Application of GC-C-IRMS in the ABP - wada-ama.org · Xavier de la Torre. Application of GC-C-IRMS in the ABP. Athlete Biological Passport Symposium. 5-7 November 2018. Rome, Italy

Xavier de la Torre

Application of GC-C-IRMS in the ABP

Athlete Biological Passport Symposium

5-7 November 2018Rome, Italy

• What we know so far

• Previous steps on IRMS application in doping analysis

• Longitudinal application

• Application to real passports

• Conclusions

Outline

Athlete Biological Passport Symposium - November 2018 2

What we know…..

• ABP needs to accumulate data before being effectiveDifficulties on the Results Management – Interaction with APMUsDelay on the final decisionNot fully understood by Athletes and Media

• ABP evaluation is not always effectiveDHEAT transdermalFemale athletesMicro dosing

• The inclusion of additional parameters is not easyHarmonization of new markers detection

Hydroxylated steroidsSulphated steroids


Previous steps on IRMS application in doping analysis

• IRMS Steroids data are more stable than the corresponding concentrations• Delta values are stable in a short, mid and long term period for a given individual• Delta and delta-delta values are normally distributed in the population and

individuals• The individual variability is much lower than the population one• Longitudinal evaluation of the delta values extends the detection window and an

equivalent approach to steroid module of the ABP is possible


Variability Concentrations vs Delta values (Male-M1)

SD=0,2

SD=0,3

SD=0,4

CV%=23

CV%=27

CV%=30

-29,0

-28,0

-27,0

-26,0

-25,0

-24,0

-23,0

-22,0

-21,0

-20,0

-19,0

17-Mar-13 6-May-13 25-Jun-13 14-Aug-13 3-Oct-13 22-Nov-13 11-Jan-14 2-Mar-14 21-Apr-14

δ13

C ( ‰

)

Time

5bdiol

M-3DS POP

M+3DS POP

µ-3DS LONG

µ+3DS LONG

5bdiol


Mean Mean ± 2SD Mean ± 3Sd Outlier

d T_M1 d T_M6 d T_M12-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)

Mean Mean ± 2SD Mean ± 3SD Outlier

d A_M1 d A_M6 d A_M12-26

-25

-24

-23

-22

-21

-20δ

13C

(‰)


d Et_M1 d Et_M6 d Et_M12-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)


d 5adiol_M1d 5adiol_M6

d 5adiol_M12-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)


d 5bdiol_M1d 5bdiol_M6

d 5bdiol_M12-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)


d E_M1 d E_M6 d E_M12-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)

δ 13C (‰) A δ 13C (‰) Et δ 13C (‰) 5adiol

δ 13C (‰) 5bdiol δ 13C (‰) T δ 13C (‰) E

Variability of δ13C (‰) values (TCs)Short, medium an long term period Vol #1


Variability of δ13C (‰) values (TCs)Short, mid an long term period

Variability of δ13C (‰) values (ERCs)Short, mid an long term period

Mean Mean ± 2SD Mean ± 3SD Outlierd 11bOHA_M1

d 11bOHA_M6d 11bOHA_M12

-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)


d 11KetoE_M1d 11KetoE_M6

d 11KetoE_M12-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)


d PD_M1 d PD_M6 d PD_M12-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)


d PT_M1 d PT_M6 d PT_M12-26

-25

-24

-23

-22

-21

-20

δ 13

C (‰

)

δ 13C (‰) 11OHA δ 13C (‰) 11KetoE

δ 13C (‰) PD δ 13C (‰) PT

Vol #1


Variability of ∆δ values Short, mid an long term period

Mean Mean ± 2SD Mean ± 3SD Outlierdd (PD-A)_M1

dd (PD-A)_M6dd (PD-A)_M12

-2

-1

0

1

2

3∆

δ

Mean Mean ± 2SD Mean ± 3SD Outlierdd (PD-Et)_M1

dd (PD-Et)_M6dd (PD-Et)_M12

-2

-1

0

1

2

3

∆δ

Mean Mean ± 2SD Mean ± 3 SD Outlierdd (PD-5adiol)_M1

dd (PD-5adiol)_M6dd (PD-5adiol)_M12

-2

-1

0

1

2

3

∆δ

Mean Mean ± 2SD Mean ± 3SD Outlierdd (PD-5bdiol)_M1

dd (PD-5bdiol)_M6dd (PD-5bdiol)_M12

-2

-1

0

1

2

3

∆δ

Mean Mean ± 2SD Mean ± 3SD Outlierdd (PD-T)_M1

dd (PD-T)_M6dd (PD-T)_M12

-2

-1

0

1

2

3

∆δ

Mean Mean ± 2SD Mean ± 3SD Outlierdd (PD-E)_M1

dd (PD-E)_M6dd (PD-E)_M12

-2

-1

0

1

2

3

∆δ

∆δ (PD-A) ∆δ (PD-Et) ∆δ (PD-5adiol)

