Top 4 Takeaways from LSPA’s Life Science Futures Conference

Last week, I had the privilege of attending the Life Sciences Futures Event, hosted by the Life Sciences Pennsylvania Association (LSPA). And as a specialized scientific computing provider for Life Sciences teams in R&D, pre-clinical, clinical, and through to commercialization, attending the Life Science Futures Conference last week was an important reminder of the “why” behind what we do.

Sure, we help Life Sciences organizations, both big (enterprise) and small (startup and midsize) accelerate the discovery and development of their next scientific breakthrough with our specialized Bio-IT services, which is critical, but it’s even more significant than that. And when you take a step back from the hustle and bustle of getting to and from each session, between networking and important meetings across the two days, you realize that every person in the building plays a critical role, as a collective ecosystem, towards the improvement of human health, patient outcomes and the overall well-being of individuals worldwide.

Now that’s a powerful “why” I can get behind. And one that brought like-minded industry leaders, Biotechs, Pharmas, researchers, medical professionals, innovators, and service providers across Pennsylvania together for this great event.

From inspiring and top-notch opening speakers in Olympian Scott Hamilton and David Fajgenbaum, MD, MBA, MSc, to expert-led discussions on the state of the industry, AI and innovation in the LifeSciences, and the unique journey and experiences of startups — and more – here are my top 4 takeaways from the event:

Startups are Relentless – And for Good Reason:

Startups in the Life Sciences are a testament to relentless determination. Fueled by a passion to improve human health and well-being, these innovative companies are on a challenging journey where the stakes are high, but the rewards are profound. They push the boundaries of scientific knowledge, pursuing breakthroughs in Biopharma. With often incredibly lean teams, they confront obstacles, navigate regulatory complexities, and persevere through countless setbacks. This relentless spirit makes them pioneers in an industry that demands nothing less than uncompromising commitment to innovation and progress. And this was evident in the many reverse pitch presentations that took place across the two days.

Innovation is Thriving – in PA and Beyond:

It’s no secret that innovation drives the Life Sciences industry. And the Life Science Futures conference, and the speakers, panelists and reverse pitch teams truly showcased the remarkable pace of innovation happening across the PA Life Sciences scene – and beyond. From groundbreaking research occurring within startup, emerging, and enterprise teams, to cutting-edge technologies being developed as we speak, and the unique and purpose-built places that exist for these Life Sciences teams to call home—it’s evident that we’re collectively pushing boundaries, and leveraging strategic partnerships, in many forms, to drive outcomes.

Interdisciplinary Collaboration is Essential – And More Important Than Ever

Life Sciences companies continue to realize the benefits of collaboration. And collaboration that is interdisciplinary might just be the secret sauce. Whether it’s partnering with other organizations, academic institutions, big pharma, startups, or similar, it’s hard to argue that collaboration—from diverse vantage points—fosters innovation. The conference showcased numerous successful partnerships that have led to breakthroughs in drug discovery and development, fostering a dynamic ecosystem that can truly accelerate science. For us, this emphasizes the importance of offering tailored, specialized, flexible, and integrated Bio-IT solutions from cross-functional teams that can truly bridge the gap between science and IT.

Data is the Currency of Life Sciences and Innovation:

The value of data in the Life Sciences cannot be overstated, and this was evident throughout nearly all panel discussions and presentations. Scientists and researchers are generating enormous amounts of data that needs to be FAIR: findable, accessible, interoperable, and reusable. And data that’s effectively managed, is the difference maker in  R&D and development teams within the Life Sciences that succeed—or fail. Just like how the inspiring keynote, David Fajgenbaum, MD, MBA, MSc, and his team at Everycure are looking for new uses for existing drugs by identifying and evaluating all potential drug repurposing opportunities using existing data and AI. 

LSPA Futures Conference: Inspiring Action

Attending the Life Science Futures conference was a reminder of the remarkable work happening in the Life Sciences sector in PA, and the perhaps small, but critical role that specialized scientific computing service providers, like us, play in this important journey.

So, kudos to those I had the privilege to meet, and also those I didn’t, who are driving and supporting the incredible work and innovation happening throughout the PA Life Sciences ecosystem. 

And thanks for letting me tell you a little about what we do at RCH Solutions.

Molly Ellwood

Business Development Executive

mellwood@rchsolutions.com

Overcoming Operational Challenges with AI Drug Discovery

While computer-assisted drug discovery has been around for 50 years, the need for advanced computing tools has never been so crucial.  

