A Partly Cloudy Day: Which Applications & Workflows Work Best in the Public Cloud

Life science researchers are beginning to actively embrace public cloud technology. Research labs that manage IT operations more efficiently have more resources to spend on innovation.

As more life science organizations migrate IT infrastructure and application workloads to the public cloud, it’s easier for IT leaders to see what works and what doesn’t. The nature of life science research makes some workflows more cloud-friendly than others.

Why Implement Public Cloud Technology in the Life Science Sector

Most enterprise sectors invest in public cloud technology in order to gain cost benefits or accelerate time to market. These are not the primary driving forces for life science research organizations, however.

Life science researchers in drug discovery and early research see public cloud deployment as a way to consolidate resources and better utilize in-house expertise on their core deliverable—data. Additionally, the cloud’s ability to deliver on-demand scalability plays well to life science research workflows with unpredictable computing demands.

These factors combine to make public cloud deployment a viable solution for modernizing life science research and fostering transformation. It can facilitate internal collaboration, improve process standardization, and extend researchers’ IT ecosystem to more easily include third-party partners and service providers.

Which Applications and Workflows are Best-Suited to Public Cloud Deployment?

For life science researchers, the primary value of any technology deployment is its ability to facilitate innovation. Public cloud technology is no different. Life science researchers and IT leaders are going to find the greatest and most immediate value utilizing public cloud technology in collaborative workflows and resource-intensive tasks.

1. Analytics
Complex analytical tasks are well-suited for public cloud deployment because they typically require intensive computing resources for brief periods of time. A life science organization that invests in on-premises analytics computing solutions may find that its server farm is underutilized most of the time.

Public cloud deployments are valuable for modeling and simulation, clinical trial analytics, and other predictive analytics processes that enable scientists to save time and resources by focusing their efforts on the compounds that are likely to be the most successful. They can also help researchers glean insight from translational medicine applications and biomarker pathways and ultimately, bring safer, more targeted, and more effective treatments to patients. Importantly, they do this without the risk of overpaying and underutilizing services.

2. Development and Testing
The ability to rapidly and securely build multiple development environments in parallel is a collaborative benefit that facilitates life science innovation. Again, this is an area where life science firms typically have the occasional need for high-performance computing resources – making on-demand scalability an important cost-benefit.

Public cloud deployments allow IT teams to perform large system stress tests in a streamlined way. System integration testing and user acceptance testing are also well-suited to the scalable public cloud environment.

3. Infrastructure Storage
In a hardware-oriented life science environment, keeping track of the various development ecosystems used to glean insight is a challenge. It is becoming increasingly difficult for hardware-oriented life science research firms to ensure the reproducibility of experimental results, simply because of infrastructural complexity.

Public cloud deployments enable cross-collaboration and ensure experimental reproducibility by enabling researchers to save infrastructure as data. Containerized research applications can be opened, tested, and communicated between researchers without the need for extensive pre-configuration.

4. Desktop and Devices
Research firms that invest in public cloud technology can spend less time and resources provisioning validated environments. They can provision virtual desktops to vendors and contractors in real-time, without having to go through a lengthy and complicated hardware process.

Life science research organizations that share their IT platform with partners and contractors are able to utilize computing resources more efficiently and reduce their data storage needs. Instead of storing data in multiple places and communicating an index of that data to multiple partners, all of the data can be stored securely in the cloud and made accessible to the individuals who need it.

5. Infrastructure Computing
Biopharmaceutical manufacturing is a non-stop process that requires a high degree of reliability and security. Reproducible high-performance cloud (HPC) computing environments allow researchers to create and share computational biology data and biostatistics in a streamlined way.

Cloud-enabled infrastructure computing also helps life science researchers monitor supply chains more efficiently. Interacting with supply chain vendors through a cloud-based application enables researchers to better predict the availability of research materials, and plan their work accordingly.

Hybrid Cloud and Multi-Cloud Models May Offer Greater Efficiencies

Public cloud technology is not the only infrastructural change happening in the life science industry. Certain research organizations can maximize the benefits of cloud computing through hybrid and multi-cloud models, as well. The second part of this series will cover what those benefits are, and which life science research firms are best-positioned to capitalize on them.

 

About RCH Solutions

RCH Solutions is a global provider of computational science expertise, helping Life Sciences and Healthcare firms of all sizes clear the path to discovery for nearly 30 years. If you’re interesting in learning how RCH can support your goals, get in touch with us here.  

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