Technological Advances in Circulating Tumor DNA (ctDNA) Detection for Monitoring Minimal Residual Disease (MRD)

*Corresponding author: Zarfeen Fatima Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. Technological Advances in Circulating Tumor DNA (ctDNA) Detection for Monitoring Minimal Residual Disease (MRD) Zarfeen Fatima 1, *, Ayesha Nadeem 2, Aitzaz Sajid 1, Pakeeza Rehman 3 and Kinza Tariq 2 1 Aitzaz Lab and Diagnostic Centre Mandi Bahauddin, Punjab, Pakistan. 2 Department of Biochemistry, Faculty of science, University of Agriculture, Faisalabad, Punjab, Pakistan. 3 Department of Allied health sciences, faculty of science, university of Sargodha Punjab, Pakistan. World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 Publication history: Received on 23 September 2025; revised on 01 November 2025; accepted on 03 November 2025 Article DOI: https://doi.org/10.30574/wjbphs.2025.24.2.0939 Abstract The ability to assess minimal residual disease (MRD) through circulating tumor DNA (ctDNA) is revolutionary within oncology as it provides the most precise modality for identifying residual cancer post curative therapies. This review examines the advancements in the technologies for ctDNA-based MRD detection published from the year 2020 to present while briefly mentioning the technologies developed prior as a reference for the time line. This review explains the transformation of the older PCR-based technologies to next generation sequencing technologies which include digital PCR, tumor-informed assays like CAPP-seq, and novel technologies that analyze the tumor epigenome and fragmentome as well. All of these technologies demonstrate the increasing ability of the practitioner to identify and monitor cancer during treatment to custom the treatment and therapy to the patient. From the treatment of various different cancers there is specific disease, treatment and therapy monitoring and customizing available to the practitioner. However, there are still numerous issues such as standardization, analytical validation and routine clinical integration of the technology remain. This review aims to describe the available technologies, their integration within the clinical paradigm, assess their value and technologies and forecast the prospective of ctDNA MRD surveillance. Keywords: Cell-free DNA; Technologies; Cancer; digital PCR; Next generation sequencing 1. Introduction Circulating tumor DNA (ctDNA) consists of short segments of cell-free DNA that are released from apoptotic and necrotic tumor cells, providing a unique perspective on tumor biology and evolution (1). This integration of the detection and quantification of ctDNA into liquid biopsy technology represents a groundbreaking advancement, particularly in the field of monitoring MRD after curative intent treatment (2). Minimal Residual Disease, or MRD, is defined as small, clinically undetectable, residual cancer cells that remain post primary treatment (3). As a result, cancer cells that remain and are detectable through ctDNA testing are of a significant clinical and operative change to patient care, as clinicians can provide timely and targeted care before the patient undergoes a clinical relapse. Monitoring MRD through ctDNA is predicated by the notion that tumoral cells, through necrosis, apoptosis, and active secretion, incessantly release fragments of shed DNA into the bloodstream (4). Advanced cell-free DNA molecular techniques allow for the identification of tumor-derived fragments of ctDNA as opposed to “normal” circulating cell-free DNA (cfDNA) and these fragments of cfDNA contain tumor-specific, genetic, and epigenetic alterations (5). The clinical applications of ctDNA for MRD cancer detecti World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 69 on has been documented for colorectal cancer, lung cancer, breast cancer, and melanoma, and where post-treatment ctDNA is present, there is a notable risk for disease recurrence (6). Monitoring MRD requires different analytical approaches as the sensitivity and specificity required for MRD monitoring is distinct from diagnostic functionalities. When diagnosing a cancer, the tumor fraction is higher (0.1-10%) as compared to MRD monitoring where the fraction of circulating tumor DNA is only a minute 0.001-0.01% of the total cfDNA. This prompted the development of more advanced analytical techniques from basic quantitative PCR to next generation sequencing systems with molecular error correction and tumor-informed designed strategies (7). 