Today, machine learning is proving invaluable in managing some of the intricacies of R&D and powering breakthroughs thanks to its ability to process millions of data points in mere seconds.

Of course, AI drug discovery and development tools have their own complex operational demands. Ensuring their integration, operation, and security requires high-performance computing and tools that help manage and make sense of massive data output.

Aligning Biochemistry, AI, and system efficiency

The process of creating and refining pharmaceuticals and biologics is becoming more complex, precise, and personalized, largely due to the robust toolkit of artificial intelligence. As a result, combining complex scientific disciplines, AI-aided tools, and expansive IT infrastructure has come to pose some interesting challenges.

Now, drug discovery and development teams require tools and AI that can:

• Optimize data and applicable storage and efficiently preprocess massive molecular datasets.
• Support high-throughput screening as it sifts through millions of molecular predictions.
• Enable rapid and accurate prediction of molecular attributes.
• Integrate large and diverse datasets from clinical trials, genomic insights, and chemical databases.
• Scale up as computational power as demands surge.

Challenges in Bio-IT for drug discovery and development

Drug discovery and development calls for a sophisticated toolset. The following challenges demonstrate the obstacles such tools must overcome.

• The magnitude and intricacy of the molecular datasets needed to tackle the challenges of drug discovery and development require more than storage solutions. These solutions must be tailored to the unique character of molecular structures.
• High-throughput screening (HTS)—a method that can rapidly test thousands to millions of compounds and identify those that may have a desired therapeutic effect—also requires immense processing power. Systems must be capable of handling immediate data feeds and performing fast, precise analytics.
• Predicting attributes for millions of molecules isn’t just about speed; it’s about accuracy and efficiency. As a result, the IT infrastructure must be equipped to handle these instantaneous computational needs, ensuring there are no delays in data processing, which could bottleneck the research process.
• The scalability issue extends far beyond capacity. Tackling this requires foresight and adaptability. Planning for future complexities in algorithms and computation means pharma teams need a robust and adaptive infrastructure.
• Integrating data into a holistic model poses significant challenges. Teams must find ways to synthesize clinical findings, genomic insights, and chemical information into a unified, coherent data model. This requires finding tech partners with expertise in AI-driven systems and data management strategies; these partners should also recognize and address the peculiarities of each domain, all while providing options for context-driven queries.

As we can see, high-level Bio-IT isn’t just an advantage; it’s a necessity. And it’s one that requires the right infrastructure and expertise from an experienced IT partner.

Mastering the Machine Learning Workflow

Bridging the nuances of drug discovery with the technicalities of artificial intelligence demands specialized knowledge, including: 

• Machine learning algorithms. Each drug discovery dataset has unique characteristics, and the AI model should mirror these idiosyncrasies. Initial testing in a sandbox environment ensures scalability and efficiency before amplification across larger datasets.
• Data preprocessing. High-quality data drives accurate predictions. Effective preprocessing ensures datasets are robust, balanced, capable of interpolating gaps, and free from redundancies. In the pharmaceutical realm, this is the bedrock of insightful machine-learning models.
• Distributed computing. When handling petabytes of data, traditional computational methods may falter. Enter distributed computing. Platforms like Apache Spark enable the distributed processing essential for the seamless analysis of massive datasets and drawing insights in record time.
• Hyperparameter tuning. For pharma machine learning models, tweaking hyperparameters is key to the best performance. The balancing act between trial-and-error, Bayesian optimization, and structured approaches like grid search can dramatically impact model efficiency.
• Feedback mechanisms. Machine learning thrives on feedback. The tighter the loop between model predictions and real-world validations, the sharper and more accurate the predictions become.
• Model validation. Ensuring a model’s robustness is critical. Cross-validation tools and techniques ensure that the model generalizes well without losing its specificity.
• Integration with existing Bio-IT systems. Interoperability is key. Whether through custom APIs, middleware solutions, or custom integrations, models must be seamlessly woven into the existing IT fabric.
• Continuous model training. The drug discovery landscape is ever-evolving. Models require a mechanism that constantly feeds new insights and allows them to evolve, adapt, and learn with every new dataset.

Without the right Bio-IT infrastructure and expertise, AI drug discovery cannot reach its full potential. Integrating algorithms, data processing, and computational methods is essential, but it’s their combined synergy that truly sparks groundbreaking discoveries.

