Transcript Dr. Olah presentation - University of Connecticut

LC-MS in Drug Discovery
Timothy V. Olah, Ph.D.
Director, Bioanalytical Research
Pharmaceutical Research Institute
Bristol-Myers Squibb Company
[email protected]
University of Connecticut
20 February 2007
Drug Discovery Programs at BMS
Wallingford, CT:
Virology: HIV (AIDS), Hepatitis C,
CNS: Anxiety, Depression, Alzheimer’s, Migraine
Lawrenceville, NJ:
Oncology: Cancer
Immunology: Rheumatoid Arthritis, Asthma
Hopewell, NJ:
Cardiovascular: Thrombosis, Atherosclerosis
Metabolic Diseases: Diabetes, Obesity
BMS Bioanalytical Research
Wallingford:
Deborah Barlow, Marc Browning, Mike Donegan, Daniel Morgan,
Kim Snow, Sarah Taylor, Kim Widmann
Lawrenceville:
Hollie Booth, Chris Caporuscio, Georgia Cornelius,
Celia D'Arienzo, Lorell Discenza, Mohammed Jemal, Zheng Ouyang,
Asoka Ranasinghe, Bogdan Sleczka, Yi Tao, Xia Yuan, Jian Wang,
Steven Wu
Hopewell:
Hong Cai, Cecilia Chi, Jim Smalley, Minjuan Wang, Richard Wong,
Baomin Xin, Carrie Xu, Hongwei Zhang, Joanna Zheng
Bioanalytical Research Staffing
•
•
•
•
•
•
•
Personnel: 30 scientists
Location: WFD (7), LVL (13), HPW (9)
Mass Spectrometers : 30 MS/MS
Full Phase Programs: 34
Early Phase Programs: 25
Research Initiatives
Samples 1-4Q 2006: ~184,000
Total Number of Samples Analyzed
by BAR (FTE) in Support of Discovery
200000
Total samples
184056
175000
150000
139789
145795
125000
100000
84335
75000
65672
56618
50000
25000
0
2001 (7)
2002 (10)
2003 (14)
2004 (19)
2005 (19)
2006 (20)
BAR-Discovery Annual Sample Count
Compounds
compounds analyzed
3000
2632
9203
10000
2533
8500
2500
6567
2000
6024
7355
7673
2225
7000
5500
1500
1730
1672
4000
1000
2500
500
1000
0
-500
2002 (10)
2003 (14)
2004 (19)
2005 (19)
2006 (20)
samples per analyst
per BAR FTE
Outline
• LC-MS in Drug Discovery
• Drug Discovery Process
• Strategies and Work Flow Processes
• Development and Implementation of Multiple
Component LC-MS-based Bioanalytical Methods
• Examples, Questions, Comments
• What is of interest to you today in regards to
the Pharmaceutical Industry ?
Bioanalytical Research’s Goal
To generate accurate and precise data in
the quantitative analysis of drug
discovery candidates in samples from
in vivo and in vitro studies that support
their biological characterization and
optimization as potential development
candidates.
The Gilbert Bioanalytical Chronicles
“The challenges of bioanalysis stem from the need to
accurately and reproducibly measure part per million
to part per trillion quantities of analyte in complex
biological matrices, full of potentially interfering
endogenous or drug-related substances.”
