George Barisas
Deborah A. Roess- 1Department of Chemistry, Colorado State University, Fort Collins, CO, United States
- 2Department of Biomedical Sciences, Colorado State University, Fort Collins, CO, United States
Introduction
Bioanalytical chemistry sits at the intersection of chemistry, biology, and medicine and deals most broadly with identifying, quantitating, and establishing properties of components in biological materials. The overall goal in bioanalytical chemistry is to create methods that are accurate, reliable, and quantitative in biological samples where target molecules of interest may exist in very low concentrations and in very complex media.
Scope of bioanalytical challenges
As in Analytical Chemistry generally, the three challenge areas of Bioanalytical Chemistry deal with extending the sensitivity of existing analytical methods, the specificity of these methods and their applicability in various contexts. The grand challenges in bioanalytical chemistry represent pressing unsolved problems and ambitious goals in the field.
Sensitivity challenges
Achieving high analytical sensitivity remains a central challenge in bioanalytical chemistry, particularly for low-abundance biomolecules in complex biological matrices. Detection limits in the femtomolar to attomolar range are often hindered by matrix effects, non-specific adsorption, ion suppression, autofluorescence, and instrumental noise, while wide dynamic ranges and single-molecule measurements exacerbate reproducibility and signal reliability issues (Stanley et al., 2025).
Recent technological advances are addressing these limitations: nanostructured and plasmonic materials enhance optical and spectroscopic signals (Dasgupta and Ray, 2024), micro- and nano-fluidic platforms reduce sample loss, high-resolution mass spectrometry and ion mobility improve low-abundance detection and digital bioassays transform analog signals into discrete events for single-molecule quantification (Barman et al., 2025). Complementary developments in nanopore sensing, single-molecule fluorescence (Barman et al., 2025), and machine learning–based signal processing further enhance both sensitivity and specificity.
Looking forward, emerging trends focus on integrating extreme sensitivity with spatial, temporal, and functional resolution, enabling single-cell, subcellular, and in vivo analyses, while multi-modal and hybrid platforms, combined with AI-driven data interpretation (Schmidt, 2024), promise holistic, adaptive systems capable of interrogating biomolecular processes at unprecedented depth in native biological contexts.
Advances in healthcare mean that many diseases are treatable if identified early at a stage where biomarkers may be present at very low concentrations in a clinical sample and where detecting such markers reliably remains challenging. However, single-molecule and single-cell analysis remains a particular Frontier challenge. While we can detect single molecules in some contexts, doing so reliably in complex biological systems such as blood or tissue with high specificity is extremely difficult. Nonetheless, recognizing the heterogeneity of individual cells has proven to be crucial for understanding disease (Kim and Takahashi, 2025). Equally important, there remains the challenge of obtaining information from the thousands of different molecules within a single cell that affect cell function.
Characterizing individual molecules is as important as detecting them and much more difficult (Stanley et al., 2025). It is important to note that properties of individual molecules may differ greatly from average properties of samples observed by ensemble methods. Yet physiological effects of molecules representing only a small fraction of the total population may be different from, and possibly more significant than, those attributable to the population as a whole (Komatsu and Mizuno, 2025). This is particularly critical in early stages of disease diagnosis and treatment where small but important changes in the repertoire of cell molecules or individual molecules in body fluids may signal the onset of a disease process.
Specificity and selectivity challenges
Achieving high specificity and selectivity in bioanalytical chemistry remains a formidable challenge due to the complexity of biological matrices. Endogenous compounds, and overlapping signals can confound detection, while the wide dynamic range of analytes and structural heterogeneity—such as post-translational modifications or isomeric variants—further complicates accurate identification (Shen et al., 2024). Affinity-based assays, mass spectrometry, and spectroscopic techniques all face distinct sources of interference and, at the single-cell or single-molecule level, nonspecific adsorption and environmental sensitivity exacerbate these limitations (Vasilescu et al., 2025).