∆δ (PD-5bdiol) ∆δ (PD-T) ∆δ (PD-E)

Vol #1


Normale Attesa

-25.0 -24.5 -24.0 -23.5 -23.0 -22.5 -22.0 -21.5 -21.0 -20.5X <= Soglia Categoria

0

5

10

15

20

25

30

N. o

sser

vazi

oni

-24.5 -24.0 -23.5 -23.0 -22.5 -22.0 -21.5 -21.0 -20.5Valore

-3

-2

-1

0

1

2

3

Valo

ri N

orm

ali A

ttesi

Normale Attesa

-26.0 -25.5 -25.0 -24.5 -24.0 -23.5 -23.0 -22.5 -22.0 -21.5X <= Soglia Categoria

0

2

4

6

8

10

12

14

16

18

20

22

N. o

sser

vazi

oni

-26.0 -25.5 -25.0 -24.5 -24.0 -23.5 -23.0 -22.5 -22.0Valore

-3

-2

-1

0

1

2

3

Val

ori N

orm

ali A

ttesi

Normale Attesa

-27.0 -26.5 -26.0 -25.5 -25.0 -24.5 -24.0 -23.5 -23.0 -22.5 -22.0 -21.5

X <= Soglia Categoria

0

2

4

6

8

10

12

14

16

N. o

sser

vazi

oni

Distribution of δ13C (‰) in the Population Normal distribution and P-P plots

A (n=76)

Et (n=73)

5bdiol (n=71)

Etiocolanolone

-25.5 -25.0 -24.5 -24.0 -23.5 -23.0 -22.5 -22.0 -21.5Valore

-3

-2

-1

0

1

2

3

Valo

ri N

orm

ali A

ttesi


-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5Valore

-3

-2

-1

0

1

2

3

Valo

ri N

orm

ali A

ttesi

Normale Attesa

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0X <= Soglia Categoria

0

5

10

15

20

25

30

35

N. o

sser

vazi

oni

Normale Attesa

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0X <= Soglia Categoria

0

2

4

6

8

10

12

14

16

N. o

sser

vazi

oni

-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5Valore

-3

-2

-1

0

1

2

3

Valo

ri N

orm

ali A

ttesi

Distribution of ∆δ in the Population Normal distribution and P-P plots

PD-E (n=62)

PD-Et (n=71)