John Gilbert et al., “High Performance Liquid Chromatography with Atmospheric Pressure
Ionization Tandem Mass Spectrometry as a Tool in Quantitative Bioanalytical Chemistry,” in
Biochemical and Biotechnological Applications of Electrospray Ionization Mass
Spectrometry, American Chemical Society (1995)
Relative Amounts
1.0 gram
0.001 gram
0.000001 gram
0.000000001 gram
0.000000000001 gram
(milligram)
(microgram)
(nanogram)
(picogram)
Stages of Drug Discovery and Development
Compound
Discovery - Nomination
PreClinical - Clinical
GLP
Factors for Consideration
• Bioanalytical Method Requirements
• Application of Technologies
• Risk Assessment
Drug Discovery Process
A
New Chemical Entities
from Medicinal Chemistry
B
H
Physical Properties
Reporting
High
Throughput
Screening
C
Information Management
Bioassays: Potency /
Selectivity
D
ADME
Characteristics
G
Data Interpretation
Automation
Experimental
Design
F
Sample Analysis
E
In Vitro and / or
In Vivo
Experiments
Drug Discovery Process
A
New Chemical Entities
from Medicinal Chemistry
B
H
Physical Properties
Reporting
High
Throughput
Screening
C
Information Management
Bioassays: Potency /
Selectivity
D
ADME
Characteristics
G
Data Interpretation
Automation
Experimental
Design
F
Sample Analysis
E
In Vitro and / or
In Vivo
Experiments
Relationship of Drug Metabolism
with Medicinal Chemistry
in Early Drug Discovery
•
Add information to compliment HTS data
•
Assist in the selection of compounds based upon
their ADME characteristics for further evaluation
•
Provide direction to medicinal chemists for the
design of their next compound in a series
•
Identify trends in the architecture of a class of
compounds that correlates with a response in an
ADME assay (e.g. Potency with P450 inhibition)
“Absorption, Distribution,
Metabolism, Excretion”
Stomach
(Excretion)
Duodenum
(Absorption)
Portal Vein
Intestine
Liver
(Distribution)
(Metabolism)
Kidney
Systemic
Circulation
Desirable ADME Characteristics

Absorption
- good solubility and permeability

Distribution
- good exposure at the target, minimal elsewhere
- acceptable protein binding: estimate “free concentration”

Metabolism
- minimal first pass effect
- metabolism by two or more CYP (not 2D6) to few metabolites
- minimal potential to inhibit or to induce

Excretion
- balance between metabolism and excretion of parent drug
Experiments to Assess ADME Characteristics

Absorption
- Caco-2 cells, PAMPA, PgP-transport
- in vivo PK profiling
• Distribution
- in vitro protein binding, in vivo tissue distribution studies
• Metabolism
-
Metabolic stability in microsomes, S9 fractions, hepatocytes
P450 Inhibition: microsomes and/or rCYPs, co-administration
P450 Induction: Gene Chips, PXR, multiple dosing studies
Metabolite characterization
• Excretion
- Quantitation of drugs and metabolites in biological fluids
BAR Responsibilities
• Analyze samples from in vivo studies:
– Early Exposure (Biology), Coarse PK, Full PK,
PK/PD, Tissue Distribution, “Bioequivalence”,
TK (CV Telemetry, Pre-ECN, ECN) …
– Co-Administration: Screening (N-in-one), P450
Inhibition, Marker Compounds, Stable Label…
– All routes of administration (IV, PO, IP, SQ, IN…)
– All types of formulations by Pharmaceutics.
BAR Responsibilities
• Analyze samples from in vitro studies:
– serum protein binding, tissue binding,
serum/plasma/chemical stability…
– intrinsic clearance, P450 inhibition, pgP,
PAMPA, Caco-2…
– biological assays, heart/liver perfusion…
BAR Responsibilities
• Analyze samples in all types of species
and biological matrices:
– mice, rats, marmoset, guinea pig, rabbit, dogs,
monkeys, chimp, human…
– blood, plasma, serum, urine, bile, CSF, SV,
brain, lung, heart, liver, GI tract, kidney,
muscle, tumor, adipose tissue…
– microsomes, hepatocytes, S9 fractions, rCYP,
incubation systems, mixed matrices, buffers,
dosing solutions…
BAR Responsibilities
• Rapidly develop and implement multiple
component bioanalytical methods using
LC-MS/MS-based detection.
– Analyte and Internal Standard
– Analyte(s) and Internal Standard(s)
• Co-Administration Studies, Pro-Drugs
– Parent Compound, Metabolite(s), IS
– Parent Compound, Distinct Equilibrium Forms
Keys to Developing Successful
Screening Strategies
the TIME required to generate data
TIME
DATA
the quality of
DATA required to
generate
meaningful results
RESULTS
the type of
RESULTS that are
requested
in the screen
“Scaling” Annual BAR Output:
Number of Compounds Evaluated
• 10,000 - 30,000 evaluated in “Screens”
• 1000 - 3000 evaluated in “Early Phase”
• 100 - 300 evaluated in detail “Full Phase”
• 10 - 30 evaluated for “Nomination”
• 1 - 3 compounds “NDA” approved
Bioanalytical Work Flow
A
Sample Receipt/Tracking
B
Method
Development
H
Reporting
LC-MS/MS
C
Preparation of
Analytical
Standards & QCs
D
Information Management
Programming
Automation
G
Notebooks and Ancillary
Data
Standard Operating Guidelines
Sample
Preparation
F
Data
Processing
E
Sample Analysis
What is LC-MS?