Navigating Bio-IT in drug discovery

As the pharmaceutical industry advances, machine learning is guiding drug discovery and development to unprecedented heights through enabling the creation of sophisticated data models. 

By entrusting scientific computing strategies and execution to experts who understand the interplay between research, technology, and compliance, research teams can remain focused on their primary mission: groundbreaking discoveries.

Get in touch with our team if you’re ready to start a conversation about harnessing the full potential of Bio-IT for your drug discovery endeavors.

If You’re Not Doing These Five Things to Improve Research Outcomes, Start Now

Effective research and development programs are still one of the most significant investments of any biopharma. In fact, Seed Scientific estimates that the current global scientific research market is worth $76 billion, including $33.44 billion in the United States alone. Despite the incredible advancements in technology now aiding scientific discovery, it’s still difficult for many organizations to effectively bridge the gap between the business and IT, and fully leverage innovation to drive the most value out of their R&D product. 

If you’re in charge of your organization’s R&D IT efforts, following tried and true best practices may help. Start with these five strategies to help the business you’re supporting drive better research outcomes.

Tip #1: Practice Active Listening

Instead of jumping to a response when presented with a business challenge, start by listening to research teams and other stakeholders and learning more about their experiences and needs. The process of active listening, which involves asking questions to create a more comprehensive understanding of the issue at hand, can lead to new avenues of inspiration and help internal IT organizations better understand the challenges and opportunities before them. 

Tip #2: Plan Backwards 

Proper planning is a must for most scientific computing initiatives. But one particularly interesting method for accomplishing an important goal, such as moving workloads to the Cloud or optimizing your applications and workflows for global collaboration, is to start with a premortem. During this brainstorming session, team members and other stakeholders can predict possible challenges and other roadblocks and ideate viable solutions before any work begins. Research by Harvard Business Review shows this process can improve the identification of the underlying causes of issues by 30% and ultimately help drive better project and research outcomes.

Tip #3: Consider the Process, Not Just the Solution

Research scientists know all too well that discovering a viable solution is merely the beginning of a long journey to market. It serves R&D IT teams well to consider the same when developing and implementing platform solutions for business needs. Whether a system within a compute environment needs to be maintained, upgraded, or retired, R&D IT teams must prepare to adjust their approach based on the business’ goals, which may shift as a project progresses. Therefore, maintaining a flexible and agile approach throughout the project process is critical.  

Tip #4: Build a Specialized R&D IT Team 

Any member of an IT team working in support of the unique scientific computing needs of the business (as opposed to more common enterprise IT efforts) should possess both knowledge and experience in the specific tools, applications, and opportunities within scientific research and discovery. Moreover, they should have the skills to quickly identify and shift to the most important priorities as they evolve and adapt to new methods and initiatives that support improved research outcomes. If you don’t have these resources on staff, consider working with a specialized scientific computing partner to bridge this gap. 

Tip #5: Prepare for the Unexpected 

In research compute, it’s not enough to have a fall-back plan—you need a back-out plan as well. Being able to pivot quickly and respond appropriately to an unforeseen challenge or opportunity is mission-critical. Better yet, following best practices that mitigate risk and enable contingency planning from the start (like implementing an infrastructure-as-code protocol), can help the business you’re supporting avoid crippling delays in their research process. 

While this isn’t an exhaustive list, these five strategies provide an immediate blueprint to improve collaboration between R&D IT teams and the business, and support better research outcomes through smarter scientific computing. But if you’re looking for more support, RCH Solutions’ specialized Sci-T Managed Services could be the answer.  Learn more about his specialized service, here. 

Challenging times or shifting conditions, such as those brought about by the unprecedented global health crisis, highlight the need to ensure your team has the technology, workflows, and processes in place to continue to deliver innovation at a rapid pace, despite the hurdles.

For most regions in the U.S., life has been toppled in different ways following urgent stay-home orders put in place to flatten the curve and reduce the immediate impact of the spreading coronavirus. In ways largely unexpected a few weeks or a month ago, millions of employees now have to work from home and school their children digitally, and hospitals are facing an unprecedented number of patients in need of care.

While working from home is necessary at a time like this, it leaves critical employees away from secure buildings and far from IT teams who can keep their devices or information safe. In our industry of Life Sciences and Healthcare, this is a particularly troubling fact.  

