1 BUILDING AN IT INFRASTRUCTURE FOR BIOTECHS – A NEW WAY OF THINKING

Building an IT Infrastructure for Biotechs – A New Way of Thinking

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2 BUILDING AN IT INFRASTRUCTURE FOR BIOTECHS – A NEW WAY OF THINKING

Here is how the “start-up” story used to go. Like those that have come to define Silicon Valley, high-tech companies were started in garages and basements with money from a parent’s retirement account and everything else the likely college-aged founders could beg, borrow, and (ideally) not steal.

Biotech companies, on the other hand, traditionally required well-connected founders, large, expensive labs with fancy six-digit-dollar equipment, enabled by funding from venture capitalists well-established in the space.

But times have changed, and today, that story is much different.

The table stakes for “playing” in the biotech start-up scene have come down significantly from what they used to be, where it took anywhere up to $10 million just to get started, according to Jared Friedman, a partner at Y Combinator.

“Just like new infrastructure brought down

the cost to start a tech company, new infrastructure has brought down the cost of doing biology dramatically. Today, founders

can make real progress proving a concept for a

biotech company for much less, often as little

as $100K.”

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Technical innovations have invigorated the Life Science biotech start-up scene. Access to data, faster and cheaper than ever before, has opened doors to exploration and discovery at a staggering pace. Remember, in 2003, when the cost of sequencing a genome came in at a cool $2.7 billion? Now, the cost is only a few hundred dollars.

Powerful techniques, e.g., manipulating genomes with CRISR, once developed, can now be easily leveraged for many applications.

Miniaturization, e.g., advances in disciplines such as microfluidics, multiplexing, and ultra-high density plate formats, allows researchers to collect massive amounts of data from ever smaller samples.

And evolving business models and process innovations—such as virtualization of the team ecosystem, increased outsourcing by way of Contract Research Organizations (CRO), wet-lab accelerators and shared lab spaces that come equipped with whatever fancy instrumentation needed—have also significantly lowered the barriers to entry in the biotech sector.

IT lies at the core of many of the advancements driving the biotech trend. Cloud-based data storage and analysis. Machine learning algorithms that can analyze big data quickly. And remote collaboration tools that enable virtual teams worldwide to work together, share data, and pursue discovery faster and more efficiently than ever before, have emerged as critical and defining characteristics of success.

Together, these innovations allow biotech start-ups to be leaner, with smaller upfront costs for lab space, equipment, and scientists, and, ultimately, more competitive in the very fast-paced Life Sciences environment.

Information technology has moved

from the periphery of the biotech

world to the center.

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Building a Best-In-Class Biotech IT InfrastructureQuick innovation cycles also mean that today’s biotech entrepreneurs need to be agile and flexible, and adapt quickly while avoiding spending on technology that might be outdated tomorrow.

It also dramatically changes how and where biotech founders develop their core expertise and invest their money. While the newest flow cytometer and the Ph.D. to run it might have been a competitive advantage ten years ago, today, your Bio-IT infrastructure contributes to whether or not your biotech business will succeed or fail.

Information technology has moved from the periphery of the biotech world to the center. Biotech entrepreneurs have to dedicate significant resources and executive attention early in the life of their company toward developing a Bio-IT architecture and system that will support them during times of rapid growth and constant changes.

5 BUILDING AN IT INFRASTRUCTURE FOR BIOTECHS – A NEW WAY OF THINKING

Seven Important Characteristics of Biotech IT SystemsNow that we have established how much Life Sciences and biopharma companies rely on their IT infrastructure and how mission-critical a well-planned and expertly deployed Bio-IT system is, this section will examine the characteristics of those systems, with the specific requirements of early discovery and development in mind.

Secure

Security is an overarching concern for the life science industry. Viruses, ransomware, and hackers all pose real threats to your system, and an increasing number of internet-connected endpoints, e.g., in manufacturing, make your systems susceptible to attacks. Loss of valuable proprietary information is just one of the problems. Companies dealing with sensitive patient information are prime targets for hackers in an age where medical information is considered ten times more valuable than credit card information on the black market.

Accessible

Mobile devices, virtual teams, and remote service providers all need access to your system and data. While virtualization can lower cost and increase productivity, it also opens your system to additional threats requiring you to develop a measured plan that keeps the system accessible without compromising security.

