Improving the Metabolite Identification Process with Efficiency and Speed: LightSight Software for Metabolite Identification

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1 Improving the Metabolite Identification Process with Efficiency and Speed: LightSight Software for Metabolite Identification Overview LightSight Software for Metabolite Identification is a complete environment to find metabolites quickly and easily by streamlining the process from acquisition through to confirmation. Designed and built by ADME researchers, with input from over one hundred sessions with scientists worldwide, it makes the process of identifying metabolites more efficient than ever before. Using the PeakPerform Peak Finding Algorithm, the MS/MS acquisition wizard, and the automated comparison of MS/MS spectra, LightSight software allows you to efficiently identify and confirm metabolites in data acquired on Applied Biosystems/MDS Sciex triple quadrupole and hybrid quadrupole-linear ion trap mass spectrometers. Combined with high precision low flow chromatographic techniques, the metabolite identification process from data acquisition to matched workflow data analysis reduces the time spent on metabolism studies. Introduction The importance of metabolism studies to the drug discovery process is undisputed. The benefits to pharmaceutical companies of, for example, identifying potentially toxic metabolites in a drug candidate as early as possible, are significant. Despite the importance of ADME studies, the process of conducting them is extremely time-consuming and inefficient. Improvements in the instrumentation and/or the software to automate parts of the process hold the potential for considerable benefits to drug metabolism researchers. A typical metabolism study workflow is used to illustrate where significant efficiency gains have been made in metabolism data collection through improved LC instrumentation, and in data processing through improved software for metabolite identification. LightSight Software for Metabolite Identification LightSight software is a complete environment that streamlines the metabolite identification workflow from acquisition through to confirmation of metabolites. Key Features: A single integrated workspace displaying all the data associated with a potential metabolite. PeakPerform algorithm intuitive and well-defined processing parameters to allow rapid sample-to-control comparisons. Automatic generation of dedicated MS/MS methods based on the potential metabolites identified. Automatic comparison of the MS/MS spectrum of a potential metabolite to that of the parent compound. Automatic report generation. The process of metabolite identification is made more efficient compared to traditional manual sample and control comparisons. Figure 1 shows an overlaid display of the extracted ion chromatograms (XIC) of both the sample and control, and the adjacent display of the parent and

2 metabolite MS/MS spectra, allowing you to quickly and effectively compare spectra visually, and thus make better decisions. Figure 1. The processing workspace displays all the data associated with a metabolite in one view. Using the simple Acquire MS/MS Data wizard, you can create and start using complex multi-period, multi-experiment methods with a few mouse clicks. Using a sophisticated scheduling algorithm, MS/MS data for all the potential metabolites are acquired in as few injections as possible, often no more than one. Figure 2 shows the list of potential metabolites from the survey scan that need MS/MS data for confirmation. The wizard incorporates these into a period-based dedicated MS/MS acquisition. Overall, a significant improvement in throughput for the data analysis process and acquisition of confirmatory MS/MS for metabolism studies is accomplished. Figure 2. The Acquire MS/MS Data wizard generates MS/MS method(s) automatically.