Reasons to Prepare: Common Threats in the New Working Normal

Companies or enterprises, whether involved in crisis response and management or not, should be prepared to counter potential DDoS attacks, large scale phishing attempts, and even ransomware attacks that may increase as a result of new remote work standards. Hospitals, in particular, are at higher risk, so these enterprises need to go back to the basics, patching systems as soon as possible and not falling into the trap of – “we can’t afford that activity or downtime now.”

VPN connections, which have become a relatively common way for enterprises to provide their employees with secure connections, still present some risk if not properly deployed. As more and more employees are working from home, organizations are struggling to maintain network privacy and handle security issues. Also, because of bandwidth capacity issues, organizations may struggle to provide secure VPN connections for all of their remote employees. And, since not all employees understand how VPN works, they may engage in activities like streaming videos that drastically tax the bandwidth for all the users.

The increased use of online meetings, which has been a critical tool for many companies to enable collaboration among employees, also exposes vulnerabilities, as not all users understand the importance of creating—and attending—only password-protected events. 

Moreover, the IT Operations teams that are typically able to respond immediately to a security breach or threat thereof, when in the office, are now at risk of being hampered by poor connectivity. Things that previously involved 10 to 15 minutes window to resolution—whether a system outage or something serious of nature like an ongoing attack—may now involve double or even triple the time due to slower connections.  

Best Practices to Protect: Rules to Work By

The good news is that many of the tools that allow for secure remote work already exist, including some that offer VPN’s (example Cisco Anyconnect VPN, Zscalar Private Access), two-factor authentication, password managers, secure file transfer and other security features and tools.     

In addition, there are several best practices organizations should work by not only through times of crisis but also year-round for maximum protection and continuity:

1) Secure System Access

All employee logins, not only critical ones, should be protected by strong multi-factor authentication as quickly as possible. Single sign-on solutions  (SSO), such as Okta, can help users reduce the number of logins the users have to complete to go about their everyday work while protecting your critical data.  And for the most sensitive system access, encrypted VPN’s should be enforced as a requirement to log in.  Additionally, a companywide, one-time password reset cycle with a prefaced notice that a maximum secure password is now critical.

 2) Ensure Redundancy

It is essential to maintain service levels when data center or service failure occurs. To do so, move traffic to a different zone, region, or geographical area from the affected area, and keep core applications deployed to an N + 1 standard so, in the event of a failure, there is sufficient or adequate capacity to enable the load to be load-balanced to the remaining sites or geographical locations. 

 3) Safeguard Availability

Ensure critical systems are backed up locally as well as across multiple isolated locations or regions. Each location should be designed and engineered to operate independently and with high reliability. Create a system design that has highly resilient systems and should be well-architected to provide service availability.

 4) Maintain Detailed Business Continuity Plans

A good plan outlines measures to avoid and lessen environmental disruptions, not just what to do to recover from them and includes operational details about the steps to take to before, during, and after an event. The Business Continuity plan is supported by testing that includes simulations of different scenarios when a service is disrupted. It is important to document people and process performance during and after testing, corrective actions that need to be taken, and lessons learned with the aim of continuous improvement.

 5) Prepare For the Unlikely 

A pandemic, for example, is an important event-type for which all businesses should prepare. The events of the past months remind us why. Mitigation strategies include alternative staffing models to transfer critical processes to out-of-region resources and activation of crisis management plans to support critical business operations. 

Bottom line: No matter what is thrown at you or your team, taking steps to ensure your important work can continue is critical. 

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. 

A few months ago, I shared some of the observations I’ve made while leading a company—a company that exclusively supports R&D in the Life Sciences, no less—through a global pandemic brought upon by a novel virus.  

While there’s no doubt the realities of much of what transpired in 2020 presented challenges not yet seen or felt by many in my generation and younger, they also fueled a new type of perseverance; one where even the slightest glimmer of silver was enough to line our conscience and tell us to push forward through the tribulations, no matter how hard they seemed. 

And in fact, it was through these toughest of times that I have come to appreciate how meaningful our successes really are, not just from a business perspective, but more importantly, as individuals.

Of all that RCH has accomplished this past year, I think I’m most proud of the fact that RCH’s headcount increased by 58% in 2020. In a time where so many around the world faced the added anxiety of joblessness or financial insecurity, we were not only able to retain our team of incredible professionals, but add to it. 

