The document discusses the integration of informatics tools in drug discovery workflows to enhance transparency, trust, and productivity. It emphasizes that while informatics cannot improve the inherent quality of scientific work, it can streamline processes and make data access easier, ultimately fostering trust in experimental outcomes. The document also highlights the need for careful customization and collaboration in implementing informatics systems to effectively support scientific efforts.

1. Integrating Informatics Tools to Improve
Transparency, Trust, and Productivity
Across the Drug Discovery Workflow
Mark J. Hayward,* Chi Zhang,* Romel Campbell,** and
Qing Ping Han*
Lundbeck Research – 215 College Rd. - Paramus, NJ 07652
*Analytical, **IT
Chemical &
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2. First principles
• There’s no substitute for quality science
• Informatics cannot change the quality of the science
– However, informatics can add significant value to the science output
Informatics can extract high value information and conclusions from the scientific data,
thereby streamlining scientific processes toward much higher efficiency
Informatics can make it much easier to find / view the data
Informatics can make it much easier to transfer the data to the next step in the process (next
assay or ELN)
Informatics can make the data find the scientist
The sum of these value added steps is much greater transparency and functional utility of the
data for many scientists
• The combination of quality science with the transparency and functional
utility added with informatics can lead to great trust in the experimental
outcomes
• Trust in the experimental outcomes results in a much more effective
research organization that can focus most on the larger organizational
goals*
• The impact of trust on productivity has been shown to be many fold at all
scales, from individual all the way up to societal*
Chemical &
*SMR Covey, "The speed of trust,"
Pharmacokinetic
Simon & Schuster, New York, 2006.
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3. Where can informatics help trust?
• Informatics can support
5 of 7 components of
trust
• Much of that trust is
driven by openness
• Thorough transparency
allows the 4 other
components to be
demonstrated (over time)
– Ability, competence,
integrity, and reliability
– Of course, the quality of
science must be there to
have something to
demonstrate (data driven!)
• High transparency
also can drive toward
high quality because Areas where
there is no place to transparency can help
hide low quality!* build trust
Chemical & *It is not uncommon to encounter resistance when shifting to high transparency
Pharmacokinetic
SMR Covey, "The speed of trust," Simon &
3 *You should do it anyway!
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Lundbeck Research Schuster, New York, 2006.

4. More first principles
• Informatics is not an entity unto itself
• Informatics must be enabling (i.e. saves steps) without
creating barriers or false metrics – it must remove barriers!
• Informatics initiatives often fail because:
– The input information barrier makes it more work to use informatics
Classic mistake: request forms requiring huge amounts of information
– The expectation is that the informatics will substitute for F2F
communication
There is no substitute for F2F communication and this always needs to
be promoted more than the informatics
– The informatics system was really only intended to generate metrics
Users will only use it to game the metrics
• Without clear added value, users generally resist learning
yet another informatics system – It should be a tool with
clear ENABLING benefits that end users want to use
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5. Still more first principles
• No single informatics approach is sufficient – informatics is only
part of the picture – other processes must be addressed on a
case by case basis
• There are many systems and interfaces that must be addressed
– Informatics links to ELNs
– Informatics links to instruments
– Informatics links to other data bases
– Instrument links to other data bases
– Adding value to instrument data
– Informatics links to visualization and reporting tools
• Informatics requires customization as does all of the processes
– Processes should be viewed holistically and the most effective
approach selected
Buy informatics package and get vendor to install / set up
Outsource customization to vendor or 3rd party
In-house programming
– Be patient, it’s a multiyear effort to get most pieces in place (always will be more)
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6. And now the content of this
presentation
How we used the first principles to address
analytical efforts in a drug discovery organization
Crucial goal: extract highest overall scientist
efficiency in their transition to ELNs
Note: notebook #s, compound IDs, and projects are not visible for proprietary
compounds, samples, projects, etc.