Reliable

Given the increasing dependence of biotech companies on their Bio-IT systems, the reliability and continuity of these systems becomes a significant concern. Even “just” losing Internet connection can have a dramatic impact on your operations, from shutting down your Internet-of-things based manufacturing to interrupting your ML algorithm in the middle of crunching through a data set and shutting down the platform your team uses to communicate with service providers and remote colleagues. Avoiding downtime of Bio-IT systems by building duplicated systems and putting contingency and restoration plans in place becomes vitally important.

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Scalable

An additional piece of equipment, a new customer, or partner can result in other large data sets that need to be stored and analyzed. The ability to quickly scale up can mean the difference between being able to act upon an opportunity—or not. Once a task is finished, scaling down to avoid excess capacity is similarly desirable. The larger the fluctuations in the amount of data you have to deal with, the more critical it is to build your Bio-IT ecosystem so it can be rescaled on short-notice.

Fast

Computing speed can’t become the bottleneck when analyzing a large set of data that helps you hone in on the biomarkers to identify patients most likely to benefit from your new drug or all the data your new high-content screening platform generates. Your Bio-IT system needs to be designed with your current and future requirements for computing speed in mind.

Flexible

Flexibility is a crucial requirement for life science and healthcare companies that deal with structured and unstructured data from diverse sources. Genomics, proteomics, and a whole slew of other “omics” data, image-based data, raw data from instruments such as mass specs or screening platforms, questionnaires, or noisy real-world data are just a few examples. These disparate and changing data types require a flexible infrastructure that can cope with diversity.

Supported

Finally, the best IT system is only worth the investment if it is up and running, well-maintained, and users, including non-expert users, are trained and supported through all of their unique use-cases.

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Balancing Scientific Discovery and Business Needs – an IT ChallengeA biotech’s Bio-IT infrastructure can significantly alter the company’s trajectory and momentum, so it’s essential to get that piece of the puzzle right. Doing so helps advance the company’s initiatives, makes the organization more attractive to talented employees, instills confidence in investors, and demonstrates to a potential buyer that the biotech can deliver results outside of the Wild West.

But “getting it right” is not always easy.

Leaders who once lived R&D may find themselves removed from that work as they attend to all the realities of running a business, while those who were hired to support a particular effort, may be thrust into new roles simply because there is a need to get something done. And fast.

It’s at this point where biotech leaders have the opportunity to create an infrastructure that will stretch and respond to their evolving needs. By focusing their time and efforts on tasks that are “core” to their business success and outsourcing other “context” tasks that, while important, are not directly related to their scientific mission or purpose, they create real differentiation from the competition.

Core vs. Context Tasks - When To Bring in a Specialist to Help Shoulder the LoadMaximizing success as a biotech start-up, for most, begins with a core goal: Improve patient outcomes through novel discovery.

From there, teams, usually small in size, dedicate themselves to science. Hone their discovery. Secure funding. Hire a few exceptional people. Demonstrate results through pristine data and analytics. Secure even more funding. Hire a few more great people until they are ultimately allowed to market their great innovation.

The reality is, however, the path is not nearly that linear. And maintaining the core focus that inspired discovery is not always easy, particularly as science becomes a business and the business’ needs compete for resources.

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Outsourcing context tasks, such as payroll, accounting, HR, and even IT, are often the first places biotech entrepreneurs look to gain back time. There are many reputable agencies or services that can perform these tasks with relative ease, speed, and cost.

But grouping IT—a function that is so deeply woven within the fabric of successful biotechs—with other context tasks, maybe a mistake. Here’s why:

The IT competencies required for running a business are very different from those needed for accelerating science.

Enterprise IT functions—like desktop and network support, web security, employee hardware, and software needs—while important, are less nuanced and can be executed more rigidly.

Bio-IT functions—like high-performance computing, Cloud workflows, data management, scientific application, and instrumentation support—demand deep and specialized experience and requires that a team of multi-discipline specialists, including cross-functional IT experts, data scientists, research software specialists, and Ph.D’s, work together as a responsive task force to grow the long-term viability of a novel concept.

It’s for this reason that Bio-IT has emerged as a wholly separate function from enterprise IT, and must be treated as a core capability in a growing biotech.

