Impurity Recovery

An impurity is a substance observed in the drug substance or drug product that isn’t intended to be a part of it. The same is applicable for the excipients used during the manufacturing of the drug product. These impurities can originate from synthesis, during the formulation process, through API excipient in compatibility, during stability due to degradation process, through packaging material and through different equipment when they come into contact with the formulation. These impurities are classified as organic, inorganic and elemental impurities. These undesired chemical entities required strict control and monitoring during release and stability studies through different high-end instruments like HPLC, GC, LCMS, GCMS. Impurity testing is a critical aspect of pharmaceutical analysis. Accurate impurity testing (Recovery of impurity from the sample) is essential to maintain the purity of the drug. Impurity testing is also important with respect to the safety and efficiency of medicine and patients. The impurity testing also ensures that regulatory compliance is met as per ICH Q3A and Q3B, as well as general chapters 232 and 233.

Analytical method development is a basic and critical part of the impurity testing. A stability-indicating method must be developed and validated for the quantification of impurities. This method should be able to detect all the possible listed impurities as well as the impurities observed during stress testing. A force degradation study is conducted, and a mass balance should be established to show that as the assay decreases, impurities increase. Linearity and recovery (accuracy) of impurity during validation plays important role in concluding that quantitation of impurities from the sample is performed accurately and precisely in each analysis. This topic will discuss the role of recovery, linearity and mass balance during stress testing of impurities.

Analytical Method Development and Validation

Analytical method development is a basic and critical part of impurity testing. A stability-indicating method must be developed and validated for the quantification of impurities. This method should be able to detect all the possible listed impurities as well as the impurities observed during stress testing. A forced degradation study is conducted, and a mass balance should be established to show that as the assay decreases, impurities increase. Linearity and recovery (accuracy) of impurities during validation play an important role in concluding that quantitation of impurities from the sample is performed accurately and precisely in each analysis. This topic will discuss the role of recovery, linearity and mass balance during stress testing of impurities.

Linearity of Impurity and Response Factor Determination:

A linearity experiment is performed on each known impurity by doing serial dilutions and by injecting equal concentrations of drug substance and impurities into chromatography, and the response is calculated. This response is then plotted as an area observed against the concentration injected, and by comparing the response of impurity at “X” concentration against the response of drug substance at the same concentration. This response factor is important during the quantification of impurities as it ensures the accurate and reproducible quantification of all impurities. It also ensures that when known impurities are not available or not stable at normal conditions, and it is not possible to inject these impurities during every analysis, this one-time activity of performing the response factor experiment is very helpful. Sometimes the cost of the impurities is also high and it is not possible to inject these impurities every time. It corrects for detector sensitivity differences between the impurity and the substance (API), ensuring compliance with regulatory standards (ICH). RRF is defined as the ratio of the response of an equal amount of an impurity to the drug substance, often determined by the slope method. Some organisations round the response factor value to 1.0 when the observed response factor is in the range of 0.80 to 1.2. or 0.90 to 1.1 and 0.95 to 1.05. The British pharmacopoeia does not recommend using the response factor if the observed value is less than 0.2 or higher than 5. If the response factor is calculated during validation, it will eliminate all the above issues. If the response factor is being used for the calculation of impurity levels in the sample, then linearity should be performed ahead of the recovery experiment to determine the response factor, and impurity recovery should be calculated by using the response factor. (refer Table-1)

Recovery of Impurity (Accuracy):

Accuracy or recovery determines the ability of the solvent to extract the product from a complex sample. The solvent used in the test method must be able to dissolve all the components in the sample matrix to ensure accurate results. The known impurities should be extractable within a range of 90% to 110% for a specification level up to 1.0%. For impurities with a specification of less than 0.5%, an accuracy range of 80% to 120% is acceptable. For LOQ (limit of quantitation) levels, an accuracy range of 75% to 125% is acceptable. These are generally acceptable limits with respect to specification but may vary from organisation to organisation. In general, the accuracy experiment is performed at LOQ, 50%, 100% and 150% levels for impurities with respect to specification. In this study, impurity solution at the mentioned concentration is spiked into the sample solution in triplicate and compared with unspiked samples for the response. Calculation of recovery or accuracy studies can be done against an individual impurity standard or against the response factor determined during the linearity experiment. (refer Tables 2 and 3).

Mass Balance:

Mass balance is a critical activity that refers to the calculation of the total quantity of drug substance and its associated impurities under stress conditions. Assay method and related substance method results are used to predict and draw conclusions on the mass balance. Samples are subjected to different stress conditions and analysed as per the method, and total impurities are reported. This value is then compared to the untreated samples’ results, and the mass balance is calculated. A properly designed and executed mass balance study ensures that the quantity of active ingredient and its degradation products is equal to the amount of drug present in the product before stress testing. Although there is no specific limit for mass balance, a mass balance between 95–105% is acceptable. If mass balance is achieved in this region, it also confirms the stability-indicating nature and reproducibility of an analytical method. Accurate mass balance also increases confidence in the quality of testing and data generated during analysis. If a mass balance is not achieved, it questions the ability of the analytical method with respect to specificity, to recover impurities, or a nonlinear response of the detector. It can be concluded that mass balance is not just an activity or mathematical calculation, but it also gives evidence of the specificity of the method. (refer Table-4).

Case Study Explained:

A related substance method with two known impurities is considered for the case study, and Linearity (Response factor calculation), Accuracy (Recovery) of impurities and Mass balance experiment results are tabulated.

