Pharmaceutical companies face a wide range of problems in their research and development activities. One common problem a pharma research and development team encounter is data management because of the large volume of data ranging from terabytes or petabytes.
Thanks to the advanced HPC systems with cloud capabilities, software applications, and network devices, pharma R&D can identify, organize, and manage large volumes of data. The purpose is to streamline data management processes and increase efficiency using advanced HPC systems based on innovative algorithms tailored to the R&D needs.
Better Drug Discovery
The drug discovery process can take advantage of HPC architectures, including the grid and cloud computing architectures. Research shows that HPC cloud architecture provides a more streamlined and cost-effective solution in performing drug discovery calculations.
A pharmaceutical company’s R&D team can use HPC cloud architectures to access and exploit high computing power to perform their drug-based research, discovery, and development.
Cloud computing facilitates CDD web server development, allowing researchers to access data and information in biotech and chemical databases using various software packages. Studies confirm that the use of cloud-based HPC architectures can lead to new drug discovery and development using novel techniques, tools, and methodologies.
Streamlined Genomics Research
Genomics research performed by biotech engineers, Bioinformatics researchers, and pharmaceutical teams generate large volumes of data. Using HPC resources, scientists can develop personalized treatments and focus on next-generation medicine. However, this requires rapid analysis of data related to DNA sequences.
Thanks to the advanced HPC architectures, the cost of DNA sequencing is $1,000 per genome, which was $10,000 in 2017. The reason is that Cloud-based HPC systems facilitate researchers, biotechnologists, and pharma Bioinformaticians with increased speed, refined computational resources, and optimized data analysis.
Efficient and Fast Data Sharing
According to Clovertex, scalability and speed are the most prominent virtues of HPC systems. However, IT professionals at Clovertex also say that HPC systems offer greater flexibility with improved storage options. R&D teams can use HPC cloud-based storage applications to store a high volume of research data effectively and securely.
Bear in mind that file system storage allows R&D teams to share data across different pharma projects in a more seamless way. Similarly, block storage solutions allow for high-scale performance and shared storage applications for the computation of petabytes of data.
Using the HPC system, R&D teams at pharmaceutical companies can scale up their pipeline and use advanced and tailored solutions to research multi-target block, DNA-protein data, mutagenesis data, and create different models to optimize the drug-discovery process.
Save Resources and Time
HPC uses supercomputers to perform advanced calculations. Researchers can now recreate three-dimensional images on the screen using supercomputers. For example, the purpose is to perform simulation of cell division in different organisms, analyze DNA interactions, RNA mechanisms, cancer cell progression, create cardiovascular models, study neurological pathways, etc.
HPC has numerous applications in the pharma industry. One of the primary benefits of HPC is saving time and resources. Because everything is done virtually, researchers use fewer resources and perform quick data processing, leading to more standardized scientific research and development.
The big pharma industry faces big data problems and requires high-performance computing technology to streamline its operations. HPC systems help pharma R&D to study and analyze data at micro and macro levels.
It also allows them to design virtual drug development models, saving more time and money and using theoretical and experimental research. Contact Clovertex for HPC and cloud computing solutions.