Analytical Procedure Development and Proposed Established Conditions: A Case Study of a Mass Spectrometry Based NDSRI Analytical Procedure

Abstract

With the finalization of the ICH Q14 Analytical Procedure Development guideline, how to apply enhanced approaches (such as analytical quality by design (AQbD)) to develop an analytical procedure, and to propose Established Conditions (ECs) and corresponding reporting categories, is increasingly being discussed. To gain practical experience in applying an enhanced approach for method development and identifying ECs, we developed, validated, and implemented an analytical procedure for a nitrosamine drug substance-related impurity (NDSRI). Here, as an example of the application of Q12 Lifecycle Management guideline principles in regards to analytical procedures, we briefly elaborate how: 1) the principles documented in the ICH Q14 guideline for analytical procedure development were applied, with the focus on identifying an Analytical Target Profile (ATP), knowledge management and risk assessment; 2) analytical procedure robustness according to the recommendations in ICH Q2(R2) Validation of Analytical Procedure guideline and Q14, were evaluated; and 3) mass spectrometry ECs and associated proposed reporting categories were proposed.

Introduction

In accordance with the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q12 Lifecycle Management guideline,¹ Established Conditions (ECs) for analytical procedures may include method parameters, operational conditions, and acceptance criteria. Applicants may propose ECs and reporting categories for changes to the analytical procedure that differ from those described in regulations found in 21 CFR 314.70 or 21 CFR 601.12 and guidance regarding changes to approved applications or licenses. The extent of ECs and their reporting categories could vary based on the understanding of the relationship between analytical procedure parameters and analytical procedure performance, the analytical procedure complexity, and control strategy. A justification to support the identification of ECs and corresponding reporting categories for changes to ECs based on risk management and development data may be provided to regulators to obtain post-approval regulatory flexibility. With the finalization of the ICH Q14 Analytical Procedure Development guideline,² how to apply enhanced approaches (such as analytical quality by design (AQbD)) to develop an analytical procedure, and to propose ECs and corresponding reporting categories, is increasingly being discussed.^3–5

To gain practical experience in applying an enhanced approach for method development and identifying ECs, we developed, validated, and implemented an analytical procedure for a nitrosamine drug substance-related impurity (NDSRI). Specifically, a tandem mass spectrometry (MS/MS) instrument without a liquid chromatographic delivery step instrument was used to quantitate N-nitrosobumetanide in bumetanide drug products using d5-N-nitrosobumetanide as internal standard (IS). The analytical procedure was developed in support of a recently published FDA study investigating mitigation approaches for NDSRIs using bumetanide as a model drug.⁶ Here, as an example of the application of Q12 principles in regards to analytical procedures, we briefly elaborate how: 1) the principles documented in the ICH Q14 guideline² for analytical procedure development were applied, with the focus on identifying an Analytical Target Profile (ATP), knowledge management and risk assessment; 2) analytical procedure robustness according to the recommendations in ICH Q2(R2) Validation of Analytical Procedure guideline⁷ and Q14, were evaluated; and 3) mass spectrometry ECs and associated proposed reporting categories were proposed.

Material and Methods

The N-nitrosobumetanide standard and IS d5-N-nitrosobumetanide were purchased from Toronto Research Chemicals and TLC Pharmaceutical Standards Ltd, respectively. Stock solutions were prepared in methanol and working solutions were made by diluting stock solutions with 50 % methanol in water (v/v). Commercially available and in-house formulated bumetanide drug products⁶ (tablets) were grounded and extracted with five volumes (v/w) of ethyl acetate by sonicating for 30 min in a water bath, and then spinning them in a centrifuge at 30,000 g for 10 min. The supernatant was dried under vacuum and then reconstituted with one volume of 50/50 methanol/water, sonicated for 30 min in a water bath, and then spun in a centrifuge at 30,000 g for 10 min. The supernatant was then mixed 1:4 with 50 ng/mL IS working solution.

