Scholarlink

<p>Chemotherapy remains a cornerstone in the treatment of multiple solid and gynecologic malignancies, including endometrial cancer, ovarian cancer, and breast cancer. Carboplatin, epirubicin, gemcitabine, paclitaxel, topotecan, and docetaxel are widely used in combination regimens; however, there is still a lack of sensitive, rapid, and multiplex technologies for real-time monitoring of chemotherapeutic drug concentrations. In this study, we developed a carboxyl-polyethylene glycol (PEG)-modified magnetite (Fe₃O₄@PEG) nanoplatform combined with artificial intelligence (AI)-driven spectral analysis to achieve ultra-sensitive and multiplex detection of six chemotherapeutic drugs. Fe₃O₄ nanoparticles were synthesized by co-precipitation and subsequently functionalized with carboxyl-PEG to enhance drug capture efficiency and resistance to matrix interference. Using a confocal Raman imaging system, SERS spectra of single and mixed drug systems were collected, and convolutional neural networks (CNNs) were employed for automated feature extraction and classification to enable qualitative and quantitative analysis. The constructed SERS platform achieved 10⁻⁷–10⁻⁸ milligrams per milliliter (mg/mL) detection limits for all six drugs in serum matrices, with classification accuracies exceeding 95% in multiplex mixtures. For improved quantitative accuracy and normalization, the 2078 cm⁻<sup>1</sup> Raman peak of deuterated methanol (CD₃OD) was employed as an internal standard to correct for potential fluctuations in laser intensity and sample concentration. Within the simulated therapeutic concentration range, quantitative regression yielded <i>R</i><sup>2</sup> ≥ 0.98. This AI-SERS platform offers advantages of multiplex detection, trace-level sensitivity, and strong anti-matrix interference, holding great promise for pharmacokinetic monitoring and individualized chemotherapy optimization across a broad range of solid tumors.</p> Graphical abstract <p>Schematic illustration of an AI-integrated Fe<sub>3</sub>O<sub>4</sub>@PEG–SERS nanoplatform for multiplex detection of six chemotherapeutic agents (carboplatin, epirubicin, gemcitabine, paclitaxel, topotecan, and docetaxel). Carboxyl-PEG–modified magnetite nanoparticles enhance drug adsorption and stability, while convolutional neural networks enable accurate qualitative and quantitative spectral analysis for personalized chemotherapy optimization.</p> <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Application of surface-enhanced Raman scattering combined with artificial intelligence for multiplex detection of chemotherapeutic agents used in solid tumors

  • 期刊论文

  • 发表日期：

    2025年12月1日

查看全文
  • Biqing Chen,
  • Jiayin Gao,
  • Haizhu Sun,
  • Yinghan Zhao,
  • Yan Liu,
  • Xinpeng Lv,
  • Xiaohong Qiu,
  • Yang Li

摘要

Chemotherapy remains a cornerstone in the treatment of multiple solid and gynecologic malignancies, including endometrial cancer, ovarian cancer, and breast cancer. Carboplatin, epirubicin, gemcitabine, paclitaxel, topotecan, and docetaxel are widely used in combination regimens; however, there is still a lack of sensitive, rapid, and multiplex technologies for real-time monitoring of chemotherapeutic drug concentrations. In this study, we developed a carboxyl-polyethylene glycol (PEG)-modified magnetite (Fe₃O₄@PEG) nanoplatform combined with artificial intelligence (AI)-driven spectral analysis to achieve ultra-sensitive and multiplex detection of six chemotherapeutic drugs. Fe₃O₄ nanoparticles were synthesized by co-precipitation and subsequently functionalized with carboxyl-PEG to enhance drug capture efficiency and resistance to matrix interference. Using a confocal Raman imaging system, SERS spectra of single and mixed drug systems were collected, and convolutional neural networks (CNNs) were employed for automated feature extraction and classification to enable qualitative and quantitative analysis. The constructed SERS platform achieved 10⁻⁷–10⁻⁸ milligrams per milliliter (mg/mL) detection limits for all six drugs in serum matrices, with classification accuracies exceeding 95% in multiplex mixtures. For improved quantitative accuracy and normalization, the 2078 cm⁻1 Raman peak of deuterated methanol (CD₃OD) was employed as an internal standard to correct for potential fluctuations in laser intensity and sample concentration. Within the simulated therapeutic concentration range, quantitative regression yielded R2 ≥ 0.98. This AI-SERS platform offers advantages of multiplex detection, trace-level sensitivity, and strong anti-matrix interference, holding great promise for pharmacokinetic monitoring and individualized chemotherapy optimization across a broad range of solid tumors.

Graphical abstract

Schematic illustration of an AI-integrated Fe3O4@PEG–SERS nanoplatform for multiplex detection of six chemotherapeutic agents (carboplatin, epirubicin, gemcitabine, paclitaxel, topotecan, and docetaxel). Carboxyl-PEG–modified magnetite nanoparticles enhance drug adsorption and stability, while convolutional neural networks enable accurate qualitative and quantitative spectral analysis for personalized chemotherapy optimization.