The lab of the future transcends digital tools. It’s not just about laboratories.
The lab of the future focuses on the entire enterprise. It creates business value by employing advanced digital tools and techniques to make actionable scientific data accessible at the bench, in the boardroom, and anywhere that data can drive revenue, speed up innovation, and inform critical business decisions.
The objective of establishing a lab of the future isn’t merely to eliminate paper or adopt a new digital tool. It’s to prepare the enterprise for long-term flexibility and growth as the identity of a research company, a diagnostics firm, an oil and gas entity, or a consumer goods provider becomes insufficient. One must also operate as a tech company to thrive in today's competitive landscape. This requires positioning the lab as a crucial driver of innovation and insight.
In essence, the lab must evolve into a lab of the future. Many similar organizations are already collaborating with scientific data advisors to facilitate this evolution. This paper aims to help labs keep pace — and even get ahead — in a swiftly approaching future.
The benefits of an AI-driven, interconnected lab of the future are far-reaching
Creating and expanding a lab of the future is a complex endeavor. It necessitates substantial expertise in data orchestration and continuous investment in cutting-edge tools and technologies. What makes all this effort worthwhile? The answer is significant, impacting individual enterprises, their customers, and society at large.
Image Credit: LabVantage Solutions
The lab of the future — Rather than being confined within a LIMS, the lab of the future utilizes advanced technologies to make scientific data available, actionable, and immediate for the right people at the right time.
The optimized company — Meaningful, machine-enabled analysis allows leadership teams to uncover vital lessons, insights, warnings, and opportunities embedded within scientific data, guiding their decision-making and empowering them to surpass competitors and tackle market complexities confidently.
Partnership ecosystems — As organizations learn to access, contextualize, and utilize vast amounts of scientific data, new practices and standards will emerge to foster collaboration among partners. The lab of the future will be pivotal in this collaborative era, promoting multidisciplinary research and discovery.
Customers and patients — The lab of the future will help facilitate positive outcomes by delivering precise diagnostics, advanced therapies, and high-quality, sustainable products that patients and customers require for healthy, meaningful lives.
Real solutions for global challenges — This push for a collaborative, data-driven future will enable companies across various sectors to address humanity’s most complex issues: food insecurity, energy crises, climate change, medical shortages, supply chain disruptions, and much more. To resolve these challenges, innovative solutions are essential — and labs of the future are needed now.
Five key principles behind every lab of the future
To fulfill the promises outlined above, architects of the lab of the future must base their vision on several core principles. These principles are the foundation for every lab to build future success; like guiding stars, they will steer organizations from their current state on the digital transformation spectrum toward a fully integrated lab ecosystem tailored to their objectives.
Transitioning from a paper-based lab to a lab of the future generally involves three major phases: (1) moving from paper-based records to a LIMS and adopting some digital capabilities, (2) moving to augmented lab workflows and leveraging digital twins to simulate and predict lab outcomes, and (3) establishing a fully integrated data ecosystem within a digitally native lab. Understanding the principles that drive each phase can help labs accelerate their transformation. Image Credit: LabVantage Solutions
First principle
In a lab of the future, data drives intelligence
For a lab at the outset of its digital transformation journey, applying this principle may mean transitioning from manual data management to a LIMS; as they delve deeper into their transformation, this principle involves connecting all lab systems — their LIMS, ELN, LES, and SDMS — into an optimized informatics landscape. From there, labs can incorporate tools like artificial intelligence into their data strategy, enhancing both upstream data capture and downstream analysis in ways unattainable with siloed systems and human interventions alone.
Second principle
A lab of the future maximizes interconnection and automation
In a lab of the future, instruments share data and integrate seamlessly with lab systems, liberating operators from repetitive data-related tasks and minimizing productivity loss due to human error.
Third principle
A lab of the future adopts today’s best digital tools
When it comes to leveraging artificial intelligence and other cutting-edge tools, leaders of a lab of the future won’t use phrases like “we might experiment with it” or “let’s just try it.” Instead, they are fully committed to enhancing their competitive edge by strategically deploying proven and emerging technologies in commercially meaningful ways.
Fourth principle
A lab of the future delivers accurate intelligence in real time
In today’s fast-paced post-2020 environment, labs cannot afford to wait even moments for a data dashboard to refresh. From accelerating research and clinical development to bringing products to market swiftly, companies and their clients need intelligent, real-time analytics. The lab of the future addresses this by providing immediate insights that operators across R&D and Quality can rely on.
Fifth principle
Company leaders can measure the ROI of their lab of the future
To elevate a lab to new heights, one must understand precisely how investments in digitization will yield returns. The lab of the future, designed around intelligence-driven systems, enables corporate leadership to measure this ROI transparently, predictably, and accurately. This is the advantage of liberating scientific data from the “black box” of lab systems and integrating it into the enterprise data lake — it not only assists the lab in planning its next steps but also enables the organization to make strategic, informed investments in its future.
The role of artificial intelligence, machine learning, and other advanced technologies
AI and other advanced technologies can elevate science and yield better outcomes — whether by minimizing risk in quality labs or speeding up discovery in pharmaceutical R&D.