2. Conventional methods In the early days, methods developed for ctDNA detection were based on standard quantitative PCR and allele-specific PCR techniques that focused on hotspot mutations(8). While these approaches were uncomplicated and inexpensive, they lacked sensitivity enough for analytical purposes where the detection thresholds were 0.1% - 1% of the variant allele fraction (9). In the case of ctDNA as used for MRD applications, where the concentration is several orders of magnitude lower, the approaches became even more inadequate, causing high false negative rates and limiting the utility of the method clinically (10). In the MRD setting, standard approaches to next-generation sequencing also do not employ molecular error correction and face the same challenges. With sequencing and DNA polymerase, the error rates of e.g. 10-3 to 10-4 creates a noise floor in low frequency variants (11). Issues such as low method specificity arising from false-positive results generated from PCR amplification, sequencing errors, and DNA damage artifacts (12). Conventional approaches also tend to remain focused on targeted gene panels or hotspot mutations. This fixation may not only overlook patient-specific variants but also tumor heterogeneity and clonal evolution concerns (13). In addition, the misidentification of clonal hematopoiesis of indeterminate potential (CHIP) mutations in cfDNA could result in a false positive. Age-related mutations may be misidentified as tumor-derived variants (14). Such limitations fuel the development of more robust and inclusive detection approaches. 3. Digital PCR (DPCR) Technologies Compared with qPCR, digital PCR (dPCR) has advanced the detection of circulating tumor DNA (ctDNA) by offering absolute quantification and greater sensitivity for low-frequency variants (15). This is due to the partitioning of the sample into thousands or millions of individual reactions which allows a binary (yes/no) detection of target molecules in a reaction without standard curves (16). The two primary systems for performing dPCR are droplet digital PCR and chamber-based digital PCR systems. Droplet digital PCR (ddPCR) is the most frequently used dPCR technology for ctDNA ofddPCR. The Bio-Rad QX200 and QX ONE systems produce 20,000 nanoliter-sized droplets per sample that can be used for individual PCR reactions (17). Such partitioning allows the detection of rare variants at 0.001% frequency and greater (18). Recent improvements to ddPCR technology focused on droplet generation, fluorophore chemistry, and data analysis (19). Extensive validation of the ddPCR analytical performance for MRD used numerous cancer types. For detection of KRAS, BRAF, and PIK3CA mutations in colorectal cancer, ddPCR is the most sensitive option and approaches detection levels of 0.01% VAF (20). For lung cancer, ddPCR has focused on EGFR mutations and provided strong clinical outcome correlations, while trends in ctDNA clearance provided prognostic information (21). The construction of multiplexed ddPCR assay technology is one of the recent advancements. This new technology has the ability to simultaneously identify several targets which is a considerable improvement over the original digital PCR which had extensive limitations in this regard (22). The design of probes using Locked Nucleic Acids (LNA) and Peptide Nucleic Acids (PNA) has resulted in increased specificity and decreased background noise (23). The introduction of automated sample preparation has decreased the amount of time spent on preparation and varied the reproducibility of ddPCR which brings this new technology even closer to routine clinical application (24). Nonetheless, with regard to the comprehensive monitoring of MRD, ddPCR has some basic shortcomings. The technology is designed for the precise detection of a limited, known, targeted variant, which lacks the broad-spectrum coverage expected from sequencing. Thus, the limited throughput of ddPCR technology also excludes it from population screening and other research applications where multiple samples of several analyses require simultaneous processing (25). World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 70 4. Comparison of representative MRD technologies Table 1 Comparison of MRD technologiesDrawn from supplied studies (5, 6, 8) Technology Typical LOD reported Personalization required Clinical validation examples ddPCR (targeted hotspots) practical low-percent to 0.01% scale with optimized input and workflows (5), (6) No (per-locus assays) HPV16 cfDNA detection workflows; comparative hotspot studies (5), (6) Tumor-informed NGS (personalized panels, UMI) down to ~0.02% variant allele fraction reported for deep panels; detection improves with number of tracked variants (8) Yes (tumor tissue informs panel) Large retrospective/prospective MRD cohorts and Signatera-style workflows showing MRD correlates with recurrence (8), (9), (10) Plasma-only epigenomic/fragmentomic assays variable; combining genomic + epigenomic increased sensitivity by ~25–36% versus genomic alone in CRC cohorts No (tumor-naïve) Plasma-only MRD in colorectal cancer with high PPV and improved sensitivity when integrating epigenomic signatures 4.1. Tumor Informed Personalized Sequencing By monitoring patient specific panels for tumor tissue that include dozens to thousands of somatic alterations, the tracking of minimal residual disease becomes increasingly more sensitive as the information from multiple independent variants is consolidated. Evidence, both commercial and academic, about postoperative ctDNA positivity and subsequent relapse is multiple and illustrates the effectiveness of these methods (8), (9), (10). 