The tandem mass spectrometry method for quantifying N-nitrosobumetanide was developed using an Agilent 6460C Triple Quadrupole MS/MS system interfaced with a non-chromatographic sample delivery system (Agilent 365 RapidFire). The principle of sample delivery is similar to liquid chromatography though the there is only limited separation. More details about the instrument had been described in our previous publications.^8,9 Processed samples were loaded onto C18 cartridge with 0.1 % formic acid in water (1.25 mL/min) and eluted with 0.1 % formic acid in methanol (0.6 mL/min). The time for aspiration, load/wash, elution and re-equilibration time was 600, 6000, 7000 and 2000 ms, respectively. The mass spectrometry was operated under polarity switch mode and Multiple Reaction Monitor (MRM) data acquisition parameters are listed in Table 1. Electrospray Ion Source (ESI) parameters were optimized as follows: gas temperature 350 °C; gas flow 13 L/min; sheath gas heater 300 °C; capillary voltage 3000 V. Peak areas were calculated using Agilent RapidFire Integrator^® software.

Table 1.

MRM parameters for analyte and internal standard.

	Precursor ion m/z	Product ion m/z	Fragmentor (V)	CE	Cell accelerator voltage	Dwell time (ms)
Negative mode
Nitroso-bumetanide, Quantifier	392.1	318.1	100	15	3	10
Nitroso-bumetanide, Quanlifier	392.1	362.1	100	6	3	10
d5-Nitroso-bumetanide (IS), Quantifier	397.1	323.1	100	15	3	2
d5-Nitroso-bumetanide (IS), Quanlifier	397.1	367.1	100	6	3	2
Positive mode
Nitroso-bumetanide, Quanlifier	394.1	321.1	100	18	3	10
Nitroso-bumetanide, Quanlifier	394.1	364.1	100	10	3	10
d5-Nitroso-bumetanide (IS), Quanlifier	399.1	326.1	100	18	3	2
d5-Nitroso-bumetanide (IS), Quanlifier	399.1	369.1	100	10	3	2

Results and Discussion

The analytical procedure was validated for the following validation parameters: specificity, accuracy, precision, sensitivity and analytical range, according to the ICH Q2(R1) guideline.¹⁰ The quantitation limit (QL) for the method was 0.1 ppm (supplemental fig. 1) and the linear range was 0.1–500 ppm (supplemental fig. 2). Method turnaround time was rapid, documented at 15.6 s per sample. The method was implemented for >1000 in-house formulated bumetanide drug product samples as part of an FDA research project on mitigating NDSRI formation in-house manufactured drug products.⁶

Analytical Target Profile

Method design and development began with defining the Analytical Target Profile (ATP).² The ATP requirements relate primarily to the intended purpose. Table 2 illustrates the ATP proposed using the “Sakuratinib Maleate” case described in section 13.1.1 of ICH Q14 guideline² as template. The project was completed before FDA published Recommended Acceptable Intake Limits for Nitrosamine Drug Substance-Related Impurities (NDSRIs) Guidance for Industry.¹¹ A sensitivity of 0.1 ppm QL was necessitated by the proposed acceptable intake (AI) limit of 26.5 ng N-nitrosobumetanide when the project started (the updated AI limit is 1500 ng/day¹¹). Specificity was equally crucial to ensure no interference caused by other components in drug product samples.

Table 2.

Analytical target profiles.

