AI Article Synopsis

  • qNMR can struggle with accurately measuring low-purity organic compounds because it can't always separate unwanted signals from the target signal.
  • The HPLC-qNMR method first removes impurities via HPLC, making the quantification of the main compound easier and more accurate, saving time and money compared to traditional methods.
  • The new ISC-HPLC-qNMR approach adds a correction factor for cases where HPLC can't fully purify samples, improving accuracy and allowing for analysis without needing to identify all impurities.

Article Abstract

Quantitative nuclear magnetic resonance (qNMR) has a potential risk of inaccurate quantification of complex organic compounds with low purity due to incomplete separation of the impurity signals and the target component signals. The high performance liquid chromatography-qNMR (HPLC-qNMR) method removes impurities from the sample by HPLC and accurately determines the purity of the sample by qNMR, avoiding the laborious, time-consuming, and costly step of qualitative and quantitative determination of impurities in conventional mass balance methods. An improved method, named post-collection purity correction for internal standard correction-HPLC-qNMR (ISC-HPLC-qNMR), was developed and demonstrated on a complex compound oxytetracycline with low purity. In this method, a correction factor was introduced to compensate for the inability to achieve 100% purity through the HPLC purification procedure. The purity value with standard deviation of the oxytetracycline study material using this method was 82.00% ± 0.82%, while that obtained from the conventional qNMR with deconvolution was 81.70% ± 0.35%. The consistency of these results demonstrated that the improved method extends the applicability to the samples where HPLC is not capable of purifying complex compounds with low purity to near 100%, especially containing highly similar structural-related impurities. Furthermore, this method allows purification and quantification without the need to identify impurities in the sample, resulting in significant savings of time and cost. Additionally, it effectively compensates for the limitations of qNMR deconvolution in handling peak overlap in the sample.

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Source
http://dx.doi.org/10.1039/d4ay00949eDOI Listing

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