validation of quantitative nmr · 2020-06-02 · methods, validation is not commonly performed for...

Validation of Quantitative NMR

Implications for early phase of pharmaceutical development


Suzanne de Goeij 2


Implications for early phase of pharmaceutical development

Author: Suzanne de Goeij

Master of Science Analytical Chemistry track Universiteit van Amsterdam Name: Suzanne de Goeij Student number: 5938325 Supervisors UvA: Dr. W. Th. Kok Abbott Weesp: C. Sänger – van de Griend

F. J. J. Overmars


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SAMENVATTING

Dit verslag heb ik geschreven naar aanleiding van mijn Research project aan het einde van de Master of Chemistry met Analytical Science als specialisatie. Deze Master of Chemistry heb ik in deeltijd gevolgd aan de UvA en de VU in de periode van september 2008 tot en met september 2012. Het praktische werk is uitgevoerd bij Abbott Healthcare Products in Weesp, binnen de afdeling Advanced Analytical Technology (op dat moment ook mijn werkgever) in de periode juli – oktober 2010. Wegens een reorganisatie is de afdeling opgeheven waar het praktisch werk werd uitgevoerd. Na een nieuwe baan, trouwerij en de geboorte van mijn dochter, heb ik het verslag afgeschreven wat hier nu ligt. Ik wil via deze weg iedereen hartelijk bedanken die mij geholpen heeft.

Aan de ontwikkeling van een nieuw geneesmiddel zit een lang ontwikkelingstraject. Na een research fase komen nieuwe componenten in de development fase. Zodra de eerste klinische testen uitgevoerd gaan worden in de vroege ontwikkelingsfase moet de API (active pharmaceutical ingedient, de actieve stof) vrijgegeven worden volgens vooraf gestelde specificaties. Veelal worden chromatografische technieken gebruikt voor het bepalen van de zuiverheid. Deze methodes worden gevalideerd volgens de regels van de ICH (International Conference of Harmonization of technical requirements for registration of pharmaceuticals for human use), richtlijnen voor het valideren van analytische methodes. Nuclear Magnetic Resonance (NMR) wordt in de vroege ontwikkeling veel gebruikt voor structuur opheldering. Naast structuur opheldering kan NMR ook gebruikt worden als kwantitatieve techniek voor het bepalen van de zuiverheid. Een kwantitatieve NMR methode maakt gebruik van een interne standaard, waarvan de zuiverheid bekend is. Binnen Abbott Weesp werd Q-NMR steeds meer gebruikt voor de vrijgiftes van API, maar een validatie van de methode en techniek ontbrak. In deze studie heb ik Q-NMR als methode gevalideerd aan de hand van twee praktijk voorbeelden en een standaard met bekende zuiverheid. Er is gekeken naar de validatie termen, specificiteit, lineariteit, precisie, accuracy, robuustheid en detectielimieten. Deze termen zijn gevalideerd met de specificaties die voor chromatografische methodes gelden. Uit de resultaten is gebleken dat kwantitatieve NMR goed gebruikt kan worden in de vroege ontwikkelingsfase en voldoet aan alle geldende specificaties voor chromatografische methodes. Voor de late ontwikkeling wordt een chromatografische methode ontwikkeld voor routine matige analyses.


Suzanne de Goeij 4

SUMMARY

Quantitative NMR is increasingly being used for content determination of drug substance in the early phase of pharmaceutical development. For the release of an active pharmaceutical ingredient (API) for clinical studies, a validated method is required. Although this is common practice for chromatographic methods, validation is not commonly performed for Q-NMR yet. In this study Q-NMR was validated in terms of specificity, linearity, precision, accuracy, robustness and detection limits. The specifications were set according to the ICH Q2 (R1), guidelines for analytical procedures, text and methodology. Q-NMR was validated towards two development APIs and one primary standard. Specificity was validated by spiking the API with known impurities. Linearity was investigated at nominal level and impurity level. The CV was less than 0.3 % at the nominal level, 1.3 % at resonance signal 1.1 ppm (6H) and 6.0 % at resonance signal 6.7 ppm (1H). The slopes in the high and low range were within 5 % RSD, so linearity is proven over the whole range. The precision experiment resulted in a repeatability CV of less than 1.0 %, method precision less than 2.0 % and intermediate precision less than 0.4 %. Accuracy was validated by comparison with another technique and the results were within the specified 2 % range. Quantitation limits were determined using the linearity data and calculated as 0.20 % at resonance signal 1.1 ppm (6H) and 0.74 % at resonance signal 6.7 ppm (1H).


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ABBREVIATIONS

A Intercept ABS Absolute content ADC Analogue to Digital Converter ANOVA Analysis of variances API Active Pharmaceutical Ingredient B Slope CE Capillary Electrophoresis CV Coefficient of Variance DAD Diode Array Detection df Degrees of freedom DL Detection Limit EM Exponential Multiplication (EFP) ERETIC Electronic references to access in vivo concentrations FID Free induction decay GM Lorentz-Gaussian function (GFP) GC Gas Chromatography HPLC High Pressure Liquid Chromatography ICH International Conference of Harmonization of technical requirements for registration of pharmaceuticals for human use Ix/Iis Integral API divided by integral internal standard lb Line broadening n.a. Not analyzed NMR Nuclear magnetic resonance MSD Mass Spectrometry Detection NS Number of scans ppm Part per million R Correlation coefficient Rs Resolution Sanal Estimation of the random measurement error S/N Signal to noise ratio SOP Standard Operation Procedure Sr Residual standard deviation SS Sum of squares std (A) Standard deviation in intercept std (B) Standard deviation in slope QL Quantitation Limit Q-NMR Quantitative Nuclear magnetic resonance TFA Trifluoroacetic acid wx/wis Weight API divided by weight internal standard


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Index Samenvatting ........................................................................................................................................... 3

Summary ................................................................................................................................................. 4

Abbreviations ........................................................................................................................................... 5

1. Introduction ..................................................................................................................................... 8

2. Principles of Quantitative NMR......................................................................................................... 9

2.1 Acquisition parameters ........................................................................................................... 11

2.2 Processing parameters ............................................................................................................ 12

3. Quantitative NMR (Q-NMR) ........................................................................................................... 14

4. Validation ....................................................................................................................................... 16

4.1 Specificity ............................................................................................................................... 16

4.2 Linearity.................................................................................................................................. 18

4.3 Precision ................................................................................................................................. 18

4.4 Accuracy ................................................................................................................................. 20

4.5 Robustness ............................................................................................................................. 20

4.6 Detection limit and quantitation limit ..................................................................................... 21

5. Experimental .................................................................................................................................. 23

5.1 General equipment ................................................................................................................. 23

5.2 Specificity ............................................................................................................................... 24

5.3 Linearity.................................................................................................................................. 24

5.4 Precision ................................................................................................................................. 25

5.4.1 System precision ............................................................................................................. 25

5.4.2 Method precision ............................................................................................................ 25

5.4.3 Intermediate precision .................................................................................................... 25

5.5 Accuracy ................................................................................................................................. 27

5.6 Robustness ............................................................................................................................. 27

5.6.1 Acquisition parameters ................................................................................................... 27

5.6.2 Processing parameters .................................................................................................... 27

5.6.3 Spectra evaluation (integration) ...................................................................................... 27

5.7 Detection limit and quantitation limit ..................................................................................... 28


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6. Results and discussion .................................................................................................................... 29

6.1 Results Specificity ................................................................................................................... 29

6.1.1 Discussion Specificity....................................................................................................... 33

6.2 Results Linearity...................................................................................................................... 34

6.2.1 Discussion Linearity ......................................................................................................... 39

6.3 Results Precision ..................................................................................................................... 41

6.3.1 Results System Precision ................................................................................................. 41

6.3.2 Discussion System Precision ............................................................................................ 41

6.3.3 Results Method Precision ................................................................................................ 42

6.3.4 Discussion Method Precision ........................................................................................... 42

6.3.5 Results Intermediate Precision ........................................................................................ 42

6.3.6 Discussion Intermediate Precision ................................................................................... 44

6.4 Results Accuracy ..................................................................................................................... 45

6.4.1 Discussion Accuracy ........................................................................................................ 45

6.5 Results Robustness ................................................................................................................. 46

6.5.1 Discussion Robustness .................................................................................................... 46

6.6 Results Detection limit and Quantitation limit ......................................................................... 47

6.6.1 Discussion Detection limit and Quantitation limit ............................................................ 49

7. Conclusion ...................................................................................................................................... 50

References ............................................................................................................................................. 52

Appendix I .............................................................................................................................................. 54

Appendix II ............................................................................................................................................. 56


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1. INTRODUCTION

New molecules for further pharmaceutical development have to successfully transverse a long path to the market. The pharmaceutical industry breaks this path into four development phases. In the early phase of development (pre-Phase I and Phase I) general a chromatographic method, mostly LC, is developed for content determination of the main compound and its impurities. This method must be validated on several items before the clinical studies can be started.

An alternative for chromatographic analysis in the early phase of pharmaceutical development is Nuclear Magnetic Resonance (NMR) spectroscopy. NMR spectroscopy is already commonly used in pharmaceutical industries for structure elucidation to support the organic chemistry. NMR as an analytical method for quantitative analysis of the Active Pharmaceutical Ingredient (API) is being used increasingly.

The use of Quantitative NMR (Q-NMR) is valuable in the content determination of the main compound and all impurities. A Q-NMR method is rapidly developed and all proton containing impurities can easily be determined quantitatively. When Q-NMR is used for the release of the API in pre-phase I and phase I, a validation of the used method is required. Currently, during the method development some validation parameters are taken into account, however a full validation is missing.

Validations of analytical methods are commonly done according to the guidelines of the international conference of harmonization of technical requirements for registration of pharmaceuticals for human use (ICH). In this study the use of Q-NMR is challenged through the use of traditional validation requirements applied in the regulated pharmaceutical industry.

In this study Q-NMR is validated to establish this technique as fully equivalent to liquid chromatography in the early phase of development. The Q-NMR validation study is set up as validation of a particular API including extra parameters. The results of this validation study can be used in future development of new Q-NMR methods.


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2. PRINCIPLES OF QUANTITATIVE NMR 1-6

The successful story of Nuclear magnetic resonance (NMR) started in 1945 with the discovery of the phenomenon in solids by Purcell and Bloch. A few years later NMR was further developed to a powerful analytical method used in academic and industrial research.

A charged nucleus has a spin causing an angular momentum while it also behaves as a circulating charge resulting in a ring current. This ring current creates magnetic moment µ. The magnitude of the angular momentum (p) is given by the spin quantum number I. The magnetic moment and angular moment are related by = where is the gyromagnetic ratio. The gyromagnetic ratio is specific for each nucleus. When placed in a magnetic field a magnetic moment assumes a precession around the main field (B0). The spin quantum number of a proton is 1/2. For the elements with a spin of I = 1/2 there are two energy values when placed in a magnetic field, corresponding to two m-values m = + 1/2 and m = - 1/2, commonly named as α and β states.

Figure 1: Spin 1/2 in α and β state

The proton is the most interesting nuclei in NMR, because of the natural abundance (99.9885%), its gyromagnetic ratio and its presence in almost every molecule. Also 19F has a spin of I =1/2 and a natural abundance of 100% and is therefore used in NMR. In comparison, 13C has a natural abundance of only 1.11%.

The energy (E) difference between two states is given by: ∆ = ℏ where y is the gyromagnetic ratio, ћ the reduced Planck constant and B0 the static magnetic field. The energy difference corresponds to the energy that can be absorbed or emitted by the system, described by the Lamor frequency ω ( = ).

As there is an energy difference between the two states, there is also a difference between the occupancy of the α and β states. The relative population of a state is given by the Boltzmann distribution = ∆ / ≈ 1 − ∆ = 1 − ℏ where kB is the Boltzmann constant ( = 1.3805 x 10-23 J/K) and T the absolute temperature in K.