Integrated, state-of-the-art strategies may address these challenges. High-resolution separations, multidimensional chromatography, and high-resolution mass spectrometry enhance discrimination of closely related species, while orthogonal detection methods, engineered antibodies and aptamers, CRISPR-based sensors, and machine learning–assisted signal deconvolution improve both selectivity and specificity (Martens et al., 2025). Looking forward, emerging technologies—including single-molecule and super-resolution imaging, nanopore sensing, high-throughput microfluidics, and AI-driven multi-omics—promise to deliver adaptive, multiplexed, and highly precise measurements (Mona, 2024). Together, these innovations are poised to extend the limits of bioanalytical performance, enabling the reliable characterization of biomolecular complexity in situ and in real time.
Real time monitoring of biological processes as they occur is crucial for understanding dynamic systems like metabolism, molecular signaling cascades in cells, or immune system responses involving a complex network of cells and soluble molecules (Gao et al., 2025). While, for example, in situ monitoring of single-cell neurotransmitters was achieved over 50 years ago (Adams, 1976), current methods can, at best, provide snapshots of these processes without the advantage of discerning critical temporal information. The challenge of real-time monitoring is the detection of events in complex systems and maintaining the integrity of the biological system while making its components available for analysis (Rubini et al., 2025). The challenge is best appreciated when recognizing that bioanalytical methods often require the destruction of a sample as a prelude to extraction or purification of molecules of interest. This makes it impossible to maintain the sample’s native environment where spatial and temporal relationships as well as chemical context may be key components of molecular function.
The spatial “omics” challenge involves mapping of molecules in cells or tissues with molecular resolution to produce maps of molecule location and interactions within their native environments. A July 2025 review in Cell (Skinnider et al., 2025) examines barriers hindering clinical deployment of single-cell omics and outlines requirements for deriving actionable clinical readouts. Spatial analysis can then be combined with multi-omics integration (Fulcher et al., 2024) where genomics, proteomics, metabolomics, and other “omics,” now evaluated separately, are integrated within large datasets for analysis of interactions and evaluation of biological phenotypes, an enormously complex challenge. Spatial omics technologies overlay molecular data onto biological spatial dimensions to provide high-resolution insights into cellular heterogeneity and tissue microenvironments, but analysis remains challenging due to high-dimensional, sparse data often contaminated by noise and uncertainty (Bai et al., 2024).
Applicability in new contexts challenges
Bioanalytical chemistry is increasingly applied beyond traditional clinical and pharmacokinetic studies (Cai et al., 2025), extending into environmental monitoring, food safety, and synthetic biology, where detection of trace analytes in complex matrices is essential (Shi et al., 2024). These emerging applications pose unique challenges, including high sample heterogeneity, interfering compounds, and the need for minimally invasive measurements in living systems. To address these demands, hybrid approaches combining chromatography, mass spectrometry, microfluidics, single-cell analysis, and biosensor technologies (Kontiza et al., 2024)—augmented by machine learning for data interpretation—are being deployed to enhance sensitivity, specificity, and throughput (Zhang et al., 2025). Looking forward, continued innovation in miniaturization, automation, and integrative analytical strategies will enable real-time, precise monitoring across diverse contexts, ensuring that bioanalytical chemistry remains a versatile tool for addressing complex scientific and societal challenges.
While laboratory results are essential elements in patient care, the use of sophisticated diagnostics at the patient bedside remains a persistent challenge (Zalama-Sánchez et al., 2024). The demand for sensitive, rapid, and affordable diagnostic techniques has surged, particularly following the COVID-19 pandemic, driving development of CRISPR-based diagnostic tools that provide precise, rapid, and portable diagnostics for on-site testing without access to extensive infrastructure. Machine learning is being embedded into various point-of-care testing modalities to enhance accuracy, sensitivity, and overall efficiency (Han et al., 2025).
Devices that are portable, affordable, require minimal training, yet capable of delivering rapid, accurate results for clinical decision-making, will become increasingly necessary for patient care, particularly in resource-limited settings (Wang et al., 2024). Developing such instrumentation is clearly challenging. This is particularly obvious when considering that standardization and reproducibility across laboratories and platforms remains difficult. This is especially true for complex biological measurements that take place in an environment that demands broad analytical capabilities that meet strict regulatory standards (Stuckey et al., 2024).
Notable progress in areas related to this grand challenge
There has been recent progress in existing areas such as analytical instrumentation that have advanced bioanalytical chemistry in the context of chemical biology. These contributions are important and representative of topics welcome in this journal.