(LC) Liquid Chromatography:
Chromatography is a separations method that relies on differences in
partitioning behavior between a flowing mobile phase and a stationary
phase to separate the components in a mixture.
A column holds the stationary phase and the mobile phase carries the
sample through it.
Sample components that partition strongly into the stationary phase
spend a greater amount of time in the column and are separated from
components that stay predominantly in the mobile phase and pass
through the column faster.
(www.chem.vt.edu/chem-ed/ac-meths.html)
HPLC Analysis
Elution
Gradient
Recondition
X time
0
meaningful data
What is LC-MS?
(MS) Mass Spectrometry:
Mass spectrometers use the difference in
mass-to-charge ratio (m/z) of ionized
compounds to separate them from each
other.
Compounds have distinctive fragmentation
patterns that provide structural information
to specifically detect compounds.
(www.chem.vt.edu/chem-ed/ac-meths.html)
Types of Mass Spectrometers
•
•
•
•
•
•
•
•
•
LC-MS (single quadrupole)
LC-MS/MS (triple quadrupoles)
LC-Q (ion traps, linear ion traps)
LC-Q-TRAPS (quadrupole linear ion traps)
LC-TOF-MS (time-of-flight)
MALDI-TOF-MS
Q-TOF-MS (quadrupole time-of-flight)
FT-MS (Fourier Transform)
Others
Uses of Mass Spectrometry
in Drug Discovery
• Qualitative Analysis
Elucidation of the structural characteristics of
various substances in different matrices:
What is in the sample?
• Quantitative Analysis
Determination of the concentration of various
substances in different matrices:
How much is in the sample?
O
O
N
N
H
S
O
N
O
O
O
O
O
NH2
O
O
O
N
O
O
O
N
Diltiazem
C22H26N2O4S
Carbamazepine
C15H12N2O
Reserpine
C33H40N2O9
MW = 414.2 Da.
MW = 236.1 Da.
MW = 608.3 Da.
N
O
O
S
HO
N
O
N
NH2
O
NH
N
O
O
O
N
N
N
O
O
Cl
Bumetanide
C17H20N2O5S
Pyrilamine
C17H23N3O
Ketoconazole (ISTD)
C26H28N4O4Cl2
MW = 364.1 Da.
MW = 285.2 Da.
MW = 530.1 Da.
Cl
Types of MS Detection Methods
•
•
•
•
•
•
•
Full Scan Spectra
Selected Ion Monitoring
Product Ion Spectra
Neutral Loss Scans
Multiple Reaction Monitoring
Accurate Mass Measurements
Others
Sulfasalazine
C18 H14 N4 O5 S
MW 398.40
O
C OH
N
H
N
S
O O
N N
OH
+Q1: 5 MCA scans from sulfasalazine_FinalQ1_Pos.wiff
399.0
7.4e6
7.0e6
Max. 7.4e6 cps.
Full Scan Spectrum
6.5e6
6.0e6
5.5e6
5.0e6
4.5e6
Intensity, cps
4.0e6
3.5e6
3.0e6
2.5e6
2.0e6
400.0
1.5e6
1.0e6
400.9 401.1
5.0e5
0.0
396.5
397.0
397.5
398.0
398.5
399.0
m/z, amu
399.5
400.0
400.5
401.0
401.5
m/z 119
Product Ion Spectrum
O
m/z 94
N
C OH
H
N
N N
S
O O
m/z 165
m/z 223
OH
m/z 137
Multiple Reaction Monitoring
+ ES Ionization
+
+
Collision
gas Ar
+
+
+
+
+
+
Q1 – Fixed
precursor m/z
(m/z “x”)
Ar
+
+
+
+
+
+
+
+
+
Q2 – Collision
chamber
Q3 – Fixed
product m/z
(m/z “y”)
MRM Transition
m/z – m/z
11.5
12
12.5
13
13.5
14
14.5
Multiple Reaction Monitoring
+ ES Ionization
+
+
Collision
gas Ar
+
+
+
+
+
+
Q1 – Fixed
precursor m/z
(m/z 399)
Ar
+
+
+
+
+
+
+
+
+
Q2 – Collision
chamber
Q3 – Fixed
product m/z
(m/z 223)
MRM Transition
m/z 339 – m/z 223
11.5
12
12.5
13
13.5
14
14.5
Multiple Reaction Monitoring:
specific precursor / product ion pair
399 m/z -> 223 m/z
Plasma Extract SIM: m/z 603