4.2. Methylation Assays In pilot validations across multiple tumor types, the targeted methylation qMSP panels (e.g., PcMM qMSP) demonstrated low copy number limits of detection (approximately 10 to 30 methylated copies) with a competitive turnaround and cost profile in comparison to NGS (7). 4.3. Error Suppression and Panel Design Strategies to curb false positive results in the contemporary MRD panel landscape involve unique molecular identifiers, matched white blood cell sequencing to remove clonal hematopoiesis and background noise databases (8, 11). The aforementioned strategies, alongside patterned panel design, scratch the surface of the efforts being made to resolve the challenges that MRD presents. 5. Next-Generation Sequencing Approaches Advanced sequencing technologies, coupled with molecular error correction, have enabled the analysis of multiple genomic regions to focus on sensitivity and specificity in detecting ctDNA-based MRD (26). These techniques can be categorized into tumor-informed and tumor-agnostic methods, each providing distinct advantages and applicable scenarios. Regarding the various next-generation sequencing ctDNA MRD methods, in aligned technical constructs, these have consolidated into three broad class distinctions. These include tumor-informed personalized sequencing where multiple patient-specific variants are monitored, tumor-naive targeted panels with deep error suppression, and the epigenomic or fragmentomic strategies that derive utility from methylation and fragmentation patterns (1, 3, 8). Key strategies focused on MRD detection prescribed limits and heightened confidence for MRD declarations include error suppression (unique molecular identifiers, statistical integration across many loci) and the broadening of variant lists (1, 8). World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 71 5.1. Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) CAPP-Seq is a new and innovative technique that combines ultra-deep sequencing of plasma cfDNA with personalized tumor profiling and was established by Diehn and coworkers (27). CAPP-Seq makes use of tumor tissue sequencing to detect patient-specific variants, and then customizing assays for circulating tumor DNA (ctDNA) by targeting these identified variants. The original CAPP-Seq protocol integrated sophisticated bioinformatics algorithms on top of molecular barcoding to suppress sequencing errors and achieved a detection limit of 0.02% Variant Allele Frequency (VAF) (28). The more recent versions of CAPP-Seq use more advanced technology. The addition of duplex sequencing technology has has greatly diminished the error rate, allowing the detection of variants at frequencies above 0.001% (29). The implementation of machine learning algorithms on capture probes has improved on-target capture efficiency and diminished off-target capture (30). The most recent advances in standardized protocol development and quality control metrics have made CAPP-Seq more widely adopted in more centers (31). CAPP-Seq has demonstrated robust clinical validation while expanding its use to various cancers. For clinical feasibility of CAPP-Seq-based MRD detection in non-small cell lung cancer, it surpassed standard imaging, achieving an impressive median lead time of 5.2 months before imaging showed disease progression (2). In studies involving colorectal cancer, findings were similar, with a post-operative ctDNA positive diagnosis and a disease recurrence risk set at 7.2 (32). 5.2. Targeted Error Correction Sequencing (TEC-Seq) TEC-Seq is an alternative tumor-informed method that reaches ultra-high sensitivity through the implementation of unique molecular identifiers (UMIs) and sophisticated error correction techniques (33). Like CAPP-Seq, tumor sequencing results are integrated into customized patient capture panels, but TEC-Seq uses different molecular barcoding and consensus calling techniques (34). TEC-Seq has better throughput and lower cost per sample while maintaining CAPP-Seq comparable detection limits. The unique feature of TEC-Seq is its highly sophisticated error correction techniques that combine molecular barcoding, strand-aware consensus calling, and noise background modeling (35). This enables the highly confident distinguishing of true low-frequency variants from high-frequency artifacts. Machine learning has been applied to improve the accuracy of variant calling and the reduction of false-positive rates (36). 