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Generally, the energy difference ΔE is very small compared with the average energy kBT and consequently the populations of the energy levels are nearly equal. In fact, the excess in the lower energy level is only in the order of the parts per million. This makes NMR insensitive and unique compared to other spectroscopic techniques like infrared and ultraviolet spectroscopy, which have almost 100% population in the ground state. The slight excess of the nuclei in the more favourable α state generates the so called net magnetization and is fundamental for NMR spectroscopy.

The elementary magnetic moments are added like vectors and form a net magnetization vector, which is in precession along the z direction of the B0 field. If the observer positions rotate with the same frequency as the precessing spins, the magnetic vector becomes static. This is called the rotating coordinate system.

The majority of the pulse techniques can be understood in terms of experiments with 90° and 180° pulses. After a 90° pulse there is no net magnetization along the z-axis, the population difference between the α and β state is equalized. Within the acquisition time the net magnetization will fall back to the equilibrium state. The magnetization happens in both the z-direction (longitudinal relaxation) and in the x-y-plane (transverse relaxation).

Following a 90-degree pulse, the recovery of the +z magnetization (Mz) follows the expression = 1 −

where M0 is the magnetization at thermal equilibrium, t is time and T1 is the first order time constant. The first order relaxation times can be in the order of seconds. After application of a 90-degree pulse the net magnetization rotates in the x-y-plane. The rotating magnetization vector will produce a weak oscillating voltage in the coils. The relaxation of the bulk magnetization vector causes the oscillating voltage to disappear and causes the NMR signal to decay in time, producing the Free induction decay (FID). The final step to the NMR spectrum is the transformation of the time dependent FID to the frequency dependent spectrum, Fourier transformation.

There are three major features that provide valuable information about the structure:

1) Chemical shift. Electrons around the nucleus shield it from the external magnetic field and thus their resonance frequencies will be different. The difference between the frequency of the reference signal and the frequency of the signal is divided by the frequency of the reference signal to give the chemical shift (in ppm).

2) J-coupling. The energy state of a nucleus may also be affected by the spin state of nuclei nearby as the nuclei are spin-spin-coupled to each other. This can be observed in the spectra as peak splitting. The multiplicity of the split peaks depends on the number of coupling adjacent nuclei. The magnitude (Hz) of the splitting is known as the coupling constant and is dependent on the strength of the coupling.

3) Signal intensity / peak area. The area under the peak gives information about the protons in the molecule.


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2.1 Acquisition parameters

There are several basic requirements to be taken into account before acquisition. The basic acquisition scheme of Q-NMR experiments is relaxation – excitation – acquisition. The parameters used in these three steps are described below.

Shimming Shimming is used prior to the operation of the magnet to eliminate in homogeneities in its field.The basic requirement for an accurate quantitative measurement is a highly homogeneous magnetic field. Magnetic in homogeneity causes signal distortion or inappropriate peak shapes. In homogeneities in the magnetic field are corrected for shimming. When the field is shimmed properly the best S/N and resolution ratios can be obtained. Shimming can be done manually or automatically.

Relaxation delay The delay before the excitation is called the relaxation delay. The excited net magnetization vector is allowed to return to its equilibrium state during this time. For quantitative measurements it is crucial to allow magnetization to recover fully before applying the new pulse. For spins to relax fully after a 90-degree pulse, it is necessary to wait a period for at least 5xT1 of the slowest relaxing nuclei to prevent saturation and loss of signal.

Excitation pulse To reduce the recovery time for the magnetization in a quantitative experiment it is more efficient to use a smaller flip angle. The optimum flip angle, known as the Ernst Angle, can be calculated using the equation: cos = where α is the optimum pulse angle for the pulse repetition time tr. Calculating the optimum flip using the longest T1 relaxation time in the sample and a reasonable repetition time leads to the largest S/N in the shortest time.

Receiver Gain The spectral window defines the size of the observed frequency window. The excitation pulse is usually given automatically in the middle of the spectral window. When the emitted signal is detected, it is sampled and converted with the analogue to digital converter (ADC) The digitization process converts the alternating voltage into a binary number proportional to the magnitude of the signal. There are two critical parameters involved. The dynamic range describes how fine the amplitude resolution is that can be achieved and the time resolution corresponds to the minimum dwell time that is needed to digitize a single data point. The ADC has a limited dynamic range and it gives the smallest signal that is measurable in the presence of a large signal. To acquire a NMR spectrum the receiver gain has to be adjusted in a way that the largest signal in the FID fills the digitizer. If the receiver gain is set too high, saturation of the receiver occurs and results in a distorted spectrum. The receiver gain is set automatically.

Acquisition time The acquisition time is the length of the time that is spent to sample the FID. The required acquisition time depends on the smallest line width in the spectrum.


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Signal to noise ratio (S/N) High S/N ratio is needed for accurate quantitative work, especially with low levels of impurities. The S/N ratio can be improved by several options: - Increasing the concentration of the sample - Increasing the number of scans - Increasing of the magnetic field - Using more sensitive probe heads like cryogenically cooled ones When limited sample is available or the solubility is limited the easiest way of get the desired S/N is increase the number of scans. The S/N is proportional to the square root of the number of scans.

2.2 Processing parameters

There are several ways to improve the acquired data prior to the Fourier transformation. Depending on the desired results, resolution, S/N and baseline flatness can be improved with appropriate mathematical functions.

Windowing Generally, window functions are used to enhance the S/N ratio at the cost of the resolution and vice versa . In a routine spectrum, most of the signals decayed to zero after a few seconds. Usually, the acquisition time is several seconds. The end of the FID contains only noise. Fourier transformation of this noisy part results in introducing additional noise throughout the spectrum This can easily be reduced if all data points of the FID are multiplied with a decaying exponential function:

= Where a is positive time constant.

For Q-NMR measurements the exponential multiplication (EM) is typically used. The exponential factor force the tail of FID towards zero and increases the apparent decay rate of the NMR signal which causes line broadening (lb expressed in Hz) Exponential multiplication is a compromise between resolution and S/N. A larger line broadening (lb) for the EM function improves the S/N but the simultaneous line broadening of the signal may complicate the integration routine. The best compromise is to use a small line broadening (lb = 0.3 Hz) and a larger number of scans.7

Instead of a positive exponential function a Lorentz-Gaussian function (GM) is also used. = The function is determined by two variables, the degree of line narrowing, a, and the point on the acquisition time at which the functions reaches the maximum value, b.

In daily use the exponential function is used within Abbott Weesp with a lb of 0.3 Hz. In the validation study the use of Gaussian function is also validated to compare results and justify that GM can also be used in quantitative purposes.

Zero Filling Another parameter before the Fourier transformation is performed is zero filling. This parameter doubles the number of data points in the time domain by appending zeros to the end of the FID to


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improve the frequency resolution in the spectrum. Half of the collected data points are in use after the Fourier transformation. Usually a zero filling factor of 2 is used.

Phase correction After the Fourier transformation the spectrum requires a phase correction. Zero- and first-order phase error are introduced into the NMR spectrum by a mismatch between the receiver and the reference phase and by the precession of magnetization during the short delay required for the pulse ring down prior to the start of the acquisition. In Q-NMR carefully phasing is essential. All NMR processing software includes automatic phasing, however manually phasing of spectra for quantitative analysis is still necessary.

Baseline correction Correct determination of the signal area depends greatly on the baseline of a spectrum. In an ideal NMR spectrum the baseline would be flat and set to zero and the area of an isolated signal could be determined. In real NMR spectra there is always some baseline distortion due to several causes. In manual integration, the baseline is estimated by drawing a straight line from one end of a peak to the other end. There are a number of automatic baseline corrections in the software with various algorithms available. Within Abbott Weesp the baseline correction is automatically performed by the in-house written software named QINT.

Spectra evaluation/Integration After phasing and baseline correction the spectrum is ready for integration. Integration of the peak area, together with phase and baseline correction, is the most crucial step in Q-NMR analysis. To include 100% of the peak area, an integral would have to extend to infinity in either direction. In order to cover 99% of the peak area the integral region should be extended to 20 times the peak width in both directions. Griffith and Irving8 studied the effect of the integral width to the accuracy of the area of the Lorentzian peak. To obtain 99.5% of the peak area the integral needs to extend 39 times the peak width.

To reduce personal influences, in-house written software is used within Abbott Weesp, QINT version 10, for quantitative purposes. QINT performed an automatic baseline correction and determine the integration value of each integral. Phase correction is manually done by the analyst. Integration borders are set manually at the peak of interest (peak integration). The software command QINT is entered after these operations. QINT performs the baseline correction and calculate the value of the integrals. The software set 16 data points around the chosen begin and end points of the integration. QINT makes an average of these points to get a better determination of the baseline level. The standard deviation of the integral is calculated to get an idea about the variation of the chosen signal. A limited validation of the QINT software is done.9 QINT is always used within Abbott Weesp for all quantitative measurements. In this study QINT is used for all experiments. The use of QINT versus the manual integration is validated by measuring the intermediate precision.


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3. QUANTITATIVE NMR (Q-NMR) 1-3,10

The most important fundamental relation of Q-NMR is that the signal response (integrated signal area) Ix in a spectrum is directly proportional to the number of nuclei Nx generating the corresponding resonance signal: =

Where Ks is a spectrometer constant that remains the same for all resonances in a NMR spectrum. In NMR experiments all molecules in a particular solution underlie the same experimental conditions. In this case, Ks is for all molecules the same and therefore the intensity ratios of the spectrum are directly related to the ratios of the numbers of nuclei (having different chemical shifts) =

The area under the peak is generally called the intensity or the integral of the signal. Comparing these intensities in a spectrum directly gives the ratios of the protons in the molecule. Signal intensities are used for qualitative and quantitative purposes.

For qualitative purposes the ratio of the integrals are compared to the number of protons in the spectrum. This is used for structure elucidation. For example, ethanol has 3 signals in the NMR spectrum corresponding to the OH, CH2 and CH3 groups. Integrating these signals will show a ratio of 1:2:3 which is equivalent to the number of corresponding protons.

For quantitative use, the molar ratio nx/ny of compound X and Y can be calculated = Where n is the amount of sample (in mol), I the integral of the signal and N the number of nuclei (protons) which cause the resonance.

The amount fraction of a compound X in a mixture of m components is given by: ∑ = / ∑ / 100%

Using this method the purity can be easily calculated without a lot of method development. If all impurities show up in the NMR spectrum and can be assigned structurally, the assay is the difference from the 100% value. This method is called the 100% method. This method assumes that all components in the solution contain protons, so the method is questionable if inorganic substances are present in the sample.

A second method for the determination of the purity is the absolute quantification method. For the purity determination of a substance an internal standard, a reference standard with known purity, is used.


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The purity (Px in %) is calculated according to:

=

Where Mx and Mstd are the molar masses of the analyte and the reference standard respectively, mx and mstd the weighed mass of the compound of interest and the mass of the standard, respectively, Pstd the purity of the reference standard and Nstd and Nx correspond to the number of protons and Ix and Istd to the integrated signal area. The reference standards used in Q-NMR need to meet some specific requirements. They should be inexpensive, stable and chemically inert, available in pure form, non-hygroscopic, soluble in most NMR solvents and show a simple NMR spectrum, preferably a singlet. Within Abbott Weesp several internal standard are available, such as 1,3,5-trimethoxybenzene, maleic acid, citric acid and p-nitrotoluene. In literature more internal standards for use in Q-NMR are described.11,12

The absolute content determination and the 100% method (relative quantitation method) are in general the mostly used methods and also the two methods used within Abbott Weesp. The validation of Q-NMR in this study is performed using mainly the absolute content method and in one part the 100% method is used.

There are additional methods of purity determinations if contamination with an internal standard has to be avoided.

