The integration of NVIDIA Inference Microservices (NIMs) and a Slurm-based cluster optimized workload management, research breakthroughs are no longer a waiting game—they’re happening now.

Innoplexus is a global leader in artificial intelligence (AI) and blockchain technologies, specializing in life sciences. Founded in 2015, the company is headquartered in Eschborn, Germany, with offices in Pune, India, and Iselin and San Francisco, United States. Innoplexus offers Data as a Service (DaaS) and Continuous Analytics as a Service (CAaS) solutions, generating real-time insights from vast amounts of structured and unstructured data. This empowers organizations to make informed decisions rapidly, enhancing the efficiency and effectiveness of drug discovery and development processes.

Redefining Drug Discovery with AI and High-Performance Computing

The pharmaceutical industry is undergoing a paradigm shift with artificial intelligence (AI) and machine learning (ML) revolutionizing drug discovery. These technologies enable researchers to analyze vast biomedical datasets, identify promising drug candidates, and accelerate development cycles. However, the computational power required to train, fine-tune, and deploy sophisticated AI models presents a significant challenge. To overcome these limitations, Innoplexus, an AI-driven  research company, turned to Yotta’s Shakti Cloud, a GPU-accelerated high-performance computing platform designed for AI-driven research. Shakti Cloud enables Innoplexus to overcome computational bottlenecks, optimize research workflows, and accelerate pharmaceutical innovation.

Computational Challenges in AI-Powered Drug Research

Traditional drug discovery is a complex, multi-year process requiring extensive computational resources for data analysis, deep learning model training, and large-scale molecular simulations. AI-powered drug discovery relies on deep learning algorithms to analyze genomic, proteomic, and clinical data, predict drug-target interactions, and optimize molecular structures. However, AI-driven research generates massive datasets that demand significant processing power and storage capacity. The challenges faced by Innoplexus included high latency in data processing, prolonged AI model training cycles, and an inability to scale computational workloads efficiently. To drive faster discoveries and optimize research accuracy, Innoplexus needed a high-performance computing solution tailored for AI workloads.

Challenge

Innoplexus relies on AI-driven drug discovery, which requires massive GPU power to train and fine-tune models on vast datasets. Managing these computationally intensive tasks demands a high-performance infrastructure with robust GPU accelerators to ensure efficiency and scalability.

Solutions

Innoplexus leverages Yotta’s Shakti Cloud, powered by NVIDIA H100 GPUs and Slurm cluster technology, to handle intensive simulations and deep learning workflows. With NVIDIA NIMs integrated into Shakti Cloud, optimized for HGX with H100 GPUs, we achieve faster model training and fine-tuning, accelerating drug discovery timelines without compromising accuracy.

Accelerating AI Research with Yotta’s Shakti Cloud

Yotta’s Shakti Cloud, equipped with NVIDIA H100 GPUs, provided Innoplexus with the computational infrastructure required to accelerate AI-driven drug discovery. The platform’s high-performance GPUs deliver superior processing power, enabling faster deep learning model training, improved inference capabilities, and real-time AI model fine-tuning. By leveraging Slurm-based workload management, Shakti Cloud optimizes resource allocation, ensuring efficient parallel processing of multiple AI models and minimizing computational bottlenecks.

Innoplexus also benefited from the integration of NVIDIA Inference Microservices (NIMs) within Shakti Cloud. These microservices streamline AI model training, enhance fine-tuning capabilities, and improve inference performance. By reducing model training times and optimizing AI deployment, Shakti Cloud significantly enhances research throughput and accelerates the identification of viable drug candidates.

Impact on AI-Driven Drug Discovery

With Shakti Cloud’s GPU-accelerated infrastructure, Innoplexus has achieved substantial reductions in research timelines. AI model training that previously took months can now be completed within days, while data processing cycles have been reduced from weeks to hours. This acceleration allows Innoplexus to conduct rapid hypothesis testing, refine AI predictions, and bring potential treatments to clinical trials faster.

The enhanced computational power of Shakti Cloud has also improved predictive accuracy in drug discovery. AI models now deliver more precise drug-target interaction predictions, leading to higher success rates in clinical trial candidates and improved identification of novel therapeutic targets. By leveraging high-performance computing, Innoplexus is advancing methodologies in multi-target drug design, personalized medicine, and AI-powered drug repurposing.

Conclusion

Partnership with Yotta and the integration of Nvidia’s advanced technology, Innoplexus has significantly enhanced its AI-driven drug discovery platform. The Shakti Cloud’s high-speed, scalability, and security allow our researchers to concentrate on innovation and making scientific breakthroughs, confident in having reliable and potent computational support. This strategic collaboration has proven essential in pushing the boundaries of what’s possible in drug discovery, establishing Innoplexus as a leader in the field. We look forward to continuing this fruitful partnership, driving forward revolutionary advancements in life sciences.