Ever-Bigger Big Data

With increasing migration to the cloud, and a growing need to bridge diverse architectures and reduce data silos, the pharma industry is giving software architecture a hard look.

The sheer quantity of data companies collect is – of course – still growing. It’s an insatiable beast.

According to Forbes:
“The amount of data we produce every day is truly mind-boggling. There are 2.5 quintillion bytes of data created each day at our current pace, but that pace is only accelerating with the growth of the Internet of Things (IoT). Over the last two years alone 90 percent of the data in the world was generated. “

In the pharma industry, much of the attention is on Big Data – data that, according to Gartner, contains greater variety arriving in increasing volumes and with ever-higher velocity. Big Data is typically measured in terms of those “three Vs”: volume, velocity, and variety.

big data 01

ZDNet captured it well: “Once you start talking about data in terms that go beyond basic buckets, once you start talking about epic quantities, insane flow, and wide assortment, you’re talking about Big Data.”

The arrival of Big Data has proven a major disruptor for the life sciences industry – impacting everything from business intelligence and healthcare outcomes to drug discovery and marketing. But it has also shone a spotlight on the need for better harmonized software & infrastructure architecture to ensure maximum value can be extracted from that data.

Data in Isolated Stacks

For most life science companies, leveraging all of that data to make informed business decisions has proven a challenge. One of the barriers? Data caught in silos.

Data silos

Isolated and disconnected data sets are a growing complication for any data-driven company or organization. Silos emerge when data resides in very different systems, with isolated architectures or stacks, and incompatible modes of communication and sharing.

Software connectors to overcome these barriers have become essential to the pharma software development space. Avoiding the need to retool platforms outright, custom coding can create bridges between diverse platforms for data-sharing.

For example, we recently completed a project bridging an off-the-shelf Member Management Portal developed on top of SalesForce with an off-the-shelf SaaS reporting tool.

data silos

The Best Software Development Architecture for Pharma

Organizations confronting Big Data have raised questions (and we’ve fielded many ourselves) around how to select the best software infrastructure in order to keep up with the need to capture, manage and harness data.

The answer: It depends.

Different organizations can have very different software solutions. By way of example:

  • Company A may be confronting issues of scalability with their current systems, platforms & processes, but needs a bespoke solution to maintain highly-customized workflows.
  • Company B suffers from fragmented, siloed data that needs to be structured or integrated for further analysis. They have systems which do not talk, and need to create bridges between the platforms.
  • Company C wants to simplify existing workflows, or automate tasks. They are open to adapting their current operations to an enterprise solution.
  • Company D simply needs to combine data from their public website and their CRM to improve sales targeting.
  • Company E needs to migrate fully away from an existing platform that isn’t flexible enough to adapt to changing industry standards and compliance practices.
  • Company F uses a platform that is no longer being appropriately updated and patched.

Each of these represent a different audience, with potentially very different needs.

There are, however, commonalities they all must consider.

Company IT – What’s Already Under the Hood?

Whenever a software challenge emerges and IT departments consider a solution, the first thing to look at is what types of systems they already have. This will be a key decision factor in determining the best tech stack for a project.

Why?

As discussed in an earlier post, if existing systems reside on Windows with SQL Server, and the Company already has .NET developers on hand, a new product built on Linux with MongoDB wouldn’t be a rational choice.  Knowledge reinvestment from existing human resources is a high priority consideration.

In the Cloud

Depending on the volume of your data and the geographic disposition of your facilities, teams and data access points, cloud solutions might be ideal. Moving operations to the cloud has gained ground among healthcare-related companies, largely due to its collaborative capabilities and lower I.T. costs. With research teams increasingly spread out around the world, pharma is leveraging the cloud to improve and speed up drug discovery and other remote collaboration projects.

Compliant cloud solutions for GMP or other regulated/validated systems (usually with PaaS providers) have emerged and typically require an Enterprise agreement in order to get the proper contracts in place. Cloud solutions offer huge cost saving benefits for ongoing IT support and scalability.

The Enterprise Software Option

Enterprise solutions can provide a unifying framework to help reduce the complexities of management. Much depends on a Company’s willingness to compromise on relevant workflows and options present in an enterprise system.

The skills and time of your organization’s team are your most expensive and hardest-to-obtain resources. Selecting an architecture which is aligned with what your staff can both use and maintain is key.

Enterprise software is sometimes expensive for good reason. Depending on your needs, it may only seem costly when in fact it can offer important long-term benefits, such as helping you achieve budgetary stability & predictability.

There is a very high cost to free solutions, and few offer a long-term well-supported platform with extensibility and flexibility to adapt to how you operate.

Validation

In the pharma space, validation is critical. A system requiring validation consists not just of the custom code, but the whole stack. For this reason, it is important to select framework vendors and hosting providers who can support that objective.

Data Security

Data security must be top-of-mind when choosing the right software development architecture for pharma or another healthcare-related field. Ongoing long-term security support from the source vendor must be a pre-requisite when selecting software.

What Really Matters When Selecting Software Architecture

Here’s what really matters when it comes to software development: the selected underlying technology is not nearly as important as how it is applied.

Good software architecture, built to interface with your other existing systems (both custom and off-the-shelf), makes it easier for your team to do their jobs. It creates efficiencies, it improves & simplifies compliance, and it empowers your organization’s decision-making.

Proper software and infrastructure stack selection is essential. There are a number of variables involved in the final selection (e.g., existing systems & platforms, overall software development objectives, long-term scalability), and the choice can impact everything from operating efficiencies and R&D collaboration to key business decision-making and even patient health.