Five major obstacles to Cloud shift for life science R&D - and how to overcome them...
2020 was a year we will all remember. It was also a year where we let go of some of our deep-seated convictions. We changed the way we work, communicate, and collaborate. Without a doubt, it was a year that invited us to reconsider our organizations.
Over the last two years, we observed a significant mindset change in life science research organizations towards the cloud technologies landscape. Less fear and skepticism, a better understanding of the capabilities, and rising expectations.
Because cloud computing solutions bring more agility to the business than ever before, all industries are showing increasing interest in this technology.
Nevertheless, some obstacles specific to our business remain.
1. Instruments are On-prem and cannot be connected
The laboratory's critical on-premise equipment has been a major obstacle to the development of cloud offerings in the Laboratory Informatics space. For a long time, to be controlled and exploited, it required local networks (or even USB sticks!) and proprietary software. Connecting equipment to work together often proved difficult. Capturing data for further analysis could be frustrating. This is no longer true today.
IoT-related technology is making great progress. Modern instruments are now “connected”, specific devices exist that can enable connectivity on legacy instruments, and standardized data interface protocols, such as SILA 2.0, AnIML, or Allotrope are opening up new horizons. The cloud has never been closer.
Companies to watch: Elemental Machines, TetraScience, LabVoice
“ Our voice-enabled LabVoice Smart Device securely connects your lab software and equipment with our SaaS platform to enhance data capture and instruments controlling.”
2. There are too few cloud-ready software providers
The Life Science research software industry is late to the cloud compared to other businesses, but it is catching up - fast! While historical software vendors work on cloud-ready versions of their existing tools, new actors fully embrace the Cloud-first philosophy and offer best-in-class software in a full SaaS environment. These offers include all the necessary features like APIs, security, and scalability that research organizations now expect.
This evolution runs at a rapid pace and transforms drastically the software architecture of new applications where composability is the key to success.
Examples of SaaS native solutions: Benchling notebook, DS ScienceCloud, PerkinElmer Signals Notebook, CDD Vault, Discngine 3decision
3. Legacy software and dependencies make any cloud shift project impossible
No Life Science Company was built in a day and research processes are usually based on tools implemented over time and across many projects. The consequence? The complex interactions between these tools and the age of some components can create a seemingly impenetrable wall when it comes to migrating to the cloud. This would be true if cloud shift was a monolithic approach.
But this is not the case. Refactoring, Lift & Shift, Transform & Move... There are multiple paths to the cloud, adapted to each situation and each tool. All these strategies should combine to fit the specific objectives and constraints of the research lab. The limitation? The design of this global strategy requires both an excellent understanding of the scientific challenges and a perfect mastery of technological contingencies.
4. "I.T. will not allow it"
A few years ago, corporate I.T. groups were controlling everything related to data and applications: networks, servers, PCs, development environments, vendor selection, data governance, security, monitoring… In many organizations, specialized R&D I.T. groups were even carrying (if not Confiscating) the roadmap to transform their organization's data assets into actionable scientific knowledge. Nowadays, the vast expansion of cloud providers and the emergence of new SaaS offerings are disrupting how corporate R&D informatics groups operate. It is not a loss of power or a diminishing influence on business activity, it is an opportunity to accelerate and improve the efficiency of pharmaceutical research.
Massive digital transformation programs have been recently initiated in many organizations by Top management with the objective to rapidly benefit from the new advances in the cloud era. A new generation of computer-savvy employees (Data scientists, UI/UX designers, Cloud experts…) have been hired and the constantly evolving technological landscape is hard to master. In this context, the role of I.T. groups needs to rapidly change as the possibility for business users to bypass I.T. good practices increases. I.T. departments need to maximize the benefits of the new advances by adjusting their role:
Software Architecture and infrastructure: The combination of PaaS/SaaS solutions offers unlimited power to deliver scalable solutions to scientists. Software-defined WAN allows organizations to securely benefit from the multi-cloud capabilities. Automation helps in maximizing responsiveness to new requests.
Low-Code: The next generation of application development environments are now available, and it should be I.T.'s role to organize, secure, and coach data scientists and power users when using these frameworks. Non-experts can build apps and will do it. They need help and support for that.
Authentication and Authorization: Decrease risks of security breaches by using a centralized security management system and intelligent monitoring
Vendor selection: Help business users select cloud software providers with updated I.T. requirements on security, interoperability, UX/UI principles, performance, and monitoring.
Some Cloud acronyms you should know - Our selection: IaaS, SaaS, PaaS, BYOD, DaaS, DbaaS, IPaaS, SD WAN
5. Security is the weak point of the cloud
When it comes to the Cloud shift in life science organizations, security issues are at best a matter of question, often a matter of concern and sometimes a sticking point. All of this is fair game. Migrating to the Cloud means entrusting the company's most sensitive data to others. Who would do this without any hesitation?
Nevertheless, here too old beliefs often prevail, based on an understanding of the Cloud that does not take into account its most recent advances. These advances directly impact how much you can trust your SaaS providers and how safe your data is in the cloud. Long story short, the best SaaS providers are the transparent ones.
Several years ago, evaluating the impact of adopting a SaaS offer on your company security posture was a complex journey, but with vendors adopting certifications like ISO27001 or SOC2 that offer visibility on a predefined level of security and exposure, this evaluation is now made much easier. These security certifications will act as accelerators to Life Science Research companies’ third-party cybersecurity management, by positioning their trust cursor on key points like credentials management (SSO, Identity Federation, encryption keys management), data regulation compliance (GDPR compliance), data sovereignty (data storage country) and finally the vendor risk (vendor transparency on security processes).
And if one wants to accelerate the pace of your cloud shift even more, why not outsource third-party cybersecurity management to independent information security assessors (Cybervadis, Kroll, BitSight, ….)?
To conclude, the Cloud Shift of your infrastructure is not a simple project. It requires the consideration of many parameters: technological, scientific, security, usage, budget, etc. Nevertheless, most, if not all, of the obstacles that were placed in the path until now have been addressed by the offers available on the market. Business sectors with similar constraints to life science have already switched to the cloud. We are now convinced that the solutions exist in the life science sector to make the most of the opportunities offered by the cloud.