Six Ways Data Visualization Tools Improve Biotech/Pharma R&D Outcomes

Six Ways Data Visualization Tools Improve Biotech/Pharma R&D Outcomes

Benefits of investing in advanced visualization innovations.

Life science innovators have increasingly realized the value of visualization to drive real insights in data analytics. Exploring the capabilities of these cloud-based tools beyond simple presentation can inspire groundbreaking developments for emerging biotech and pharmaceutical start-ups. As noted in a 2021 article in Frontiers in Bioinformatics, every major development in genomics has come in the wake of a  new invention within data computation and statistics. These are six strategic benefits of investing in data visualization as a leader in this innovative area.

Enhanced data processing and comprehension

Cloud-based information analytics provide a powerful tool for visual storytelling that illuminates the impact of your organization’s research and development efforts. For example, your scientists can access, gather, and display media from multiple platforms, databases, and sources through a single dashboard. 

Cloud-based data analysis allows deeper interaction, including the ability to revise visualizations to highlight various aspects of the narrative. You can even combine multiple complex graphics to create sophisticated views. 

Advanced data tools also accelerate discovery by reducing noisy data volume to highlight relevant patterns and connections. This benefits biopharma researchers who need to correlate market opportunities with possible drug treatments, diseases with causative agents, and chemicals with intended and unintended effects. 

Simplified, stress-free sharing and collaboration

Most data visualization software tools come in a so-called container, a plug-and-play platform that includes everything you need to run the program. Since the necessary systems in the container have already been configured to work with one another, your team won’t face the challenges that arise when various components don’t interact as intended. With this structure, researchers who don’t share the same physical space can view and comment on the same 3D data visualization in a real-time virtual environment.

Faster, more effective clinical trials

Data visualization also facilitates greater speed and value among your organization’s clinical trial programs. With these tools, your teams can:

  • Monitor key performance indicators at a glance on a customizable data dashboard
  • Instantly summarize results in a reader-friendly format
  • See a real-time overview of the trial’s progress to date
  • Track potential risks for early identification of concerning developments 
  • Iterate immediately to create new reports as needed to support updated findings

A clear competitive landscape

Adolescent biopharma companies need to understand their market rivals to have a hope of competing in the crowded drug patent landscape. With data visualization, your leaders can clarify product pipelines and intellectual property information across your pharmaceutical or biotech environment. These tools draw indelible lines between different scientists, drug classifications, mergers and acquisitions, and patent activity so you can see exactly where your firm stands and take advantage of gaps in the market.

Space beyond size limits

You can see drug data and other research visualizations in 3D space outside the size of your team’s screens. With such an expansive view, data visualization lets researchers completely immerse themselves in the data from a 360-degree perspective to avoid missing connections that could change the direction of their efforts. As a result, you can have the confidence that comes from clear, transparent data representation. At the same time, you can simplify and reduce the size of large data sets when needed to visualize them in an understandable way.

In a 2017 example reported by Biopharma Trend, Novartis used virtual reality to create a three-dimensional exploration of small molecules and targets for protein. In the 3D VR landscape, the company’s scientists viewed and analyzed interactions between these structures.

Comprehensive knowledge graphs

Many growing companies in pharmaceutical and biotech research rely on global teams at international sites in various time zones. By building knowledge graphs through data visualization, scientists can break down data access silos for integrated analysis, management, and search. This approach helps reduce errors, illuminate understanding gaps, and prevent repeated efforts.

If data visualization has shifted from an afterthought to a concept at the forefront of your biopharma company’s future, consider outsourcing this type of tech to true experts. An experienced team can create the tools you need to innovate in the competitive pharmaceutical and biotech IT space.