5.3. Safe-Sequencing System (SAFE-Seq) The first Early NGS based ultra-sensitive variant detection system is SAFE-Seq, created by Vogelstein and others (26). Unique molecular identifiers and primer amplification are incorporated in the technology to make it versatile enough to detect rare variants (37). Although it was not tailored for MRD systems, the basic principles of SAFE-Seq have been modified into a number of commercial and research systems (38). The greatest contribution of SAFE-Seq is the incorporation of unique identifiers for every DNA strand before amplification, allowing for the detection and rectification of amplification and sequencing errors (39). This has been invaluable in the detection of low frequency mutations in difficult to work with samples such as FFPE tissues and degraded cfDNA (40). 6. Tumor-Agnostic Approaches Although tumor-informed strategies have greater sensitivity for known variants, tumor-agnostic methods have more comprehensive scope and do not necessitate prior analysis of tumor tissue (41). These methods tend to use large gene panels or perform whole-exome sequencing and use sophisticated bioinformatics to detect tumor-derived variants (42). Guardant360 and FoundationOne Liquid CDx are examples of clinically-implemented, commercially available tumoragnostic approaches for MRD monitoring (43). These systems utilize proprietary error correction algorithms and clinically validated algorithms for various cancers to analyze 70-500+ genes (44). However, and particularly for the MRD applications, the sensitivity of these systems is lower than that of tumor-informed methods because tumoragnostic methods must analyze more genomic territory than can be sequenced with the available sequencing depth (45). 7. Emerging Technologies and Novel Approaches The detection of circulating tumor DNA (ctDNA) continues to develop, particularly with new technologies that enhance minimal residual disease (MRD) monitoring. These efforts emphasize increasing the detection sensitivity, decreasing costs, increasing sample processing capabilities, and broadening the types of molecular data that can be obtained from cell-free DNA (cfDNA) samples. World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 72 7.1. Epigenomic Approaches Patterns of DNA methylation in ctDNA still need to be exploited for tumor-specific information (46). Because of their more significant population coverage, unlike genetic mutations which are limited to certain subclonal tumor populations, epigenetic alterations are more likely to be detected in cases of MRD (47). There are several methodologies for examining methylation in cfDNA, including bisulfite sequencing, methylation-specific PCR, and targeted methylation arrays (48). Cristiano and colleagues developed the CancerSEEK platform, which integrates genetic and epigenetic information to enhance the sensitivity of cancer detection (49). Recent modifications of this methodology for MRD monitoring are methylation-based signatures, which proved to be highly informative in combination with mutationbased detection (50). For advanced cases of diseases, methylation techniques help in the detection of neoplasms that have low mutation burdens, including specific pediatric cancers and some adult cancers (51). 7.2. Fragmentomic Analysis Due to variations in size, distribution, and fragmentation of cfDNA, it is possible to trace DNA back to the tumor and differentiate it from normal cfDNA (52). Fragmentomic analysis studies the distribution and length of fragments and the specific end motifs (53). This approach has facilitated the design of frameworks for the integration of genetic and epigenetic analyses, where both are employed as multi-modal detection techniques (54). Recent studies show contrasts in the length of tumor-derived cfDNA fragments and normal cfDNA fragments, with the former being shorter and having distinctive periodicity (55). Machine learning models are created to capture these differences for use in ctDNA detection systems (56). DELFI (DNA Evaluation of Fragments for Early Interception) is one of the first systems designed for fragmentomic analysis in cancer screening and monitoring (57). 7.3. Protein-Based Approaches With respect to the integration of protein liquid biopsies with ctDNA to create protein multi-analyte liquid biopsies, this has just begun to garner interest in the field (58). Further information with respect to ctDNA analysis can be gathered from circulating tumor cells (CTCs), extracellular vesicles, as well as soluble protein biomarkers and tumoral interstitium (59). 7.4. Artificial Intelligence and Machine Learning Integration of AI and ML into the technology advancement of ctDNA analysis (60). Several cross-sectional aspects of ctDNA analysis would result in the improved accuracy of variant calling, the suppression of background noise, and clinical interpretation feedback (61). In deep learning especially, algorithms can evaluate complex patterns in sequencing that are missed by older approaches (62). Numerous commercial platforms apply AI and ML algorithms in their analytics. In the case of the Exact Sciences Cologuard test, it employs machine learning to analyze methylation patterns (63). Likewise, the GRAIL Galleri test uses deep learning to analyze methylation patterns of multiple cancers (64). Such technologies are likely to advance the role of ML and AI in ctDNA-based MRD monitoring. 