Case Study Parameters

Test Concentration: 100ppm

Specification limit for Related compound A: NMT 0.3%

Specification limit for Related compound B: NMT 0.1%

Specification limit for unspecified Impurity: NMT 0.1%

Table-1 Linearity Experiment:

Concentration of Drug substance, Related compound A and Related compound B.

Linearity Levels	Drug Substance		Related Compound A		Related compound B
	Final Concentration (ppm)	Mean Area	Final Concentration (ppm)	Mean Area	Final Concentration (ppm)	Mean Area
Linearity-1 (LOQ)	0.030	0.160	0.030	0.153	0.029	0.158
Linearity-2 (50%)	0.508	2.581	0.150	0.700	0.049	0.273
Linearity-3 (100%)	1.015	4.999	0.299	1.402	0.098	0.531
Linearity-4 (120%)	1.218	6.096	0.359	1.693	0.118	0.644
Linearity-5 (150%)	1.523	7.587	0.449	2.113	0.147	0.797
Correlation coefficient (r)	1.000		1.000		1.000
Slope	4.965		4.685		5.407
Y-intercept	0.021		0.006		0.003
Relative Response Factor	NA		0.94		1.09
Correction/Response Factor	NA		1.06		0.92

Table-2: Accuracy for Related compound A (Limit 0.30%) (0.30ppm is 100%)

Accuracy Levels	Amount Added (ppm)	Amount Recovered (ppm)	% Recovery	Mean	SD	% RSD
Level-1 (LOQ)	0.030	0.030	98.9	94.7	3.71	3.92
	0.030	0.028	91.9
	0.030	0.028	93.3
Level-2 (50%)	0.152	0.147	96.8	96.5	0.28	0.29
	0.152	0.147	96.5
	0.152	0.146	96.2
Level-3 (100%)	0.304	0.294	96.6	97.0	0.39	0.40
	0.304	0.296	97.4
	0.304	0.295	97.0
Level-4 (150%)	0.456	0.450	98.8	98.5	0.19	0.20
	0.456	0.449	98.4
	0.456	0.449	98.5

Table-3: Accuracy for Related compound B (Limit 0.10%) (0.10ppm is 100%)

Accuracy Levels	Amount Added (ppm)	Amount Recovered (ppm)	% Recovery	Mean	SD	% RSD
Level-1 (LOQ)	0.030	0.029	98.1	97.5	0.62	0.63
	0.030	0.029	96.8
	0.030	0.029	97.5
Level-2 (50%)	0.050	0.051	102.5	101.9	1.07	1.05
	0.050	0.051	102.5
	0.050	0.050	100.7
Level-3 (100%)	0.100	0.097	97.0	97.3	0.28	0.29
	0.100	0.098	97.5
	0.100	0.097	97.3
Level-4 (150%)	0.150	0.149	99.1	98.9	0.12	0.12
	0.150	0.148	98.8
	0.150	0.148	98.9

Table 4: Forced Degradation Study results with Mass balance

Degradation Mechanism	Degradation Condition	Total Impurity (%)	% Assay	% Mass Balance
Control Sample	As Such Sample	0.03	99.8	N.A.
Acid treated sample	5.0 mL O.1N HCI, kept in Acid Hydrolysis water bath at 80°C for 15 minutes.	0.03	98.8	99.0
Base Treated sample	5.0 mL 0.5N NaOH, kept in water bath at 50°C for 90 minutes	5.15	90.7	96.0
Oxidation sample	5.0 mL 3% H202, kept in water bath at SO°C for IS minutes	1.17	97.9	99.2
Thermal Sample	Sample kept at 105°C in oven for 24 Hrs.	0.03	98.8	98.5
Humidity sample	Sample kept at – 90% RH at Room temperature for 72 Hrs	0.03	98.3	98.5
Photolytic Sample	Photo control Sample	0.04	98.8	99.0
	Photo exposed Sample	0.04	98.5	98.7

Conclusion:

Based on the data, it can be concluded that during impurity quantification in routine day-to-day analysis, response factor, accuracy and forced degradation parameters play an important role.

The three parameters discussed in this post, linearity (response factor), accuracy (recovery) and mass balance  are interdependent and must be evaluated together to build confidence in the analytical method. Linearity establishes the response factor, which is then used to calculate accurate impurity recovery. Recovery confirms that the method can reliably extract and quantify each impurity from the sample matrix. Mass balance, in turn, draws on both assay and impurity data to verify that the method accounts for all chemical changes introduced by stress conditions.

When mass balance falls within the acceptable range of 95–105%, it provides holistic evidence of method specificity, linearity, and reproducibility. Together, these three elements form the foundation of a robust stability indicating method and are essential to meeting regulatory expectations under ICH Q3A, Q3B, and related guidelines.

FAQ:

Reference:

• Halsey, Holst, et al. “Challenges with Retention and Recovery of Impurities Containing Acidic Moieties during Analytical UHPLC Method Development and Validation for Gefapixant Freebase.” Journal of Pharmaceutical and Biomedical Analysis, vol. 237, Elsevier BV, Oct. 2023, pp. 115772–72, https://doi.org/10.1016/j.jpba.2023.115772
• ‌Sinha, Anusha. “The Role of Mass Balance in Forced Degradation Studies: Ensuring Method Validity  -.” Resolvemass.Ca, 13 Nov. 2025, https://resolvemass.ca/forced-degradation-mass-balance/.