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Internal standards can introduce potential inaccuracies if the internal standard does not behave similarly to the analyte under the same experimental conditions, leading to systematic errors. Additionally, the cost and complexity of developing and validating internal standards can be high, particularly if they require specialized synthesis or characterization. Moreover, if the internal standard is not well-mixed or has variable concentration across samples, it can lead to inconsistent results. Finally, the presence of an internal standard could complicate data interpretation, especially in complex matrices.

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