Using an external standard is another option to determine the purity of a sample. A coaxial capillary is filled with a reference standard and inserted in a NMR tube containing the analyte solution or in a separate tube, using two NMR tubes one filled with the analyte and the other one with the standard solution. The standard addition method is another possibility for the determination of the purity. Add different known amounts of a standard to a solution, dilute and make up to a fixed volume. A graph is plotted of the peak area versus the concentration of the standard added to the unknown sample. Extrapolation of the plot provides the concentration of the analyte in the unknown sample. The standard addition method is also used in electrochemical and chromatographic methods

Another option for the determination of the purity is to make a calibration line. This is comparable to chromatographic methods. A series of standard solutions with known concentrations of the analyte is used to determine the response of the instrument. All instrumental parameters should be the same.

In 1999 Akoka13 proposed an alternative to internal standards based on a calibrated reference signal. ERETIC (electronic references to access in vivo concentrations) is an electronic reference signal added to the spectrum. The ERETIC signal can be calibrated using a solution of known concentration. The ERETIC method provides an artificial signal that has all the characteristics of a real NMR signal and its parameters. When using ERETIC the sample remains uncontaminated and sample preparation is very simple. Reference signals do not overlap with signals of the analyte because the ERETIC parameters can be chosen freely in a spectral area without analyte signals.


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4. VALIDATION

NMR spectroscopy is increasingly being used as an analytical method for quantitative analysis of the organic compound. In the early stage of drug development, Q-NMR is used for both structure elucidation and assay determination of the drug substance.

Validation of Q-NMR was done for specific methods in literature.14,15,21-23 In all cases the method passed the validation specifications.

In the pharmaceutical industry validation of analytical methods is required in the development of drug substances. Validation of analytical methods is commonly performed according to the guidelines of the international conference of harmonization of technical requirements for registration of pharmaceuticals for human use (ICH).16 In this document four different types of analytical procedures are described. In this study the guidelines of validation of an assay determination are followed. In the ICH guidelines the assay determinations of a drug substance is described as: Assay procedures are intended to measure the analyte present in a given sample. The same validation characteristics may also apply to assays associated with other analytical procedures. The guidelines are set for chromatographic analytical procedures such as HPLC, GC and CE and are therefore not always directly applicable for Q-NMR methods.

For the validation of chromatographic methods within Abbott Weesp a SOP is distracted from the ICH guidelines, “SOP CPD 05-16-001 Guidance to validation, adjustments and transfer of analytical methods”.17 This guideline and the background document, “Validation, adjustments and transfer of analytical methods”18 resulted in the set-up of this study based on the quantitative measurements of the API (drug substance) in early development.19-20 The SOP is development phase related, for the Q-NMR validation study the early phase of development is applicable, pre-clinical, clinical phase I and II. In a later phase of development of potential new medicine a chromatographic method will be developed for routine analysis.

The analytical performance of the method is expressed in terms of specificity, linearity, precision, accuracy, robustness, detection limit and quantitation limit. A number of these parameters are applicable for Q-NMR in general and do not need to be validates again in a specific assay for a particular compound.

The validation parameters are discussed in separate paragraphs.

4.1 Specificity

According to the ICH guidelines the specificity is the ability to assess unequivocally the analyte(s) in the presence of components which may be expected to be present.16 Typically these might include synthetic impurities, degradation products, sample matrix, etc. This definition has the following implication for assay determinations: Provide an exact result which allows an accurate statement on the content or potency of the analyte in the sample.


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The translation of the ICH guidelines for specificity for NMR is: the unambiguous assignment of all NMR lines to the structure of the analyte.1

In NMR spectroscopy the response of the protons of interest attributed to the API being studied should be adequately resolved from those of small related impurities that can be present in the sample. Using NMR for structure determinations, all compounds containing protons, drug substance and most impurities can be analysed and assigned. The exceptions are compounds without protons like salts.

In most cases the specificity will not be a problem since most organic compound exhibit spectra with more than one resonance frequency. By integrating all signals of the main compound, the integral for each proton is calculated and the lowest integral value per proton is used for calculation of the purity. This can differ from batch to batch since there could be different impurities in other synthetic routes to get the desired compound. In the absolute assay determination the region of the signal from the internal standard is checked on the presence of impurities in the 100% spectrum (without internal standard). A common and simple way to determine the specificity in Q-NMR is to run a spectrum of a sample and spike this with known impurities. Also 2D spectra like COSY, HSQC, HMBC can be used to check the purity of the signal and check on overlapping integrals. Beside 2D spectra, measurement of other nuclei e.g. by 13C or 19F NMR can give more information of the structure and the purity. In this Q-NMR validation study the specificity for a particular Q-NMR method is evaluated by spiking an API with different process related impurities at a level of 1%. The spectra are acquired with and without decoupling of 13C satellites to show and prove that there is no difference. 13C decoupling measurements prevent overlapping of the 13C satellites with the signals of interest and therefore show enhanced resolution. This is also done in other validation items, linearity and precision.

The specifications for validating a chromatographic method according to SOP are not applicable for the validation of a Q-NMR method.17-19 The identification in chromatographic methods is mostly done by comparison with a reference standard. This reference standard is usually qualified as such by H-NMR analysis, so this approach is not possible for NMR. The identification in Q-NMR is done by 1D and 2D measurements and assigning the signals to the correlating carbons and protons. The signal with the lowest integral value is used for quantification. Peak purity or signal purity in Q-NMR is checked during the method development with spiking the known impurities and solvents. The specifications for the specificity for Q-NMR methods are set as: no impurities or solvents are interfering with the main compound or internal standard. At least one resonance signal from each impurity or solvent can be used for quantitative analysis and is not overlapping with other resonance signals. The specificity must be evaluated for every Q-NMR method separately and has to be done in every validation of the Q-NMR method.


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4.2 Linearity

The linearity of an analytical procedure is its ability (within a given range) to obtain test results which are directly proportional to the concentration (amount) of analyte in the sample16

The experimental setup for the linearity experiments is defined by the concentration range, number of levels, and number of measurements for each level and the order of measurements. The order of measurements in chromatography is relevant due to the possible carry over effect. In Q-NMR carry over is not relevant. Also the number of injections of each level is different compared to chromatography. In Q-NMR the measurement of the sample will always give the same spectra when using the same acquisition settings and system. The variation in the results is due to the processing parameters like phase corrections and integration of the spectra.

The linearity in Q-NMR is never an issue since, by theory and practice, the intensity of the response is directly proportional to the amount of nuclei contributing to this signal. The limitation of the linearity at high levels is the solubility of the API in the solvent and at low levels the detection limit with a certain number of scans. In several published articles the linearity is determined and they all obtained a correlation coefficient for linear regression ≥ 0.999.14,21-23 In the study of Webster et al14 an experiment has done to demonstrate that the mass of the internal standard is not critical to the linearity validation.

The linearity for this study was tested at 5 levels in a range of 70 – 130% of the nominal level, which is usually done in early phase of development. In a later development phase the linearity at lower level in chromatographic analysis is determined. In this Q-NMR validation study the linearity at lower levels of the API is also part of the validation to proof the linearity at impurity level. To evaluate the linearity at lower levels, six various contents of the API in the range of 0.01 – 1 % of the nominal level are analysed. When the linearity meets the specifications over both ranges and taking into account the study of the linearity in literature, linearity is not needed to be validated in every new method.

The correlation coefficient, slope and residual sum of squares will be calculated of each result. The linearity is validated when the specifications and the F-test for linearity is passed. The linearity over the low and high range is proven when the slopes are regarded as equal if the ratio of the slopes is within 95 – 105 %. The intercept of the calibration lines is expected to be small. The significance of the intercept is tested on its equality to zero in a Student’s t-test with a maximum error contribution of 0.3% at the nominal level and 1.0% at the impurity level. 17

4.3 Precision

The precision of an analytical procedure expresses the closeness of agreement (degree of scatter) between a series of measurements obtained from multiple sampling of the same homogeneous sample under the prescribed conditions.16 Precision can be considered at three levels: repeatability, intermediate precision and reproducibility. The result of the determination of the precision of an analytical procedure is usually expressed as the variance, standard deviation or coefficient of variation of a series of measurements. In this Q-NMR validation the precision is studied at 3 levels, the system precision, method precision and intermediate precision.


Suzanne de Goeij 19

System precision The system precision is comparable to the repeatability in the ICH guidelines. The repeatability is defined as the precision under the same operating conditions over a short interval of time. The results of the linearity experiments can be used to determine the system precision. In the linearity experiments the samples are measured in triplicate at the same day, instrument and with the acquisition settings. The repeatability is calculated and specified according to the SOP.17-19 The repeatability is determined at the level X out of the linearity results with: ( ) 100%

The specifications for the repeatability are ≤ 1.5% for high levels (70 – 130% of the nominal level) and ≤ 5.0% for low impurity levels (0.01 – 1% of the nominal level). Method precision The method precision is determined by analysing six independently prepared samples of a representative drug substance. These samples will be prepared, measured and processed on six different days. The spectra are acquired using the standard 1D pulse program and using the inverse-gated 13C-decoupling sequence. The result of the method precision is the standard deviation over the six results and the comparison of the two pulse programs. For complete comparison of the method, the results will be compared with the data obtained within the accuracy experiments. The method precision is validated when there is no significance difference in the results of the three experiments and the average content of the 3 experiments within 2%. Intermediate precision The third part of the precision validation is the intermediate precision. In this part the inter analyst variation is validated together with different processing functions. The intermediate precision is determined by analysing two APIs and a primary standard using the absolute content determination (duplicate) and the 100% method. This is a standard procedure within Abbott Weesp for content determinations. For each sample two types of spectra are acquired; the standard 1D pulse program and the inversed-gated 13C decoupling method. All spectra are processed by 5 different analyst using different processing techniques. The 5 different analysts are all NMR analyst performing Q-NMR analysis in the development phase of Abbott Weesp. The different processing techniques consist of: - Fourier transformation using Exponential filter (EFP) - Fourier transformation using Gaussian filter (GFP) - Manual using the Bruker Top Spin software - Semi-automatic with in-house written software QINT version 10.

The intermediate precision is validated when there is no significant difference between analysts, acquisition methods and integration functions. The result of the validation of the precision is a coefficient of variance which can be used in future Q-NMR methods. All solutions are prepared ones by the same analyst. The samples are measured ones and processed by the different analyst according to the above described processing methods.


Suzanne de Goeij 20

The results of the validation of the precision will be used in further Q-NMR methods and therefore not validated in developing new Q-NMR analytical methods.

4.4 Accuracy

The accuracy of an analytical procedure expresses the closeness of agreement between the value which is accepted either as a conventional true value or an accepted reference value and the value found. 16

According to the SOP the accuracy results are determined based on the specificity and/or linearity and /or precision results.17-19 The accuracy of an analytical method is the extent to which test results generated by the method and the true value agree.

In NMR the accuracy can be checked by any substance using the stoichiometry, the ratio 2:3 for proton signals of the CH2 and CH3 groups in ethylbenzene will be found exactly in H-NMR.

In the validation of Q-NMR accuracy is validated using a primary standard with known content (CoA). The content of this standard is measured by Q-NMR and by an independent technique, titration. The results are compared to the results obtained by the certificate of analysis.

The accuracy is validated when the results of the Q-NMR experiments and the independent technique are not significantly different, examined with a t-Test. According to the SOP the accuracy is validated when the mean of the Q-NMR is within the 2% range of the mean from titration.17

Part of the method development of a new Q-NMR method is structure elucidation. Besides the stoichiometry, 2D spectra will be acquired to elucidate and prove the structure. Therefore it is not required to again validate the accuracy in the development of new Q-NMR methods.

4.5 Robustness

The robustness of an analytical method is a measure of its capacity to remain unaffected by small variations in method parameters and provide an indication of its reliability during normal use. The evaluation of robustness should be considered during the development phase and depends on the type of procedure under study. It should show the reliability of an analysis with respect to deliberate variations in method parameters. 16

The approach of the SOP for the validation of the robustness is chromatographic specific and cannot be used for in Q-NMR.17-19 In Q-NMR there are several acquisition and processing parameters that can have an effect on the outcome of the analysis.