-23.1-22.9

-22.7-22.5

-22.3-22.1

d A

0

2

4

6

8

10

12

N. o

sser

vazi

oni

d ANDRO: SW-W = 0.9558, p = 0.2760

A

-24.2-24.0

-23.8-23.6

-23.4-23.2

d Et

0

2

4

6

8

10

12

N. o

sser

vazi

oni

d ETIO: SW-W = 0.9533, p = 0.2398

Et

-24.30-24.04

-23.78-23.52

-23.26-23.00

d 5adiol

0

1

2

3

4

5

6

7

8

N. o

sser

vazi

oni

d 5a3aD: SW-W = 0.9462, p = 0.1729

5adiol

-24.30-24.08

-23.86-23.64

-23.42-23.20

d 5bdiol

0

2

4

6

8

10

12

14

N. o

sser

vazi

oni

d 5b3aD: SW-W = 0.8984, p = 0.0123

5bdiol

-24.50-24.16

-23.82-23.48

-23.14-22.80

d T

0

1

2

3

4

5

6

7

8

9

10

N. o

sser

vazi

oni

d TESTO: SW-W = 0.9569, p = 0.3344

T

-25.10-24.82

-24.54-24.26

-23.98-23.70

d E

0

2

4

6

8

10

12

N. o

sser

vazi

oni

d Epi: SW-W = 0.9633, p = 0.4371

E

-24.20-23.94

-23.68-23.42

-23.16-22.90

d 11OHA

0

1

2

3

4

5

6

7

8

N. o

sser

vazi

oni

d 11bOHAndro: SW-W = 0.9657, p = 0.5631

11OHA

-23.50-23.24

-22.98-22.72

-22.46-22.20

d 11KetoE

0

2

4

6

8

10

12

N. o

sser

vazi

oni

d 11KetoEtio: SW-W = 0.9621, p = 0.3903

11KetoE

-23.80-23.42

-23.04-22.66

-22.28-21.90

d PD

0

2

4

6

8

10

12

N. o

sser

vazi

oni

d Pdiolo: SW-W = 0.9683, p = 0.5797

PD

-23.3-23.1

-22.9-22.7

-22.5-22.3

d PT

0

1

2

3

4

5

6

7

8

9

N. o

sser

vazi

oni

d Ptriolo: SW-W = 0.9738, p = 0.7430

PT


Distribution of δ 13C (‰) in Vol #1 (n=28) (Shapiro Wilk Normality test; P>0,05)

-1.10-0.82

-0.54-0.26

0.020.30

Dd PD-A

0

2

4

6

8

10

12

N. o

sser

vazi

oni

?d (PD-A): SW-W = 0.9677, p = 0.5885

∆δ (PD-A)

0.10 0.44 0.78 1.12 1.46 1.80

Dd PD-Et

0

2

4

6

8

10

12

N. o

sser

vazi

oni

?d (PD-Et): SW-W = 0.9381, p = 0.1336

∆δ (PD-Et)

0.00 0.28 0.56 0.84 1.12 1.40

Dd PD-5adiol

0

1

2

3

4

5

6

7

8

9

N. o

sser

vazi

oni

?d (PD-5a3aD): SW-W = 0.9655, p = 0.5336

∆δ (PD-5adiol)

-0.30 0.24 0.78 1.32 1.86 2.40

Dd PD-5bdiol

0

2

4

6

8

10

12

14

N. o

sser

vazi

oni

?d (PD-5b3aD): SW-W = 0.9043, p = 0.0228

∆δ (PD-5bdiol)

0.10 0.46 0.82 1.18 1.54 1.90

Dd PD-T

0

1

2

3

4

5

6

7

8

9

N. o

sser

vazi

oni

?d (PD-T): SW-W = 0.9363, p = 0.1347

∆δ (PD-T)

1.2 1.4 1.6 1.8 2.0 2.2

Dd PD-E

0

1

2

3

4

5

6

7

8

9

10

N. o

sser

vazi

oni

?d (PD-EPI): SW-W = 0.9236, p = 0.0620

∆δ (PD-E)


Distribution of ∆δ (PD-TC) Vol #1 (n=28)

Reference Population vs. Pharmaceutical Preparations

δ Ref Pop (A) δ Drugs-32.8 -31.6 -30.5 -29.3 -28.1 -26.9 -25.8 -24.6 -23.4 -22.3 -21.1

0

2

4

6

8

10

12

14

16

18

N. O

bser

vatio

ns

n=40

N=105

[1] Ueki M. et al. Rapid Commun. Mass Spectrom., 1999, 13, 2237–2243.[2] de la Torre X. et al. J. Pharm. Biomed. Anal., 2001, 24, 645–650.[3] Cawley A. et al. Drug Test. Anal., 2010, 2, 557–567.[4] Forsdahl G. Drug Test. Anal., 2011, 3, 814–819.[5] Brooker L. Drug Test. Anal., 2014, 6, 996–1001. [6] Pharmaceutical seized by the Carabienieri (NAS) 2014


Individual Reference vs. Pharmaceutical Preparations & Population

δ Ref Pop (A) δ Drugs δ A Vol#1-32.8 -31.6 -30.5 -29.3 -28.1 -26.9 -25.8 -24.6 -23.4 -22.3 -21.1

0

2

4

6

8

10

12

14

16

18

N. O

bser

vatio

ns

n=28


Individual Reference vs. Pharmaceutical Preparations & Population

δ Ref Pop (A) δ Drugs δ A Vol #1 δ A Vol #4-32.8 -31.6 -30.5 -29.3 -28.1 -26.9 -25.8 -24.6 -23.4 -22.3 -21.1

0

2

4

6

8

10

12

14

16

18

N. O

bser

vatio

ns

n=28


Longitudinal application


To test the sensitivity of the IRMS Bayesian Model where theABP Steroid module and the positive criteria for IRMS basedon population references fail.