3 Manual vs. Automated Metabolite Identification: A Validation Study LightSight software contains a new peak finding algorithm (PeakPerform Peak Finding Algorithm) for superior sample-to-control comparisons. This was validated against manually processed data using a set of 14 different drugs shown in Table 1. Compound MWT Species Survey Scan Polarity Terfenadine Rat EMS + Buspirone Rat Q1 + Loperamide Rat EMS + Verapamil Rat EMS + Erythromycin Rat EMS, NL + Haloperidol Rat Q1 + Bendroflumethiazide Rat Precursor (2), Q3 - Nicardipine Dog EMS, Precursor (2), NL (2) + Brompheniramine Rat Q3 + Bromocriptine Rat, Dog, Rabbit EMS + Chlorthalidone Rat EMS - Benzbromarone Rat EMS, Precursor - Ketoconazole Rat Q3 + Diclofenac Rat Q1, EMS - Table 1. Drug compounds used in metabolite ID study to compare manual vs. automated techniques. The molecular weight, species and the survey scan with polarity of the mass spectrometer is listed. Experimental Details Each compound was incubated (5-50 µm) in rat liver microsomes with a NADPH regenerating system for 1 hour at 37 C. Samples were injected (5-10 fold dilution) using both an Agilent 1100 System and a Tempo ht LC system with various mobile phase gradient elution methods. Data was collected on a 4000 Q TRAP mass spectrometer. The metabolites formed were identified through manual processing and the results were used as the baseline for comparison against the new algorithm and overall data processing experience with LightSight software. Traditional Manual Metabolite Identification Process Survey scans (either linear ion trap EMS, Q1, Q3, precursor ion or neutral loss) of both the sample (1 hour time point) and the control (t = 0) were evaluated for differences, i.e; potential metabolites based on peaks present in the sample, but not the control. Manual processing of the data was carried out by extracting 25 amu wide chromatograms (XIC) for the entire mass range for both the sample and the control (Figure 3). Each of these chromatograms was visually inspected and potential peaks identified. The spectra corresponding to these peaks were also examined for correct m/z and isotopic abundance (Figure 4). An XIC was then re-extracted and compared to the control for the corresponding mass of interest (Figure 5). Following this peak identification process, corresponding MS/MS data was collected to eliminate or confirm the peak as a metabolite of the parent drug. Table 2 shows a summary of the results for the manual metabolite identification process for one of the drug compounds in the study, terfenadine. For terfenadine, 9 metabolites were identified and confirmed with MS/MS data through the traditional manual workflow; mass range extraction, peak identification, m/z assignment, re-extraction of mass of interest and MS/MS for confirmation. With this traditional manual workflow the identification of metabolites for the 14 drugs studied took approximately 300 hours of processing time, which corresponds to the profiling of about 7-8 compounds a month.

4 XIC of +EMS: 25 to amu from Sample 2 (Rat microsomes (oxidative) t=1hr) e7 6.0e7 4.0e7 Max. 7.3e7 cps. XIC of +EMS: 25 to amu from Sample 1 (Rat microsomes (oxidative) t=0) of... Max. 8.5e7 cps e7 6.0e7 4.0e7 Sample Control Peak D Figure 3. XIC of mass range m/z for the terfenadine drug study. The survey scan range covered m/z. I n t... I n t... I n t e n s i t y... XIC of +EMS: 25 to amu from Sample 2 (Rat microsomes (oxidative) t=1hr) e7 Max. 7.3e7 cps XIC of +EMS: 25 to amu from Sample 1 (Rat microsomes (oxidative) t=0) of... Max. 8.5e7 cps. 8.5e7 5.0e EMS: to min fro... Max. 5.2e6 cps. +EMS: to min fro... Max. 4.9e6 cps. 5.0e6 4.0e6 2.0e m/z, amu I n t e n s i t e5 5.0e5 Peak D m/z, amu Figure 4. Determination of m/z for Peak D. XIC of +EMS: to amu from Sample 2 (Rat microsomes (oxidative) t=1hr) e7 1.5e7 1.0e7 Max. 2.3e7 cps e XIC of +EMS: to amu from Sample 1 (Rat microsomes (oxidative) t=0) of... Max. 4.9e6 cps. 4.9e6 4.0e6 3.0e6 2.0e6 1.0e Peak D Figure 5. XIC of m/z ion of interest (Peak D). Comparison of sample and control.