How to Tell if Your Computing Partner is Adding Value: A Service Model That Fits Research Goals

How to Tell if Your Computing Partner is Actually Adding Value to Your Research Process: Service Model

Part Four in a Five-Part Series for Life Sciences Researchers and IT Professionals  

If 2020 and 2021 proved anything to us, it’s that change is inevitable and often comes when we least expect it. The pandemic shifted the way virtually every company operates. While change can feel unnerving, it is important to make changes that better your work and your company. 

The Life Sciences industry is no different. Whether your company shifted drastically in response to the pandemic or not at all, it’s still important to take a look at your business or team operations to see in what areas you can continue to improve. For teams conducting drug discovery,  development or even pre-clinical workce such area that can often be improved is your external scientific computing support. 

We’ve highlighted several items for teams to take into consideration when evaluating their current partners. So far in our five  part blog series we’ve taken a look at following three considerations:


  • #1 – Life Science Specialization and Mastery
  • #2 –  Bridging the Gap Between Science and IT
  • #3 – A High Level of Adaptability


In this installment, we take a deeper look at Consideration #4: A Service Model that Fits Research Goals. 


Consideration #4: A Service Model that Fits Research Goals

It’s no surprise that every company is likely to have different research goals. A one size fits all approach is not an acceptable strategy. Do you know what sets your current partner apart from their competitors? Do they offer a commodity service, or is there a real and tangible value in what they deliver, and how they deliver it? Your partner’s service model can make an enormous difference in the value you get from their expertise. 

There are two models that life science organizations typically use; computing partners operating under a staff augmentation model or a Managed Service providers model. It is no surprise that these two models work in very different ways and in turn offer very different results for the companies that use them. 

IT staff augmentation may allow your organization to scale its IT team up or down based on current needs. This can help scientific IT teams retain project control and get short-term IT support on an as-needed basis, but it often requires the researchers to obtain, deploy and manage human resources on their own. This can be time consuming and tedious for the organization.  Often, outcomes related to staff augmentation services are guided by rigid, standardized service level agreements that prioritize process over results. Unlike in many other industries, these standards can be limiting in the dynamic world of scientific research and discovery, preventing teams from appropriately adapting their scope as project needs and goals change.  

Managed IT services, on the other hand, offer a more balanced approach between operations and project management. This allows research teams to save time they would otherwise spend managing IT processes, and it enables the delivery of specialized services tailored to your team’s specific needs. And, unlike the staff augmentation model that provides an individual resource to “fill a seat,” a managed services model is based on a team approach.  Often a diverse team of experts with a range of specialization work collaboratively to find a solution to a single issue.  This shifts the focus to prioritize outcomes and enables for a fluid and nimple approach, in a cost and time efficient manner. The end result is better Outcomes for all. 


How Your Computing Partner’s Service Model Influences Research Success

Meeting your research goals requires efficiency and expertise and when comparing the staff augmentation model versus the managed IT model, you can see the clear differences. When choosing the managed IT model you’re going to be offered a level of continuity and efficiency that the staff augmentation model can not compete with. When your organization is pressed for time and resources, having a managed IT model allows you to focus and expedite your work, ultimately accelerating the journey toward  your discovery and development goals.

When you work through evaluating your current partners, be sure to consider whether they operate with a service model that fits your research and development needs and goals. 

And stay tuned for the final installment of this series on how to evaluate your external scientific computing resources, in which we’ll discuss our last but certainly not least important consideration: Dedication and Accountability.

Part 3: How to Tell if Your Computing Partner is Adding Value – Adaptability

How to Tell if Your Computing Partner is Actually Adding Value to Your Research Process: Adaptability

Part Three in a Five Series for Life Sciences Researchers and IT Professionals  

 If you’re still not sure you’ve sourced the ideal scientific computing partner to help your team realize it’s research compute goals, here’s another quality to evaluate: adaptability. 

By this point, we hope you’ve already read the first two installments in this five part series on how to tell if your partner is adding value (if not, start with #1 – Life Sciences Specialization and Mastery and #2 – The Ability to Bridge the Gap Between Science and IT). Here, we will take a look at the importance of adaptability, and why that quality matters to R&D teams (and their IT counterparts). 