Intended Purpose
Investigation of the impact of additives on the formation of N-nitrosobumetanide in-house formulated bumetanide drug products
Link to Critical Quality Attribute (Control of NDSRI)
The analytical method should be capable of quantifying N-nitrosobumetanide, with:
1) a sensitivity which can meet the AI limit set by the FDA.
2) specificity, report range, accuracy and precision which can detect and differentiate between the mitigating effect of different additives in the drug product formulation.
Characteristics of the Reportable Results
Performance Characteristics	Acceptance Criteria	Rationale
Specificity	Absence of interference in blank sample matrix	General recommendation by ICH Q2 and Q14 guidelines
	Quantifier/Qualifier ratio for test samples within 80–120 % of that for QC samples	Recommendation in ICH Q2(R2) Annex II7 Good practice currently being used by regulatory agencies for quantifying nitrosamines9,13–15
Sensitivity	Quantitation limit (QL) of0.1 ppm	The QL of0.1 ppm was necessitated by the proposed AI limit
Accuracy	80–120 % for QL QC samples 85–115%for all other seven levels of QC samples	General recommendation by ICH Q2 and Q14 Guidelines
Precision	80–120 % for QL QC samples 85–115%for all other seven levels of QC samples	General recommendation by ICH Q2 and Q14 Guidelines
Report Range	0.1–500ppm	The QL of 0.1 ppm was necessitated by the proposed AI limit.  There is a typical linear response between analyte concentration and instrument response.  A report range of0.1–500 ppm was needed to differentiate the mitigating effect of different additives with the analytical procedure.
Matrix Effect	Internal standard normalized matrix effect (IS-nME) of 90–110 % in blank sample matrix, with a coefficient of variation (CV) less than 15 %	Reference material comparison to controls for possible matrix effects as described in Q2(R2). Requirement of sample suitability assessment to ensure acceptable sample response (Q14 section 6).

Technology Selection

Mass spectrometry detection was selected based on the sensitivity requirement.^9,12 The high throughput non-chromatographic sample delivery system was selected since over 1000 samples needed to be analyzed. The sample preparation method was designed based on the solubility of the target analyte, API (active pharmaceutical ingredient) and excipients. Our previous experience with this non-chromatographic mass spectrometry system for quantitating six nitrosamines in angiotensin receptor blocker drug products significantly benefited the development and implementation of the current method.⁹

Knowledge Management

An important factor during development was that there was limited prior knowledge of N-nitrosobumetanide detection by mass spectrometry-based approaches. Knowledge of the MS fragmentation pattern of N-nitrosobumetanide and impact of MS parameters on signal intensity of each MRM transition were gained during the initial analytical procedure development. Physico-chemical characteristics of the API and all the excipients were known, and they were the basis for design and development of the sample preparation approach. Drug product samples were first extracted with ethyl acetate as most of the excipients were not soluble in ethyl acetate. Then, the dried extract was re-constituted with 50/50 methanol/water because the solubility of the API in water was low. Minimal residual API and excipients in the final sample solution significantly reduced the risk of interference and matrix effects that could have been caused by the API and excipients in-house formulated bumetanide drug products.

Risk Assessment

The lack of chromatographic separation capability with the non-chromatographic sample delivery system posed a higher-than-normal risk of specificity issues caused by interferences. To mitigate such risk, four MRM transitions were used (two under negative mode as quantifier and primary qualifier, the other two under positive mode) to assure specificity, and the acceptance criteria of quantifier/qualifier ratio for test samples was set as §20 % of that for QC samples throughout the method lifecycle. This approach has been recommended in ICH Q2(R2) Annex II and implemented in nitrosamine methods by regulators worldwide.^9,13–15 Two MRM transitions under negative mode was selected as quantifier and primary qualifier due to better ionization efficiency. In addition, during method development, sodium adduct precursor ions of analyte were identified under the positive ionization mode that could reduce method sensitivity and impact data accuracy. Thus, the quantifier and primary qualifier MRM transitions acquired under negative ionization mode were applied to mitigate the risk associated with uncontrolled sodium ion levels in drug products, solvents, and operational systems. Multiple formulations of drug products with different excipients and additives complicated the variable influence and necessary control of the matrix effect as each formulation was a different sample matrix. Therefore, a deuterium-labeled internal standard d5-N-nitrosobumetanide was used to control for matrix effects; this strategy is provided as an example in the ICH Q2R2 Annex II⁷ and been implemented for nitrosamine analytical procedures.^9,13–16 Accordingly, internal standard normalized matrix effect (IS-nME)¹⁷ was evaluated as part of the sample suitability assessment described in ICH Q14 guideline section 6². The acceptance criteria for IS-nME was set at 90–110 % with a CV of less than 15 %. During each analytical run, the acceptance criteria for the internal standard response was set at 50–150 % of that QC samples throughout the lifecycle of the method. The need for analysis of large number of samples from multiple formations posed another operational challenge with increased total experimental time and concern for sample stability. Such challenge was addressed by using this high throughput non-chromatographic system that minimized analysis time across the sample set.^8,9