And within that team, it was a year of personal and professional growth. For example, Mohammad Taaha, Senior Systems Engineer, recently earned the AWS Architect Pro Certification. More important is his ability to help the customer implement solutions through his unique blend of technical efficiency and understanding of the needs of R&D I.T. as they evolve to support science initiatives.  

Lyndsay Frank, Systems Engineer, has been with RCH for over seven years. During that time, and in the last year especially, she has emerged as a leader thanks to her unique desire—and ability—for problem-solving. With a background in science (Biology) and I.T. (Bioinformatics), she personifies RCH’s unique ability to tackle those most challenging issues faced by research scientists today. 

And Mike Wlodarczyk, Account Executive. Mike joined RCH in March of 2020, just as the world was shutting down. In spite of the limitations he experienced in a customer-facing role, his tenacity has proved invaluable, and RCH has experienced significant growth in the Boston area primarily due to Mike’s efforts to support existing customers and expand our relationships within new business as well.  

These are just three of the many examples of impressive resilience and determination the members of our team displayed this past year. And for their efforts, RCH earned the ability to expand our business in new ways…. 

• Like working with existing customers on larger, global-scale scientific computing projects within architecture, engineering, and operations functions.  
• Providing more direct services in the areas of data science and data management in the Cloud and on-prem, across multiple organizations from research, manufacturing, customer services, and beyond.
• Stepping in as a thought partner on how to best implement emerging technologies in support of tools for research teams.
• And simply being asked to provide an objective assessment and guidance on existing platforms, applications, workflows, and strategic initiatives as they relate to our experience in scientific computing for Life Sciences organizations of all size and scale across the globe.

In total, our services business increased 52.7% last year, signaling an important shift in the perception of the value RCH delivers. Sure, we can still be the team you call to fix things. But better yet, we’re cementing our role as the team you should call to help establish and implement the right bio-IT strategy the first time around and set your team on the proper path for scale.   

As we look at the potential of the year ahead, I feel confident that we will continue to grow as a valuable resource within our industry not only because we provide a very specialized offering to a very specific industry, but also because of our trusted reputation that allows companies to make safe decisions in this uncertain time.  

In 2021, we will continue to focus on providing the best support to our customers, with new solution offerings, flexible services delivery, and dedicated resources.   

We will continue to create a work environment that breeds success and security, safely, introducing new development, training and certification programs to enhance our team’s skill-set and satisfaction. 

And we will continue to be a champion of scientific innovation and the life-saving discovery work our customers are called to deliver.  

After a year of such difficulty, there is no greater promise of hope than that which is made possible by the power of scientific innovation. And that will serve is inspiration and motivation for our team, even on the most challenging of days still to come. 

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. 

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

Immunology

Informatics

Molecular Dynamics

Numerical Analytics

Pharmacokinetics

Precision Medicine 

Pre-Clinical

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. 

On December 8, 2020, IBM announced what amounts to the death of CentOS, a long-running project that released freely available versions of Red Hat Enterprise Linux (RHEL).  For those keeping track, that means: 

CentOS7 will keep its EOL thru 2024

CentOS8, that was to live into 2029, will now reach EOL in 2021

There will not be any CentOS9

The news—while not entirely surprising given the fact that CentOS is essentially a clone of RHEL, which IBM acquired in 2018—is significant, as it ends CentOS as we know it and will have a major impact on R&D teams within the Life Sciences space, and far beyond. Here’s why.

While many in the Life Sciences community have standardized RHEL for the Enterprise — a commercially supported, solid option for Linux hosting—CentOS has been attractive for Life Sciences’ scientific and technical compute needs (Research, Analytics, AI, etc. focuses) not only because it aligns with corporate Linux standards (administratively and operationally), but also because it’s free of charge and can be used at scale for High-Performance Compute (HPC), Map-Reduce, Research Compute, Analytics, and so-on without the burden of Enterprise licensing costs.

Nonetheless, the use of CentOS has not been without frustration. 

RHEL has not advanced as quickly as some in the Research and AI communities need, as the library of components to support cutting-edge software packages aren’t easily adapted to support newer software. And because of the historical Fedora → RHEL→ CentOS development cycle, CentOS has lagged even behind RHEL, adding a bit of salt to the “lack-of-keeping-current” wound.

What Now, For Compute at Scale?

