Scientific and operational maturity of CE–MS: are we close?

Abstract

Capillary electrophoresis–mass spectrometry (CE–MS) has regained momentum through advances in sensitivity, separation efficiency, and expanding applications in proteomics, metabolomics, and biopharmaceutical analysis. These developments have led to increasing claims that CE–MS is approaching technological maturity. However, while scientific capability is well established, its operational maturity—defined by robustness, reproducibility, and ease of deployment—remains limited. Drawing lessons from the industrialization of liquid chromatography–mass spectrometry (LC–MS), we argue that widespread adoption depends not only on analytical performance but also on engineering architectures that stabilize interfaces and enable standardized workflows. Ultimately, the future of CE–MS will depend as much on system-level engineering as on advances in separation science.

Towards operational maturity of CE-MS

Capillary electrophoresis (CE) is increasingly positioned as a complementary front-end to liquid chromatography (LC) for mass spectrometry (MS), offering orthogonal separation based on electrophoretic mobility. This enables high-resolution analysis of charged biomolecules and highly polar metabolites that are challenging for conventional chromatographic workflows. Recent studies demonstrate the analytical capabilities of CE–MS, from high-resolution separation of proteoforms and charge variants to sensitive detection of highly polar metabolites and small molecules, across proteomics [1–7], metabolomics and glycomics [8–11], and biopharmaceutical characterization [12–15]. These advances have prompted renewed discussion of whether CE–MS is approaching technological maturity [16]. However, technological maturity can be interpreted in different ways. While CE–MS has achieved substantial scientific maturity, its operational maturity—defined by robustness, reproducibility, and ease of deployment across laboratories—remains limited.

The distinction between scientific capability and operational maturity provides a useful framework for interpreting the current state of CE–MS. Figure 1 summarizes this framework and illustrates how the transition from experimental capability to operational maturity has historically shaped the evolution of analytical platforms. Many technologies initially demonstrate strong performance in expert laboratories before evolving into routine analytical infrastructure widely deployed across research and industrial environments. CE–MS may now be approaching a similar transition.

Figure 1.

Scientific versus operational maturity of CE–MS and implications for broader adoption.

(A) CE–MS and LC–MS as complementary front-end separation platforms for mass spectrometry, based on electrophoretic and chromatographic separation mechanisms, respectively.

(B) Conceptual comparison of scientific and operational maturity. CE–MS demonstrates strong analytical capability but remains limited in operational maturity, whereas LC–MS has achieved both.

(C) Fragmentation across hardware, electrical integration, software, data analysis, and workflows can limit robustness, reproducibility, and standardization in CE–MS.

(D) Biopharmaceutical applications may serve as a forcing function for the development of robust, reproducible, and standardized CE–MS platforms.

In this Opinion, we examine the gap between scientific capability and operational maturity in CE–MS, discuss the engineering and operational challenges limiting broader deployment, and outline potential pathways toward robust and standardized CE–MS platforms.

CE–MS as a complementary MS front-end

CE–MS and LC–MS represent fundamentally different strategies for coupling separation science with MS (Figure 1A). LC–MS relies on chromatographic separations across nano-, micro-, and analytical-flow regimes and has achieved widespread adoption through decades of engineering optimization. By contrast, CE–MS separates analytes based on electrophoretic mobility under strong electric fields, enabling intrinsically high separation efficiency, particularly for charged molecules.

These complementary mechanisms provide distinct analytical advantages. CE–MS offers high-resolution separation of peptides, proteoforms, protein complexes, and other charged biomolecules, while enabling efficient analysis of highly polar metabolites that often exhibit poor retention in conventional reversed-phase chromatography. As a result, CE–MS is increasingly used alongside LC–MS in multi-platform analytical strategies to improve molecular coverage.

It is important to distinguish between online CE–MS, where electrophoretic separation is directly coupled to electrospray ionization MS, and offline CE–MS workflows, where electrophoretic separations are followed by subsequent MS analysis. In this Opinion, we focus on direct CE–MS interfaces because robust online coupling is central to operational maturation.

