Designing and Installing Pharma Labs

How are emerging design principles like operational insight, molecular infrastructure and human-centred design reshaping safety, agility and performance across the life sciences landscape?

David Broderick at Unispace

As biopharma discovery cycles accelerate and novel modalities push scientific boundaries, lab environments are struggling to keep pace. Today’s R&D teams navigate growing complexity from cell and gene therapy (CGT) to artificial intelligence (AI)-powered workflows yet many still operate in spaces built for another era. A quiet revolution is underway. By blending operational insight, modular infrastructure and human-centred design, labs are becoming intelligent ecosystems; adaptive, data-ready and built for the realities of contemporary science.

Speed meets complexity: why labs must evolve beyond flexibility

The pace of innovation across life sciences has never been greater. Advances in biologics, mRNA vaccine platforms, targeted oncology and CGTs continue to redefine what is scientifically possible. At the same time, AI-driven discovery tools are compressing early research cycles from years to months, generating unprecedented volumes of data and placing new pressures on scientific workflows and infrastructure. Yet, many labs remain rooted in a design philosophy developed for a different era when workflows were linear, modalities were stable and equipment needs were largely predictable. Today’s R&D programmes evolve weekly, equipment footprints expand or contract with remarkable speed, regulatory expectations grow more complex, and the competition for scientific talent means that well-being and user experience are no longer nice-to-have additions, but prerequisites for performance and retention. In this environment, the question is not whether a facility is flexible; flexibility alone is insufficient. The real challenge is whether a laboratory can anticipate change, absorb operational complexity and actively enhance scientific performance, rather than simply accommodating it.

Meeting this challenge requires labs to be reconceived as intelligent ecosystems; dynamic spaces where infrastructure, digital capability and human experience operate as an integrated whole. This shift involves more than making areas easier to reconfigure – it demands systems and environments that can sense, respond and support scientific activity in real-time spaces intentionally designed to evolve with discovery, not after it.

Designing labs that think: from flexible to intelligent

Flexibility has long been considered the benchmark of modern lab design. Movable benches, modular casework and adaptable zones have become common features across R&D settings. But contemporary science introduces complexities that modularity alone cannot solve. The next evolution is the intelligent lab environment that integrates physical adaptability with digital insight, operational understanding, and human-centred planning.

An intelligent lab functions as a coordinated system, not a collection of independent parts. Building services, digital infrastructure, equipment networks and human workflows operate together, enabling real-time adjustment and long-term evolution.

Modular infrastructure
One defining element is the advancement of modular infrastructure. The focus is no longer just on reconfiguration, but on the speed and continuity with which change can occur. Structural grids, interface points and utilities must enable teams to transition between modalities, equipment types or research phases without significant downtime. As programmes scale or shift, the environment should adapt without sacrificing safety or compliance.

Digital integration
Digital integration forms the second cornerstone. Data has become a material in its own right, shaping how labs operate and evolve. Intelligent labs now incorporate sensors, environmental monitoring platforms, equipment telemetry and digital traceability systems. Together, these provide visibility over conditions that influence quality, validation and reproducibility. European studies have shown that dynamically optimised heating, ventilation and air conditioning (HVAC) systems driven by occupancy and containment data can reduce energy consumption by up to 25% while maintaining biosafety performance, highlighting how digital intelligence strengthens operational stability.1

Human-centred design
The third pillar is human-centred design. Scientific output is inseparable from the experience of the people producing it. Intelligent labs prioritise ergonomics, intuitive circulation, environmental comfort and collaboration areas designed around real user needs. These considerations improve accuracy, reduce fatigue, and enable teams to work with greater focus and efficiency. Far from aesthetic enhancements, they function as operational enablers, supporting the consistency and quality demanded in regulated R&D environments.

Together, these elements shift lab design from a one-off construction exercise to an ongoing cycle of learning and optimisation. The intelligent lab is not simply flexible; it is adaptive.

Human-centred labs as a competitive advantage

Historically, the human experience within labs was secondary to technical infrastructure. Today, it is recognised as a critical driver of quality, safety and organisational competitiveness. As scientific work becomes more cognitively demanding, and as talent markets tighten, the lab environment plays a direct role in recruitment, retention and performance. Safety-by-design remains fundamental. Clear contamination pathways, ergonomic equipment placement and intuitive wayfinding minimise risk and reduce the cognitive load associated with complex protocols. When safety is embedded in the physical layout, validation cycles shorten, operational uptime improves and teams experience fewer compliance-related disruptions. Design that naturally reinforces correct behaviours reduces reliance on procedural controls and supports reliable lab practice.