Method Development

The ICH Q14 guideline describes minimal and enhanced approaches to analytical procedure development.² There is a continuum of options between the categories of minimal and enhanced approaches.⁵ Prior to procedure development, we identified an ATP for the procedure according to its intended use. During initial steps of the procedure development, we evaluated prior/gained knowledge and conducted a risk assessment to identify parameters/variables potentially impacting analytical procedure performance. In addition, the control strategy was defined based on risk assessment and development data (detailed information presented in the “control strategy” section below). Overall, identifying an ATP, evaluating prior knowledge, conducting a risk assessment, and defining the control strategy were the elements that were included in the enhanced approach during analytical procedure development (Q14 guideline section 2.1).²

Control Strategy

The control strategy consists of a set of controls derived from mechanism of the technology, prior and gained knowledge, risk assessment, and development data.² A check of instrument and operational control was monitored with a system suitability test prior to and after each analytical run, and with calibrators and QC samples within each analytical run. Sample suitability was assessed by IS-nME, the acceptance criteria for which was set at 90–110 % with the CV less than 15 %. Ongoing monitoring of method performance focused on the quantifier/qualifier ratio and the internal standard response of study samples, which helped to verify and assure specificity and control for any matrix effects. As mentioned previously, the acceptance criteria of quantifier/qualifier ratio for test samples was set as §20 % of that for QC samples throughout the method lifecycle; the acceptance criteria for IS-nME and IS response was set at 90–110 % with the CV less than 15%, and 50–150 % of that QC samples, respectively, throughout the lifecycle of the analytical procedure. In addition, parallelism experiments were performed to demonstrate the trackability of IS in selected sample matrixes.¹⁸

Method Robustness

Triple quadrupole mass spectrometers with electrospray ion sources from different vendors (and even different modules from same vendor) are designed differently. Consequently, the MRM parameters that should be optimized on each mass spectrometers may be different. During method development, MRM parameters were developed and designed to evaluate method robustness according to ICH Q2(R2) Annex II.⁷ In this study, the procedure was fully validated with one set of parameters and partially validated at the extrema of the gas temp, sheath gas heater setting, gas flow, capillary voltage or fragmentor voltage ranges. Using a series of experiments with the validation parameter set where one parameter set as in Table 3, QL and high QCs accuracy and precision were accepted at individual points in the 200 to 350 °C for gas temperature, 100–375 °C for sheath gas heater, 3 to 13 L/min for gas flow, 1500–4500 V for capillary voltage and 60 to 135 V for fragmentor, respectively (Table 3). For purposes of the current study, the data in Table 3 could be considered as potential proven acceptable ranges for analytical procedures (PARs). Importantly, a more extensive validation study may be necessary to include additional validation data including the extrema of these ranges to provide assurance of fitness for purpose across the ranges.² In addition, such data may also provide justification for performance-based acceptance criteria if a different MS/MS system were be used (e.g., due to method transfer or change of facility).

Table 3.

Evaluation of mass spectrometry method robustness based on recommendations in ICH Q2R2 Annex II.