The implementation of CE–MS is further complicated by the diversity of electrophoretic modes, including capillary zone electrophoresis (CZE), isoelectric focusing (IEF/icIEF), micellar electrokinetic chromatography (MEKC), and related variants, as well as heterogeneous device formats spanning capillaries and microfluidic chips. This diversity increases configuration and operational complexity and reinforces the need for system-level architectures that can stabilize and integrate workflows across different CE–MS formats.

Scientific capability versus operational maturity

A useful framework for interpreting CE–MS development is to distinguish between scientific maturity and operational maturity (Figure 1B). Scientific maturity reflects what is achievable in expert laboratories, whereas operational maturity reflects whether performance can be reproduced reliably across laboratories with minimal intervention.

By this definition, CE–MS has already achieved substantial scientific maturity. Numerous studies demonstrate exceptional separation performance and analytical sensitivity across proteomics, metabolomics, and glycomics applications. However, translating these capabilities into routine workflows remains challenging. Many CE–MS implementations still require substantial expertise in instrument configuration, interface tuning, and method optimization.

Interface challenges in CE–MS

A central barrier to operational maturity lies in the CE–MS interface [17, 18]. CE operates at ultralow flow rates, typically in the nanoliter- to low microliter-per-minute range (nl–μl/min), rendering electrospray generation highly sensitive to perturbations in fluidic and electrical conditions. Unlike LC–MS, CE–MS must simultaneously manage electrophoretic separation current, electrospray ionization stability, and electrical grounding across tightly coupled functional layers. This coupling can contribute to current fluctuations, bubble formation, spray instability, and reduced reproducibility, particularly under prolonged operation or when interfacing with complex sample matrices. In addition, the narrow operating window associated with ultralow-flow electrospray increases sensitivity to minor variations in interface geometry, solvent composition, and electrical contact. These limitations do not primarily reflect insufficient analytical capability, but rather the challenges of integrating separation and ionization into a stable and standardized operational architecture. These are fundamentally engineering, not chemical, limitations.

Substantial progress in CE–MS interface engineering has nevertheless been achieved over the past decade, and several commercial and laboratory-developed interfaces have demonstrated improved stability and reproducibility under optimized operating conditions [16]. However, broader deployment of CE–MS remains constrained by challenges in operational standardization, system integration, and cross-laboratory reproducibility. These limitations become particularly important under ultralow-flow operating conditions, where minor variations in interface configuration, electrical contact, coating quality, or user operation can affect long-term performance consistency.

Addressing these interface-level challenges and improving integration across analytical workflows therefore represents an important frontier in the continued maturation of CE–MS technologies (Figure 1C).

The historical evolution of LC–MS demonstrates that technological maturation depends less on incremental performance gains and more on system architectures that stabilize and integrate system components. Robust interfaces and standardized workflows transformed LC–MS into a routine platform. Performance enables possibility; engineering enables adoption (Box 1)..

Box 1. Lessons from LC–MS industrialization.

Liquid chromatography–mass spectrometry (LC–MS) was once a technically demanding coupling of two complex systems. Early implementations were limited by unstable electrospray interfaces, fragmented hardware configurations, and lack of standardized workflows, restricting use to specialist laboratories.

Over time, LC–MS evolved into a routine analytical platform across proteomics, metabolomics, and clinical analysis. This transition was driven not only by improvements in analytical performance, but more critically by advances in interface engineering, system integration, and infrastructure development. Robust electrospray interfaces, modular hardware architectures, and automated workflows enabled reliable operation at scale.

A key lesson is that technological maturation depends on architectures that stabilize and decouple functional layers of the analytical system, including separation, ionization, and mass spectrometric detection. For CE–MS, the central challenge is therefore not only improving analytical capability, but developing engineering frameworks that enable stable, reproducible, and scalable operation.

Applications driving renewed interest in CE–MS

Applications in proteomics, metabolomics, and biopharmaceutical analysis are driving renewed interests in CE–MS. These areas demand high sensitivity and complementary molecular coverage.

In proteomics, CE–MS has enabled highly sensitive analysis of small sample volumes and has been particularly valuable in emerging single-cell proteomics workflows.