8. Clinical Applications and Validation Studies The clinical translation of ctDNA-based MRD monitoring is one area that has advanced very quickly. Numerous studies have demonstrated its applicability to several cancers and different clinical environments. This led to the construction of clinical guidelines and received the necessary regulatory endorsements to move forward as prospective large-scale trials. 8.1. Colorectal Cancer Colorectal cancer is among the most frequently diagnosed cancer cases in the world. In addition, it has been the most studied cancer type in ctDNA MRD monitoring, supporting its clinical utility in large-scale studies such as CIRCULATEJapan. In this study, which included over 1,000 patients with stage II-III colorectal cancer, it was shown that ctDNA positivity after surgery correlated with a recurrence risk that was several times greater (hazard ratio 3.8, 95% CI 2.46.1) (65). CIRCULATE-Japan also demonstrated that ctDNA as a prognostic factor stood independently of other clinicopathological factors (66). DYNAMIC is the first randomized controlled trial that studies ctDNA-guided treatment in colorectal cancer (67). Patients with post-surgical ctDNA positivity were randomized to receive either adjuvant chemotherapy or surveillance, while patients with ctDNA negativitiy were monitored without any treatment (68). DYNAMIC demonstrated that treatment based on ctDNA levels provided similar outcomes as the standard of care, thus proving that overtreatment in patients with negative ctDNA could be avoided (69). World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 73 More studies have also been done in use of ctDNA monitoring during and post adjuvant chemotherapy. In the COBRA study, it was shown that recurrence risk increased when ctDNA was persistently present, whilst renewed positivity after ctDNA clearance was associated with worse outcomes (70). These were the findings that most likely influenced the inclusion of ctDNA testing in clinical guidelines and the construction of ctDNA-guided treatment protocols (71). 8.2. Lung Cancer Non-small cell lung cancer (NSCLC) is a major application area for ctDNA-based MRD monitoring. ctDNA detection preceded radiographic progression by a median of 70 days in the TRACERx study (a landmark longitudinal analysis of tumor evolution) (72). Using a tumor-informed approach, the study also demonstrated that, in the majority of patients, ctDNA monitoring coupled with conventional imaging provided the earliest diagnosis of disease recurrence (13). Multiple investigations have been conducted on ctDNA monitoring in the adjuvant treatment stage for early-stage NSCLC. The ADAURA study, which focused mostly on osimertinib efficacy and conducted ctDNA analysis, showed that disease-free survival was shorter when patients presented with ctDNA positive NSCLC (73). Further investigations showed that there was an association between improved outcomes and ctDNA clearance during treatment with osimertinib (74). Combining ctDNA monitoring with the use of immunotherapy has been particularly promising in lung cancer. Studies have shown that during treatment with immune checkpoint inhibitors, ctDNA kinetics can predict response and identify patients who are more likely to experience disease progression (75). Monitoring ctDNA alongside immune biomarkers like tumor mutation burden could be useful for prediction (76). 8.3. Breast Cancer Research on circulating tumor DNA (ctDNA) in breast cancer concentrates primarily on early diagnosis and monitoring patients during the adjuvant phase (i.e. post-surgical treatments aimed at minimizing the likelihood of cancer recurrence). The c-TRAK TN study, for example, illustrated the potential of ctDNA as a monitoring tool for aggressive breast cancer (triple-negative breast cancer). The study reported that the presence of ctDNA post-surgery was associated with considerably shorter disease-free intervals (77). The study demonstrated that ctDNA, using a tumorinformed approach, provided prognostic information that was considerably greater than what standard clinical metrics (i.e. tumor size/stage) provided (78). For hormone receptor-positive breast cancer, ctDNA research has been primarily aimed at informing adjuvant endocrine therapy (i.e. hormone-blocking therapy). The identification of ESR1 mutations in ctDNA has been described as a definitive way of flagging resistance to aromatase inhibitors, a key treatment for advanced breast cancer (79). Moreover, the integration of ctDNA with other liquid biopsy techniques, like circulating tumor cell analysis, is viewed as an important strategy to streamline the assessment and longitudinal management of the disease (60). 