Biotechnology

Solutions for Life Sciences

It takes almost a decade and close to a billion dollar to bring a new drug to market. Obviously, the key business driver, for using HPC in this industry, is to shorten research and development timeframe and costs.Using in-silico drug discovery methods, a new drug can be brought to market sooner. Computational biology deals with a myriad of challenges and has applications diverse areas ranging from agriculture, health care and medicine, and cosmetic to the pharmaceutical sector.

At CRL, we have successfully designed and build complete HPC solutions for various applications in this sector:

  • Drug Discovery
  • Genomics
  • Bio and Chemo Informatics

Drug Discovery

It takes almost a decade and close to a billion dollar to bring a new drug to market. Obviously, the key business driver, for using HPC in this industry, is to shorten the time frame and costs.

Drug discovery cycle is largely expedited by the use of in-silico discovery methods. A widely deployed computational method is Virtual Screening, which scans through very large datasets of chemical structures (millions of compounds) to identify those structures that are most relevant to the specific discovery target.

At CRL, we have automated the complete pipeline workflow for hit identification using virtual screening. The integrated workflow is implemented to provide great flexibility in specifying virtual screening parameters and for enabling selection based on interactions. The entire solution is remotely accessible at our HPC facility over the web.

We have catered to the needs of some of the prominent names in the industry, organizations like the National Chemical Laboratory, Advinus, Genotype, and Indian Institute of Sciences to name a few.

Genome Analysis

With the technological advances in next generation sequencing, the bottle neck in sequencing projects has shifted from obtaining reads to the alignment and post processing of the massive data churned out by the sequencing machine. Sequence assembly is a complex and computationally intensive task. The freeware tools available for genome assembly are serial in nature and cannot handle Denovo assembly of eukaryotic genomes.

At CRL, we have developed a tool for parallel Denovo assembly which makes the assembly process faster and cheaper. We provide an automated pipeline in our HPC Cloud for the analysis of next generation sequencing data covering De Novo assembly, resequencing, analysis and annotation.

Delivering Value to Life Sciences Customers

At CRL, we provide a complete ecosystem with a production ready state-of-the-art HPC infrastructure, domain expertise in Life Sciences, and in-house HPC expertise to support custom needs of the life sciences industry.

We deliver value to life science customers in many ways:

Infrastructure Provisioning: Ready access to the world’s fastest commercially available supercomputer ‘Eka’. With 1800 production ready compute nodes, 20 Gbps high speed interconnect and high throughput scalable storage providing a peak performance of 172 TeraFlops; your enterprise has immediate access to a powerful HPC infrastructure without the need for capital investments or long term lease options.

Application Services: The application domain team at CRL comprises of experts with wide experience in life science applications. CRL provides the expertise required to port and commission various life science applications on a High Performance Computing infrastructure. User workflows can be optimized and customized based on varying requirements within short turnaround times.

Remote Access: CRL provides secure remote access mechanisms for submissions, monitoring and intermediate data transfers to review the execution results.

Parallel Programming: The HPC expertise at CRL extends to parallel programming on using MPI, OpenMPI/pThread based or even hybrid methodologies. Parallelization using libraries like HP MPI, Intel MPI, OpenMPI and Mvapich, among others, is done at CRL to successfully improve scalability and performance of existing application codes.