Pittcon06 Auto Chrom

Advanced Chemistry Development, Inc. (ACD/Labs)

A Fully Automated System for Chromatographic

Method Development Utilizing LC/MS/DAD

Detection

Mike McBrien, Andrey Vazhentsev, and Alexey GalinMarch 15/06

Visionary Software for Scientists Spectroscopy • Chromatography • PhysChem • Chemical Naming • Drawing • Databasing • Enterprise Solutions

Outline

The ChallengeInstrument ControlStrategy BuildingMutual Automated Peak MatchingComposite SamplesConclusion

Method Development Software Today

Users:Design studiesConfigure instruments

Computers Collect, process dataUsers:

Organize datafilesInterpret/extract dataTransfer data to modeling software

Computers model separationUsers:

reconfigure instrument…

The ChallengeSoftware can do better:

Configuring sessions on the CDSInterpreting dataManaging informationContributing to workflowEliminating unnecessary injections

AutoChrom is designed to further enhance the MethDev workflow.

Improving on MDS

The next generation of method development:

Instrument controlStreamlining data interpretationEnabling data managementConsistent decision-makingClear, concise reportingEasy redesign of methods

ACD/AutoChrom

Direct instrument control Automated peak tracking:

UV- and MS-MAPCustom WorkflowsComplete data management:

Data organization by method/wave“Live” peak transferInstrument control

Managing Instrument Data

Instrument Control - Configuration

AutoChrom is designed to support virtually any setup that the CDS supports:

Column switchersOvensReservoirs and solvent volumesInjection vials and wells

Even manually-controlled valves can be used; AC prompts the user to change settings.

Managing Method Development Waves

Instrument Control – Conditions

Currently, AutoChrom controls only ChemStation PlusConfigured for complete control of the CDS:

TemperatureGradientColumn selectionEtc.

AutoChrom is designed to allow the user to specify virtually any experiment required.

ACD/AutoChrom 1.0Configuring Console

Data Management – MethDev Tasks

The MethDev strategy is divided into tasks:

ScreeningScreening/optimization1D optimization2D optimization

Upon completion of a given task, the software waits for instructions or moves to the next task.

Designing Method Development Approaches

Strategy Builder

Users drop waves into strategy, and double-click

each wave to configure specific requirements.

Decision-makingDecisions are based on existing LC Simulator algorithms:

Selection modes (screening);Optimization modes (continuous variables).

Suitability can be a function of:Run time;Retention;Resolution.

Users establish their success criteria for each method development wave.

Data Review

Combination of manual and automated toolsHyphenated detection (MS and/or DAD) aids in component trackingReviewed data is automatically updated to the data management and decision support system

Data Review (2)

AutoChrom reads peak tables directly post-analysisUsers retain access to hyphenated data throughout the method development sessionAt any time in the future, LC/MS/DAD data can be reviewed.

Data Interpretation

Peak Matching

Perhaps the greatest challenge in computer-assisted method development.All peaks must be tracked across all experimentsHumans use spectra, intuition, and test injections.Computers are more limited.

Matching Peaks for Complex Work

Each component in a separation must be tracked

Manual peak tracking can be tedious in CA MethDev; it’s impossible in

AMD!min6 8 10 12 14 16 18 20

min6 8 10 12 14 16 18 20

YMC Pro C18 pH 2.5

XTerra RP18 C18 pH 7

Peak Matching

DAD detectors are ubiquitousMS detection is becoming commonThe challenge:

Develop a tracking system that works for DAD alone, or DAD/MS.

The solution:Mutual Automated Peak matching (MAP)

UV-Mutual Automated Peak Matching

Data augmentationDeducing the number of componentsKey Set selectionKey Set refinementFinding peaksDetection of “missing” components

Anal. Chim. Acta, 490 (2003) 41-58.

MS-Mutual Automated Peak Matching

MS offers significant advantages:Greater resolutionS/NOrthogonal signal strength

The MS-MAP algorithm was designed to take advantage of the differences in these detectors

LC/MS Componentization: IntelliXtract

Combined approach of logic and chemometricsUser-transparent extraction of chromatographic informationIdeally suited to support of chromatographic peak matching2.5 years’ development at ACD/Labs

Basic Componentization Workflow

Starting list of potential chromatographic peaksFiltering Real Peaks from NoiseGrouping peaks based on retention timesPrimary ion cluster sortingSearching for missing isotope ionsIon cluster analysisIon Cluster Annotation

MS-MAP: Reconciling Components

IntelliXtract is used primarily as a noise reduction and peak picking toolMatches are based on clustersPerfect co-elution is a problem (today)Solution:

Logic-based reconciliation (if new component arises in run2, then re-examine run1)Orthogonal detection (UV-MAP)

A note on detectors

DAD and MS are complementary:Intensities don’t correlateFunctional vs. weight difference

UV-MAP and MS-MAP are both useful:

MS-MAP is sensitive to co-elutionUV-MAP is sensitive to S/N

Using UV and MS greatly reduces “misses”

Information Management

Data Organization

AutoChrom’s interface is designed specifically for transparent communication of method development workWave data are arranged hierarchically:

MethodTrial

Probe (subsample injected)Detector (one or more datafiles)

Data HierarchyProject

Experiment

Subsample

Detector

Managing Experimental Information

All experimental data for the session are managed, grouped

in waves.

Managing Experimental Information

All signals are linked to the original injection.

Peak tables are extracted from the original data.

Linking multiple method development waves

Managing Method Development Sessions

Column ScreeningGradient Optimization

A Data Explosion

Forced degradation samples:ComplexLow level, unknown impuritiesMultiple samples – one methodLOTS of hyphenated data

Each time a formulation is changed, new impurities may appear – the method

must be redesigned.

Composite Samples

Sometimes more than one injection represents a single sampleChromatograms must be combined to represent an overall, expected behavior

Composite Chromatograms

Multiple conditions = different impurities:

HOOHHeatLightAcidBase

The final method should separate all components

for all samples.

Too Much Data

Each set of chromatographic conditions gives 18 (!) datafiles:

6 subsamples3 detectors

All elution data must be cross-correlated and transferred to method design software

Example: Managing Stability Data

Each method has had 5 samples injected.

Example: Managing Stability Data

AutoChrom combines tRs into one chromatogram

per method.

Reports

Communicating a MethDev Project

AutoChrom is designed to create a concise summary of an immense amount of dataRigorous method development for composite samples generates GB of instrument filesAutoChrom organizes, interprets, and communicates this dataConcise reports can be created in minutes

The Math

In one MethDev session:~50 sets of conditions~5-7 samples~10 components~3 detectors

We need to extract/track/organize at least 7500 peaks!

Speed vs. Organization

The method development console organizes raw data:

Peak data is summarized for entire projectRaw data is indexed but opened only on demandProjects are ~100KRaw data can be more than 4GB

Compatibility

Instrument control in v1.0 for ChemStation Plus:

Fully automatedUser-interactive

All instruments can be used:Manual input of data still enables considerable time savings in data interpretation and organization

Conclusion

Streamlining the method development session:

MS/UV supportChemometricsComposite chromatogramsUnprecedented rigor in modeling and reporting

Acknowledgements

ACD/Labs:Rhiannon JonesAndrey Bogomolov

Johnson and Johnson:Rudy SneyersWilly Janssens

Supplemental Information

Slides available at www.acdlabs.comBooth#2340Poster 470-67P:

“Managing LC/MS/DAD Data in Forced Degradation Studies”

Presentation 860-6: “Chromatographic Peak Tracking through

Chemometric Analysis of Hyphenated Data”

Pittcon06 Auto Chrom

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