9. Challenges and Limitations Significant advancements have been achieved in ctDNA-based MRD monitoring. However, for comprehensive clinical application, there are still gaps that need to be filled. 9.1. Analytical Challenges Detecting minimal residual disease (MRD) is particularly challenging because the concentrations of circulating tumor DNA (ctDNA) are so low that even the most advanced technologies are likely to miss evidence of clinically relevant disease (80). The unpredictable patterns of tumor shedding ctDNA create additional challenges, as negative results do not always signify that no residual disease is present (81). Moreover, preanalytical variables, such as the collection, processing, and storage of samples, may contribute to instances where ctDNA is not present when it is expected to be, leading to challenges around disease detection. Continued efforts are needed to devise more effective strategies to mitigate these challenges (82). In addition, the non-uniformity of testing frameworks and laboratory setups is a major obstacle. The absence of coherent protocols results in highly disparate outcomes that physicians cannot interpret consistently (83). To address these problems, the development of reference materials, calibration standards, and proficiency testing in quality control will be essential in aligning the disparate laboratories in the world (84). 9.2. Biological Challenges Understanding the biology behind the shedding of circulating tumor DNA (ctDNA) perplexes researchers. Tumor characteristics such as size, location, blood supply, and tissue type influence the levels of circulating tumor DNA even when the tumor burden is similar in clinical cases (85). Certain cancers, particularly those with fewer mutations or World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 74 specific histological subtypes, release cognate DNA at even lower levels and challenge the limits of contemporary detection methods (1). Clonal hematopoiesis adds complexity as well. Age-related mutations in blood cells result in cellfree DNA (cfDNA) fragmentation that can be classified as tumor-related mutations (86). Although sequencing matched leukocytes provides some clarity, cfDNA analysis becomes even more convoluted and costly (87). 9.3. Clinical Challenges There are also challenges associated with integrating ctDNA into routine clinical practice. For example, in urgent clinical scenarios, the typical 7-14 day turnaround time is largely inadequate (88). Moreover, the expensive tumor-informed testing strategy that involves both tumor tissue and plasma sequencing is futile and burdensome in decision-making (89). Moreover, physicians require adequate education to interpret ctDNA results accurately. Familiarity with the tests’ constraints, their analytical capabilities, and their role in the whole clinical context of the patient is essential (90). Improved clinical decision support systems along with more refined treatment pathways will facilitate clinicians' ability to employ these tests optimally (91). 9.4. Regulatory and Reimbursement Challenges As the regulatory environment around ctDNA testing continues to develop, an asymmetry of compliance mandates for lab-developed tests and FDA-approved ones will remain (80). The evidence needed to support regulatory approval, and to obtain reimbursement for clinical use, is considerable and, in some cases, will require obtaining evidence through large randomized controlled trials (92). The lack of standard reimbursement policies for ctDNA testing, and partial reimbursement for its clinical uses, add to the challenges. To justify complete reimbursement, cost-effectiveness analyzes of treatment plans guided by ctDNA must be done (93). Establishing billing codes and reimbursement policies is crucial for the clinical use of ctDNA testing (94). 10. Comparative Analysis of Technologies A range of challenges and opportunities arises from the various technologies in ctDNA detection concerning their clinical implementation. Each method’s pros and cons help define its clinical utility. Table 2 Analysis of technologies Technology Sensitivity (VAF) Throughput Turnaround Time Cost Multiplexing Capability Key Advantages Key Limitations ddPCR 0.0010.01% LowMedium 4-6 hours LowMedium Limited (1-4 targets) High precision, absolute quantification Limited breadth, single/few targets CAPP-Seq 0.0010.02% Medium 7-14 days High High (100+ targets) Ultra-high sensitivity, personalized Requires tumor tissue, complex workflow TEC-Seq 0.0010.01% Medium 7-14 days High High (50-200 targets) Excellent error correction Requires tumor tissue, high cost Tumoragnostic NGS 0.01-0.1% High 7-14 days MediumHigh Very High (300+ targets) No tumor tissue required Lower sensitivity, higher background Methylationbased 0.01-0.1% MediumHigh 7-14 days Medium High Applicable to low-mutation cancers Less mature technology Fragmentomics Variable High 2-7 days LowMedium N/A Rapid, costeffective Requires combination with other methods World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 75 11. Future Perspectives and Technological Developments Post-market ctDNA MRD monitoring is growing and new technologies are being developed to address some of the field’s limitations and expand ctDNA MRD monitoring’s various clinical applications. 