©2012 Waters Corporation 1

Accurate Mass Quantitation of In Vivo Plasma Samples Using High Resolution Qtof

and MSE Data Analysis Across a Global Network

Is Quantitative Bioanalysis ready for HRMS?

Mark Wrona, Waters CorporationEBF, Barcelona, 15 Nov 2012

©2012 Waters Corporation 2

Why ISNWhy ISN’’t Qualitative information t Qualitative information on iton it’’s own good enough?s own good enough?

in vivo (blood, tissues, urine, bile, etc)

in vitro (microsomes, hepatocytes, S9)

Rat

Characterized Relationship Predicted/Modeled

Dog Monkey Human

Rat Dog Monkey Human

BOTTLENECK

Keeping track of information and putting all of this into

perspective

©2012 Waters Corporation 3

Is accurate mass data collection for Is accurate mass data collection for quantification the RIGHT answer?quantification the RIGHT answer?

2 Scenarios

If you’re already doing qualitative work ABSOLUTELY, helps put this data in context across datasets. As we begin to understand and put in place better data integration systems, this will only provide benefits.

If you’re (thinking of) shifting traditional quantitative work into this space, the benefit of doing so must outweigh the negatives

o Sensitivity/Specificityo Accuracyo Reproducibilityo Datasize Processing Time

Must be “fit-for-purpose”

©2012 Waters Corporation 4

Vertex CollaborationVertex CollaborationExperimental DetailsExperimental Details

4 Rats Dosed 75mg/kgPlasma collected at t = 0 (predose), 1, 1.5, 2, 4, 6, 24hr

Pool Time Points,Protein Precipitate with Acetonitrile and dilute 1:1 w/ Water

Inject on Xevo G2 Systems equipped with Acquity UPLCsAND Thermo Quantum Ultra QqQ system to compare

0 1 1.5 2 4 6 24

©2012 Waters Corporation 5

Standard Curves Standard Curves –– QqQ vs QTof QqQ vs QTof 1ng/mL1ng/mL--10000ng/mL10000ng/mL

©2012 Waters Corporation 6

Std Curves Study 1 CVsStd Curves Study 1 CVs–– Laval Laval Thermo Ultima TQ vs Xevo G2 QTofThermo Ultima TQ vs Xevo G2 QTof

StandardConc

QqQCalc

QqQDeviation

QtofCalc

Qtof deviation

0.25 0.1 141% 0.0

1 1.0 23% 0.8 47%

2.5 2.7 3% 2.7 8%

5 4.4 6% 5.4 8%

25 25.9 4% 25.9 4%

50 49.3 4% 49.7 1%

100 97.7 4% 97.0 2%

250 262.9 1% 270.6 1%

500 503.9 1% 514.6 2%

1000 982.0 2% 967.4 7%

2500 2637.4 0% 2644.2 0%

5000 5168.0 4% 5202.9 3%

10000 9310.2 1% 9652.8 1%

In terms of sensitivity and general performance, we are closer than you think!

©2012 Waters Corporation 7

PK Data PK Data -- QqQ vs QTofQqQ vs QTof

Tof Data includes additional rich information includes on hydroxylations and glucuronides Even with a ballistic gradient

©2012 Waters Corporation 8

Ele

ctric

Fiel

d

Diffuse Ion

Cloud

Maximise signal

Eliminate Noise

Sensitivity and SelectivitySensitivity and Selectivitycontinuously being improvedcontinuously being improved

BUT what about software? Where do we stand on this?.....

©2012 Waters Corporation 9

Raw Data > Knowledge PathwayRaw Data > Knowledge Pathway

Huge amount of effort into getting better and better raw data– Need equal (or greater) investment in software

UNIFI processing software which creates rich links between:

raw data – processed data – tables – structural data – reports

How? At the core of UNIFI is Oracle database– DATA IS ORGANIZED

– DATA IS MINEABLE, FILTERABLE, Linked from beginning to end

©2012 Waters Corporation 10

Data Component Model Data Component Model –– Raw DataRaw Data

Components can span multiple channels of dataThe software organizes the data across all channels

into components

©2012 Waters Corporation 11

New ways of looking at dataNew ways of looking at data

Software needs to be built from the ground up to handle Quantitative information

(Quantitation can not be a special case)

©2012 Waters Corporation 12

Visualizing InformationVisualizing Information

Interaction with data needs to be flexibleQuantitative and Qualitative Information displayed in a table OR visually

©2012 Waters Corporation 13

Qualitative Information Qualitative Information ––how do metabolites track with Parent?how do metabolites track with Parent?

QuantifiedParent

MetabolitesPK 2hr

MetaboliteXICs

+O +Gluc Metabolites OverlaidDuplicate PK Sets

Su

mm

ed

XIC

Flexibility in the way you look at informationQuan/Qual is still an evolving art!

©2012 Waters Corporation 14

ConclusionsConclusions

HRMS Data IS capable of generating high quality quantitative data

The wealth of information generated by these instruments now exceeds the capacity of most analysts and labs to use the extra data efficiently. Why bother going from TQ to HRMS if you can’t really use the extra information anyways?

Software and assisted workflows are the key to processing the data. This provides workflows for HRMS that both meet acceptance criteria for bioanalysis AND gives facile access to the extra rich information inherently contained in HRMS data.

©2012 Waters Corporation 15

AcknowledgementsAcknowledgements

And thank you for your attentionAnd thank you for your attention!!