Regardless of the challenges, Life Sciences (and beyond) will now be faced with a new challenge: Pay for RHEL in support of computing at scale, which may be one of the drivers behind IBM’s new direction, or, more likely, turn to another free solution, like Ubuntu—a program that is posed to become more prevalent in the Scientific and Technical Computing realm. (For the record, Life Sciences already leverages Ubuntu Linux, the assertion here is that as the dominance of CentOS is forced to ebb, Ubuntu use will scale).

The upside for such compute, includes the continued availability of freely distributed operating system options (and third-party commercial support available, if warranted) and a bit more of an aggressive inclusion schedule for components needed to support newer software applications.  The downside, however, is that adoption may be hindered by Enterprise IT push-back. Moreover, when adoption does begin, the Linux offerings, unlike UNIX, will vary in terms of components and operational tact.

As an aside, back-in-the-day, UNIX was UNIX—variants needed to be blessed (certified) before being allowed to use the trademarked name.  In contrast, Linux distros vary in included components and their versions, and perhaps more notably in administrative practices.  No variations being show-stoppers, but enough that training, SOPs, and the like will need updating.

How the Dice Will Land

Any real judgment on the merits of IBM’s CentOS direction is for time to tell. However, this move will most certainly cause Scientific and Technical computing teams to re-evaluate their choice of Linux—remember, a move to Ubuntu LTS may present functional upside with a lower barrier to entry—and we may see that IBM/Red Hat loses Linux market share as advanced computing groups split from their reliance on RHEL variants. 

As we look forward, I have to believe that this move by IBM is a mistake.  CentOS (and RHEL) move too slowly for Research expectations (as well as AI/ML/DL) but remained a standard out of convenience — RHEL was the commercially supported Enterprise Linux option while CentOS (as a free, binary compatible clone) could be used at scale in Research and other disciplines. But once the largest Linux consumers in Life Sciences move from CentOS, Enterprise IT teams already facing the challenge of supporting multiple Linux variants,  may elect to save costs and run RHEL only where software vendors mandate.

It is conceivable that market pressure could further influence IBM’s direction toward a more positive outcome for dévotes of CentOS, but let’s not bet on this. And while it’s presumable that IBM has made this decision based on business drivers, this type of disruptive change could backfire, driving businesses away from increased controls on free software.

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. 

To say 2020 has been a year unlike any other so far would be an understatement.

COVID-19 has caused the tragic loss of more than 200,000 lives and left permanent scars on many of those fortunate enough to recover from significant disease. 

It’s disrupted global economic growth, at both macro and micro levels, in unprecedented ways, forcing businesses in many sectors to close their doors for the very last time. 

It’s pushed individuals and families to the brink, as parents juggle work obligations with child-rearing.

It’s exceeded the limits of many of our nation’s healthcare facilities, in many ways changing the nature of public health perhaps forever.

And it’s exposed deep and fundamental ideological divides within our country.

It’s been a very challenging year, indeed. 

But on the reverse side of hardship, lies an opportunity for renewal. Yes, the COVID-19 pandemic has caused many terrible ripples to undulate into our world, but it’s also provided a never-before opportunity to reframe, and in many ways, refocus.  

It has shifted the way we leverage technology to stay connected with one another, personally and professionally.  

It has reminded us how important it is to take care of each other and reemphasized the role of the community. 

It has given families the opportunity to slow their pace of life and enjoy more time together.  In my own home specifically, my wife and I were fortunate to have two of our adult children return home through the shut-down. This special time we experienced together as a family likely would not have happened otherwise.

In addition, It has given our earth the opportunity to take a deep breath, with less CO2 and an overall reduction in air pollution.  

And It’s thrust into the spotlight the amazing power of scientific innovation.

It’s in observing this yin and yang, a natural force of our dynamic world, that has led me to this conclusion:  Nothing substitutes the power of perspective, especially in a pandemic. 

Like many of you reading this, I’ve found myself in a unique position these last several months. 

As the head of a company critical to enabling the innovation required to stop novel diseases such as the coronavirus, not only am I reminded of how fragile life can be at the hands of terrible diseases, I also see how powerful it can be in the fight against them, thanks to the potential and the promise of scientific and medical innovation. From this seat, I see a world without limits. 

But that means I’m also tasked with leading our growing team of employees who rely on their income to take care of themselves and their families. It’s a great privilege and responsibility, one that requires both vigilance and patience when balancing the wellbeing of our team with our commitments to our customers, and one that I take very seriously.  I’m very proud of how our team has responded so far, and I look forward to leading this group toward a bright future ahead.   

