Peak-purity by LC-MS and LC-DAD Knut Dyrstad Erlend Hvattum Sharon Jara Arnvid Lie

1. Peak-purity by LC-MS and LC-DADKnut DyrstadErlend HvattumSharon JaraArnvid Lie

2. Peak-purity • Peak-purity is of vital importance for documenting the safety and the efficacy of a pharmaceutical drug • The improvement of the chemical syntheses and the pharmaceutical processes requires knowledge about purity • LC-MS is the matter of choice (standalone equipments as MS, NMR and IR are frequently used to explore composition) • Among all samples being analyzed, the challenge is to scientifically evaluate which samples need the extra purity attention • The supplementary use of LC-MS and LC-DAD-PCA (chemometrics) in purity investigations will be discussed

3. Peak-purity assesment by LC-MS • Traditionally it is a manual task; i.e. time consuming • Different scans accross the peak is evaluated to determine whether co-eluting compounds are present • Ideally, both negative and positive ESI should be employed

4. Example HPLC-parameters Mobile phases: A = 0.1% TFA in water; B = 0.085% TFA in MeCN Column: Symmetry C18, 3.5, 4.6x150mm Flow: 0.9 ml/min UV: 200 – 400 nm Column temp.: 30 ºC; MS-parameters QTof-micro MS (Waters) Positive ion ESI mode Capillary spray at 3kV Temperatures: 100º (source) and 300º (dessolvation) Cone voltage: 30V Scan range: m/z 100 – 2000 and 2 secs/per scan Sample Exact mass of compound = 1257.49 u Concentration = 2.12 mg/ml in water

5. UV-chromatogram Mass chromatogram

6. [M + 2H]2+ [M + H]+ [M + 3H]3+

7. 6 = range 460:465 5 = range 454:459 4 = range 448:453 3 = range 442:447 [M+2H]2+ [M+H]+ [4M+3H]3+ 2 = range 436:441 [M+3H]3+ [5M+4H]4+ [6M+4H]4+ ? ? 1 = range 430:435

8. UV m/z 601.3 m/z 572.3 m/z 687.3

9. Conclusion • One or possibile two compounds were found to elute at the rising edge of the main peak • One compound was found to elute at the falling edge of the main peak

10. Principal Component Analysis on LC-DAD spectra – PCA Peak Purity The use of PCA has become an essential tool within spectra interpretation of NIR, IR, RAMAN, UV of Fluorescence spectra. The high number of wavelengths (~ 1200 wavelengths) makes PCA a necessary tool. PCA is often used in combination with pre-spectral transformation as derivation, normalization and “scattering” corrections. All these tools are available in Unscrambler. The PCA algorithm is VERY adequate to evaluate changes in DAD spectra as a function of retention time in LC-DAD

11. Principal Component Analysis on LC-DAD spectra – PCA Peak Purity • Why: To reveal any co-eluted constituents in LC interfering with the real purity. • How: Perform principal component analysis on UV/VIS DAD spectra from a LC run. • When: • Impure (main) peak is suspected • Evaluate resolution as a function of method conditions during method development to • Control of GxP material and stored samples (at elevated temperatures) • Compare new peaks with historical peaks • Determine if a LC-MS analysis should be used / put up

12. Principal Component Analysis on LC-DAD spectra – PCA Peak Purity How does PCA work: Data matrix

13. The 3 most relevant chemometrics (statistical) parameters in peak purity PCA are: • Loadings: Show which part of the UVVIS spectrum having largest change during retention time • Scores: Show how the retention having the largest in the UVVIS spectra change (~Scores of PC1 is comparable to the single wavelength chromatogram at abs max) • Residual variance: Show how the level of unexplained UVVIS variance at each time point • The first PC shows the largest change in spectra during time leaving noise behind. The second PC shows the second largest systematic change in the spectra leaving noise behind, and so on. • The score chromatogram from PC1 is usually shows the single wavelength chromatogram. • The score chromatograms from PC2, PC3, PC4, etc., show chromatograms dependent on (small) changes in UVVIS spectrum that may indicate different chemical constituents than the main constituent. • Since the loadings from PC2, PC3, etc., is rest-variation after lower dimensionalities, these loadings spectra is not true spectra but show where the spectrum differ from main constituent spectrum. • The statistical parameters above are standard statistical output in Unscrambler and other chemometrics software.

14. PCA Peak-Purity The score chromatogram from PC1 is a function of the largest variation in UVVIS spectra. tR, min

15. Comparison of 650 nm abs max single wavelength chromatogram (upper) with score-chromatogram from PC1 (lower):

16. Sensitivity with PCA The power of using PCA (noise reduction) on several wavelength compared to single wavelength in corresponding λ-area to get detailed information about purity Consequence: Small changes in UVVIS can be found by PCA tR, min tR, min Single 364nm (above) vs PCA on 354-398nm (below) Single 282nm (above) vs PCA on 252-300nm (below) 282nm 364nm tR, min tR, min

17. PCA Peak-Purity – case study • Polymer based drug consisting of groups of different molecular weights • High degree of co-elution / difficult (mission impossible?) to get peak separation • Difficult to analyze with standard LC-MS equipment • Challenging to achieve reproducible chromatograms

18. PCA Peak-Purity – case study Detected by PCA

19. PCA Peak-Purity – case study – degraded sample Evaluation of residual variance after PC1 and PC2 for this degraded sample revealed several components being important for selecting storage conditions. No component here

20. Comparison with the LC-MS case PC1 PC2 UV Used for PCA Residual variance after PC1 The PCA peak-purity indicated 2-3 peaks 2 peaks on the rising edge 1 broad “bump” peak on the falling edge

21. Pitfalls with PCA Peak-Purity Non-linearity in absorbance can sometimes looks like co-eluting peaks. This have a often a systematic profile in residual variance.

22. Pitfalls with PCA Peak-Purity MeCN gradient system will always affect the residual variance at λ < ~250 nm. Can be solved by (1) analyze a narrow time frame, (2) adjust to isocratic solvent composition over the specific peak or analyze DAD spectra above ~250 nm.

23. Pitfalls with PCA Peak-Purity Evaluate the noise in scores, loadings and residual variance. Noise profile If the absorbance spectrum is suspected to be completely identical then LC-DAD is insufficient (~isomerism).

24. Thanks for your attention!