For the validation of the robustness in Q-NMR three different effects can be distinguished: - Acquisition parameters - Processing parameters - Spectra evaluation (integration)

The acquisition parameters are validated in several studies in literature and not repeated in this study.7,11


Suzanne de Goeij 21

The influence of processing parameters like windowing, zero-filling, phasing and baseline correction was investigated in several studies and not validated in this study.7,11,15,24 However there are different window functions applied (Exponential (EFP) and Gaussian(GFP)) in different parts of the validation study. In the set up and evaluation of the intermediate precision and linearity the effect of these parameters are already discussed and will not be repeated in this part.

The spectra evaluation variation is due to the integration settings. The proper setting of the integration limits is critical but well known to the analyst working with the NMR. The contribution of the integration variation is obtained in other parts of this validation study, the linearity and precision experiments. In the QINT software a standard deviation is calculated over the average integration region.9 This standard deviation and the relative standard deviation are measurements of the selection of the integration region set by the analyst. The coefficient of variance is calculated and can be used in future Q-NMR analysis.

4.6 Detection limit and quantitation limit

The ICH guidelines defined the detection limit as: The detection limit (DL) is determined by the analysis of samples with known concentrations of analyte and by establishing the minimum level at which the analyte can be reliably detected. The definition of the quantitation limit (QL) of an analytical procedure is the lowest amount of analyte in the sample which can be determined with a suitable precision and accuracy.16

The ICH guidelines present different ways of determination of the detection limit and the quantitation limit. Not all are applicable for Q-NMR.16 - Based on visual evaluation. In general used for non-instrumental methods, but may also be used with instrumental methods. Although Q-NMR is an instrumental method, the visual evaluation is applicable for NMR methods. - Based on signal to noise. This approach can only be applied to analytical procedures which exhibit baseline noise. Determination of the signal-to-noise ratio is performed by comparing measured signals from samples with known low concentrations of analyte with those of blank samples and establishing the minimum concentration at which the analyte can be reliably detected. A signal-to-noise ratio between 3 or 2:1 is generally considered acceptable for validating the detection limit and a typical S/N ratio for quantitation is 10:1. - Based on the standard deviation of the response and the slope. The DL is expressed as DL: 3.3 σ / S and the quantitation limit is expressed ad QL: 10 σ / S Where σ is the standard deviation of the response and S is the slope of the calibration line - Based on the standard deviation of the blank. Calculation of the standard deviation of the response out of a number of blank samples - Based on the calibration curve. A specific calibration curve should be studied using samples containing an analyte in the range of DL or QL. The residual standard deviation of a regression line or the standard deviation of y-intercepts of regression lines may be used as the standard deviation. This approach is most used within Abbott Weesp and can be used for the determination of the DL and QL for Q-NMR.


Suzanne de Goeij 22

The specifications for DL and QL in the SOP are based on chromatographic methods and standard levels of noise. The DL and QL can be abstracted from the calibration line, with DL = 6 Sr / B and QL = 10 Sr / B, where SR is the residual standard deviation and b is the slope of the calibration line.17

Determining the DL and QL with the same approach as chromatography is not relevant for Q-NMR. Experimental parameters can be changed in such manner that an adequate S/N level is achieved, as long as the compound solubility and availability are not limited. For example, when analysing the same sample with increased number of scans the DL and QL become lower. Also increasing the magnetic field strength and using a modern probe result in lower detection and quantitation limits. To prove the low DL of Q-NMR an impurity at low level (25 ppm) was measured.


Suzanne de Goeij 23

5. EXPERIMENTAL

5.1 General equipment

NMR equipment, Bruker, DPX400 Autosampler. Samples are measured using the autosampler of Bruker. Samples are automatically acquired using the standard 1D pulse program. The number of scans (NS) and relaxation delay (D1) are set manually for each experiment. In some parts of the validation study an inverse-gated 13C-decoupling pulse program is used. In-house written software QINT version 10 is used for spectra evaluation.

Equipment titration (used for accuracy experiments) Metrohm titrator.

In the tables below an overview of the used chemicals are presented. Due to confidentiality the structures and names of the intermediates of the APIs cannot be shown. Table 1: Used chemicals

Chemicals Supplier Charge no DMSO-d6 Cambridge #7F-019 D2O Aldrich 06939JJ TFA Merck S5313360911 NaOH Fluka 82050

Table 2: Overview of used reference standards

Standards Supplier Charge no Purity (%m/m) Trimethoxy benzene Abbott Weesp ARS1028AA-001 99.5 Sodium citrate dihydrate Abbott Weesp ARS0006AB-030 100 Potassium hydrogenphthalate Sigma Aldrich 027K3732 100.0

Table 3: Overview of used samples.

Samples Purity (%m/m) API 1 * 100.2 Intermediate B* 98.9 Intermediate F* 99.6 Hexynoic acid 97.8 API 2* 99.4 Intermediate Rh* 99.2 Intermediate PA* 98.0 Intermediate P* 97.5

* Absolute content determined by NMR. Others purity certificate of analysis. In Q-NMR the absolute content is calculated using the equation:

= ∗ ∗ ∗ ∗ In all Q-NMR experiments this equation is used to calculate the absolute content.


Suzanne de Goeij 24

5.2 Specificity

The specificity for a particular Q-NMR method was evaluated by spiking two different API with different process-related impurities at a 1 % level. The first sample was API 1 with the process impurities Intermediate B, Intermediate F and Hexynoic acid. The second sample was API 2 with the process impurities intermediate Rh, intermediate PA and intermediate P. The API 2 in solution was not stable, an isomer formed when the solution was exposed to light. This was another process impurity in API 2.

The API 1 samples, including the process impurities, were dissolved in DMSO, 20 mg in 1 ml DMSO. The impurities were spiked at a level of 1% of the total amount of API 1. The same procedure was performed for the API 2 samples. Because the spiked sample of API 2 was sensitive towards light, the samples were measured directly and after 24 hours exposure to light.

All impurities were measured independently as well as in spiked samples. The samples were measured by the standard 1D pulse program and the by the inverse-gated 13C-decoupling sequence with NS=80 and D1=19.

Results were obtained by comparing the spectra and assign the signals to the correlating protons.

5.3 Linearity

For NMR methods the nominal level is typically 20 mg of a representative API in approximately 1 ml of DMSO or other solvent. The API used in the linearity experiments was API 1. Due to the acid end groups, in all samples a few drops of TFA were added to prevent a big water peak in the middle of the spectrum. For each sample an amount of 12 – 15 mg of internal standard, Trimethoxy benzene, was weighed.

For assay determinations, the linearity was evaluated by five various contents of the API, 70 – 85 – 100 – 115 – 130 % of the nominal level. Each sample was measured randomized three times. According to the SOP this should be 6 times for carry over effects. Since it is not possible to have carry over effects in Q-NMR, the samples were measured 3 times, to have sufficient data points for statistical calculations.

To evaluate the linearity at lower levels (e.g. for impurities at low levels), seven various contents of the API, 0.01 – 0.03 - 0.05 – 0.25 – 0.50 – 0.75 – 1.0 % of the nominal level were analysed. Each sample was measured three times. All spectra were acquired automatically with ns=80 and d1=35 and the samples were measured randomised.

The linearity samples were processed using different methods. The samples originating from the lower levels experiments were processed using the Exponential multiply and the Gaussian multiply (both using QINT10), the high levels samples were processed using the normal procedure (Exponential multiply and QINT10). The linearity was calculated at 2 signals in the API 1 spectrum, at 1.1 ppm (6H) and 6.7 ppm (1H), the internal standard was calculated at 6.1 ppm. The results were checked on outliers with the Grubb’s outliers test. The linearity was calculated by plotting the ratio weight API/Weight internal standard against the ratio integral API/integral internal standard. The correlation coefficient, slope and residual sum of squares were calculated of each result.


Suzanne de Goeij 25

The linearity was determined using the least squares method. An F-test was performed on the results where the data points are on a straight line and the residuals (Sr) are not larger than the random measurement error (Sanal).

25

The significance of the intercept was tested on its equality to zero in a Student’s t-test and calculated. This is calculated according to the SOP with: Intercept ≤ p x q x (a + b x X) where p is the error contribution (0.3% for nominal level and 1.0% for impurity level) and q is the boundary value for the bias, set at 3.0.17-19

5.4 Precision

The precision was determined at three levels, system precision, method precision and intermediate precision.

5.4.1 System precision

The system precision was extracted from the results of the linearity experiments. The repeatability was calculated according to the SOP by the level X out of the linearity results using the equation:

= ( ) 100%

Where Sr is the standard error of the residuals in the linearity experiments, A the intercept and B the slope of the calibration line. 17-19

5.4.2 Method precision

The method precision was determined by analysing six independent samples of API 1 with internal standard trimethoxy benzene. Around 20 mg of sample and 20 mg of internal standard was dissolved in 1 ml DMSO. To prevent a big water peak a few drops of TFA were added to the sample. The samples were prepared, measured and processed on 6 different days.

The spectra were acquired by using the standard 1D pulse program and by using the inverse-gated 13C-decoupling sequence, NS=80 and D1=35. The processing was performed by using the normal procedure, EFP and QINT10. The absolute content, average and standard deviation were calculated. The results were evaluated using the t-test.

5.4.3 Intermediate precision

The intermediate precision was determined by analysing two APIs (API 1 and API 2) and a primary standard (potassium phthalate). The APIs were analysed with internal standard trimethoxy benzene in DMSO and the primary standard with sodium citrate dihydrate in D2O. Around 20 mg sample and 20 mg of internal standard was dissolved in 1 ml solvent. For each compound 3 samples were prepared, two absolute content samples (ABS 1 and ABS 2) and one sample for 100% analysis (without internal standard) All samples were prepared by one analyst.

The spectra were acquired by using the standard 1D pulse program and by using the inverse-gated 13C-decoupling sequence, NS=80 and D1=35.


Suzanne de Goeij 26

All spectra were processed and calculate by 5 different analysts, using different processing types. The samples were analysed once but processed by different analyst and using different processing types.

Different methods of processing were used to calculate the content of the samples. In the table below a total overview of all processing’s done by one analyst is presented. The first processing was a manual processing using the Bruker TopSpin software (not routine within Abbott Weesp). The other processing was based on the QINT10 program (semi-automatic). For each results an Exponential multiply (EFP) and Gaussian multiply (GFP) was performed.

Table 4: Overview of different processing types for 3 compounds carried out by one analyst.

Compound Standard 1D 1H-NMR spectroscopy 13C-decoupled 1H-NMR

Manual processing

(TOPSPIN) Semi-automatic processing

(QINT10) Semi-automatic

processing (QINT10)

EFP GFP EFP GFP EFP GFP

API-1 -1 -1 100% 100% 100% 100%

ABS1 ABS1 ABS1 ABS1 ABS1 ABS1


API-2 -1 -1 100% 100% 100% 100%



100% 100% 100% 100% 100% 100%

Primary ABS1 ABS1 ABS1 ABS1 ABS1 ABS1

Standard ABS2 ABS2 ABS2 ABS2 ABS2 ABS2

1 100% analysis was not performed with the Bruker software except for the primal standard due to the complexity of the spectra of the APIs.

All results of the calculated content for each analyst, sample and processing are summarized in a table.

The results were evaluated with ANOVA using the software program (SAS 9.2 proc GLM). The results were compared to each other on main effect and interactions.


Suzanne de Goeij 27

5.5 Accuracy

The accuracy of Q-NMR was determined by comparing the content determination results of the primary standard, potassium phthalate analysed with Q-NMR and titration.

The Q-NMR results were obtained by weighing and analysing 6 different solutions of 20 mg potassium phthalate dissolved in 1 ml D2O and 20 mg internal standard sodium citrate. The spectra were recorded automatically with NS=80 and d1=35. The processing was performed by using the normal procedure, EFP and QINT10. The absolute content was calculated.

The titration results were obtained by 6 times an acid/base titration with NaOH. The samples originated from the same standard, the analysis was performed by another analyst. The measurements were done by weighing 150 mg of sample, dissolved in 70 ml water and titrated with 0.1M NaOH.