5 Peak m/z Value Ret. Time (min) Peak Area Peak Height % Total Area * D e8 2.27e7 3.6 E e7 5.25e6 0.8 G (Parent) e9 2.04e H e8 1.70e7 2.7 I e9 2.16e K e7 1.19e7 1.9 J e8 4.10e7 6.4 L e8 2.06e7 3.2 N e7 6.48e6 1.0 M e8 9.11e Table 2. Metabolites identified for terfenadine using a traditional manual sample-to-control comparison. On average, approximately 3 days of data analysis and processing was done per drug study to identify and confirm potential metabolites. *Highlighted text corresponds to >5% total area. Automated Metabolite Identification Process With LightSight Software and the new PeakPerform Algorithm, this process was significantly improved to approximately 1.5 hours for a single drug sample to control comparison. For the 14 drugs tested, LightSight software found all the metabolites identified and confirmed by the manual process. The total processing time for the 14 drugs was 23 hours. This is greater than a 13 times improvement in efficiency and speed for the data review and processing stages. Table 3 shows the metabolites identified by LightSight Software. Peak m/z Value Ret. Time (min) Peak Area Peak Height % Total Area * D e8 2.27e7 3.5 E e7 5.25e6 0.8 G (Parent) e9 2.04e H e8 1.70e7 2.8 I e9 2.16e K e7 1.19e7 1.8 J e8 4.10e7 6.8 L e8 2.06e7 3.0 N e7 6.48e6 0.6 M e8 9.11e Q e7 8.38e6 1.4 R e7 6.03e6 0.9 S e7 5.56e6 0.8 Table 3. Metabolites identified for trefenadine using LightSight software. LightSight identified all metabolites plus an additional 3 metabolites overlooked through the manual process with a significant improvement in overall review and processing time.

6 Throughput Considerations Data acquisition was also improved with a higher performing gradient chromatographic elution. The Tempo ht LC System is a new front-end capillary LC system designed for rapid, precise gradient delivery, high-resolution HPLC applications. The Validation study to compare traditional manual data review and processing with LightSight software used the Agilent 1100 LC system for gradient elution over a 20 minute overall cycle time. Using the Tempo ht LC system, the same number of metabolites identified and confirmed for each parent drug was achieved, but with a significant reduction (greater than a factor of 6) in the overall cycle time of the LC acquisition. Figure 6 shows the terfenadine drug study and the overlaid XICs of the parent drug peak from the original LC conditions (20 minute cycle time) and the Tempo ht LC conditions (3 minute cycle time). Original LC conditions: 400 µl/min, 20 minute gradient analysis time Parent Drug RT = 16.3 min Tempo ht LC conditions: 15 µl/min, 3 minute gradient analysis time Parent Drug RT = 1.58 min Figure 6. Terfenadine drug study comparing chromatographic conditions with overlaid XICs. The original LC conditions were operated with a 400 µl/min flow rate and a gradient mode elution profile with a 20 minute overall cycle time. The parent drug eluted at 16.3 minutes (shown in grey). This same study was moved to the Tempo ht LC system and a factor of 6 improvement in throughput was achieved while maintaining the number of metabolites identified. The parent drug eluted at 1.58 minutes. Summary LightSight software automates the most tedious aspects of the typical metabolite identification workflow, while efficiently supporting the work of the metabolism researcher with its simple and clear design. LightSight software produced a factor of 13 improvement in time savings over traditional manual data review and acquisition. Data acquisition was also improved with a higher performing gradient chromatographic elution. For the same set of compounds, Tempo ht LC produced an average gain in throughput of 6 times, without loss of chromatographic resolution or in the number of metabolites identified.

7 The combination of the new LightSight software and the higher performing LC system saved a significant amount of time for the overall metabolite ID process. Easy identification and confirmation of metabolites Custom-designed user environment PeakPerform Algorithm for superior sample-control comparisons Reporting that gives confidence in results Tempo ht LC system for higher throughput chromatographic separations Applera Corporation is committed to providing the world s leading technology and information for life scientists. Applera Corporation consists of the Applied Biosystems and Celera Genomics businesses. Applied Biosystems/MDS SCIEX is a joint venture between Applera Corporation and MDS Inc. Applied Biosystems and AB(design) are registered trademarks and Applera is a trademark of Applera Corporation or its subsidiaries in the U.S. and/or certain other countries. MDS and SCIEX are registered trademarks of MDS Inc. LightSight, PeakPerform and Tempo are trademarks and Q TRAP is a registered trademark of Applied Biosystems/MDS SCIEX, a joint venture between Applera Corporation and MDS Inc Applera Corporation and MDS Inc. All rights reserved.