Lab of the future: four technologies to watch

Next-generation laboratory testing capabilities are being shaped by the convergence of advanced scientific technologies and data-driven insights, enhancing efficiency and quality in drug discovery and development.

Below are several noteworthy advances reshaping how new therapies are discovered, validated and progressed into clinical trials. These include novel testing platforms such as advanced proteomics and spectral flow cytometry, along with modernised sample collection and the digitalisation of laboratory workflows.

Proteomics: boosting early stages of discovery

A better understanding of the unique protein biosignatures associated with a specific disease can generate deeper, more nuanced insights regarding the biological functions and pathways involved in disease onset and progression.

By measuring the functional proteins within cells, proteomics provides a more detailed and accurate view of disease mechanisms and drug responses than genomics or transcriptomics alone. These insights can help identify novel drug targets and guide the development of precision therapies at the earliest stages of drug discovery.

In the past decade, several novel proteomics platforms have emerged, enabling researchers to evaluate thousands of proteins with high sensitivity and reproducibility. These systems offer exceptional multiplexing, measuring more than 5,000 proteins from a single sample as small as 2 µL.

These technologies:

• Help identify unique protein networks that reflect a specific biological state, track changes linked to disease progression, or reveal the mechanism of action of drug candidates in early development
• Detect and quantify proteins at low concentrations, enabling researchers to assess biological responses to combination therapies – particularly valuable in immuno-oncology
• Use a dual-antibody approach to generate a DNA barcode, readable by quantitative PCR or next-generation sequencing. Samples can be collected at multiple times to track changes over time
• Support precision medicine by identifying novel biomarkers, especially for neurodegenerative diseases such as Alzheimer’s disease.

These new platforms deliver scalable throughput without sacrificing sensitivity. The proteomic data generated is often combined with data from genomic testing or flow cytometry to deliver a multi-omics perspective.

Proteomics is expected to expand rapidly at the discovery level, where artificial intelligence-driven technologies can cull large datasets and eventually deliver predictive models.

High-parameter spectral FCM: powering next-generation immune profiling

High-parameter spectral flow cytometry has rapidly evolved into a cornerstone technology in drug discovery and early-phase clinical development. By enabling deep, multiparametric analysis of immune and cellular responses at single-cell resolution, spectral flow cytometry provides unparalleled insights into the complex biological systems that underpin therapeutic efficacy and safety.

Unlike conventional flow cytometry, spectral FCM captures the entire emission spectrum of each fluorochrome across multiple detectors. This allows accurate discrimination of fluorochromes with highly overlapping emission spectra and offers greater flexibility in panel design. As a result, full-spectrum FCM can resolve 30 or more markers in a single assay, greatly increasing the dimensionality of cellular analysis. This is a key advantage in early-phase trials, where sample volume may be limited and maximising analytical depth is essential.

Comprehensive immune profiling and pharmacodynamic monitoring are crucial in early-phase clinical trials. Spectral FCM allows researchers to track dynamic changes in immune cell phenotypes and functional states, helping to elucidate the mechanisms of action of investigational drugs. The high-dimensional data it generates also supports the identification of predictive and pharmacodynamic biomarkers that correlate with clinical outcomes, guiding patient stratification and dose optimisation. In addition, spectral FCM is central to monitoring immune modulation – including activation, suppression and exhaustion – key indicators of therapeutic response, particularly in immuno-oncology.

Recent advances have extended the use of spectral FCM beyond traditional immunophenotyping. In preclinical and translational research, it is now routinely used to:

• Characterise rare and functionally distinct cellular subsets, such as regulatory T cells, tissue-resident memory cells and myeloid-derived suppressor cells
• Monitor immune checkpoint expression and T-cell exhaustion markers in response to immunotherapies
• Assess target engagement and downstream signalling events in real time to identify early indicators of therapeutic activity.

These capabilities are particularly valuable in oncology, autoimmune disease and infectious disease research, where immune complexity and heterogeneity demand high-resolution analytical tools.