The results were calculated using the following equation: % = ∗ ∗ ∗ 100% The results of the Q-NMR and the titration of the primary standard were checked on outliers by performing the Grubb’s outlier test. To evaluate the results a t-test was performed.

5.6 Robustness

5.6.1 Acquisition parameters

In the literature validation of the acquisition parameters is extensively reported and hence was not repeated here.7,11 This was discussed in the introduction.

5.6.2 Processing parameters

In the intermediate experiment, the impact of the Gaussian and Exponential multiply of the FID was validated. The influence of processing like windowing, zero-filling, phasing and baseline correction was investigated in several studies and was discussed in the introduction.7,11,15,24 For all experiments a lb = 0.3Hz was used for Exponential window and lb = 0.6Hz for Gaussian window. Phase correction was done automatically by the software and checked manually applying zero and first order phase corrections. Baseline corrections were done using the QINT software and validated within the intermediate precision.

5.6.3 Spectra evaluation (integration)

The spectra were processed using the QINT software. In this software the uncertainty in the integral was calculated. The data of the linearity experiments were used for this validation item. Of each concentration range, low and high and at the two resonance signals, the coefficient of variance was calculated for the API and the internal standard.


Suzanne de Goeij 28

5.7 Detection limit and quantitation limit

The detection limit and quantitation limit in this validation study were determined using the data of the linearity study. The DL and QL calculated from the linearity is described as: DL/QL = x * SR / b, where x indicates 3,3 (according to ICH) or 6 (according to SOP) for DL and x=10 for QL, SR was determined by using the residual standard deviation of the calibration line. The DL and QL were calculated according to these equations.

The DL and QL are calculated from the low range (0.01 – 1 %) samples (results at the resonance signal of 1.1 ppm and 6.7 ppm and processed using EFP and GFP) used in the linearity experiment. The DL is also determined visually for the samples processed at 6.7 ppm.

In NMR spectroscopy there are a number of possibilities to improve the DL and QL. A potential genotox impurity from the synthesis of an API was used to challenge the LD and LQ on a 400 MHz spectrometer with a limit test. A 100 ppm, 50 ppm and 25 ppm solution of the genotox impurity was made by dilution and spiked into a solution of API in THF. Also a non-spiked sample of the API was measured with the same acquisition parameters as the impurity. All spectra were measured with the inverse-gated 13C-decoupling sequence to prevent overlapping satellites with the impurity.


Suzanne de Goeij 29

6. RESULTS AND DISCUSSION

6.1 Results Specificity

The specificity was validated by spiking 2 different APIs with process and synthesis impurities. The first sample was API 1 (A) with the process impurities Intermediate B (B), Intermediate F (F) and Hexynoic acid (H). In the spectrum below this API is presented with the spiked impurities, the spectrum is obtained with NS=80 and the standard 1D pulse program.

H9007001_1037.158.001.1r.esp

8.5 8.0 7.5 7.0 6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5Chemical Shift (ppm)

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Nor

mal

ized

Inte

nsity

Spectrum 1: Total spectrum of API 1 with spiked impurities.

H9007001_1037.158.001.1r.esp

3.5 3.0 2.5 2.0 1.5 1.0Chemical Shift (ppm)

0.05

0.10

0.15

Nor

mal

ized

Inte

nsity

Spectrum 2: Zoomed in spectrum of spiked API 1

H

A

A

A

A+F+B

DSMO

* *

H

A+H

F

B

H


Suzanne de Goeij 30

H9007001_1037.158.001.1r.esp

8.5 8.0 7.5 7.0 6.5Chemical Shift (ppm)

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11N

orm

aliz

ed In

tens

ity

Spectrum 3: Zoomed in spectrum of spiked API 1 (part 2)

The spectrum below was acquired with inverse-gated 13C-decoupling using the same sample solution and the same zoom as spectrum 2 to show the absence of 13C satellites.

H9007001_1037.159.001.1r.esp

3.5 3.0 2.5 2.0 1.5 1.0 0.5Chemical Shift (ppm)

0.05

0.10

0.15

0.20

Nor

mal

ized

Inte

nsity

Spectrum 4: Zoomed in spectrum of API 1 acquired with inverse-gated 13C-decoupling.

B

A

A

* * B F B

A

A+F+B

F B

B

F

A

H H

A

A

A+H

DMSO

H

A+F+B


Suzanne de Goeij 31

The same experiments were done for API 2. Process and synthesis impurities were spiked to API 2 and measured with the normal 1D pulse sequence and inverse-gated 13C-decoupling. The API 2 (A) was spiked with the process impurities intermediate Rh (Rh), intermediate PA (PA) and intermediate P (P). The API is sensitive towards light, an isomer (I) was formed after exposure to light. Therefore the spectrum was acquired directly after sample preparation and after 1 day.

H9007001_1031.107.001.1r.esp

8.0 7.5 7.0 6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0Chemical Shift (ppm)

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0.12

0.13

0.14

0.15

0.16

Nor

mal

ized

Inte

nsity

Spectrum 5: Full spectrum of API 2 with spiked impurities, acquired with standard 1D pulse program

H9007001_1031.107.001.1r.esp

3.5 3.0 2.5 2.0 1.5 1.0Chemical Shift (ppm)

0.05

0.10

0.15

Nor

mal

ized

Inte

nsity

Spectrum 6: Zoomed in spectrum of API 2 (part 1)

IPA

A

A+PA+P

* * *

A+PA+P

PA+P

A A

* *

PA

DMSO

Rh P

A+PA

A

A+PA+P

* * IPA

A+PA+P

PA+P

A A

PA

DMSO

A+PA+P


Suzanne de Goeij 32

H9007001_1031.107.001.1r.esp

8.0 7.5 7.0 6.5 6.0 5.5 5.0 4.5Chemical Shift (ppm)

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

0.070

0.075N

orm

aliz

ed In

tens

ity

Spectrum 7: Zoomed in spectrum of API 2 (part 2).

The spectrum below was acquired after one day of exposure to light, the isomer formed can be seen at 7.6 ppm.

H9007001_1031.114.001.1r.esp

8.0 7.9 7.8 7.7 7.6 7.5 7.4 7.3 7.2 7.1 7.0 6.9 6.8 6.7 6.6Chemical Shift (ppm)

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

0.070

0.075

Nor

mal

ized

Inte

nsity

Spectrum 8: Zoomed in spectrum of the aromatic area of API 2 solution acquired after 1 day (isomer formed).

Rh Rh

* * * *

A

P

A+PA

A+PA+P

A

Isomer


Suzanne de Goeij 33

The spectrum below was acquired with inverse-gated 13C-decoupling using the same sample solution as spectrum 8 and using the same zoom as spectrum 7 to demonstrate the absence of satellites.

H9007001_1031.115.001.1r.esp

7.5 7.0 6.5 6.0 5.5 5.0 4.5 4.0Chemical Shift (ppm)

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0.055

0.060

0.065

0.070

0.075

Nor

mal

ized

Inte

nsity

Spectrum 9: Full spectrum of inverse-gated 13C-decoupling sequence of API 2 solution acquired after 1 day.

6.1.1 Discussion Specificity

The specificity for the two APIs was demonstrated and met the specifications. There was a resonance signal which could be used for quantification and there was an empty space in the spectrum for an internal standard. The expected process impurities and solvents were not interfering with other signals in the spectrum and could be quantified. The spectrum with the decoupling of the 13C satellites could be integrated without concerning the overlapping satellites with impurities or main compound. In these examples there was a resonance signal were the main compound and internal standard were not interfering with the impurities and solvents. In case the impurities or solvents are overlapping with the main compound change of solvent, temperature, pH value or adding a specific shift reagent can be used.

Specificity was validated in different set ups in several studies.14,22,23 The Q-NMR method passed the specifications of the specificity. The specificity must be validated for each new Q-NMR method and re-evaluated when new impurities are discovered. This is also part of the method development of the quantitative assay.

Rh Rh

A A

I

P

A+PA A+PA+P


Suzanne de Goeij 34

6.2 Results Linearity

The linearity was validated at 70 – 130% of the nominal level of the API and at the low levels of impurities, 0.01 – 1%. The quantification of API 1 was performed by checking the lowest integral per proton, mostly the integral at 1.1 ppm (two CH3 groups, representing 6H) or at 6.7 ppm (single H, representing 1H). The validation of the linearity was done at both resonance signals. Due to the weights of the internal standard and the API, the real range of the validation is 62 – 120 %. For clarification, in the rest of the report the range 70 – 130 % is discussed.

First the linearity of the 70 – 130 % of the nominal level is evaluated and secondly the linearity at the lower levels.

Linearity at 70 – 130 % of the nominal level. Table 5: Results of 70 – 130% of the nominal level at 1.1 ppm

% Wx/Wis IX/IIS (1) IX/IIS (2) IX/IIS (3) Average IX/IIS

70 1.4 0.511 0.511 0.513 0.512

85 1.8 0.663 0.663 0.664 0.664

100 2.1 0.811 0.814 0.814 0.813

115 2.3 0.833 0.835 0.834 0.834

130 2.6 0.965 0.970 0.970 0.968

Figure 2: Linearity at 1.1 ppm API 1 in the range 70 – 130%

y = 0,3717x + 0,0005R² = 0,9999

0.4

0.5

0.6

0.7

0.8

0.9

1

1.2 1.6 2 2.4 2.8

IX/I

IS

WX/WIS

Linearity at 1.1ppm API 1 70-130%


Suzanne de Goeij 35

Table 6: Results of 70 – 130% of the nominal level at 6.7 ppm

% Wx/Wis IX/IIS (1) IX/IIS (2) IX/IIS (3) Average IX/IIS

70 1.4 0.506 0.506 0.500 0.504

85 1.8 0.658 0.655 0.654 0.656

100 2.1 0.805 0.803 0.802 0.804

115 2.3 0.825 0.825 0.825 0.825 130 2.6 0.960 0.957 0.959 0.958

Figure 3: Linearity at 6.7 ppm API 1 in the range 70 – 130%

Linearity at 0.01 – 1 % of the nominal level. The lowest points in the linearity study (0.01 - 0.03 - 0.05%) were visible detected and manually integrated if possible. The results of the precision experiments show repeatability at these levels of > 10%. The data of the 0.01 – 0.05 % samples are presented in the tables, but these data points were taken out in the calculations and results of the graphs.

In the results of the 0.01 – 1% of the nominal level results, at the resonance signal of 1.1 ppm, one point was marked as outlier (due to an integration error) according to the Grubb’s outlier test. This point was taken out of the results and calculations in the EFP and GFP processing. Table 7: Results of 0.01 – 1% of the nominal level at 1.1 ppm, processed with EFP.

% Wx/Wis IX/IIS (1) IX/IIS (2) IX/IIS (3)

0.01 0.02E-02 0.09E-03 0.19E-03 0.17E-03

0.03 0.07E-02 0.38E-03 0.33E-03 0.26E-03

0.05 0.10E-02 0.39E-03 0.52E-03 0.46E-03

0.25 0.53E-02 1.96E-03 1.92E-03 1.95E-03

0.50 0.97E-02 3.53E-03 3.65E-03 3.61E-03

0.75 1.59E-02 5.33E-03* 5.88E-03 5.89E-03

1.0 2.14E-02 7.89E-03 7.72E-03 7.73E-03 *Point marked as outlier, based on Grubb’s outlier test

y = 0,3699x - 0,0046R² = 0,9999

0.4

0.5

0.6

0.7

0.8

0.9

1

1.2 1.6 2 2.4 2.8

IX/I

IS

WX/WIS

Linearity at 6.7ppm API 1 70-130%


Suzanne de Goeij 36

Figure 4: Linearity at 1.1 ppm API 1 in the range 0.25 – 1 %

Table 8: Results of 0.01 – 1% of the nominal level at 1.1 ppm, processed with GFP.