Liquid Chromatography–Mass Spectrometry (LC–MS/MS) remains the cornerstone of quantitative proteomics, metabolomics, and drug–target engagement studies (Alanazi, 2025), while Capillary Electrophoresis–MS (CE–MS) (Pont et al., 2024) offers ultra-high resolution for charged biomolecules and single-cell metabolomics applications, and Ion Mobility Spectrometry (IMS) adds structural information and enhances resolution for complex molecular mixtures (Liu et al., 2023) and is now integrated with MS for 4D analyses.
Similarly, the Optical and Spectroscopic Techniques of Fluorescence and Fluorescence Resonance Energy Transfer (FRET) methods remain central to probing biomolecular interactions and conformational dynamics in live cells (Suryawanshi et al., 2025; Fang et al., 2023). These approaches have been extended to Single-Molecule Fluorescence Microscopy (Yan et al., 2025) to provide direct visualization of reaction kinetics and heterogeneity at the single-molecule level. Related methods such as Raman and Surface-Enhanced Raman Scattering (SERS) now provide label-free vibrational spectroscopy for molecular fingerprinting and live-cell metabolite tracking (Pirutin et al., 2023). Enhanced sensitivity via plasmonic substrates (and Infrared and Terahertz Spectroscopy provide complementary label-free detection of molecular structure and hydration dynamics in biological samples (Mor et al., 2025).
Electrochemical Biosensors, including voltametric, impedimetric and amperometric devices (Roehrich and Sepunaru, 2024; Dunham and Venton, 2024), have a long involvement with chemical biology, including in situ measurements on living cells. These allow real-time monitoring of metabolites, nucleic acids, or enzyme activity at sub-micromolar to attomolar levels. More sophisticated electrochemical approaches including Field-Effect Transistors (FET) (Smaani et al., 2024) and Plasmonic Nanosensors combine nanomaterials with transduction amplification for high-sensitivity, multiplexed detection (Mor et al., 2025) while Lab-on-a-Chip and Microfluidic Devices Enable integration of sample prep, reaction, and detection steps for high-throughput and point-of-care bioanalysis (Mazzaracchio and Arduini, 2025).
Imaging and Spatially Resolved Analysis (Lukowski et al., 2025), in addition to optical imaging methods, especially fluorescence imaging, are providing new types of imaging information. Mass Spectrometry Imaging (MSI) offers spatial metabolomic and proteomic maps in tissues (Mazzaracchio and Arduini, 2025), bridging analytical chemistry and systems biology. Super-Resolution (Yusoh et al., 2025) and Correlative Microscopy (Podlipec et al., 2025; Chen et al., 2025) integrates fluorescence, electron, and Atomic Force Microscopy (AFM) imaging to link molecular identity with cellular architecture. Cryo-Electron Microscopy (Cryo-EM) (Jeyaraj et al., 2025) offers sub-optical resolution structural elucidation of biomacromolecular assemblies.
Conclusion
In conclusion, meeting the goal of these bioanalytical challenges will permit us to understand the role of molecules in complex environments as, for example, the relationship between the microbiome and its host, where new analytical approaches will be required. These challenges drive innovation in instrumentation, materials science, computational methods, and fundamental measurement science and interdisciplinary collaboration between chemists, biologists, engineers, and clinicians.
Author contributions
GB: Writing – review and editing, Writing – original draft. DR: Writing – original draft, Writing – review and editing.
Funding
The author(s) declared that financial support was not received for this work and/or its publication.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author GB declared that they were an editorial board member of Frontiers at the time of submission. This had no impact on the peer review process and the final decision.
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Keywords: bioanalytical chemistry, challenges in sensitivity, challenges with specificity, extending bioanalytical chemistry to new areas of interest, single molecules
Citation: Barisas G and Roess DA (2025) Grand challenges in bioanalytical chemistry. Front. Chem. Biol. 4:1746545. doi: 10.3389/fchbi.2025.1746545
Received: 14 November 2025; Accepted: 08 December 2025;
Published: 19 December 2025.
Edited and Reviewed by:
Isabel Correia, University of Lisbon, PortugalCopyright © 2025 Barisas and Roess. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: George Barisas, Z2VvcmdlLmJhcmlzYXNAY29sb3N0YXRlLmVkdQ==