Electrophoretic separations provide excellent resolution for peptides and proteoforms, enabling deeper exploration of complex proteomes [1–7].

In metabolomics, CE–MS is widely recognized for its ability to analyze highly polar metabolites such as amino acids, organic acids, nucleotides, and central carbon metabolites. These compounds often exhibit poor chromatographic retention but can be efficiently separated using electrophoretic techniques. As a result, CE–MS is frequently used as a complementary analytical platform alongside LC–MS [8–11].

Biopharmaceutical analysis represents another rapidly expanding application area. Electrophoretic separations are widely used for charge-variant analysis of monoclonal antibodies and other therapeutic proteins. Coupling these separations directly with mass spectrometry offers the potential for more detailed molecular characterization, including the identification of proteoforms, glycoforms, and post-translational modifications [12–15].

Biopharma as a forcing function

Biopharmaceutical analysis may act as a key forcing function for CE–MS maturation (Figure 1D). Regulated environments impose stringent requirements for reproducibility, robustness, and consistency. In this context, technologies are shaped more by engineering discipline than by analytical novelty. As CE–based separations become more widely used for therapeutic protein characterization, there is growing interest in integrating these separations with mass spectrometry in ways that support routine high-throughput analytical workflows. Meeting these requirements will likely require advances not only in analytical performance but also in system architecture and interface engineering.

Engineering architectures for CE–MS maturation

The evolution of LC–MS suggests that technological maturation depends not only on analytical performance but also on engineering architectures that stabilize and integrate the functional layers of the analytical system. These layers include separation, interface design, ionization, mass spectrometric detection, software control, and data analysis.

Advancing CE–MS toward operational maturity will similarly require system-level architectures that stabilize interfaces, decouple functional layers, and enable modular integration. The key question is no longer whether CE–MS can work, but whether it can operate reliably and at scale.

Applying this architectural perspective to CE–MS highlights several opportunities to improve operational robustness. These include stabilizing the interface between electrophoretic separation and electrospray ionization, improving electrical isolation between separation and ionization voltages, and developing modular front-end architectures to support more reliable CE–MS platforms (Figure 2).

Figure 2.

Engineering architectures for operationally robust CE–MS.

Conceptual illustration of how engineering architectures and system integration may drive the operational maturation of CE–MS. The historical evolution of LC–MS demonstrates how early challenges in interface stability and system integration were addressed through modular front-end architectures that functionally decoupled separation, ionization, and mass spectrometric detection. By comparison, CE–MS demonstrates strong analytical capability but remains more difficult to standardize for robust and routine deployment across laboratories. In CE–MS, tightly coupled electrophoretic separation, electrical integration, electrospray ionization, and mass spectrometric detection can contribute to variability in robustness and reproducibility. Modular architectures that stabilize and functionally decouple these operational layers may improve workflow integration, reproducibility, automation, and cross-platform implementation, thereby supporting the transition of CE–MS from specialized research tools to broader infrastructure-grade analytical platforms.

Engineering layers shaping CE–MS maturation

The key engineering dimensions underlying this transition can be summarized across several system layers. Table 1 compares the historical industrialization of LC–MS with the current state of CE–MS across separation technologies, interface design, ionization stability, hardware integration, software workflows, and application drivers. Across many of these layers, LC–MS benefited from decades of engineering innovation and industrial standardization.

Table 1.

Engineering layers shaping operational maturity of CE–MS^a

System layer	LC-MS industrialization	CE-MS today	Engineering principle
Separation	Standardized chromatographic flow regimes and column technologies	Electrophoretic separations operating at ultra-low flow	Stabilization of low-flow separations and reproducible flow control
Interface	Robust and standardized LC–ESI interfaces enabling routine LC–MS coupling	Multiple CE–MS interface configurations with variable robustness and stability	Architectures that functionally decouple separation, ionization, and MS operation
Ionization	Standardized electrospray emitters and stable ionization geometries	Spray sensitivity to bubbles, flow fluctuations, and electrical coupling between separation and ionization	Stabilized electrospray generation under ultra-low-flow conditions
Hardware integration	Integrated LC–MS instruments and standardized modules	Heterogeneous CE–MS configurations across laboratories	Modular front-end architectures compatible with modern MS platforms
Software and workflows	Automated LC–MS control software and mature data pipelines	Variable levels of automation and workflow integration across CE–MS platforms	Integrated control, automation, and data-processing pipelines
Applications & adoption	Broad adoption in proteomics, metabolomics, and clinical MS	Primarily specialized research applications	Standardized and validated workflows enabling broader adoption
Industrial drivers	Biopharma, clinical MS, and proteomics demanded robust LC–MS platforms	Growing demand for characterization of complex biomolecules	Application-driven standardization and validation of CE–MS workflows