Parameters Deliberated
Gas temperature (°C)	200		250		300
	QL QC*	High QC**	QL QC	High QC	QL QC	High QC
Accuracy (%)	103.73	109.21	101.86	108.13	100.14	96.85
Precision (%)	2.61	2.43	2.19	2.35	2.12	2.29
Sheath gas temperature (°C)	100		150		200
	QL QC	High QC	QL QC	High QC	QL QC	High QC
Accuracy (%)	101.82	105.26	100.26	106.79	103.35	97.13
Precision (%)	2.48	2.37	2.48	2.34	2.61	2.43
	250		375
	QL QC	High QC	QL QC	High QC
Accuracy (%)	102.41	104.12	102.19	104.08
Precision (%)	2.94	2.66	2.30	2.36
Gas flow (L/minute)	3		5		10
	QL QC	High QC	QL QC	High QC	QL QC	High QC
Accuracy (%)	103.93	105.17	107.32	104.74	104.18	97.37
Precision (%)	2.66	2.78	2.67	2.70	2.27	2.26
Capillary voltage (V)	1500		4000		4500
	QL QC	High QC	QL QC	High QC	QL QC	High QC
Accuracy (%)	99.27	102.45	104.90	99.06	96.44	105.00
Precision (%)	3.02	3.11	2.19	2.37	2.30	2.35
Fragmentor (V)	60		120		135
	QL QC	High QC	QL QC	High QC	QL QC	High QC
Accuracy (%)	104.79	108.75	97.10	103.17	104.97	96.94
Precision (%)	2.26	2.35	2.62	2.81	2.94	3.09

^*0.1 ppm.

^**500 ppm.

Proposed ECs and Reporting Categories

ECs in analytical procedures help establish which parameters are critical for obtaining reliable results that can ensure an efficient product control strategy during the product life cycle. Changing ECs for an analytical procedure may necessitate a certain level of regulatory reporting; the level of regulatory activity can be different depending on the strategy employed by the applicant to define ECs, the amount of procedure, process, and product knowledge, and the extent of the changes. Table 4 describes the proposed ECs and corresponding reporting categories (ICH Q12 definitions) for mass spectrometry detection and quantitation. An explanation for the ECs follows the table.

Table 4.

Proposed established conditions, reporting categories and rationale.

Proposed ECs		Overall Risk Assessment	Proposed ICH Q12 reporting category	Rationale	Supporting data
Method
Mass Spectrometry		High	Prior Approval (PA)	Analytical Target Profile: sensitivity Control Strategy: IS-nME and quantifier/qualifier ratio	MS was the only analytical technology that demonstrated sensitivity required by the ATP. Change in technological principle represents a high risk to sensitivity and other performance characteristics
Equipment
Triple Quadrupole Mass Spectrometer under negative ionization mode		High	PA	Analytical Target Profile: sensitivity, matrix effect Control Strategy: IS-nME and quantifier/qualifier ratio	QQQ detection was selected in development studies to obtain sensitivity requirements. Change in detector type is also accompanied by significant risk to other performance measures.
Conditions
Internal standard	Not using	High	PA	Analytical Target Profile: sensitivity, matrix effect Control Strategy: IS-nME and quantifier/qualifier ratio	Matrix effects due to change of excipients, additives and formulation parameters was not well controlled if an internal standard was not used.
	Using other stable isotope labeled internal standard(s)	Low	Notification Low (NL)	Other stable isotope labeled IS should have similar physico-chemical characteristics of the analyte. A risk assessment will help identify other issues that may arise with the change.	No data on other ISs. Prior knowledge gained from previous developed methods support the rationale. A bridging study showing comparable results between original and new IS would be needed to make the change.
Gas temperature		Low	NL if within 200–350 °C	Method performance was not impacted when the parameters fall in the ranges listed.	Method Robustness data (Table 3) demonstrates the method performed adequately under listed conditions. However, if changes need to be made, suitable bridging studies need to be performed to demonstrate the revised method still meet the validation criteria, and the data is comparable for original and revised methods.
Sheath gas heater		Low	NL if within 100–375 °C
Gas flow		Low	NL if within 3–13 L/minute
Capillary voltage		Low	NL if within 1500–4500 V
Fragmentor		Medium or Low	NL if within 60–135V
Acceptance Criteria:
Method validation: specificity, sensitivity, accuracy, precision, report range
Control strategy: IS-nME, quantifier/qualifier ratio
Widening		High	PA	The performance characteristics and criteria ensure the quality of the reportable result. Widening of performance characteristics and criteria could have a negative impact on data quality.	Method validation and implementation to over 1000 samples from 26 different formulations indicated the acceptance criteria for specificity, sensitivity, accuracy, precision, report range, IS-nME, and quantifier/qualifier ratio were achievable and crucial for assuring data quality.
Narrowing		Low	NL