Plasma Extract MRM: m/z 603-> m/z 483
Plasma Extract SIM: m/z 617
Plasma Extract MRM: m/z 617-> m/z 483
Full Scan Spectrum
BMS-724296 13 (0.247) Cm (9:15)
492.37
100
336.28
%
Precursor Ion
Scan ES+
5.00e6
494.25
377.27
220.23
245.13
0
200
524.49
565.11
387.01
299.07
647.04
690.86
732.56
m/z
250
300
350
400
450
500
550
600
650
700
Product Ion Spectrum
BMS-724296 D 18 (0.339) Cm (8:18)
Daughters of 492ES+
1.25e7
336.11
100
%
120.38
140.06
233.95
0
100
150
200
250
300
350
400
450
500
m/z
550
Multiple Reaction Monitoring: two analytes
(m/z 492 -> m/z 336), (m/z 539 -> m/z 332)
S102504 PK 026
MRM of 6 Channels ES+
539.07 > 332
1.60e5
2.03
100
IS
%
Multiple Reaction Monitoring
(m/z 539 -> m/z 332)
0
S102504 PK 026
MRM of 6 Channels ES+
492.1 > 336.15
2.04e5
1.89
100
BMS-724296
Multiple Reaction Monitoring
(m/z 492 -> m/z 336)
%
0
1.50
2.00
2.50
3.00
3.50
Time
4.00
Examples of the Use of Multiple
Component LC-MS/MS-based
Bioanalytical Methods in Drug Discovery
• Determination of Drugs and Metabolites
• Co-Administration Studies
Bioanalytical Method for Determination of
BMS-xxxxx and Metabolites in Biological Fluids
to Support the Diabetes Program
Structures
Cl
Cl
R
R
Parent Compound
MW=392.88
“Styrene”
Metabolite
MW=390.87
Cl
O
Cl
R
R
“Alcohol”
Metabolite
MW=408.88
OH
“Ketone”
Metabolite
MW=406.88
Multiple Component Bioanalytical Method
Mass Spectrometry:
Negative Ion Electrospray
Multiple Reaction Monitoring
Parent
Styrene Metabolite
Ketone Metabolite
Alcohol Metabolite
Diol Metabolite
Internal Standard
Function
2
2
1
1
1
1
Reaction
Dwell(secs)* Cone Volt. Col.Energy
391.5 > 313.1
0.2
45
15
389.4 > 311.1
0.2
45
15
405.6 > 327.7
0.1
40
15
407.8 > 329.9
0.1
40
15
423.3 > 333.5
0.1
45
20
379.5 > 289.21
0.1
45
30
Chromatography Requirements
STD 10K in FFA/FFB (Neat Soln.)
655956METAB070604002
Diol Metabolite
2.69
100
Ketone
MRM of 5 Channels ESTIC
7.59e5
Parent Compound
Alcohol
3.63
Styrene
%
0
1.00
2.00
3.00
4.00
5.00
6.00
Time
7.00
Due to isotopic interferences there was a need for chromatographic
separation of the parent compound and the metabolites.
Chromatography Requirements
STD 10K in FFA/FFB (Neat Soln.)
655956METAB070604002
100
MRM of 5 Channels ES423.34 > 333.55
7.59e5
2.69
Diol Metabolite
%
0
655956METAB070604002
100
MRM of 5 Channels ESIsotopic interference from Ketone 407.8 > 329.99
1.65e5
3.37
Alcohol Metabolite
%
0
655956METAB070604002
100
3.63
Ketone Metabolite
MRM of 5 Channels ES405.59 > 327.65
4.85e5
%
0
655956METAB070604002
100
MRM of 5 Channels ES391.5 > 313
3.28e5
4.76
Isotopic interference from Styrene
%
0
655956METAB070604002
100
Parent Compound
MRM of 5 Channels ES389.38 > 311.13
2.36e5
4.53
Styrene Metabolite
%
0
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
5.50
6.00
6.50
Time
7.00
BMS-XXXXX
Prodrug and Metabolites
O
O
N
O
O
O
O
O
Parent, M+H+ =457
Prodrug, M+H+ =514
O
O
O
O
O
Metab M+H+ =473
O
O
Metab M+H+ =385
O
O
O
O
Metab M+H+ =487
A representative chromatogram with all
of the required separations achieved
XIC of +MRM (6 pairs): 457.1/236.0 amu from Sample 41 (Sample_770780_1) of Metabolites.wiff (Turbo Spray)
Max. 1.7e5 cps.