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7. Responsibilities of the drug discovery
Analytical group at Lundbeck Research USA
• Analysis
– LC/MS, SFC/MS and NMR for structure and purity
Challenging compounds done by Analysts
QC of compound library done by Analysts
Provide tools for Med Chemists to address straight forward
compounds and reaction mixtures (Open Access – NMR, LC/MS,
SFC/MS, & high res LC/MS)
• Purification
– LC/MS and SFC/MS based (5 mg to 50 g)
• ADME / Physico-Chemical measurements
– LogD, permeability, pKa, solubility, stability, water content…
• Mechanistic Bioanalysis (and other challenging bioanalysis)
– LC & SFC with UV, fluorescence, electrochemical, & MS/MS
detection for biomarkers in all fluids and tissues
• Formulations
– Solubility in excipients and stability / solubility in formulations
Chemical &
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8. Responsibilities from a purely
informatics point of view
Empower for raw data
VM SDMS & email for processed and raw data
world Pharmacology DB for finished pharma data
Corp IT Sample & ELN DBs for sample & experiment data*
(collaboration /
trust are crucial)
VMs for secure remote access
PC world
Red =
Corp IT
Green = Lab PCs: some with Office PCs (>100)
barcode readers (28) Home PCs (>50)
Analytical
Empower TopSpin Xcalibur Sirius
MassLynx
LCs & SFCs (23) LC/MSs & SFC/MSs (10) NMRs (2) GC/MS (1) & LC/MSs (5) Titrators (2)
Corp IT: OS, networking, Office apps, & anti-virus SW. Analytical: instrument SW & SDMS connections
Chemical & Effective data access &
Pharmacokinetic 8 *LIMS / ELN providers beginning to recognize
Sciences resource utilization are crucial! need: R Mullin, C&E News, 90(19), 2012, 11-14.
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9. Software used
• MassLynx / OpenLynx / FractionLynx (V4.1 SCN798)
– Primary drivers of choice:
Automation of LC/MS or SFC/MS hardware operation
Open Access interface for deploying to non analytical scientists
(OpenLynx)
Best automation & control of purification hardware (FractionLynx)
• Empower (V2 FR5)
– Primary drivers of choice:
Massive chromatographic data collection
– Many instruments (>20)
– 10000 chromatograms per month coming mostly from 2 FTEs
Most effective automatic peak integration
Best system suitability software (an Empower feature) for method
development (quality of science)
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10. Software used
• NuGenesis / SDMS (V7.1)
– Primary drivers of choice:
Automation of a generic way collect, distribute, find, and view
analytical data
Collects / makes transparent data from Empower, MassLynx, Sirius,
TopSpin, and others (for chemists and biologists)
Focus is on automatic “printing” (transfer approach) of processed data
Some raw data collected too, but not seen as great advantage
Primary portal to the chemistry ELN (Symyx)
• WDC (Waters Data Converter, an Empower feature) (V2)
– Primary drivers of choice:
Convert MassLynx (MS) data into Empower data
Empower has most effective automatic peak integration
Empower has best system suitability software (an Empower feature)
for method development (quality of science)
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11. Ordinary uses of the software
Some examples with focus on quality of science
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12. NMR – TopSpin auto print to SDMS
• Used for detailed
compound
structure analysis
• Mostly Med
Chemist use in
Open Access
mode (data finds
chemist)
• Rich methods set
including most 2D
experiments
• Data easy to find
in Vision
• Some
reprocessing of
raw data
performed in
TopSpin and/or
ACD (available on
desktop) for
publication
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13. OA-LC/MS – OpenLynx auto print to
SDMS
• Used for compound
molecular weight and
purity analysis
• Mostly Med Chemist
use in Open Access
mode (data finds
chemist)*
• Frequently used for
reaction monitoring
• Rich methods set
including 2 choices
each of column,
gradient, and pH.