Consideration #3: High Level of Adaptability

In today’s world adaptability is a highly sought after skill. Whether it’s in your personal or professional life, the ability to shift and adjust to change is vital. 

In the context of scientific computing, adaptability is less about survival and more about the ability to see things from different perspectives. In a research environment, though the end goal often remains, the process or needs associated with achieving that goal, can often be fluid.  Being able to or evolve to reach new or shifting goals with precision and performance is a skill not everyone one—or every team—possesses. 

In a research environment, scientists are not always able to predict the results their work will yield, thus needing to work hand in hand with a partner that is able to adjust when necessary. Whether you and your team need a few new resources or a new strategy entirely, a good computing partner will be able to adapt to your needs!

There are even more benefits to having a highly adaptable partner including increased level of performance, smoother transition from one project to the next, and more efficiency in your company’s research. A great scientific computing partner should be able to meet these needs using scalable IT architecture and a flexible service model. If your partner’s service model is too rigid, it may indicate they lack the expertise to readily provide dynamic solutions.

A Better Model for Your Dynamic Needs

Rigid service models may be the norm in many industries, but it does not predict success in the world of life science research. And too often, those partners that fall into the “good enough” category (as we mentioned above) follow these strict SLAs that don’t account for nuance or research environments.  

A partner that is not adaptable will inevitably be incapable of keeping up with the demands of shifting research. Choose a scientific computing partner whose services align with your scientific initiatives and deliver robust, consistent results. Prepare for the next year’s challenges by reaching out to a partner that offers highly specialized scientific computing services to life science research organizations like yours.

As you take all of these points into account, be sure to come back for consideration #4: A Service Model that Fits Research goals. 


Part 2: How to Tell if Your Computing Partner is Actually Adding Value to Your Research Process – Bridging the Gap Between Science and IT

Part Two in a Five-Part Series for Life Sciences Researchers and IT Professionals

As you continue to evaluate your strategy for 2022 and beyond, it’s important to ensure all facets of your compute environment are optimized— including the partners you hire to support it. 

Sometimes companies settle for working with partners that are just “good enough,” but in today’s competitive environment, that type of thinking can break you.  What you really need to move the needle is a scientific computing partner who understands both Science and IT

In part two of this five-part blog series on what you should be measuring your current providers against, we’ll examine how to tell if your external IT partner has the chops to meet the high demands of science, while balancing the needs of IT. If you haven’t read our first post, Evaluation Consideration #1: Life Science Specialization and Mastery, you can jump over there, first.  

Evaluation Consideration #2: Bridging the Gap Between Science and IT 

While there are a vast number of IT partners available, it’s important to find someone that has a deep understanding of the scientific industry and community. It can be invaluable to work with a specialized IT group, considering being an expert in one or the other is not enough.  The computing consultant that works with clients in varying industries may not have the best combination of knowledge and experience to drive the results you’re looking for.  

Your computing partner should have a vast understanding of how your research drives value for your stakeholders. Their ability to leverage opportunities and implement IT infrastructure that meet scientific goals, is vital. Therefore, as stated in consideration #1: Life Science Specialization and Mastery, it’s vital that your IT partner have significant IT experience.  

This is an evaluation metric best captured during strategy meetings with your scientific computing lead. Take a moment to consider the IT infrastructure options that are presented to you. Do they use your existing scientific infrastructure as a foundation? Do they require IT skills that your research team has? 

These are important considerations because you may end up spending far more than necessary on IT infrastructure that goes underutilized. This will make it difficult for your life science research firm to work competitively towards new discoveries. 

The Opportunity Cost of Working with the Wrong Partner is High

Overspending on underutilized IT infrastructure draws valuable IT resources away from critical research initiatives. Missing opportunities to deploy scientific computing solutions in response to scientific needs negatively impacts research outcomes. 