Objective

δ (‰ )

Time

Androstenedione orTestosterone administration

Detection capacity using WADA criteria


Experimental and Methods

SP IRMSEnzymatic hydrolysis, liquid-liquid extraction with TMS derivate and measure in multi-target screenings GC/MS/MS

Enzymatic hydrolysis, liquid-liquid extraction, HPLC purification and GC-C-IRMS detection

Mazzarino, M. et al. Anal. Chim. Acta 683, 221–6 (2011).de la Torre, X., et al. Anal. Chim. Acta 756, 23–29 (2012).

3 samples/week for 1 month2 Samples/month for 6 months1 Sample/month for 1 year

28 samples/volunteer

Urine samples collection, longitudinal study


3 Male Caucasian volunteers (41 ± 8 yrs)100 mg androstenedione (AED) p.o. (ASN Androstene 100 TM, Hood River, OR, USA)Urine samples collected before and for 5 days after the administrationThe androstenedione capsule composition was verified and the δ13C (‰) value determined (-30.5 ± 0.3; n=5)

Administration studies

1 Male Caucasian volunteer (43 yrs) Gel (Testogel ®, Schering) , 50 mg/day (eq. to 5 mg T), every 24 h for 4 daysUrine samples collected before and for 36 h after the last administration

The testosterone δ13C (‰) value was determined (-29.6 ± 0.3; n=5)

Oral Androstenedione

Transdermal testosterone


Oral Androstenedione


AED metabolism and marker

O

O

OH

O

OH

OH

O OH

O

O

H

O

OH

H

OH

OH

HO

O

OHO

O

OH

O

OH

OHO

OH

OH

AED

7α-OH-AED

7α-OH-T

T

6α/β-OH-AED

6α/β-OH-T

4-OH-AED

4-OH-T

5α/β-DHT

5ααβ -Adiol5αββ-Adiol5βαβ-Adiol

5α/β-androstane-3,17-dione

Androsterone (5α-androstane-3α-ol-17 one)

Epiandrosterone (5α-androstane-3β-ol-17 one)

Etiocholanolone (5β-androstane-3α-ol-17 one)

Epietiocholanolone (5β-androstane-3β-ol-17 one)

5βββ-Adiol

OH

O

H

O

OO

O

OH

O

OH

OH

2α/β-OH-AED

2α/β-OH-T


IRMS Results


SP ABP moduleCase #1 (Sample at 11.5 h)



SP ABP moduleCase #1 (Sample at 21.5 h)

IRMS population-based: ∆δERC-TC(‰) vs Time (h)

-1012345678

0 12 24 36Pd-A Pd-Etio Pd-TPd-E Pd-5aAdiol Pd-5bAdiol

-1012345678

0 12 24 36Pt-A Pt-Etio Pt-TPt-E Pt-5aAdiol Pt-5bAdiol

-1012345678

0 12 24 3611KE-A 11KE-Etio 11KE-T

11KE-E 11KE-5aAdiol 11KE-5bAdiol

-1012345678

0 12 24 36

11OHA-A 11OHA-Etio 11OHA-T11OHA-E 11OHA-5aAdiol 11OHA-5bAdiol

33.5 h

30 h33.5 h

33.5 h

Case #1


IRMS population-based

Inconclusive sample

Case #1 (Sample at 38.5 h)


-26.079

-28

-27

-26

-25

-24

-23

-22

-21

-201 3 5 7 9 11 13 15 17 19 21 23 25 27

d5a3aD 0.50% 99.50%

-26.72

-28

-27

-26

-25

-24

-23

-22

-21

-201 3 5 7 9 11 13 15 17 19 21 23 25

d5b3aD 0.50% 99.50%

-25.406

-28

-27

-26

-25

-24

-23

-22

-21

-201 3 5 7 9 11 13 15 17 19 21 23 25 27

dEtio 0.50% 99.50%

-24.087

-28

-27

-26

-25

-24

-23

-22

-21

-201 3 5 7 9 11 13 15 17 19 21 23 25 27 29

dAnd 0.50% 99.50%

IRMS Bayesian approach δTC(‰) Case #1 (Sample at 38.5 h)

δ TC(

‰)


-23.198

-28

-27

-26

-25

-24

-23

-22

-21

-201 3 5 7 9 11 13 15 17 19 21 23 25 27 29

dPd 0.50% 99.50%

-23.555

-28

-27

-26

-25

-24

-23

-22

-21

-201 3 5 7 9 11 13 15 17 19 21 23 25

d11bOHAnd 0.50% 99.50%


δPd(‰) δ11bOHAnd(‰)


IRMS Bayesian approach δERC(‰)

IRMS Bayesian approach ∆δERC-TC(‰)

