Recent Advances and Challenges in Multidimensional Chromatography for Complex Sample Analysis: Applications in Pharmaceutical, Environmental, Forensic and Biological Sciences

نویسندگان

1 Department of Pharmaceutical Analysis, C.L. BAID METHA COLLEGE OF PHARMACY, Affiliated to Dr. M.G.R. Medical University, Chennai, Tamil Nadu, India

2 Department of Pharmaceutical Analysis, C.L. BAID METHA COLLEGE OF PHARMACY, Affiliated to Dr. M.G.R. Medical University, Chennai, Tamil Nadu, India

3 Department of Pharmaceutical Analysis, C.L. BAID METHA COLLEGE OF PHARMACY, Affiliated to Dr. M.G.R. Medical University, Chennai, Tamil Nadu, India

4 Department of Pharmaceutical Analysis, C.L. BAID METHA COLLEGE OF PHARMACY, Affiliated to Dr. M.G.R. Medical University, Chennai, Tamil Nadu, India

doi
10.22036/abcr.2026.560857.2494
چکیده

Multidimensional chromatography (MDC) has grown into one of the most versatile and powerful tools in modern analytical science. Instead of relying on a single separation mechanism, MDC combines two or more complementary principles within one workflow, which greatly increases peak capacity, selectivity, and analytical reliability. Over the past few years, this field has seen major advancements—such as cryogen-free GC×GC modulators, innovative selective–comprehensive LC×LC combinations, greener SFC×LC strategies, and emerging setups like CE–LC and IMS-coupled systems. When these separation technologies are linked with high-resolution mass spectrometry platforms, including TOF, Orbitrap, and IMS-based analyzers, the result is far better compound identification and structural insight. At the same time, the use of AI-driven tools for tasks like deconvolution, feature alignment, and automatic spectral interpretation has made MDC workflows faster and more efficient. MDC now finds extensive use in pharmaceutical MAM strategies, proteoform profiling, environmental exposomes, forensic investigations, and deep omics studies. With growing emphasis on automation, miniaturization, and sustainability, MDC continues to advance while challenges related to 3D systems, real-time PAT integration, and cross-laboratory reproducibility define key future directions.