven analysis. This technology stack supports compliant data storage, governance, interoperability, and machine learning across FHIR, DICOM, and other healthcare systems – giving life sciences teams a practical foundation for research, operations, and patient-focused innovation.

icon AWS HealthLake (FHIR data store)
icon AWS Omics (genomics)
icon Amazon SageMaker (clinical ML)
icon AWS GovCloud (HIPAA/FedRAMP)
icon Amazon Comprehend Medical (NLP)
icon AWS Lake Formation (data governance)
icon HL7 FHIR / DICOM integration

Who This Is For

INDUSTRY

VERTICAL APPLICATION

Pharmaceutical R&D

Drug discovery AI, clinical biomarker analysis, and real-world evidence analytics on unified AWS data platform.

Clinical Research Organizations

Scalable clinical trial data management infrastructure supporting Phase I–IV trials across multiple therapeutic areas.

Health Systems

Population health analytics, clinical risk stratification, and care gap identification using AWS HealthLake.

Digital Health Companies

HIPAA-compliant cloud infrastructure for connected medical devices, patient apps, and remote monitoring platforms.

Payers

Claims analytics, prior authorization AI, and member health risk modeling on compliant AWS infrastructure.

Schedule a Life Sciences Cloud Assessment

Sphere’s life sciences IT experts will review your current infrastructure, compliance requirements, and priority use cases – and propose an AWS cloud modernization roadmap with full compliance architecture and projected ROI.

icon No sales pressure icon Senior engineer call icon Custom ROI estimate

How It Works

Compliance Assessment

Review regulatory requirements, existing systems, and data governance policies. Define compliance architecture.

Foundation Build

Deploy HIPAA-compliant AWS Landing Zone with validated security controls, logging, and access management.

Migration & AI

Migrate clinical, genomic, or operational data to AWS with full chain of custody documentation. Build analytics pipelines, ML models, and application layer on compliant foundation.

Validation & Audit

IQ/OQ/PQ validation, penetration testing, and audit trail review for regulatory submission readiness.

ROI & Bussines Impact

Life sciences companies using Sphere’s AWS platform report 50% faster clinical trial timelines, $2M–$8M annual cost savings from infrastructure modernization, and 60–80% reduction in regulatory compliance overhead.

For pharmaceutical companies, accelerating a single trial by 6 months represents $10M–$50M in value from faster time to market.

Let’s Connect

Trusted by

Flexible, fast, and focused — Sphere solves your tech and business challenges as you scale.

Luke Suneja

Client Partner

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Hear From Our Clients

Sphere Partners
Selah Ben-Haim VP of Engineering at Prominence Advisors

Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).

Sphere Partners
Ben Crawford Senior Product Manager at Enova Financial

I would expect to be delighted. It’s been a really positive experience, working with Sphere, and I would expect you to have the same.

Sphere Partners
Mark Friedgan CEO at CreditNinja

Sphere consistently prioritizes the needs of their clients, demonstrating both agility and teamwork. They bring innovative and well-considered solutions, consistently surpassing my expectations.

Sphere Partners
René Pfitzner Co-Founder at Experify

Sphere provided excellent full-stack development manpower to augment our team and work with us.

Sphere Partners
Bruce Burdick Chief Information Officer at Integra Credit

We've been working with Sphere and its excellent consultants since our founding. Their combination of offshore talent, pricing, and shift offsetting is hard to beat. They provide crucial augmentation to our in-house team. We simply couldn't achieve our production ambitions without their service.

Sphere Partners
Jemal Swoboda CEO at Dabble

The resources and developers that Sphere Software provides are skilled and have the required technical expertise to complete their tasks successfully, with the team easily scaled in either direction. The deliverables are always high-quality.

Sphere Partners
Arthur Tretyak Founder and CEO at IntegraCredit

With Sphere, we were able to migrate in half the time it would take to train an additional FTE…

Sphere Partners
Lee Ebreo VP of Engineering at Credit Ninja

These things would not have been achievable if we did not build our own in-house system. We augmented our development team capabilities using Sphere’s developer, who works very well with our Dev Lead in Chicago. Sphere’s developer was an expert in the new system, and continues to be an expert as we evolve it.

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Sphere in Numbers

We understand that actions speak louder than words and numbers
but here are some key facts about us.

20

Years of Experience

230

Delivered Projects

200+

Senior Specialists

94%

Satisfaction Rate

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Frequently asked question

AWS HealthLake is used to store, normalize, and analyze health data in FHIR format. It helps healthcare and life sciences organizations unify patient and clinical data from different systems so teams can improve analytics, interoperability, and downstream AI use cases. Sphere uses AWS HealthLake as a core layer when building modern clinical data platforms on AWS.

WS HealthLake is designed to work with FHIR-based healthcare data, which makes it useful for organizations that need a centralized and standardized health data store. It can help bring together records from EHRs, care platforms, research systems, and other healthcare applications. Sphere helps clients design this integration layer so the data model works in practice, not only on paper.

Yes, AWS can be used to build HIPAA-compliant healthcare applications when the architecture, access controls, encryption, logging, and operational processes are designed correctly. Compliance depends on the full solution, not only the cloud service itself. Sphere builds healthcare and life sciences environments on AWS with that full picture in mind, including governance, security, and audit readiness.

AWS Omics is used to run and scale genomics workflows such as sequence analysis, variant calling, annotation, and population-level research pipelines. It helps organizations process large volumes of genomic data more efficiently without building all infrastructure from scratch. Sphere uses AWS Omics in solutions where genomics processing needs to connect with broader research or clinical data platforms.

Amazon SageMaker is used to build, train, deploy, and monitor machine learning models for healthcare and life sciences use cases. These can include clinical risk scoring, operational forecasting, patient stratification, and adverse event detection. Sphere applies SageMaker as part of a controlled ML workflow so models fit real data, validation, and monitoring requirements.

Amazon Comprehend Medical is used to extract structured medical information from unstructured clinical text such as notes, discharge summaries, and medical records. It can identify entities like conditions, medications, and protected health information to support search, analytics, and workflow automation. Sphere uses it where medical NLP can reduce manual work and improve access to usable clinical insights.

HL7 is a broader family of healthcare data exchange standards, FHIR is a modern standard for exchanging healthcare data in a more flexible and API-friendly way, and DICOM is the standard used for medical imaging data. Many healthcare environments need all three because clinical records, interoperability, and imaging rarely live in one system. Sphere designs platforms that connect these standards in a cleaner and more workable architecture.

AWS Lake Formation is used to manage data access, permissions, and governance across large healthcare and life sciences datasets. It helps organizations control who can access which data and under what conditions, which is important for privacy, compliance, and internal security. Sphere uses Lake Formation to make governance part of the platform design from the start.

AWS GovCloud is used by organizations with stricter regulatory, security, and data handling requirements, including public sector and highly regulated workloads. In healthcare and life sciences, it can be relevant when clients need stronger isolation or alignment with specific federal compliance expectations. Sphere helps clients assess when GovCloud makes sense and when a standard AWS architecture is the better fit.

A strong AWS healthcare platform usually combines interoperable data storage, governance, security controls, analytics, and machine learning in one architecture. That often means using services such as AWS HealthLake, SageMaker, Lake Formation, Comprehend Medical, and integration across FHIR and DICOM-based systems. Sphere’s approach is to build these platforms around actual operational and regulatory needs, so the result is usable by clinical, research, and IT teams alike.

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