^aComparison of LC–MS industrialization with the current state of CE–MS, highlighting system-level engineering layers that enabled LC–MS to become a routine analytical platform and that may guide the operational maturation of CE–MS.

By comparison, CE–MS implementations remain more heterogeneous. Advancing CE–MS toward operational maturity will likely require coordinated innovation across multiple layers of the analytical system.

Role of artificial intelligence in CE–MS maturation

Alongside hardware engineering, advances in artificial intelligence (AI) and machine learning may accelerate the maturation of CE–MS. AI-driven approaches may support real-time monitoring, adaptive control, and automated optimization of CE–MS operating conditions, potentially improving robustness, reproducibility, and operational consistency across laboratories. Data-driven methods may also assist signal quality monitoring, method optimization for different analyte classes, and streamlined data-processing workflows, while machine learning models could help harmonize datasets across laboratories and instruments [19, 20].

However, AI-driven instrument control in CE–MS remains limited and is still emerging. Importantly, these approaches ultimately depend on sufficiently stable and standardized hardware platforms and cannot compensate for unstable hardware or poorly engineered interfaces. As a result, AI is likely to function primarily as a complementary layer that enhances system stability and operational optimization, rather than replacing the need for robust engineering architectures within CE–MS systems. In this context, hardware architectures define the performance ceiling, whereas AI may help approach it through system-level monitoring, optimization, and control, complementing the hardware and architectural elements illustrated in Figure 2 and Table 1.

Concluding remarks

CE–MS is entering a critical transition from an expert-driven methodology to an infrastructure-grade analytical platform. Several important engineering and operational challenges remain unresolved and will likely shape the future trajectory of CE–MS (see Outstanding questions). Continued progress will depend on system architectures that enable robust, reproducible, and standardized workflows across laboratories. Advancing CE–MS toward operational maturity will therefore require coordinated efforts from instrument manufacturers, academic researchers, and funding agencies to develop robust engineering architectures, transferable operational expertise, and standardized implementation strategies. Closer collaboration between industry and academia may further accelerate knowledge transfer, hands-on training, and development of the next generation of CE–MS scientists. The history of LC–MS suggests that analytical technologies mature not when performance peaks, but when interfaces stabilize. Successful CE–MS systems nevertheless depend on both architectural engineering and separation science, including capillary coatings and surface properties that influence reproducibility and long-term operational stability. Ultimately, as many core CE separation principles become increasingly established, whether CE–MS becomes routine or remains niche may be determined more by engineering than by chemistry.

Outstanding questions.

• What engineering architectures can best stabilize CE–MS interfaces under ultralow-flow conditions?

• How can CE separation, ionization, and MS detection be more effectively integrated?

• What level of operational standardization is needed for routine cross-laboratory CE–MS deployment?

• Can modular front-end designs improve CE–MS compatibility across instrument platforms?

• How can AI and automation improve CE–MS robustness, reproducibility, and ease of operation?

• What training and knowledge-transfer strategies are needed to support broader CE–MS adoption?

Highlights.

• CE–MS has achieved substantial scientific maturity but remains operationally immature.

• Operational maturity requires robustness, reproducibility, and standardized workflows across laboratories.

• Widespread CE–MS adoption depends on engineering architectures as much as analytical performance.

• Future CE–MS advances will require improved interface engineering, automation, and workforce training.

• Whether CE–MS becomes routine or remains niche may ultimately depend more on engineering than chemistry.