• Data easy to find in
Vision
• Some reprocessing
of raw data
performed in
MassLynx for
publication (on desktop)
• Dual UV detectors
increases dynamic
range and minimizes
need to adjust
concentration (no rework)
*Also used by Compound Management for new compounds going into collection (10-20k/yr)
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14. Purification – FractionLynx auto print to
SDMS
• Purification performed by
expert
Typical
• Big concern of Med OpenLynx
Chemists is that none of style report
target compound is lost (lots
of effort put into making
compound)
• ELSD quantifies mass
purified and 2nd UV detector
in waste stream
demonstrates none lost
(quality of science) Mass of
target peak
• Data goes into SDMS in real
time (inj by inj) and Med
Chemists can watch Rack
purification in progress as location
well as see when it is tracking
finished
• Med Chemists trust handing Target peak
not in waste
over hard to make stream
compounds to someone else
Chemical & Flexible bar-code tracking would be nice here!
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15. Physico-Chemical measurements – Sirius and
Empower reports printed to SDMS
• Quantitative LC-
UV used for most
measurements:
LogD, membrane
permeability, &
solubility
(Empower)
• Acid / base titration
used for pKa
measurement
(Sirius)
• Since these
assays “rate” the
compounds,
chemists will
question results
• Combination of
transparency and
training results in *Some critical evaluation of the data included in the
chemists believing report also helps build trust!
results
Chemical &
*R Galford, AS Drapeau, "The enemies of trust,"
Galford, Drapeau,
Pharmacokinetic
HBR, 81(2), 2003, 89-95.
89-
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16. Bioanalysis with challenging separations using
MassLynx for data acquisition and Empower for
peak integration (transfer via WDC)
• MassLynx controls
SFC/MS/MS
• WDC converts data to
Empower
• Empower does best
automatic peak integration
for large number of samples
(least amount of rework –
i.e. manual integration)
• Quantitative analysis of drug
enantiomers shown (in plasma)
• System suitability
parameters show separation
not deteriorating despite
many hundreds of injections
(quality of science)
Chemical & Transparency Allows sensitive quantitative process
Pharmacokinetic
avoids reanalysis. 16 control limits to be monitored / set.
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17. Mechanistic Bioanalysis in Empower
• Data shown for LC connected
directly to live rat brain
• Analytical chemist works directly
in same lab with biologists & all
are Empower users
• Empower does best automatic
peak integration for large number
of samples (least amount of
rework – i.e. manual integration)
• Typical experimental output:
4000 chromatograms per month
• Empower server (VM) not on
same site as lab
• Have collected data from 10 LCs
in parallel “through the wire”
• Empower is best centralized
chromatographic data system
• Server is readily & routinely
accessed from many desktops
and home computers
Chemical & Reports not going to SDMS, biologists trained in Empower
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18. Customized uses of the software
Some examples created in-house and/or by Waters with focus on
streamlining processes and getting the most effective use of scientific
efforts
These examples increase scientist efficiency and reduce human errors.
Reducing human errors & getting right answer builds more trust in results!
There’s a lot of value in tapping into Waters expertise as well as buying the SDK
and sending one of your scientists to a VB and a SQL course!
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19. Addressing other links to make the
workflow efficient
• Going from bar-coded samples to analysis
sample lists for the instrument & importing
analysis sample lists
– Empower
– MassLynx
• Post analysis data processing for physico-
chemical assays
• Adding value to Open Access LC/MS data
• Post analysis data processing for compound QC
(MW, purity, concentration)
• Automatic emailing of results (Open Access)
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20. Going from bar-coded samples to
analysis sample lists for the instrument
• Physico-chemical assays result
in racks of 2D bar-coded tubes
with separate racks for each
project
• Compound management
processes compounds on
project basis because different
biologists handle different
assays for each project
• Physico-chemical assays are
the same regardless of project,
so it doesn’t make sense to
process on a project by project
basis
• We backfill racks to streamline
physico-chemical assays With a new updated compound ID
• Then, we rescan racks and list, we are now ready to create an
query compound management
DB to get new list of compound instrument analysis list (can be
IDs* done in one step)
Chemical &
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Sciences need: R Mullin, C&E News, 90(19), 2012, 11-14.
