William Wordsworth may have “wandered lonely as a cloud” in his much-loved poem Daffodils, but he would be hard pressed to find a lonely cloud today, even in a more specialized area such as pharmaceutical R&D. A simple Google search for cloud and pharma throws up 104M hits, while a more refined search for cloud computing in pharmaceutical R&D gives a more modest 2.9M hits.
This is clearly an active area, and already the purported benefits (e.g. speed up research, cut costs) seem to be outweighing the perceived weaknesses (e.g. security concerns about protecting intellectual property and compliance) as pharma companies move many of their computing efforts from self-maintained on-premise servers to commercial cloud platforms and publish compelling case studies.
As a computational chemist or a data scientist/cheminformatician used to searching databases and applying computational analysis, visualization, prediction, and SAR techniques, how much do you really need (or want) to care about where and how your tools are housed, maintained, and accessed? Well – if you expect the tools to be available 24x7, always running the latest version in a high performance and secure environment, and with dedicated support, then perhaps a better understanding of the cloud might help.
The aim of this white paper is to help you better understand how the cloud is applied in pharma R&D, including the terminology used, the various server arrangements that are available, and the pros and cons of each.
The initial justification for moving to the cloud was to reduce IT spending on technology and infrastructure. This rationale is still valid but is now augmented with increased business value through enhanced innovation, improved analytics, scalability, automation, and resilience. McKinsey lists specific high-level corporate benefits:
Real world examples of this increased business value include two Oracle-cited cloud-based pharma success stories: (1) a rapidly accelerated synthetic vaccine development project shrunk from ninety to 5 days; and (2) cutting the time taken to virtually screen 1 million compounds from 24 hours in-house to 7 minutes 25 seconds in the cloud.
The high-level Cloud-derived benefits listed above can apply across the majority of functions in an organization; and they can certainly give you a sense of confidence that your company or institution is taking advantage of the latest and most beneficial technological advances: but as an individual practitioner of computational chemistry or cheminformatics techniques, how does the cloud help you answer your pressing day-to-day R&D questions faster, and with greater certainty and accuracy?
Whether it’s designing, creating, and filtering a large-scale virtual compound library for high throughput virtual screening, or predicting novel pharmacologically important properties across a huge collection of potential lead compounds for SAR analysis, you will be most effective and successful if you can be confident that your applications are:
All of these features and characteristics are readily available when data and applications are hosted and operational in a robust cloud environment: on the other hand, in-house/on-premises corporate and academic IT infrastructures and support staff will be hard pressed to consistently match these levels of operational excellence.
One of the major factors that slowed the uptake of cloud deployments in the biopharma sector was security. Organizations were very concerned about protecting their intellectual property – often their chemical registry files, aka “the corporate crown jewels'' – on servers outside the corporate firewall and possibly in non-approved geographic locations. That concern has largely been mitigated through stringent security controls and hybrid mixes of public and private cloud systems, but other potential disadvantages have been identified and need to be addressed:
The sections below on server and tenancy arrangements discuss how many of these concerns can and are being addressed.
If an organisation has successfully addressed most of the high-level concerns listed above, what else might a computational chemist have to worry about? The last item – lack of portability of legacy applications – may be an issue if the applications are not well documented, or the original developers (and their deep understanding) have departed. Depending on the migration path taken, the application may take a long time to be moved to the cloud, and its performance and scalability may be sub-optimal.
There are three main ways to migrate custom legacy apps to the cloud:
Another issue, possibly related to migration, might be that site- or individual-specific customizations may not be readily available in the cloud instance of the app.
This is a very brief primer to help understand the terminology used when discussing the cloud.
This is a brief primer to decode the various *aaS acronyms, and to explain the degrees of client involvement with a cloud provider, using the so-called Pizza Analogy developed by Albert Barron in 2014 to illustrate who is responsible for what and how much control they have.
Source: https://www.linkedin.com/pulse/20140730172610-9679881-pizza-as-a-service/
In cloud-speak, a tenant is a core part of any SaaS application, and consists of a logical grouping of users, data, and permissions, typically a company or organization.
There are two cloud tenancy arrangements:
Each approach has its own strengths and weaknesses, and these need to be balanced against business objectives and drivers:
Potential benefits of single tenant include:
Potential drawbacks of single tenant:
Potential benefits of multi-tenant:
Potential drawbacks of multi-tenant:
In the same way that successful drug design seeks to balance often competing molecular properties (e.g. activity vs. specificity, dosage vs. toxicity ; structure vs. synthesizability), selecting the optimal cloud environment and tenancy arrangement requires reaching an acceptable consensus among the myriad benefits and concerns outlined above. Some of these parameters may be of more concern at a corporate level (e.g. infrastructure and staff costs, security), while others will be more crucial for computational chemists (e.g. performance, scalability, customizability).
If time, infrastructure, and staff expenses are not major concerns, and complete control and customizability are of paramount importance, then a single tenant private cloud would be the choice.
If your organization has the capacity to invest in infrastructure and staff, and if maintaining complete control and customizability is of paramount importance, then a single tenant private cloud would be an optimal choice
If your organization values rapid deployment and efficient budget management, and is open to trading off some degree of control and customization for these benefits, then a multi-tenant virtual private cloud could serve as an excellent solution
These two options might be viewed as two ends of a spectrum of possible arrangements, each with its own various degrees of expense, control, security, flexibility, and customizability. In practice, many larger pharma organizations are choosing the hybrid cloud approach as an intermediate position. This merged combination of a private cloud and a virtual private cloud can provide the optimal cloud setting for particular applications, giving each sufficient compute power to deal with the anticipated data volume, and the flexibility and scalability to handle unexpected increases.
For more information on Chemaxon’s approach to the cloud, please get in touch with us through the link below.