Accelerating Scientific Discovery Through Cloud-Powered HPC Infrastructure for a global pharma
The Challenge
A global pharmaceutical's research division experienced rising computational demands as ML-driven discovery accelerated across digital biology and structural biology. Existing systems began to show limitations in handling increasingly complex analyses, resulting in slower data processing and reduced efficiency for research teams.
To sustain scientific progress and operational agility, the organization needed a scalable and secure computing environment capable of supporting advanced research pipelines with reliability, consistency, and speed.
Key challenges included:
- Fragmented Research Systems
Independent compute clusters operated by different teams limited collaboration and reproducibility, creating silos across the research ecosystem
- Rising Computational Demands
Intensive workloads such as biologics discovery and CryoEM analysis required powerful GPU capacity and faster turnaround times to support iterative modeling
- Manual Environment Management
Significant time was spent on manual setup and environment configuration, diverting researchers from core scientific activities
- Lack of Standardization
Each environment was built differently, making it difficult to ensure consistent performance, governance, and traceability across programs
Our Solution
Implementing Scalable Cloud HPC and Managed Services to Meet Growing Research Needs
We delivered a solution engineered for high performance, scalability, and security to meet the organization's research priorities. By tailoring each service to their needs, optimized computational workflows, data processing efficiency, and system reliability with the following core components:
Scalable Cloud HPC Environment
A flexible HPC framework that dynamically allocates compute and GPU resources, ensuring uninterrupted performance during peak research cycles.
Automated Infrastructure Management
Automated provisioning and configuration eliminated manual setup, delivering reproducible environments for every new study or experiment.
Optimized Compute and Storage Integration
High-throughput storage and parallel processing capabilities reduced data bottlenecks, enabling faster molecular modeling, Cryo-EM analysis, and ML-based simulations.
Centralized Monitoring and Performance Optimization
Continuous monitoring across compute, network, and storage layers ensured real-time visibility, rapid issue resolution, and cost efficiency.
Sustained Reliability and Governance
Built-in controls, access management, and traceable change history maintained compliance and operational stability across the research landscape.
The Outcomes
The unified cloud-powered platform redefined how scientific computing operates delivering agility, performance, and scalability.
Continuous Innovation Enablement
New workloads and research programs can be added on demand without downtime, ensuring seamless expansion
Operational Efficiency and Stability
Automation reduced manual effort and improved environment reliability, accelerating research readiness
Empowered Research Teams
Scientists can now run complex analyses without technical constraints, with infrastructure that scales effortlessly to their needs
Future-Ready Scalability
The platform evolves alongside growing research demands, ensuring computational resources never limit discovery
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