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21. Importing analysis sample lists:
Empower
• Add-in created to
generate lists
• Add-in reads file from
2D tube scanner
• Allows one to choose
use of 1 or 2 LCs
• Has multiple
templates to address
different assays
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Using Empower SDK 21
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22. Importing analysis sample lists:
Empower
• Open sample set
(analysis list) in the
usual way
• Analysis list
contains all needed
information
• Just put the plates
in autosampler and
hit the go button
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23. Importing analysis sample lists:
MassLynx
• Handheld bar-code reader
used to input rack #
• VB / SQL program reads
rack of 2D tubes and gets
compound IDs from DB
• Project, person, and
UPLC plate position are
added
• Hit create button to make
MassLynx list with rack
bar-code as file name
• Import list in usual way
and hit the OpenLynx go
button
Approach also implemented for Xcalibur, Sirius, etc. and all can be performed at instrument computer
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24. Post analysis data processing for
physico-chemical assays
• 6000
chromatograms
per month
generated /
processed by 1
FTE
• Sample peaks RT Chromatograms
with issues
must be matched flagged
to standard peaks
• Unexpected
impurities can
confound peak
matching
• Review of data Data can be
unavoidable viewed,
• Tools needed to integrations
corrected, and
achieve this level results
of throughput Creates sheet that can be uploaded directly to recalculated all
pharmacology DB within same tool
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Using Empower SDK 24
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25. Adding value to Open Access LC/MS data*
• Interpreting mass spectra
is fairly easy for trained
mass spectrometrists MW inserted into MS
• However MS can produce text in report file (.rpt)
a variety of peaks from
pure compounds and this
can be confusing for Med
Chemists
• Program created to
intercept OpenLynx.exe
and:
– Process in data in normal
way without printing
– Find molecular weight
(MW) of top 3
components in spectrum
based on all peaks
– Insert MW(s) into text of
report and then print (to +/- spectra are treated as arrays and fitted to all known
SDMS) adducts to determine MW. Determination cumulatively
– Example on right weighted toward most adducts and most peak intensity.*
Chemical & Saves lots of time for Med Chemists and Analytical Chemists
Pharmacokinetic 25 *Uses technique from: H Tonga, D Bella, K Tabeia,
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26. Post analysis data processing for
compound QC (MW, purity, concentration)
• Goals: verify
molecular weight
(MW), purity, and
concentration of
DMSO solutions in
compound screening
collection
• MS for MW, UV &
ELSD for purity,
ELSD for
concentration
• Off the shelf tools
have low success
rates (50-70% right
answers – threshold based)
• Manual examination MW
of data unavoidable agreement
• Needed to tool to determined by
streamline process so
3000 to 10000 adducts
compounds per year (previous
could be analyzed slide) and
quickly with little FTE
impact (<0.05 FTE) isotope ratio
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27. Post analysis data processing for
compound QC (MW, purity, concentration)
• Excel report
generated with all
needed DB* data:
– ID & structure (Isis)*
– Verification of MW
– Purity &
concentration
– Comments on
impurities and/or
presence of isomers
• Includes SDMS
link so data can be
immediately
viewed (also pdfs)
Chemical &
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Sciences need: R Mullin, C&E News, 90(19), 2012, 11-14.
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28. Automatic emailing of results:
Open Access data finds chemist
• Open Access is an Decision to
instant gratification email is by
approach, often used by analysis
type
chemists for reaction (SDMS
monitoring (reaction project)
complete?) and person
• Expectation is result in File name
<5 min Emailer set up for pdf is
• Worked with Waters to view notebook #
create SDMS emailer (no need to
• Emailer program change
generates / sends email name)
as soon as result exists!
• pdf can be dragged and
dropped anywhere it is
allowed (Symyx ELN)
• SDMS link can be
copied and pasted
anywhere text can be Actual email
placed
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>30000 drag/drops per year
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29. Summary and Conclusions
• Analytical informatics can:
– Dramatically increase transparency and access to data
– Increased transparency can in turn drive improved
quality (because everyone can see it). This facilitates
making people more open and has a significant effect!
– Enhance the value of data
– Significantly increase scientist efficiency through
workflow optimization
• Combining the benefits of informatics with high
quality science and otherwise good communication
can build great trust and collaboration among
scientists
• Achieving high levels of trust in this way can greatly
enhance overall productivity (3+ fold improvement)
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