0.01 0.02E-02 0.09E-03 0.21E-03 0.18E-03

0.03 0.07E-02 0.39E-03 0.34E-03 0.26E-03

0.05 0.10E-02 0.38E-03 0.54E-03 0.46E-03

0.25 0.53E-02 1.99E-03 1.93E-03 1.96E-03

0.50 0.97E-02 3.55E-03 3.67E-03 3.64E-03

0.75 1.59E-02 5.34E-03* 5.91E-03 5.93E-03

1.0 2.14E-02 7.92E-03 7.74E-03 7.76E-03 *Point marked as outlier, based on Grubb’s outlier test

Figure 5: Linearity at 1.1 ppm API 1 in the range 0.25 – 1 %

y = 0,3624x + 6E-05R² = 0,9992

0.00E+00

2.00E-03

4.00E-03

6.00E-03

8.00E-03

1.00E-02

0 0.005 0.01 0.015 0.02 0.025

Ix/I

IS

Wx/WIS

Linearity at 1.1 ppm API 1 0.25 - 1%, EFP

y = 0,3633x + 7E-05R² = 0,9991

0.00E+00

2.00E-03

4.00E-03

6.00E-03

8.00E-03

1.00E-02

0 0.005 0.01 0.015 0.02 0.025

Ix/I

Is

Wx/WIS

Linearity at 1.1 ppm API 1 0.25 - 1 %, GFP


Suzanne de Goeij 37

The result of the linearity at the lowest level (0.01%) at resonance signal of 6.7 ppm was too low for integration and is marked as not analysed (n.a.) in the tables.

Table 9: Results of 0.01 – 1% of the nominal level at 6.7 ppm, processed with EFP.


0.01 0.02E-02 n.a. n.a. n.a.

0.03 0.07E-02 0.37E-03 0.58E-03 0.52E-03

0.05 0.10E-02 n.a. 0.20E-03 0.13E-03

0.25 0.53E-02 1.85E-03 2.60E-03 1.77E-03

0.50 0.97E-02 4.00E-03 3.77E-03 3.64E-03

0.75 1.59E-02 5.90E-03 6.00E-03 5.76E-03

1.0 2.14E-02 7.73E-03 8.28E-03 8.05E-03

Figure 6: Linearity at 6.7 ppm API 1 in the range 0.25 – 1%

Table 10: Results of 0.01 – 1% of the nominal level at 6.7 ppm, processed with GFP.


0.01 0.02E-02 n.a. n.a. n.a.

0.03 0.07E-02 0.36E-03 0.60E-03 0.54E-03

0.05 0.10E-02 n.a. 0.22E-03 0.12E-03

0.25 0.53E-02 1.87E-03 2.65E-03 1.78E-03

0.50 0.97E-02 4.04E-03 3.81E-03 3.67E-03

0.75 1.59E-02 5.93E-03 6.04E-03 5.83E-03

1.0 2.14E-02 7.77E-03 8.37E-03 8.10E-03

y = 0,3647x + 0,0002R² = 0,988

0.00E+00

2.00E-03

4.00E-03

6.00E-03

8.00E-03

1.00E-02

0 0.005 0.01 0.015 0.02 0.025

Ix/I

IS

Wx/WIS

Linearity at 6.7 ppm API 1 0.25 - 1%, EFP


Suzanne de Goeij 38

Figure 6: Linearity at 6.7 ppm API 1 in the range 0.25 – 1%

In the table below an overview of all linearity results is presented.

Table 11: Overall results linearity

Sr df Sanal df A std (A) B std (B) SS R F calc CV

70-130% 1.1 ppm 1.66E-03 13 1.83E-03 10 4.53E-04 2.12E-03 0.372 0.10E-03 3.60E-05 0.999 0.83 0.24

6.7 ppm 1.78E-03 13 2.00E-03 10 -45.8E-04 2.27E-03 0.370 0.11E-03 4.12E-05 0.999 0.79 0.27

0.01-1% 1.1 ppm EFP 0.74E-04 9 0.57E-04 7 0.56E-04 5.05E-05 0.362 0.35E-02 0.49E-07 0.999 1.26 1.22

1.1 ppm GFP 0.78E-04 9 0.61E-04 7 0.69E-04 5.07E-05 0.363 0.37E-02 0.55E-07 0.999 1.30 1.28

6.7 ppm EFP 2.71E-04 10 2.91E-04 8 1.76E-04 1.85E-04 0.365 1.3E-02 7.34E-07 0.994 0.79 5.89

6.7 ppm GFP 2.81E-04 10 3.01E-04 8 1.88E-04 1.92E-04 0.367 1.3E-02 7.92E-07 0.994 0.80 6.04

Where Sr Residual standard deviation df degrees of freedom Sanal Estimation of the random measurement error A Intercept std (A) standard deviation in intercept B Slope std (B) Standard deviation in slope SS Sum of squares R Correlation coefficient

The F-value is calculated using =

Where statistical linearity was proven when the residual error was not larger than the random measurement error.

y = 0,3669x + 0,0002R² = 0,9873

0

0.002

0.004

0.006

0.008

0.01

0 0.005 0.01 0.015 0.02 0.025

Ix/I

IS

Wx/WIS

Linearity at 6,7 ppm API 1 0.25 - 1%, GFP


Suzanne de Goeij 39

The y-intercept in linearity should be less than a few percentage of the response. The significance and analytical relevance of the intercept was calculated according to the SOP with: 17-19 Intercept ≤ p x q x (a + b x X) where p = 0.003 (0.3%) for nominal level and 0.01 (1.0%) for impurity level and q = 3.17 In the table below the results of the intercept originating from the linearity experiments and the calculated limit is presented.

Table 12: Results of relevance of intercept

Intercept from linearity Decision limit

70-130% 1.1 ppm 4.53E-04 4.60E-03

6.7 ppm -45.8E-04 4.53E-03

0.01-1% 1.1 ppm EFP 0.56E-04 6.3E-05

1.1 ppm GFP 0.69E-04 6.4E-05

6.7 ppm EFP 1.76E-04 6.7E-05

6.7 ppm GFP 1.88E-04 6.8E-05

The results are discussed in the discussion.

6.2.1 Discussion Linearity

The linearity in Q-NMR experiments is never an issue since the intensity of the response signal is directly proportional to the amount of nuclei contributing to this signal. Some points were too low for integration or had to be taken out due to the Grubbs’ outlier test and according to the calculated repeatability at low levels. The variation in each calibration point was due to processing of the spectrum; phase corrections and integration. The limitations in the linearity are the solubility of the compound in the solvent and the DL and QL when a fixed number of scans are used. In the section about the DL and QL is described how the DL and QL can be improved. In the validation of the linearity several items were validated. The linearity was tested in the high level at 70 – 130% of the nominal value and in the low impurity level. Another parameter was the different nuclei in the same sample (with another amount of protons) and the different window functions in the low levels.

The standard deviations were calculated and with an F-test it was proven that there was no significant difference, so linearity is proven.

The difference in CV in the low range can be explained as the difference in the amount of protons, the data at 6.7 ppm was calculated with one proton, and the signal at 1.1 ppm contained 6 protons (2 CH3 groups). Due to the same experimental conditions (scans) the CV is higher at 6.7 ppm compared to 1.1 ppm; this will also be discussed in the detection limit (6.6).

In the low and high levels the slope and intercept were calculated for each result. The slopes in the high and low level were in a range of 95 – 105 %, so the linearity over the whole range (high and low) was proven.


Suzanne de Goeij 40

The significance and relevance of the intercept was calculated. At high levels the decision limit of the intercept was higher than the intercept originating from the linearity results, resulted in no significance influence of the intercept at high levels. At low levels, especially at 6.7 ppm, the intercept was significant. This is again related to the QL at 6.7 ppm, discussed in paragraph 6.6.

The correlation coefficient of the high levels and the low level at 1.1 ppm were > 0.999. For the low levels at 6.7 ppm the correlation coefficient was > 0.99. This is related to the QL, which will discuss in paragraph 6.6. The linearity was proven at low level and using different window functions. There was no significance difference in the Exponential and Gaussian window function.

Linearity was studied in several literature articles.14,21-23 A correlation coefficient of > 0.999 is always found. Due to the basic fact that NMR is a linear technique, the literature issues and demonstration of the linearity in this validation study, it is not needed to validate the linearity in further studies.


Suzanne de Goeij 41

6.3 Results Precision

6.3.1 Results System Precision

Results of the system precision (repeatability) at high level 70 – 130% of the nominal level are presented in table 13. The results were extracted from the linearity experiments at resonance signal 1.1 ppm. Table 13: Results of repeatability at high level

% Repeatability %

70 0.87 85 0.67

100 0.55 115 0.54 130 0.46

Results of the system precision (repeatability) at low level 0.01 – 1.0 % of the nominal level are presented in table 14. Results obtained from the linearity experiments at resonance signal 1.1 ppm and processed with EFP.

Table 14: Results of repeatability at low levels

% Repeatability %

0.01 56.64 0.03 34.67 0.05 24.99 0.25 6.59 0.5 3.43

0.75 2.32

1 1.75

6.3.2 Discussion System Precision

The system precision was validated by calculating the repeatability from the linearity samples at the high nominal levels and the low impurity level. The specification for the high levels was repeatability ≤ 1.5% (expressed as CV). The results were calculated with the linearity results at the resonance signal of 1.1 ppm, and at all levels the repeatability of < 1.0 % was reached, so the system precision passed the specification at the nominal level. The results of the low impurity level were calculated with the data at the resonance signal of 1.1 ppm and the EFP window function. The repeatability of the lowest levels (0.01 – 0.03 – 0.05) were > 5.0 % and are therefore not within the specifications. These levels cannot be used in the linearity study.

The system precision does not need to be validated with every new method. The DL and QL need to be determined during method development as discussed in part 6.6.


Suzanne de Goeij 42

6.3.3 Results Method Precision

The results of the method precision are presented in table 15. The ‘normal’ results are the content results of method precision measurements (6 samples measured and processed on 6 different days). The ‘13C Dec’ are the results of the inverse-gated 13C-decoupling experiments (same solution as the ‘normal’ samples). The last column shows the results obtained from the accuracy experiments (paragraph 6.4) Table 15: Results of method precision (Content in %m/m)

Normal 13C Dec Accuracy 99.2 99.4 100.6 99.6 99.4 100.1 98.9 99.1 100.5 99.5 99.5 100.4 99.6 99.7 100.8 99.2 99.5 100.0

Average 99.4 99.4 100.4 Stdev 0.31 0.21 0.30 CV % 0.31 0.21 0.30

The results were evaluating with a t-test.

6.3.4 Discussion Method Precision

The results were evaluated with a t-test. There was no significant difference between the samples acquired using the normal procedure and the 13C Dec procedure. As described in paragraph 6.4 the results of the accuracy experiments were overestimated, which resulted in a significant difference in the accuracy experiments compared to the Normal and 13C Dec experiments. However, all results are within a range of 2% and therefore the method precision is validated. It is not necessary to validate the method precision in future studies as the intermediate precision in 6.3.5 will give a coefficient of variance which can be used in future Q-NMR methods.

6.3.5 Results Intermediate Precision

The table with all the content results is presented in the appendix I. All results were evaluated with ANOVA using software program (SAS 9.2, proc GLM). The complete report is not included in this report, a summary is described and tables are presented in the appendix II. Several ANOVA models were calculated to evaluate main effects and interactions. The ANOVA was set up with main effects and interactions between analyst, method, integrator and window filter and was calculated for each compound separately. To evaluate the acquisition set up, standard 1H-NMR (QINT), 13C decoupled 1H-NMR (13CQINT) and manually settings (Bruker) were compared, so there is a comparison of QINT / 13C QINT and QINT / Bruker. The 1H-NMR (QINT) is standard used within Abbott Weesp. A full ANOVA model was calculated and checked on significant effects. Subsequently, a reduced model containing the statistically significant effects and interactions was calculated. This resulted in 12 ANOVA calculations.


