Diabetes, Cancer and Alzheimer’s are diseases that have touched all of our lives, but how does the prevention, treatment and cure of these and other diseases align to IT?
There’s no question the scientists, researchers, and medical practitioners are the driving force behind the development of new drugs and treatments that will cure the diseases that are today’s leading cause of death and disability. However, IT can make an enormous contribution by speeding up the time to market and augment how biomedical researchers improve the drug discovery process.
According to recent data “[b]ringing a new pharmaceutical drug to market takes about 12 years and can reach into the billions in R&D expenditures, industry leaders are now seeking more efficient methods of approaching this process and machine learning is emerging as a potential solution.”
Right now the ability to shorten the R&D time is being affected by reliance on legacy IT environments. From platforms that do not scale, to managing the complexity, expense, and onerous maintenance requirements, older IT platforms are artificially slowing the time to market by weeks and also consuming budget that could be used elsewhere in the organization.
And that’s where IT can be put to work to accelerate the R&D cycle.
Improvements to the R&D cycle mean savings in both time and money. For example, leveraging machine learning and artificial intelligence (AI) significantly reduces the time for modeling and simulation in the drug development process. If you can shorten the simulation time from weeks to days, then a significant competitive advantage is introduced at one of the earliest and most time consuming points in the drug development cycle.
While the type of infrastructure needed to facilitate this used to be both cumbersome in terms of physical impact and prohibitively expense, recent developments in the data storage and management industry have produced their own radical changes.
Combining technologies such as NVIDIA GPUs or the NVIDIA DGX-1 with a converged High Performance Computing (HPC) platform brings about substantial increases in speed and faster time to delivery on parallel processing workloads.
This enables pharmaceutical companies to pursue opportunities including probabilistic programming, genomic profiling, and molecular dynamic simulations. Instead of taking days, or even weeks, running simulations or sequencing genomic information can be completed in hours. In turn, this improves the early stages of drug development, reducing the time to market overall.
But both these examples and the possible use cases for this type of data management and processing infrastructure are just the tip of the iceberg when it comes to how pharmaceutical companies can put a next-generation infrastructure to work to deliver tangible business results. Once you have the IT capabilities in place a wealth of opportunities for pharmaceutical companies and the patients they help will move from possibility to reality.
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