5.9e5
5.0e5
4.5e5
In te n s ity , c p s
4.0e5
API-4000, +MRM
Column: Atlantis dC18,
3uM, 2.1x50mm
Mobile phase:
3.5e5
A: H2O, 0.1%FA
3.0e5
B: ACN, 0.1%FA
2.5e5
Time
0.01
0.80
3.00
3.10
4.10
4.20
5.50
a
5.5e5
B%
45
70
85
95
95
45
Stop
d
Flow rate: 0.3ml/min
2.0e5
3.19
c
1.5e5
e
b
1.0e5
5.0e4
0.0
0.5
1.0
1.5
2.0
2.5
Time, min
3.0
3.5
4.0
4.5
What are “Co-Administration” Studies?
(Cassette Dosing / N-in-One Studies)
Simultaneous administration of multiple
compounds (including a standard compound) to
individual animals with the subsequent
determination of the concentrations of each
compound contained within single test
samples.
1000
010401_007
MRM of 12 Channels ES+
386.1 > 264.1
9.22e6
6.90
100
%
0
010401_007
7.46
100
MRM of 12 Channels ES+
370.1 > 300.1
1.96e7
%
0
010401_007
MRM of 12 Channels ES+
399 > 329
2.48e7
7.89
100
%
0
010401_007
MRM of 12 Channels ES+
390 > 320
2.29e7
7.68
100
%
0
010401_007
MRM of 12 Channels ES+
473 > 266.2
1.97e6
4.36
100
%
0
010401_007
MRM of 12 Channels ES+
370.1 > 314.2
3.71e6
5.09
100
%
0
Time
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
SRM Chromatograms of Plasma Extract from a
Dog Dosed with 20 Substances Simultaneously
Bioanalytical Work Flow
A
Sample Receipt/Tracking
B
Method
Development
H
Reporting
LC-MS/MS
C
Preparation of
Analytical
Standards & QCs
D
Information Management
Programming
Automation
G
Notebooks and Ancillary
Data
Standard Operating Guidelines
Sample
Preparation
F
Data
Processing
E
Sample Analysis
Method Development
• LC-MS/MS-based Methods
– MS parameters are established for every analyte
– HPLC conditions required for adequate response,
specificity and sensitivity
– Preparation of biological samples is critical to the
integrity and quality of the method
• Analyte response will differ in different biological extracts
• Differentiates Bioanalytical from Analytical
Preparation of Standard and
Quality Control (QC)
Samples
• Known quantities of the compounds to be evaluated are added to
blank biological matrix at established concentration ranges
• Internal Standard is added to Standard, QC, and Test samples
• Standard, QC, and Test samples are then processed in an
identical manner
• All of the samples are then analyzed and the standard and QC
samples are used to assess assay performance in terms of
accuracy and precision
How do we assess variability of our
analytical methods in drug discovery?
Standard
Curve (ng/mL)
1000
500
Six QCs at 5 Concentrations
Accuracy &
Precision Over
Linear Range
200
100
50
20
10
5
2
1
Accuracy &
Precision at
LOQ
Assay Integrity
• Determined by Standard and QC results in
conjunction with analytical requirements of
the study
• Alternative method development is carried
out, as needed
– Modifications to MS parameters,
chromatography, sample preparation
procedures, Internal Standard selection, assay
dynamic range, etc.
• Goal to provide quality data in all analysis
Quality Control Data for
‘Compounds A and B’
Compound A (LOQ = 2.5 ng/mL)
Low
(2.5 ng/mL)
Mid
(5 ng/mL)
Mid
(10 ng/mL)
Mid
(50 ng/mL)
High
(500 ng/mL)
Mean
2.74
5.32
9.84
50.44
507.75
S.D.
0.43
0.76
1.28
3.04
53.64
%CV
15.69
14.29
13.01
6.03
10.56
%Theoretical
109.6
106.4
98.4
100.9
101.6
n
6
6
6
6
6
Compound B (LOQ = 5.0 ng/mL)
Low
(2.5
ng/mL)
Mid
(5 ng/mL)
Mid
Mid
(10 ng/mL) (50 ng/mL)
High
(500
ng/mL)
Mean
2.10
4.79
10.03
51.55
529.65
S.D.