It empowers lab staff, from technicians to investigators to data scientists, to accomplish in seconds what previously took hours, days, or weeks. Tasks once deemed impossible are now achievable with AI:
- Enhance operational performance by forecasting and proactively preparing for laboratory resource demands.
- Analyze vast datasets faster than any human, uncovering potential new treatments at an accelerated pace.
- Identify patterns and correlations in complex datasets that may elude human researchers; gain insights from unmatched datasets.
- Analyze historical or real-time operational data to anticipate future risks of failure or out-of-spec results.
- Automate processes ranging from scheduling and risk assessment to sample preparation and processing.
In one instance, AI and machine learning (ML) yielded over five times a company’s investment in just three years by delivering automated processes with 97% quality and significantly reducing the processing time for “bad” batches.
How to position your lab for the future
Every lab must chart its unique course from its current state to the digitally advanced, data-driven ideal. The company’s business objectives, competitors, market position, and current and aspirational capabilities at the bench — all these factors will dictate when and how to progress through successive phases of digital transformation. In experience, the smoothest and most effective transformations begin with a common first step.
Find a scientific data advisor who understands the vision
What is a scientific data advisor?
A scientific data advisor is an expert who recognizes the intricate journey from lab-generated insights to enterprise-level decision-making and possesses the skills and experience to facilitate that journey using today’s most advanced technologies.
As the bench-to-boardroom specialist, the scientific data advisor will assist in establishing a modern informatics strategy in the lab while collaborating with ERP or CRM advisors at the enterprise level. Their goal is to ensure decision-makers can access, comprehend, and — most critically — utilize lab data to propel the business forward.
What to look for in a scientific data advisor
Look for an individual with a background that transcends buzzwords. An effective scientific data advisor has spent years not just discussing digital transformation, but implementing it. They have assisted organizations in outperforming competitors by transforming their labs from the inside out, utilizing the right digital technologies, data architecture, and forward-thinking mindset to create meaningful change at the core of the business.
Most importantly, a strong scientific data advisor is dedicated to evolving in tandem with tomorrow’s technologies. As new capabilities arise, such as AI-driven semantic search or innovative applications for intelligent instruments, they are ahead of the curve, utilizing, testing, and adapting that technology to maximize its efficiency for clients.
How can a scientific data advisor help establish a true lab of the future?
An effective scientific data advisor will customize their approach based on business drivers, the current level of lab digitalization, and other factors. This tailored approach may include:
- Assisting in the establishment of an end-to-end data ecosystem in the lab, aligning R&D activities with QC testing and every step in between.
- Identifying untapped business value in lab data and creating the necessary technological and operational protocols to bring that value into the boardroom.
- Integrating artificial intelligence and machine learning into the lab effectively and rationally.
- Addressing scientific data lake challenges across the organization to create a more harmonized, centralized approach to collecting and utilizing lab data.
The role of people in a lab of the future
Amid the excitement surrounding digital transformation and labs of the future, an undercurrent of anxiety often arises: what will happen to human operators as labs pursue greater automation, digitalization, and efficiency?
The reality is that when undertaken responsibly and aligned with a realistic, sustainable vision of future success, building a lab of the future is not about displacing people — it’s about liberating them from tedious tasks so they can focus on higher-value work.
Given the increasing demand for lab scientists (the Bureau of Labor Statistics projects a 17% growth in employment for medical scientists in the coming years), now is the time for these changes. Instead of preparing samples, entering data, generating CoAs, and managing inventory, operators in a lab of the future will apply their skills and expertise where they can have the greatest impact: fostering innovation, achieving scientific breakthroughs, and aligning lab objectives with the overall needs of the organization and its customers.
From aspiration to success story
What matters most is the vision for the lab of the future. That vision won’t arise from a white paper — it will emerge from within the organization. The key: find scientific data advisors who will invest the time to truly understand that vision and possess the expertise to help realize it.
At LabVantage, collaboration with customers is at the forefront. The laboratory is viewed as the heart of the enterprise, and the mission is to help reimagine digital strategies and harness scientific data as a catalyst for future flexibility, growth, and meaningful contributions to the industry. From the initial step away from Excel and into best-in-class LIMS software to the adoption of an AI-driven lab informatics platform, the necessary technologies are provided as organizations move toward their lab of the future — along with the right expertise and experience to guide each step along the way.
References
- Bureau of Labor Statistics. (2024). Home. (online) Available at: https://www.bls.gov/ooh/life-physical-and-social-science/medical-scientists.html.
About LabVantage Solutions
LabVantage Solutions, Inc. is the leading global laboratory informatics provider. Our industry-leading LIMS and ELN solution and world-class services are the result of 35+ years of experience in laboratory informatics. LabVantage offers a comprehensive portfolio of products and services that enable companies to innovate faster in the R&D cycle, improve manufactured product quality, achieve accurate recordkeeping and comply with regulatory requirements.
LabVantage is a highly configurable, web-based LIMS/ELN that powers hundreds of laboratories globally, large and small. Built on a platform that is widely recognized as the best in the industry, LabVantage can support hundreds of concurrent users as well as interface with instruments and other enterprise systems. It is the best choice for industries ranging from pharmaceuticals and consumer goods to molecular diagnostics and bio banking. LabVantage domain experts advise customers on best practices and maximize their ROIs by optimizing LIMS implementation with a rapid and successful deployment.
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