Determining if your scientific computing partner is up to the task requires taking a closer look at the quality of expertise you receive. Utilize your strategy meetings to gain insight into the experience and capabilities of your current partners, and pay close attention to Evaluation Consideration #2: Bridging the Gap Between Science and IT.  Come back next week to read more about our next critical consideration in your computing partnership, having a High Level of Adaptability. 

Part 1: How to Tell if Your Computing Partner is Actually Adding Value to Your Research Process

A Five-Part Series for Life Sciences Researchers and IT Professionals

The New Year is upon us and for most, that’s a time to reaffirm organizational goals and priorities, then develop a roadmap to achieve them. For many enterprise and R&D IT teams, that includes working with external consultants and providers of specialized IT and scientific computing services. 

But much has changed in the last year, and more change is coming in the next 12 months. Choosing the right partner is essential to the success of your research and, in the business where speed and performance are critical to your objectives, you don’t want to be the last to know when your partner isn’t working out quite as well as you had planned (and hoped). 

But what should you look for in a scientific computing partner?  

This blog series will outline five qualities that are essential to consider … and what you should be measuring your current providers against throughout the year to determine if they’re actually adding value to your research and processes.  

Evaluation Consideration #1: Life Science Specialization and Mastery

There are many different types of scientific computing consultants and many different types of organizations that rely on them. Life science researchers regularly perform incredibly demanding research tasks and need computing infrastructure that can support those needs in a flexible, scalable way.

A scientific computing consultant that works with a large number of clients in varied industries may not have the unique combination of knowledge and experience necessary to drive best-in-class results in the life sciences. 

Managing IT infrastructure for a commercial enterprise is very different from managing IT infrastructure for a life science research organization. Your computing partner should be able to provide valuable, highly specialized guidance that caters to research needs – not generic recommendations for technologies or workflows that are “good enough” for anyone to use.

In order to do this, your computing partner must be able to develop a coherent IT strategy for supporting research goals. Critically, partners should also understand what it takes to execute that strategy, and connect you with the resources you need to see it through.

Today’s Researchers Can’t Settle for “Good Enough”

In the past, the process of scientific discovery left a great deal of room for trial and error. In most cases, there was no alternative but to follow the intuition of scientific leaders, who could spend their entire career focused on solving a single scientific problem.

Today’s research organizations operate in a different environment. The wealth of scientific computing resources and the wide availability of emerging technologies like artificial intelligence (AI) and machine learning (ML) enable brand-new possibilities for scientific discovery.

Scientific research is increasingly becoming a multi-disciplinary process that requires researchers and data scientists to work together in new ways. Choosing the right scientific partner can unlock value for research firms and reduce time-to-discovery significantly.

Best-in-class scientific computing partnerships enable researchers to:

  • Predict the most promising paths to scientific discovery and focus research on the avenues most likely to lead to positive outcomes.
  • Perform scientific computing on scalable, cloud-enabled infrastructure without overpaying for services they don’t use.
  • Automate time-consuming research tasks and dedicate more time and resources to high-impact, strategic initiatives.
  • Maintain compliance with local and national regulations without having to compromise on research goals to do so.

If your scientific computing partner is one step ahead of the competition, these capabilities will enable your researchers to make new discoveries faster and more efficiently than ever before.

But finding out whether your scientific computing partner is up to the task requires taking a closer look at the quality of expertise you receive. Pay close attention to Evaluation Consideration #1: Life Science Specialization and Mastery and come back next week to read more about our next critical consideration in your computing partnership, the Ability to Bridge the Gap Between Science and IT.


Bio-Pharmaceutical Companies Need Computing Support from a Specialized Bio-IT Experts

Drug research and development is one of the most complex processes in today’s world.

Not only must researchers gain familiarity with complex scientific equipment, but they must also optimize their entire laboratory infrastructure to make successful discoveries. Naturally, they must rely on IT technologies and support to do this.