Expanding advances in spectral FCM

The continued evolution of spectral FCM is being driven by several key technological innovations. Advanced unmixing algorithms have improved the accuracy and reproducibility of spectral deconvolution, even in complex panels. Automation and high-throughput platforms – including robotic sample handling and automated gating pipelines – are increasing assay throughput and standardisation. AI-driven analytics are now applied to spectral FCM datasets to identify novel populations, classify cell states and predict clinical outcomes. Meanwhile, digital integration of laboratory workflow systems enables real-time data sharing, cross-site harmonisation and centralised quality control – capabilities essential for multi-centre and global trials.

Microsampling for toxicology insights: reducing animal use in preclinical settings

In April, the U.S. Food and Drug Administration (FDA) announced a plan to reduce, refine and potentially replace animal testing in the development of monoclonal antibodies and other therapies, using validated “human-relevant” methods known as New Approach Methodologies (NAMs). This includes a spectrum of approaches, such as AI-based computational models, to evaluate toxicity, cellular lines and organoid toxicity.

Another human-relevant approach for drug developers to consider is microsampling. This technique involves collecting, handling and analysing very small volumes of liquid biological samples – typically 50 µL or less of blood – for research purposes such as toxicological assessments of new drug candidates, as well as discovery pharmacokinetics and pharmacodynamics.

Recent advances in analytical sensitivity have reduced the blood volume needed for testing. Microsampling techniques can help researchers assess toxicokinetics while also minimising animal use and addressing related ethical concerns in non-clinical and preclinical discovery.

For example, collecting smaller blood volumes allows researchers to reduce or even eliminate the need to warm rodents to obtain sufficient samples, and blood can be taken from less invasive sites. With lower volume requirements, samples can be collected from the main study rodents, removing the need for toxicokinetic satellite animals and reducing the total number of rodents required by up to 40 percent per preclinical study.

In addition, compared with traditional biofluid sampling methods, advanced microsampling offers several benefits for drug developers beyond reducing animal use, including:

• Allowing safety data and drug exposure to be evaluated within the same animal, providing higher quality insights rather than composite data from multiple animals
• Enabling higher quality serial sampling instead of relying solely on toxicology, PD and PK data
• Potentially permitting the collection of more samples for biomarkers and other endpoints
• Where stability is confirmed, removing the need for centrifugation and cold storage of analytes by using dried matrix approaches such as dried blood spots.

To encourage drug developers to adopt NAMs, the FDA has stated that companies submitting strong safety data from non-animal testing may be eligible for a streamlined review.

As research builds evidence of the benefits of microsampling for preclinical evaluation, and with growing regulatory acceptance, it will be worth watching whether the industry experiences an uptick in adoption of these sampling approaches.

Electronic laboratory notebooks: improving data compliance and reducing operational rework

In recent years, electronic laboratory notebooks (ELNs) have helped expert lab teams digitise end-to-end workflows that previously relied on paper-based documentation and processes, in both preclinical and clinical settings. Integrating ELNs into laboratory operations aims to standardise and modernise documentation while improving operational efficiency, regulatory compliance and data harmonisation across sites and teams.

By embedding ELNs into a digitised project workflow, lab teams can adopt more proactive quality control methods. For example, real-time alerts on equipment, materials and processes allow experts to act quickly to interrogate datasets and make adjustments that reduce deviations. The use of standardised templates within the ELN also increases compliance and consistency among team members, from sample receipt through to results reporting.

When technologies such as ELNs are interconnected from start to finish, workflows can support a more holistic approach to bioscience data management – strengthening efficiency and helping lab experts get it right the first time. This can include:

• Project lifecycle management platforms
• Sample oversight and tracking tools that incorporate analysis results and data tables
• Compliance with assay templates
• Real-time calculation assurance
• Management and synchronisation of collected data with sample oversight tools.

By moving to paperless laboratories, teams can also improve the sustainability of their practices.

Evolving innovations: much more to come

Whether through advances in automated workflow solutions such as ELNs, innovations in highly targeted proteomics, or developments in microsampling and spectral FCM, drug discovery and development stakeholders are helping to transform preclinical and clinical laboratory testing and analysis. Opportunities to further refine and enhance exploratory research, validation and clinical development of novel therapies continue to grow.

Stakeholders are also seeking to match the complexities of precision medicine with solutions that simplify processes, reduce administrative burdens and improve data quality and standardisation across sites – all while keeping the focus firmly on patient care.