The QL of 0.1 ppm for N-nitrosobumetanide was necessitated by the proposed AI limit for this NDSRI as described in “Analytical Target Profile” section and Table 2. Ultraviolet (UV) detectors routinely used in QC laboratories typically would not provide adequate sensitivity so mass spectrometry was selected as the analytical method. In addition, using mass spectrometry enables the employment of a control strategy such as internal standard normalized matrix effect (IS-nME) and quantifier/qualifier ratio, as described above in the “Control Strategy” section. If switching to another method, the risk assessment would be re-performed, and the analytical procedure would be re-developed and re-validated to meet the analytical target profile requirements. MRM using a triple quadrupole mass spectrometer is a common algorithm used for quantitative mass spectrometry data acquisition. Choosing negative ionization mode was based on our development data, because the sensitivity was higher and the negative impact of sodium adducts was minimized. If changing to positive ionization mode and/or other data acquisition algorithm such as in single ion monitoring using a high-resolution mass spectrometer, the method parameters would be re-optimized to fulfill the requirement for sensitivity and linearity. Risk assessment would be re-performed to update the control strategy to minimize the potential impact of matrix effects and sodium adduct formation on data quality.

As described in the ICH M10 guidance,¹⁹ using a stable isotope-labeled internal standard is recommended when quantitating drugs and metabolites in biological matrixes. This strategy is also noted in the ICH Q2(R2) Annex II examples.⁷ In the current method, using a deuterium-labeled internal standard is an important control strategy to minimize the potential impact of matrix effects due to changes of excipients, additives and formulation procedures on data quality. If not using an internal standard, the control strategy would be re-established to assure the method performance. If another stable isotope labeled IS was used with similar physico-chemical characteristics of the analyte, the IS should be isotopically pure and have no back conversion to a non-labeled form during sample processing and analysis. Another option that can be used with appropriate validation, is the use of an external calibration curve with non-labeled standards to establish instrument response as described in one high resolution mass spectrometry method.¹⁶

Changes of mass spectrometer parameters, including gas temperature, sheath gas heater, gas flow, capillary voltage, and fragmentor, within the ranges specified in the “Method Robustness” section and Table 3 did not impact overall method performance. Therefore, the risk associated with these changes was deemed to be low. It is noteworthy to emphasize that, if postapproval changes need to be made, suitable bridging studies should be performed to demonstrate the revised method still meet the validation criteria, and that the data is comparable between the original and revised methods.

The initial intended purpose of this NDSRI method was to investigate the impact of antioxidants and pH modifiers on the formation of N-nitrosobumetanide in-house formulated bumetanide drug products, not to be used for pharmaceutical development. As such the approach was used retrospectively as an example of how a laboratory scientist could provide development and validation data to support the establishment of ECs for an analytical procedure. ICH Q12 describes that each laboratorian must assess risk and criticality in the context of their specific drug and laboratory environment when proposing and justifying established conditions. Instead, this is a real-world case study elaborating on how to apply the scientific principles in ICH Q14 and Q2(R2) guidelines for analytical method development and lifecycle management. As a first attempt, we acknowledge that most proposed ECs in this example are parameter-based; however, with increasing experience gained through the implementation of similar methods and an increased understanding of the mechanism of NDSRI formation, ECs for such a method could eventually move to performance-based approaches.

Supplementary Material

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.xphs.2024.07.022.