But the kinds of IT problems that biopharma researchers have are very different than the kinds workers in other industries face. Their own support teams cannot fully dedicate the resources that their clients need, or deliver the right level of expertise necessary to prompt research executives to explore outsourced solutions.

Not all for-hire solutions are created equal. You can’t plug a typical enterprise IT help desk into the research environment. The traditional, ticket-based support structure forces researchers to wait in multiple steps before their request is escalated to an appropriately qualified support member. The typical outsourced IT support help desk simply doesn’t have the expertise necessary to solve many of these problems in a timely, scalable manner.

Instead, biopharma researchers need support from teams of computing specialists stacked with experts in a wide range of disciplines unique to the drug discovery process, including career scientists who understand the obstacles that IT infrastructure can solve in the laboratory environment. Support technicians who have expertise with technologies and equipment found in biopharmaceutical laboratories are far more valuable than non-specialized tech talent.

Why Traditional IT Helpdesk Support Comes Up Short

Most large IT staffing and consulting firms offer IT support driven by service-level agreements (SLAs). These agreements may stipulate that incoming support calls will be handled within a certain time frame. They may penalize the provider for not being able to handle certain requests on time.

But these SLAs are generally measured in ways that favor the service provider. For example, there is a fine difference between resolving a problem in 10 minutes and “responding” to a problem in the same time frame.

To be fair, the IT professionals who operate these support centers are certainly qualified to handle routine enterprise IT needs. Like every other modern organization, biopharma laboratories need their network support and generic hardware/software problems addressed. But in a research environment, the scope and complexity of these problems can quickly expand beyond an enterprise-IT help desk’s ability to help.

Unprepared IT support technicians can even cause harm to research objectives. If the support team cannot address problems in a timely or adequately skilled manner, bio-IT teams may fall short of their own objectives. This can create a cascading domino-effect that requires bio-pharma executives to revisit carefully laid plans, and explain delays to stakeholders.

RCH Solutions’ Scientific IT Support Offers Specialized Service

Research scientists and bio-IT teams need specialized scientific support for their IT infrastructure. Having a scalable team of scientific computing specialists and career scientists available on-demand is a competitive advantage in the world of biopharmaceutical research.

Not only can a specialized support team meet the full range of highly technical scientific computing needs, but these professionals have hands-on experience working in scientific domains. This makes them a valuable supplement for the strategy, implementation, and optimization of emerging technologies. Laboratories can access and deploy the latest artificial intelligence, deep learning, and machine learning technologies in a safe, scalable way, while leveraging high-performance computing (HPC) efficiently.

RCH Solutions takes bio-pharmaceutical support specialization one step further than the rest of the bio-IT industry. We bridge the gap that research organizations typically experience between their IT and research teams. This allows our clients to take a more informed approach to their equipment acquisitions and infrastructure decisions.

Our support team members have hands-on experience in the following scientific domains:

Bioinformatics & Genomics

Computational Chemistry

Computational Fluid Dynamics

Crystallography/Cryo EM

Data Science & Analytics

Deep & Machine Learning



Molecular Dynamics

Numerical Analytics


Precision Medicine 


Quantum Chemistry

Structural Biology


Make RCH Solutions Your Bio-IT Partner

As a dedicated IT advisor serving bio-pharmaceutical companies at every stage of drug research and development, we have the knowledge and expertise you need to optimize your IT infrastructure. Our scientific computing experts go further than simply solving network issues – we find ways to streamline the way your laboratory generates and processes data throughout the network.

Our informed approach results in improved collaboration, a greater degree of trust between teams, and better research outcomes for the organization. Learn more about how specialized research IT expertise can make the difference in your drug discovery efforts.

RCH Solutions is a global provider of computational science expertise, helping Life Sciences and Healthcare firms of all sizes clear the path to discovery for nearly 30 years. If you’re interesting in learning how RCH can support your goals, get in touch with us here. 

