Is HPLC assay for drug substance a useful quality control attribute?
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Updated: Jul 14, 2026

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
Published on: April 23, 2019
Jeffrey D Hofer1, Bernard A Olsen, Eugene C Rickard
1Analytical Sciences Research & Development, Eli Lilly & Company, Lilly Corporate Center, Indianapolis, IN 46285, USA.
Abstract:
HPLC is a generally accepted method for assay of drug substances. However, recent claims cast doubts on the utility of HPLC assay methods for characterizing quality [S. Görög, J. Pharm. Biomed. Anal. 36 (2005) 931-937]. This study examines the utility of the traditional drug substance HPLC assay as a quality control parameter. HPLC assay data from more than 100 batches for each of eight drug substances were compared to results from a mass balance approach (100-impurities%). Estimates of the variability of HPLC assays from our data and from the literature ranged from 0.6 to 1.1% R.S.D. This variability is an appreciable portion of a typical acceptance range (e.g., 98.0-102.0%) and frequently exceeds the variability of the manufacturing process. Therefore, the results of the HPLC assay are questionable at best to determine the acceptability of the drug substance batch. The high variability also can generate a significant percentage of false out-of-specification (OOS) results, even when the "true" purity is 99.0-100.0%. Each false OOS leads to inefficiencies because of unwarranted investigations for a root cause and/or implementation of countermeasures for a problem that does not exist. Lastly, low precision makes it nearly impossible to detect significant changes in the process mean and/or degradation during a stability study. The use of a mass balance approach for assay retains essentially the same average results as the HPLC assay but gives standard deviations that are up to 10 times less. Monitoring the assay by mass balance allows for more precise process and stability monitoring and facilitates more rapid and accurate identification of process changes.
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