MANAGED BIOTECH SERVICESGeneralist vs. SpecialistENTERPTISE IT

Staff AugmentationBIO-IT

Managed ServicesA temporary, single-focus,

limited, rigid SOW

Single-skill, individual-based

Traditional organizations and enterprises who seek a quick-fix and

expect an indefinite outcome

Service-level agreement model, handles well-defined, tactical and

routine tasks

A minimal-impact solution that serves to solve a specific problem with

a vendor-type relationship

A full-service, comprehensive and scalable solution

Multi-skill, team-based extensive team in place

Progressive organizations who seek a trusted advisor in a fluid role with well-defined objectives.

Dedicated specialists work on requirements-based projects based on custom levels of complexitiy

A transformative solution that positively impacts the business and allows for greater focus on science

SCOPE

SKILLS

WORKS FOR

DELIVERABLES

RESULTS

ENTERPRISE IT BIO-IT

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Bio-IT Roadmap and Implementation – You Don’t Have to Go it AloneMore than in many other industries, biotech companies rely on and benefit from well-architected information technology processes to support everything from R&D to manufacturing and collaboration. In this new world of flexible, nimble, more “high-tech-like” biotech companies, Bio-IT is now sharing center stage with traditional core activities such as biological research.

For senior management, this means more executive attention has to be paid to, and a larger share of expenses will have to be allocated to, information technology. That attention can’t wait until the company is mature, but is required from the start to ensure you build a Bio-IT infrastructure that supports your company’s growth.

While this sounds daunting, there are experts available to help you with strategy, design, implementation, and ongoing support for your full-range of scientific computing needs. If you (or members of your team) find yourself asking these questions, it may be time to consider the value of support from a specialized Bio-IT partner.

“Who owns that?”

As you grow, it’s unavoidable that your focus will begin to shift. Though your role was once well-defined, managing the technical complexities of a growing Biotech requires that you—or your lean and mean team—are likely spending time on tasks that fall outside of your areas of expertise. Like scientists modifying Cloud workflows or enterprise IT personnel designing analytics frameworks. While the work needs to get done, is that model making the best use of everyone’s time? Probably not. The bottom line is, if you find yourself or members of your team taking on responsibilities that aren’t maximizing your biotech’s success, it’s time to reassess.

In this new world of flexible, nimble, more “high-tech-like” biotech companies, Bio-IT is now sharing center stage with traditional core activities such as biological research.

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“How do we scale to reach our next discovery milestone?”

While many view scalability as an action item for the future, the reality is, it may first warrant a review of the past. Some of us have come from Big Pharma, where equal access to resources and the need to find creative solutions to skirt restrictive policies and procedures led to operating outside the boundaries. But building-up your biotech is best accomplished when the proper Bio-IT framework is in place. That means a shared and well-adopted platform on which you can develop specialized applications and compute workflows, thoughtfully manage data, and execute through individuals experienced in and accountable for the right outcomes. Remember, there’s no better time than now to implement best practices.

“How do we get a better handle on our data?”

When data is the most critical asset of the company, aside from the people in the organization and the partners you choose, the demand to better manage (e.g., locate, store, retrieve, and share) data grows as you do.

“How can we accomplish all that we need to?”

There comes a time in every emerging company’s life cycle when there are simply not enough hours in the day to accomplish all that is needed. The upside is that it’s a sign of progress. But the downside is that it can temper productivity and steer outcomes in the wrong direction. Without the right infrastructure, technology, workflows, and, most importantly, the roles to execute science properly, the fail-fast mindset can feel more like a failure.

“Is there a better way to do this?”

The short answer is, typically, yes. In an industry where disruption is the goal (a better drug, a more targeted diagnostic tool, or a more personalized therapy), being unable to leverage disruption within your own company to yield better outcomes puts you at a disadvantage. Assessing and reassessing your processes and resources to make sure time—and expertise—are being spent where it matters most, is an easy first step down the right path.

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About RCH SolutionsFor more than three decades, RCH Solutions has provided specialty computing advisory and managed services exclusively within the Life Sciences. Find out how RCH can support your next scientific computing initiative.

rchsolutions.com | discover@rchsolutions.com

In the industry of innovation, putting your business in the best position to succeed requires focus, attention, and the willingness to ask yourself and your team what you need to go to get to the next level.

If you’re unsure of what those questions are, perhaps the question you should be asking yourself is, “Who can help?”