Optimize Your Lab: Deploy Specialized Scientific Instrumentation Support

Biotech and pharmaceutical laboratories are complex machines responsible for undertaking some of life’s most challenging problems.

Early drug discovery is an incredibly vast and complex discipline, and it demands research scientists use an equally vast and complex range of applications and technologies to achieve results. From purpose-built research equipment to specialty software,  and cutting-edge research IT devices and architecture, today’s scientists rely on innovation more than ever to achieve tomorrow’s groundbreaking discoveries.

Usually, equipment manufacturers provide implementation and ongoing support to research laboratories that purchase their products. This is helpful when research scientists and data teams need to answer pertinent, narrow-scoped questions about set-up, service, and maintenance.

However, manufacturer support teams simply don’t have the scope or the resources to offer a holistic view of the laboratory itself. It’s not enough to get the equipment running properly – it must also run in the most efficient way possible, integrated with every other laboratory asset, in order to deliver the results you need. Successful research does not rely on any one device or process alone.

Why Manufacturer Support Isn’t Sufficient 

While manufacturer support teams play a vital technical role in helping Bio-IT teams deploy and integrate new technologies, they can’t play an advisory role that helps advance the lab’s overall drug discovery mission. This is true for a few reasons:

It Is Outside Their Scope. The core value that a manufacturer offers is just that – manufacturing. Every hour their support team might spend learning how your laboratory works and offering advice on how to improve its operations is an hour not spent delivering on their core value, which is developing and deploying the equipment they manufacture.

They Don’t Always Have the Expertise. While nobody contests the manufacturer’s technical expertise when it comes to their equipment, it’s unlikely that their support team has the knowledge needed to understand every single one of your lab’s drug discovery processes. Identifying optimal implementation simply isn’t possible without world-class, holistic expertise.

Data Bottlenecks Require Data-Driven Solutions. It makes sense to solve physical research bottlenecks with physical solutions – if DNA sequencing tasks are too slow, a new SMRT sequencer can solve the problem. But when data accessibility and integration are the culprits, you need to optimize your data infrastructure to produce results. New equipment won’t do.

Manufacturers Have a Predictable Bias. Ultimately, selling equipment is every manufacturers’ number-one priority. If you can improve research outcomes either by cheaply reorganizing your data infrastructure or by purchasing expensive new equipment, your manufacturer will recommend the expensive purchase first.

Entrust Lab Acquisitions to Expert Consultants 

In a data-heavy field like early drug discovery, optimizing the way information flows throughout your laboratory is critical. Research computing is an essential part of the processes that enable new drug discoveries to make it to market, and successful implementation requires a highly specialized set of skills.

A reputable third-party research IT advisor or service provider can help your research and data teams solve file compatibility issues, optimize interdepartmental data-flow, and establish efficient porting and networking solutions. These can transform the way your lab communicates on a daily basis, making critical data available to the scientists who need it the moment they need it.

Partnering with a data-oriented research consultancy for Bio-IT teams can grant your laboratory access to objective equipment analyses. You no longer have to take manufacturers at their word – you can drive the value of every acquisition by getting a second opinion from an expert research consultant.

Choose RCH Solutions As Your Specialized Instrumentation Support Provider

We are a team of professional biotech and pharmaceutical research experts dedicated to helping research labs optimize their approach to early drug discovery. We employ research application specialists, data scientists, and IT experts specifically to help research labs improve their research processes while spending less money.

Our specialized, service-based model treats the research laboratory as a holistic entity rather than the sum of various parts. This approach allows us to identify inefficiencies that manufacturer support teams often miss and to help researchers move closer to their goals. We help scientists choose the best tools for the job at hand and help them optimize the environment in which those tools are used.

RCH Solutions is a global provider of computational science expertise, helping Life Sciences and Healthcare firms of all sizes clear the path to discovery for nearly 30 years. If you’re interesting in learning how RCH can support your goals, get in touch with us here.