The recent coronavirus pandemic has shown some of the challenges. However, the development of the new applications will enhance the analytical capabilities, mainly as a result of using AI. These applications will be valuable because they can be applied everywhere, from patient engagement to the management of the supply chain. There is a huge potential for medical technology and life sciences disciplines to use the cloud to aid in treating diseases, although this opportunity is often slowed down by the privacy concerns around the sharing of data.

In the case of COVID-19, where massive amounts of information need to be stored, accessed, shared, and analyzed, the computing power that is needed is massive. Such massive amounts of computing power can limit other applications from functioning correctly, hence the suitability of the cloud in such an area. However, if the cloud initiative is not appropriately implemented, various problems might arise, such as security challenges, cost, and data consistency issues. To avoid these issues, some of the best practices can be adopted by organizations.

First, design your cloud solution for portability. Build custom machine images on the cloud, that mirrors those in your on-premise environment and that are deployable in the cloud. With portable, ready-to-run images, you will be able to operate faster even after migrating to the cloud. Furthermore, ensuring your deployment is similar to the on-premise environment will help you encounter fewer compatibility issues.

Secondly, leverage on automation. Even if you have ready-to-run images, assembling cloud clusters can be difficult. However, users should be worried about things such as file systems, DNS, and VPNs, among others. You can avoid this by using a variety of solutions to build clusters automatically or getting automation solutions that operate correctly across multiple cloud environments. Make sure that the automation solutions you select support the files that you have as such flexibility reduces challenges. You can also use containers to encapsulate applications and make them portable. Using containers allows applications to run consistently with stability and simplifies adoption.

There are indeed many potential challenges that users in life sciences discipline may encounter. However, the cloud offers an opportunity for efficient business operations, collaborative efforts, and innovation. Concerns regarding regulations continue to haunt this industry, just like the majority of those who want to implement cloud computing in their operations. Regardless of the concerns and challenges that are associated with cloud platforms, firms in life sciences are devising new diagnostics and therapeutics or working on vaccines with the help of the cloud. With the cloud, the level of investment that is needed to maintain the state of the art systems is low compared to in-house systems. Cloud computing platforms drive growth, maximize productivity to offer the best services, and enhance interactions among professionals and with customers.