And finally, I’m a dad. My family (which includes three children in high school and college) much like yours, is navigating uncharted waters as it relates to the resumption of “normal” life and schooling. It can be challenging, and often unnerving, to send the people you love most out into an uncertain world, but helping my family—and yours—regain confidence in the future ahead requires that cautious optimism is not only preached but also practiced. 

Combined, these roles and their intersection points give me a valuable perspective and reaffirms my commitment to support RCH customers doing critical drug and vaccine R&D, while also providing security (and also a healthy working environment) for our growing team. 

And to that end, in securing that RCH is doing everything it can to support science (even as only one small piece of that puzzle), I commit myself to:

Ensuring RCH is able to provide exceptional remote service options, both protecting our employees while continuing to support our customers’ ability to move their work forward. 

Supporting innovation, like cloud computing, AI, HPC, Analytics, etc, and other domains critical to ingenuity in the drug discovery process—through this environment and any other. 

Advocating for the work we do.  Scientific computing is not the easiest concept to understand for those who are outside of this industry, but the impact services such as ours have on science is real and tangible. 

And finally, maintaining hope. The recognition of how far medical innovation has come, and how it has transformed our society over the past 100 years leads me to believe—to know—we will come out on the other side of this crisis. Together.

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. 

The sprint toward early discovery is one of the most important legs in the long, expensive, and compliance-driven relay race to bring new drugs or treatments to market. Not only does being first to market with medical innovation provide companies with the opportunity to patent and sell a new treatment as the sole distributor, the reputational value associated with doing so can also be almost immeasurable.

But, perhaps most importantly, introducing a new drug or treatment is a catalyst for hope.

Never has this been more evident than in response to the global health crisis unfolding as the novel coronavirus spreads exponentially around the world.

As grim details of the effects on this still relatively unknown disease takeover news headlines (albeit with the bias so common of today’s click-driven mass media producers); schools and businesses remain shuttered; and essential workers, especially those in the medical industry, fight fear, fatigue, and risk to take on COVID-19 from the front lines, the world is watching with anticipation to see how medical innovation will rewrite this chapter in human history.

Thankfully, ours is an industry driven both by the exhilaration that comes with the pursuit of discovery as well as a great sense of obligation to provide hope and potential to those battling medical conditions, however significant they may be. As a result, companies from around the world, including some we proudly called clients over the years, responded to the call for treatment and support in several ways.

Sanofi and Regeneron are moving to trial an existing treatment known to suppress inflammatory reactions, that is also showing promise to treat those COVID-19 patients suffering from the most severe reactions.

In addition to its R&D efforts, Takeda, headquartered in Cambridge, is donating millions of dollars to the Red Cross to support the direct care and needs of people in the hardest-hit regions of the greater Boston area.

Moderna is moving to human studies a potential vaccine—which, traditionally, has not presented the same business opportunities as other types of drugs yet has been the catalyst for a significant boom in Moderna stock prices—in record time.

And there are many, many more companies doing important work like this.

Joining the global fight against this invisible enemy is no small task, and being first to market with a potential treatment or vaccine takes a unique combination of skill, tools, and processes.

Here are just a few of the components of a “first-place” team and process that I’ve observed through my years of experience supporting discovery in the life sciences:

Brilliant Scientists – There is no substitute for brain-power, passion and the ability to apply the principles of science, which are predictable, to an inspired vision, which is limitless, to achieve transformative results.

Supportive Bio-IT Team – When the limits of your technology, computing infrastructure, and team are pushed to enable you to do more with less, the benefits are tangible. If you haven’t experienced that for yourself, ask yourself why.

A Friction-free Workflow – Speed and agility are possible only when the barriers that impede your progress are removed. Limiting the number of snags, however minor, that slow you down is critical.

The Right Tools – There’s a tool for every job, but not always a job for every tool. Winning teams work across a stack that’s built with their needs in mind and resist the urge to introduce solutions just for the sake of it.

Availability of Resources – At the end of the day, the dollar drives many decisions. Teams that perform well make sure their dollars are spent in ways that return the most value.

Though we’re undoubtedly in uncertain and scary times, our world, thankfully, includes many of these first-place teams on the front lines of discovery, for the benefit of humankind.

I sleep a lot better at night knowing that and have hope that together, we will weather this storm.

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.