Suzanne de Goeij 43

The calculated CV (residual error) and average (avg) content of each model is presented in the table below. Table 16: Results of CV from ANOVA analysis for all models.

Model Primary st API 1 API 2

CV Avg CV Avg CV Avg QINT / 13C QINT full model 0.045 100.10 0.159 99.67 0.143 98.72 QINT / Bruker full model 0.057 100.10 0.209 99.67 0.174 98.72 QINT / 13C QINT reduced model 0.045 100.10 0.147 99.57 0.146 98.72 QINT / Bruker reduced model 0.057 100.10 0.223 99.53 0.213 98.72 Each compound is discussed separately.

Primary standard The primary standard showed significant differences between operators and methods. In the graph below the results of the reduced model of the QINT / 13C QINT comparison is illustrated. The predicted content of the model calculated by the software is plotted against the observed content. The sample ABS 2 was clearly deviating from the other results of the ABS 1 and 100% analysis, so there is a significance difference in the method. Probably the deviation of the ABS 2 content is due to a weighing error. Although there was a significance difference in the operators and the methods, the differences were very small.

Figure 7: Results of reduced ANOVA model of primary standard where QINT / 13C QINT were compared.


Suzanne de Goeij 44

API In the ANOVA analysis of both APIs there was no significant influence of the window filter used, Exponential or Gaussian. This was also validated in other validation items like linearity. In the reduced models there were differences observed. In the reduced ANOVA analysis of API 1 there was no significant difference between the operators. There was a difference in methods and in the way of integration (QINT or Bruker).

For the API2 there was a significant difference in operators, methods and integration.

Although there are some significant interactions, the differences are very small. In the table below the results and variation is shown when all data are combined. (i.e. not corrected for any effect).

Table 17: Total results of intermediate precision

Compound Mean N N miss Variance St Dev CV Primary Standard 100.10 90 0 0.074 0.271 0.271 API 1 99.61 80 10 0.136 0.368 0.370 API 2 98.74 80 10 0.087 0.296 0.299

6.3.6 Discussion Intermediate Precision

The intermediate precision was validated using 3 different compounds (2 API’s and a primary standard) and different interactions. The method of acquisition was also part of the validation, measurement of the sample using the standard 1H pulse sequence or the inverse-gated 13C-decoupling sequence. The interactions validated in this study were - Operator; 5 different operators - Method; absolute content and 100% analysis - Integrator; manual with the Bruker software or semi-automatically with the QINT software - Window function; Exponential of Gaussian window function The CVs of all results were calculated and this resulted in a CV for the primary standard of 0.27, for API 1 in 0.37 and for API 2 in 0.30. Within Abbott Weesp a CV of 2% is normally used as specification for Q-NMR analysis, so the intermediate precision passed this specification. Although there are some significant differences, these differences are very small. Together with the CV < 0.5% , the results of this experiment can be used in future Q-NMR method development. This implies that a Q-NMR experiment can be done by every operator. The use of QINT and the manual processing and the use of the Exponential or Gaussian window function has limited impact on the results. The standard procedure of measuring an ABS content in duplicate and one 100% analysis with a release of a batch is validated. In future validation of Q-NMR methods it is not needed to validate the intermediate precision.


Suzanne de Goeij 45

6.4 Results Accuracy

The results of the accuracy experiments are presented in table 18.

Table 18: Results of Accuracy experiments

Analysis NMR (%m/m) Titration (%m/m) 1 100.62 99.97 2 100.12 99.86 3 100.48 99.87 4 100.38 99.90 5 100.81 100.11 6 100.03 99.84 Average 100.41 99.93 St Dev 0.30 0.10 CV % 0.30 0.10

According to the certificate of analysis (delivered by the standard) the purity of the potassium phthalate standard was 100 %m/m. The result of the t-test shows a significant difference between the techniques.

After performing the Grubb’s outlier test, no outliers were present in the results. The results were statically tested using a t-test and the techniques were statistically different, all NMR results were overestimated. To be sure of the internal standard used in the NMR experiments the sodium citrate standard was titrated with NaOH, the results were 99.61 %m/m and 100.31 %m/m, average 99.96 %m/m. Also the water content was determined by Karl Fisher. The results were 12.03 %m/m and 12.02 %m/m.

6.4.1 Discussion Accuracy

The result of the t-test was a significant difference between the results of the different techniques. The results of the Q-NMR are overestimated > 100 %m/m. To be sure of the internal standard (sodium citrate) used in the Q-NMR experiments, the water content and the purity of the internal standard were analysed. The purity is determined by titration with NaOH and the water content is determined with Karl Fisher. The purity of the batch sodium citrate is 100 %m/m and the water content is 12.0 %m/m, which was according to the expectations. The results were significantly different but met the specifications according to the SOP (2%). The mean content NMR divided by the mean content titration result in 100.5 % which is within the 98 and 102 %. Therefore it can be concluded that the accuracy is validated.

Part of the method development of a new Q-NMR method is structure elucidation. Besides the stoichiometry, 2D spectra will be acquired to proof the structure. Therefore it is not required to validate the accuracy in the development of new Q-NMR methods.


Suzanne de Goeij 46

6.5 Results Robustness

The acquisition and processing parameters were not validated in this study as discussed in the introduction. The standard deviation in the integral was calculated using the QINT software. The coefficient of variance was calculated of each level and window function. For the high levels the 70-130% samples in triplicate were used for the coefficient of variance. At the low levels the samples in the range 0.25% - 1.0 % were used. The CV (in %) is calculated to determine a limit of decision. In the table below the CV of the results are presented.

Table 19: CV of QINT results.

High Levels Low Levels EFP Low Levels GFP CV API 1.1 ppm 0.53 0.46 0.43 CV API 6.7 ppm 0.39 0.37 0.35 CV IS 0.25 0.39 0.41

6.5.1 Discussion Robustness

The acquisition and processing parameters were not validated in this study as discussed in the introduction. The error in the integral was determined using the QINT software. The CV were calculated. The CV of the integral is in the range of 0.3 – 0.6%. An estimation of a relative standard deviation of maximum 1.0 can be set as limit when using the QINT software and integrating main component and impurities.

In future Q-NMR method development it is not needed to validate the robustness.


Suzanne de Goeij 47

6.6 Results Detection limit and Quantitation limit

The DL was visually inspected at the samples at the resonance signal of 6.7 ppm. At the lowest level of 0.01% of the nominal level no peak was visible in the NMR spectrum at the position of the proton of interest at 6.7 ppm. The lowest level where an integral over the peak could be taken was 0.03 %. The resonance signal of the CH3 group in the lowest concentration sample (0.01 %) at 1.1 ppm was visible and can be integrated. According to the results of the repeatability (precision) only the samples starting from 0.25% could be used for the calculation of the DL and QL. In the table below the results of the DL and QL are presented. The results were calculated using: , = Where x is 3 or 6 for the DL and x is 10 for the QL.17-19

Table 20: Results of the DL and QL, results in %m/m

DL (x = 3) DL (x = 6) QL (x = 10) 1.1 ppm EFP 0.06 0.12 0.20 1.1 ppm GFP 0.06 0.13 0.21 6.7 ppm EFP 0.22 0.45 0.74 6.7 ppm GFP 0.23 0.46 0.71

Another part of the validation of the detection limit was the challenge of the detection limit by the measurement of a genotoxic impurity. A genotoxic impurity was added to the API and measured at different concentration of the impurity. In the graph below the spectrum of the API without spiked impurity is presented. The spectrum was acquired with NS= 4096 and D1= 2 sec.

Spectrum 10: Spectrum of API 2 without spiked impurity

H9007001_1042.408.001.1r.esp

7.5 7.0 6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0Chemical Shift (ppm)

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Nor

mal

ized

Inte

nsity


Suzanne de Goeij 48

H9007001_1042.408.001.1r.esp


-0.0005

0

0.0005

0.0010

0.0015

Nor

mal

ized

Inte

nsity

Spectrum 11: Zoomed in spectrum of API 2 at the position of the potential genotoxic impurity.

In the spectrum below the result of 100 ppm genotoxic impurity in API is presented, the spectrum is acquired with NS= 1024 and D1= 2 sec.

Spectrum 12: Zoomed in spectrum of spiked sample with impurity (100 ppm)

In the spectrum below the result of 50 ppm genotoxic impurity in API is presented. The spectrum was acquired with NS= 3072 and D1= 2.


H9007001_1042.402.002.1r.esp


-0.0010

-0.0005

0

0.0005

0.0010

0.0015

0.0020

0.0025

Nor

mal

ized

Inte

nsity

H9007001_1042.405.002.1r.esp


-0.0005

0

0.0005

0.0010

Nor

mal

ized

Inte

nsity

Region of the impurity


Suzanne de Goeij 49

In the spectrum the results of 25 ppm genotoxic impurity in API is presented. The spectrum was acquired with NS= 4096 and D1= 2 sec.

H9007001_1042.406.002.1r.esp


0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0.0008

0.0009

0.0010

0.0011

0.0012

Nor

mal

ized

Inte

nsity


6.6.1 Discussion Detection limit and Quantitation limit

The DL and QL limit were calculated according to the ICH guidelines and the SOP. The results were extracted from the linearity experiments at the resonance signal of 1.1 ppm and 6.7 ppm and processed using EFP and GFP window functions. There was no difference in DL and QL between EFP and GFP. The DL and QL increase with the number of protons, the QL at 6.7 ppm was significant higher than the QL at 1.1 ppm. At 1.1 ppm (6H) with NS=80 and D1=35 a QL of 0.20 % was calculated. At 6.7 ppm the QL was validated at 0.71 %. The QL of 0.71 % at resonance signal 6.7 ppm explains the results of the linearity experiments. The linearity was calculated over the range of 0.25 – 1.0 % while the QL was 0.71 %. This data were acquired with a fixed number of scans.

The DL and QL in Q-NMR is dependent on the number of scans, solubility of the API and the strength of the magnetic field. These parameters can be adjusted in such way that the required DL and QL can be reached. In future validation studies of new Q-NMR methods a short validation can be performed to justify the DL and QL needed for the impurity analysis, like the experiment of the 25 ppm genotox impurity. This is also part of the method development of the quantitative assay.


Suzanne de Goeij 50

7. CONCLUSION

The validation of Q-NMR as analytical method for quantitative measurement of the API and its impurities was demonstrated. In the conclusion the results are compared to specifications of HPLC methods for API analysis in early phase of development.

The items specificity, linearity, precision, accuracy, robustness and quantitation limit were validated with respect to the ICH guidelines and the SOP within Abbott Weesp.16-19 Some of the validation items need to be validated during method development of a new Q-NMR method. This results in the following conclusions:

Specificity: In HPLC the specificity is validated when the API and impurities are baseline separated.26 According to the SOP this is specified as the resolution ≥ 1.5 for the main compound and ≥ 1.0 for impurities.17 For Q-NMR the specification was set as no impurities are interfering with the API or the internal standard. In the study the specificity of two APIs was demonstrated. In most cases the specificity will not be a problem, since most organic compounds exhibit spectra with more than one resonance frequency. The specificity must be validated for each new Q-NMR method and re-evaluate when new impurities are found.

Linearity: An HPLC method is validated towards linearity when the correlation coefficient is > 0.999, the y-intercept should be less than a few percentage of the response of the main peak and a CV ≤ 2.0 %.17,26 The validated Q-NMR method at nominal level passed this specifications at both resonance signals, the correlation coefficient was 0.999, y-intercept not significant and a CV of 0.24 % (1.1 ppm 6H) and 0.27 % (6.7 ppm 1H) was found. At impurity level the y-intercept was significant at 6.7 ppm. The correlation coefficient at 1.1 ppm was 0.999 and at 6.7 ppm 0.994. The CV at 1.1 ppm was 1.22 % (EFP) and 1.30 % (GFP), at 6.7 ppm the CV was 5.89 % and 6.04 % respectively. The results at impurity level are overlapping with the quantitation limit. The slope of the high levels is within the range of the low levels, so linearity is proven over the whole range. Since NMR is fundamentally a linear technique, which was also demonstrated in literature and in this study, it is not needed to validate the linearity new Q-NMR methods.