11.1. Next-Generation Technologies A variety of different technologies are being built and refined that will enhance ctDNA detection. Single-molecule sequencing technologies, like the ones being developed by Oxford Nanopore and Pacific Biosciences, will allow the direct analysis of cfDNA which will eliminate the need for PCR amplification, cut down on some amplification artifacts, and enhance sensitivity of cfDNA (95). These technologies will enable clinicians to perform real-time analyses and receive test results in a matter of minutes (96). Recent developments in microfluidic technology will optimize the ctDNA monitoring procedure to the point where it can be conducted at the site of clinical care and returned within hours. Clinicians will be enabled to make clinical decisions in real time rather than depending on burdensome logistical arrangements typical of centralized testing (97). 11.2. Artificial Intelligence and Machine Learning The integration of AI, ML, and automation technologies with ctDNA analysis is likely to be groundbreaking. Computational tools will enhance the precision and accuracy of variant calling, identify false-positive variants, and autonomously detect complex analytical patterns that are currently undetected by human analysts (98). Deep learning for the first time will help automate the analysis of complex genomic patterns and the integration of various data types (99). AI-driven clinical decision support systems might analyze ctDNA reports and help in making treatment decisions. These systems might generate recommendations considering unique patient variables, historical treatment data, and contemporaneous treatment monitoring systems (100). Future liquid biopsies will most probably involve more than one analyte and more than one detection technology. Disease monitoring can be more comprehensive if analyses of ctDNA are coupled with other profiling techniques for integrative assessment of disease markers such as protein variables, circulating tumor cells, extracellular vesicles, and metabolomic profiling (58). 11.3. Regulatory Evolution The evolution of the guidance documents and pathways for the regulation of MRD monitoring applications will shape the future of regulation for ctDNA testing. The FDA is expected to continue approving ctDNA tests as more clinical evidence emerges and several of these tests have already been approved for different indicationsfd. The approval and clinical implementation of regulated companion diagnostic tests for specific therapies will probably be to obtain regulatory approval faster (80, 92). 11.4. Clinical Integration The implementation of pathways and algorithms for clinical integration of ctDNA monitoring will be essential for establishing comprehensive integration. There is early stage work being done to establish guidance documents for specific clinical applications of ctDNA, but the more important work is the development of guidance documents for broader clinical applications and the consensus for these to be adopted (91). The clinical support frameworks and provider education will be fundamental for the appropriate utilization of the tests (90). 12. Conclusion The specific cancer care approaches that incorporate circulating tumor DNA (ctDNA) opened new options for personalized and precise MRD monitoring technimolecular approaches within treatment. Modern error-corrected sequencing identifies ctDNA with high sensitivity to aid numerous cancers and to assess response, evaluate recurrence, and predict therapy. The application of ctDNA continues to expand with CAPP-Seq, developments within epigenetics, and fragmentomics. Problems within standardization, cost, and clinical adoption of these technologies still pose challenges. Emerging resources like AI and point-of-care testing are expected to meet these challenges. Routine clinical integration of ctDNA monitoring will improve diagnosis and outcomes. This is dependent upon collaboration and a shift to real-world implementation from scientists, clinicians, and policymakers. World Journal of Biology Pharmacy and Health Sciences, 2025, 24(02), 068-080 76 Compliance with ethical standards Disclosure of conflict of interest No conflict of interest to be disclosed. References [1] Wan JC, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas C, et al. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nature Reviews Cancer. 2017;17(4):223-38. 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