Beyond safety, labs must also be considered multisensory environments. Air quality, acoustic conditions, vibration and daylight exposure all influence concentration, fatigue and accuracy. Research consistently links environmental stability to improved scientific precision. Draft-minimising airflow strategies, acoustic zoning that separates noisy mechanical spaces, and circadian-aware lighting contribute to more consistent cognitive performance and reduce error rates in repetitive or high-precision workflows.

Well-being and culture also play a significant role. Younger scientists entering the field expect environments that support health, balance and connection. Access to natural light, proximity to focus areas and thoughtful circulation patterns shape how teams collaborate and how they feel about their workplace. In competitive sectors, a lab that supports well-being becomes a strategic asset, strengthening retention and maintaining operational continuity.

Ultimately, human performance and scientific performance are inseparable. Labs that prioritise user experience consistently demonstrate higher productivity, lower turnover and enhanced cross-team cohesion. Intelligent design recognises this by integrating human needs into every decision, from bench height to breakout space placement.

Why operational insight belongs at the drawing board

In many traditional lab projects, operational expertise is brought in only after the architectural concept is largely fixed. In today’s complex R&D environment, this sequence is no longer viable. Effective lab design requires operational insight from the start. High-performing facilities emerge when safety, validation, engineering, procurement and facilities management inform the early brief together. This cross-functional approach identifies conflicts such as utility loads, biosafety boundaries or adjacency constraints before they become design issues, reducing rework and preventing delays.

Operational leaders bring valuable insight into how spaces are truly used, including equipment zoning, clean and dirty boundaries, circulation patterns, and workflow adjacencies. Their input ensures that layouts reflect the realities of scientific practice rather than theoretical assumptions. When operational requirements are embedded early, the transition from construction to live research is smoother, safer and more predictable. Digital tools now support more precise planning. The use of digital twins, airflow simulation and occupancy modelling allows teams to test design decisions before committing to construction, identifying risks and optimisation opportunities in advance. These methods shorten commissioning timelines, reduce regulatory friction and help facilities reach operational stability more quickly. Right-sizing is another critical factor. Compliance-driven environments often gravitate towards overdesign, especially in HVAC capacity, air-change rates and utility redundancy. While well intentioned, overdesign increases energy intensity and life cycle costs without proportionate benefit. Projects that adopt realistic equipment diversity planning and airflow zoning frequently achieve significant energy reductions. One mid-scale biologics facility, for example, achieved a 30% energy reduction by re-evaluating adjacency and airflow strategies alone, demonstrating how operational insight directly influences sustainability performance.

Fundamentally, operational planning is not an add-on to design. It is design.

Five decision rules for future-ready laboratories

As science evolves, labs must evolve with it. The following principles offer a practical framework for designing facilities capable of meeting future R&D needs:

• Start with adaptability: infrastructure should support iteration rather than permanence, with modular utilities, reconfigurable casework and structural grids that accommodate new modalities without major disruption

• Embed digital capability: laboratories increasingly rely on environmental monitoring, equipment telemetry, and data-ready infrastructure to support validation and decision-making. Designing for digital transparency enables continuous improvement and enhances resilience

• Prioritise safety and compliance through design: clear routing, intuitive layouts, ergonomic considerations and biosafety alignment reduce risk and allow teams to work confidently and efficiently

• Design for well-being and retention: factors such as daylight exposure, acoustic comfort, ventilation quality and access to collaborative spaces directly influence scientific performance and workforce stability

• Measure outcomes rather than intentions: future-ready labs use data uptime, energy intensity, environmental stability, reconfiguration costs and user satisfaction to drive ongoing optimisation. Intelligent labs do not stay static; they learn.

Conclusion: labs that learn

The future of pharmaceutical R&D requires lab environments that adapt as rapidly as the science they support. Intelligent labs integrate modular infrastructure, digital insight, operational expertise and human-centred design into cohesive, continuously improving ecosystems. They are not incremental upgrades to traditional models; they represent a fundamental shift in how organisations conceive and operate the spaces that power discovery. As research modalities diversify and discovery cycles accelerate, the labs that succeed will be those that do more than keep pace; they will anticipate change. They will learn, evolve and actively support scientific innovation through every phase of their life cycle.

References
1. Visit: researchgate.net/publication/392536299_Energy-Efficient_HVAC_Strategies_for_Enhancing_Bio-Safety_ Standards