Precision: Validating a HPLC method, the specifications for precision are split into repeatability (CV ≤ 1.0%), reproducibility (results < 2 %) and intermediate precision (CV ≤ 2%).17,26 The results of the repeatability in this Q-NMR study are CV < 1 % at nominal level. At impurity level the specification in HPLC methods is set as CV ≤ 5 %. The Q-NMR method cannot reach this specification at levels < 0.25 %. This is also discussed in the quantitation limit. The specification of the reproducibility in HPLC is set as the mean result of the main compound is < 2 %. In the method precision the reproducibility is examined and found to be < 2 %. The intermediate precision in this study is extensively determined including different processing parameters, this results in a CV < 0.4 %. The specification for the intra-day assay, often validate in HPLC, is set as ≤ 2.0 %, so the Q-NMR passed this specification.


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The precision does not need to be validated for new method. The intermediate precision demonstrated no significance differences between several parameters and therefore the operator has a certain freedom to choose the best acquisition and processing parameters.

Accuracy: HPLC methods are validated with a specification of 100 ± 2 % for accuracy experiments, mainly recovery experiments. In this validation Q-NMR is compared to titration, where the same standard is analysed with both techniques. The mean content of Q-NMR was 100.4 % with a CV of 0.3 % and for titration the content was 99.9 % with a CV of 0.1 %. Accuracy in Q-NMR is also part of the method development. Structure elucidation is done with both 1D and 2D spectra. After the complete elucidation of the structure it is not needed to validate the accuracy in a new Q-NMR method.

Robustness: Robustness in HPLC is validated as the variations in different parameters, like variation in analyst, equipment, column or small changes in method. However, in early phase of development a HPLC method is limited validated for robustness. The column to column variation can be done or study on stability in solution study. In this Q-NMR study the robustness is validated within the intermediate precision for different processing parameters. The QINT results are used to determine a common CV of maximum 1 % in the integration settings. In new Q-NMR methods it is not needed to validate the robustness. In this study the stability in solution is not validated, during method development of a new Q-NMR method, this item can be validated.

DL and QL: Detection and quantitation limits in HPLC are dependent of the used detector. Quantitation limits in Q-NMR can be easily decreased by increasing the number of scans of increasing the amount of sample. The validated quantitation limits in this study, calculated from the linearity results, are 0.20 % at 1.1 ppm (6H) and 0.74 % at 6.7 ppm (1H). The QL at 6.7 ppm explain directly the results in the linearity at low levels at 6.7 ppm. The detection of a genotoxic impurity spiked to the API is demonstrated at a level of 25 ppm. In a new Q-NMR method there is a limitation of the QL at a certain number of scans, and at a resonance signal with one proton. Increasing the number of scans of amount of sample will result in a lower QL. It is not needed to validate the QL in new Q-NMR methods.

At the nominal level in several experiments a CV was found of 0.3 % (linearity), intermediate precision < 0.4 %, 0.3 % (accuracy). In

The results of this validation study showed a performance comparable to chromatographic method and therefore Q-NMR can be used in future Q-NMR method development for API analysis in early phase of development.


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REFERENCES

1: U. Holzgrabe et al, NMR spectroscopy in pharmaceutical analysis, Elsevier first edition, 2008 2: H. Friebolin, Basic One- and Two-Dimensional NMR Spectroscopy, Wiley-VCH fourth edition, 2005 3: P. Soininen, Quantitative 1H NMR Spectroscopy, Chemical and Biological Applications, doctoral dissertation October 2008 4: C.P. Slichter, Principles of Magnetic Resonance, Springer 3rd edition 1990 5: Bruker, Training Course Nuclear Magnetic Resonance Spectroscopy 6: R.M. Silverstein, F.X. Webster and D.J. Kiemle, Spectrometric Identification of Organic Compounds, Wiley, seventh edition 2005 7: F. Malz and H. Jancke, Validation of Quantitative NMR, Journal of Pharmaceutical and Biomedical Analysis 38 (2005) 813-823 8: L. Griffiths and A.M. Irving, Assay by nuclear magnetic resonance spectroscopy: Quantification Limits, Analyst 123 (1998) 1061-1068 9: J. De Korte and P.J. Andree, Short validation QINT10; Compared to QINT 9C, Internal Document Abbott Weesp, December 2007 10: S. Kumar Bharti and R. Roy, Quantitative 1H NMR spectroscopy, Trends in Analytical Chemistry 35 (2012) 5 – 26 11: G.F. Pauli et al, Quantitative 1H-NMR: Development and Potential of a Method for Natural Product Analysis, Journal of Natural Products 68 (2005) 133-149 12: T. Rundlof et al, Survey and qualification of internal standards for qualification by 1H-NMR spectroscopy, Journal of Pharmaceutical and Biomedical Analysis 52 (2010) 645-651 13: S. Akoka et al, Concentration Measurement by Proton NMR Using the ERETIC Method, Analytical Chemistry 71 (1999) 2554-2557 14: G.K. Webster et al, Validation of Pharmaceutical Potency Determinations by Quantitative Nuclear Magnetic Resonance Spectrometry, Applied Spectroscopy 64 (2010) 537 - 542 15: G.F. Pauli, QNMR – a Versatile Concept for the Validation of Natural Product Reference Compounds, Phytochemical Analysis 12 (2011) 28-42 16: ICH Harmonised Tripartite Guideline, Validation of Analytical Procedures: Text and Methodology Q2(R1), current step 4 version, 2005 17: P. Hoogkamer and N. Lammers, Guidance to Validation, Adjusments and Transfer of Analytical Methods, SOP Internal document Abbott Weesp, June 2008 18: P. Hoogkamer and N. Lammers, Validation, Adjustments and Transfer of Analytical Methods, Scientific Background, SOP Internal Document Abbott Weesp, April 2008 19: P. Hoogkamer and N. Lammer, Chromatografie in de praktijk, chapter methode validatie farmaceutische analyse, Ten Hagen-Stam July 2001 20: S. de Goeij, Protocol Validation of 1H-NMR (Q-NMR) Spectroscopy, Internal Document Abbott Weesp, Aug 2010 21: G. Maniara et al, Method Performance and Validation for Quantitative Analysis by 1H and 31P NMR Spectroscopy. Applications to Analytical Standards and Agricultural Chemicals, Analytical Chemistry 70 (1998) 4921-4928.


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22: S. Bekiroglu et al, Validation of a quantitative NMR method for suspected counterfeit products exemplified on determination of benzethonium chloride in grapefruit seed extracts, Journal of Pharmaceutical and Biomedical Analysis 47 (2008) 958 – 961 23: R. Sharma et al, A quantitative NMR tool for the simultaneous analysis of atropine and obidoxime in parental injection devices, Journal of Pharmaceutical and Biomedical Analysis 49 (2009) 1092 – 1096 24: A. Ebel et al, Effects of zero-filling and apodization on spectral integrals in discrete Fournier-transform spectroscopy of noisy data, Journal of Magnetic Resonance 182 (2006) 330-338 25: W.Th. Kok, Statistics for Analytical Chemistry, MSc program Analytical Sciences, January 2008 26: G.A. Shabir, Validation of high-performance liquid chromatography methods for pharmaceutical analysis. Understanding the differences and similarities between validation requirements of the US Food and Drug Administration, the US Pharmacopeia and the International Conference on Harmonization, Journal of Chromatography A 987 (2003) 57 – 66.


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APPENDIX I

Table 21: Total results of intermediate precision experiment

Bruker Manual QINT QINT 13C dec

Analyst 1 EFP GFP EFP GFP EFP GFP

Proc I II III IV V VI

API 1 100% 100,00 99,64 99,56 99,37

ABS 1 99,55 99,63 99,17 99,64 99,37 99,90

ABS 2 99,34 99,62 99,59 99,52 99,43 99,47

API 2 100% 98,92 98,94 98,84 99,11

ABS 1 99,13 99,04 98,28 98,78 98,25 98,90

ABS 2 99,11 99,27 98,36 98,55 98,61 98,77

Primary 100% 100,00 100,00 100,00 100,00 100,00 100,00

Standard ABS 1 99,77 99,83 99,78 99,85 99,74 99,65

ABS 2 100,35 100,36 100,41 100,28 100,51 100,43

Analyst 2 Proc I II III IV V VI

API 1 100% 99,98 99,97 99,57 99,79

ABS 1 99,52 99,87 99,64 99,51 99,77 99,75

ABS 2 99,65 99,56 99,35 99,68 99,68 99,17

API 2 100% 98,69 98,81 98,84 98,95

ABS 1 98,67 98,67 98,46 99,03 98,88 98,39

ABS 2 99,20 98,93 98,72 98,95 98,89 98,91

Primary 100% 100,00 100,00 100,00 100,00 100,00 100,00

Standard ABS 1 99,77 99,91 99,93 99,85 99,77 99,78

ABS 2 100,31 100,47 100,40 100,43 100,28 100,37

Analyst 3 Proc I II III IV V VI

API 1 100% 99,86 99,85 99,67 99,72

ABS 1 100,21 100,79 98,79 98,87 98,80 98,82

ABS 2 100,11 100,45 98,99 99,14 98,98 99,08

API 2 100% 99,04 98,93 98,92 98,96

ABS 1 98,09 97,93 98,53 98,62 98,59 98,70

ABS 2 99,22 98,68 99,02 99,01 98,87 98,86

Primary 100% 100,00 100,00 100,00 100,00 100,00 100,00

Standard ABS 1 99,87 99,88 99,87 99,86 99,91 99,86

ABS 2 100,58 100,44 100,54 100,49 100,56 100,48


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Bruker Manual QINT QINT 13C dec

Analyst 4 efp gfp efp gfp efp gfp

Proc I II III IV V VI

API 1 100% 99,95 99,97 99,47 99,89

ABS 1 99,87 99,70 99,61 99,45 99,54 99,74

ABS 2 99,62 99,61 99,64 99,49 99,49 99,43

API 2 100% 98,51 98,66 98,64 98,83

ABS 1 98,55 99,00 98,41 98,51 98,44 98,64

ABS 2 98,76 98,91 98,61 98,84 98,49 98,71

Primary 100% 99,92 99,92 99,99 99,99 99,99 99,92

Standard ABS 1 99,79 99,93 99,87 99,85 99,82 99,86

ABS 2 100,33 100,60 100,45 100,47 100,45 100,46

Analyst 5 I II III IV V VI

API 1 100% 100,01 100,10 99,74 99,87

ABS 1 99,70 99,56 99,16 99,34 99,49 99,61

ABS 2 100,63 99,78 99,46 99,59 99,13 99,37

API 2 100% 98,83 98,89 99,29 99,36

ABS 1 98,57 98,52 98,46 98,42 98,74 98,58

ABS 2 99,28 98,44 98,06 98,19 98,42 98,53

Primary 100% 99,84 99,81 99,98 99,98 99,98 99,98

Standard ABS 1 100,00 100,01 99,94 99,90 99,98 99,95

ABS 2 100,64 100,55 100,53 100,52 100,53 100,51


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APPENDIX II

Summary of the results of the ANOVA experiments ANOVA Full model Primary standard QINT/Bruker

ANOVA Full model Primary standard QINT / 13C QINT


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ANOVA Reduced model Primary standard QINT/Bruker

ANOVA Reduced model Primary standard QINT / 13C QINT


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ANOVA Full model API 1 QINT/Bruker

ANOVA Full model API 1 QINT / 13C QINT


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ANOVA Reduced model API 1 QINT/Bruker

ANOVA Reduced model API 1 QINT / 13C QINT


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ANOVA Full model API 2 QINT/Bruker

ANOVA Full model API 2 QINT / 13C QINT


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ANOVA Reduced model API 2 QINT/Bruker

ANOVA Reduced model API 2 QINT / 13C QINT

validation of quantitative nmr · 2020-06-02 · methods, validation is not commonly performed for...

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