1.07
0.82
1.36
1.93
22.99
%CV
50.95
17.12
13.56
3.74
4.34
%Theoreti
cal
84.0
95.8
100.3
103.1
105.9
n
6
6
6
6
6
‘Compound X’ Fails Quality
Control Requirements
Run
Date
Low
Mid
Mid
Mid
Mid
High
(1ng/mL) (2 ng/mL) (5 ng/mL) (10 ng/mL) (50 ng/mL) (500 ng/mL)
Mean
-1.31
1.19
3.44
8.29
61.83
543.21
S.D.
1.12
3.31
2.67
3.58
21.15
98.78
%CV
-85.50
278.15
77.62
43.18
34.21
18.18
%Theoretical
-131.0
59.5
68.8
82.9
123.7
108.6
n
6
6
5
4
5
5
HPLC Analysis
Elution
Gradient
Recondition
X time
0
meaningful data
Peaks are sent to the MS for only 1/4 of the total run time,
leaving the MS idle for 3/4 of the time.
Multiplexed HPLC systems to Single MS/MS
Autosampler
Pump
HPLC
Pump
Switching
valve
HPLC
Detector
(MS)
0
Pump
HPLC
Pump
HPLC
4min
Staggered Parallel Analysis
System
1
System
2
System
3
System
4
Mass spectrometer data collection
System
1
Retention time and resolution comparison
between UPLC, TFC, and HPLC analysis
XIC of +MRM (3 pairs): 328.1/231.2 amu from Sample 13 (STD 625) of ASMS GABA std curve 8May06.wiff (Turbo Spray)
Max. 2.2e5 cps.
0.62
2.2e5
2.1e5
2.0e5
1.9e5
1.8e5
1.7e5
1.6e5
UPLC
1.5e5
In te n s ity , c p s
1.4e5
1.3e5
1.2e5
1.1e5
TFC
1.0e5
9.0e4
8.0e4
Conventional
HPLC
7.0e4
6.0e4
5.0e4
4.0e4
3.0e4
Resolved
glucuronide
signal
2.0e4
0.59
1.0e4
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
Time, min
1.8
2.0
2.2
2.4
2.6
2.8
3.0
Simultaneous Quantitation of Drugs and Endogenous “Biomarkers”
RT: 0.00 - 8.00
NL: 4.02E6
TIC F: + c SRM ms2
[email protected] [ 232.10]
MS gr_cyno_A_06
5.97
100
BMS-Compound
50
0
100
NL: 5.27E5
TIC F: + c SRM ms2
[email protected] [ 343.20]
MS gr_cyno_A_06
4.18
Prednisolone
50
5.97
4.68
0
100
NL: 1.26E5
TIC F: + c SRM ms2
[email protected] [ 163.00]
MS gr_cyno_A_06
4.67
Cortisone
50
4.17
0
100
NL: 1.03E5
TIC F: + c SRM ms2
[email protected] [ 121.00]
MS gr_cyno_A_06
4.49
Cortisol
50
0
100
NL: 1.98E4
TIC F: + c SRM ms2
[email protected] [ 225.10]
MS gr_cyno_A_06
2.06
Triamcinolone (IS)
50
0
100
NL: 6.91E6
TIC F: + c SRM ms2
[email protected] [ 336.10]
MS gr_cyno_A_06
6.29
BMS-(IS)
50
0
0
1
2
3
4
Time (min)
5
6
7
8
Summary
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Bioanalytical Research (BAR)
Drug Discovery Process
ADMET Characteristics
BAR Responsibilities
LC-MS/MS in Drug Discovery
Types of Analysis
Future Directions
BMS Bioanalytical Research
Wallingford:
Deborah Barlow, Marc Browning, Mike Donegan, Daniel Morgan,
Kim Snow, Sarah Taylor, Kim Widmann
Lawrenceville:
Hollie Booth, Chris Caporuscio, Georgia Cornelius,
Celia D'Arienzo, Lorell Discenza, Mohammed Jemal, Zheng Ouyang,
Asoka Ranasinghe, Bogdan Sleczka, Yi Tao, Xia Yuan, Jian Wang,
Steven Wu,
Hopewell:
Hong Cai, Cecilia Chi, Jim Smalley, Minjuan Wang, Richard Wong,
Baomin Xin, Carrie Xu, Hongwei Zhang, Joanna Zheng