2.881

-2

-1

0

1

2

3

4

1 3 5 7 9 11 13 15 17 19 21 23 25 27

dPd.5a3aD 0.50% 99.50%

3.522

-2

-1

0

1

2

3

4

1 3 5 7 9 11 13 15 17 19 21 23 25 27

dPd.5b3aD 0.50% 99.50%

0.889

-2

-1

0

1

2

3

4

1 3 5 7 9 11 13 15 17 19 21 23 25 27

dPd.And 0.50% 99.50%

2.208

-2

-1

0

1

2

3

4

1 3 5 7 9 11 13 15 17 19 21 23 25 27

dPd.Eti 0.50% 99.50%



∆δ E

RC-T

C(‰

)

Transdermal Testosterone


Transdermal T administration

Gel (Testogel ®, Schering)

50 mg/ day (eq. to 5mg T)

Every 24 h x 4 days


Campione n° T-Gel 14 CRITERI DI VALUTAZIONE

11bOH-Andro 11KetoEtio Pregnantriolo Pregnandiolo POSITIVE INCONCLUSIVE

Andro 0,2 -0,6 0,1 0,8 ANDRO INCONCLUSIVE

Etio 1,0 0,2 0,9 1,6 ETIO INCONCLUSIVE

5a3aA 3,6 2,9 3,6 4,3 a DIOLO INCONCLUSIVEINCONCLUSIVE!5b3aA 1,2 0,5 1,2 1,9 ENTRAMBI I DIOLITesto 2,1 1,4 2,1 2,8 UN DIOLO E IL TESTO INCONCLUSIVE

Epitesto 0,9 0,1 0,9 1,6 EPITESTODHEA -0,2 -1,0 -0,3 0,5

δ 13C/12C uc Ampl 44 (mV) Range di linerità (mV)

Frazione 1-7-8Etio -23,8 0,15 3719 350-7000Andro -23,0 0,09 3302 350-700011bOH-Andro -22,8 0,23 1259 350-7000

Frazione 2-65a3aA -26,5 0,29 2847 350-700011KetoEtio -23,6 0,09 1711 350-7000

Frazione 5-95b3aA -24,1 0,24 4335 350-7000Pregnandiolo -22,2 0,21 7143 350-7000

Frazione 3-6ptTesto -25,0 0,03 1832 350-7000Pregnantriolo -22,9 0,31 5158 350-7000

Frazione 4DHEA -22,6 0,11 751 350-7000

Frazione 4EpiEpitesto -23,8 0,11 1716 340-7000


IRMS Bayesian approach δERC(‰) (Sample at 12 h last adm)


δ ERC

(‰)

PPV = 99,9999991 % PPV = 99,999998 %

IRMS Bayesian approach ∆δERC-TC(‰) (Sample at 12 h last adm)


∆δ E

RC-T

C(‰

)

Methods comparison

Methods

Case WADALab ABP SP module WADA

TD2016IRMS IRMS Bayesian

Androstenedione100 mg p.o.

1 25.5 11.5 33.5 38.5

2 23.75 13.5 28.7 37.5

3 32 15 54.0 59.5

T gel 4 x 50 mg

(every 24 h) 1 0 72 (??) 96 > 104

It is evident that IRMS values evaluated with a Bayesian approach, increase the sensitivity of the technique

Time window of detection (h)



Steroid Profile ITP

Steroid Module ABP

IRMSConfirmation Method

IRMS ITP

Isotopic Module ABP

IRMSConfirmation Method

Run time 15’ / sample

One GC/C/IRMS analysis per SamplePositive QC

GC: Agilent 6890;Column : HP-5MS : 5% PhenylmethylsiliconeInjector T: 280°COven program: 150°C (1’)- @25°C/min- 260°C (3’)-@ 40°C/min-310°C (2.7 min)

Injection: 2 μL Splitless

GC/C/IRMSThermo Delta Advantage

E


Analysis Sequence

Confirmation Screening

25

PQCNQC

PQCNQC

5


Increasing workload capacity

Step h

3-12 mL Urine

3Free fraction removal

Hydrolysis + L/L

HPLC / sample 0,71,7

4-5 Injections / sample 1

Total time for 30 samples 54

Injections per sequence > 120

Step h

6 mL Urine

2No Free fraction removal

Hydrolysis + L/L

HPLC / sample 0,30,6

1 Injection / sample 0,3

Total time for 30 samples 19,4

Injections per sequence < 35


Real passports


Steroid Module

Samples collected 2015-2018


-28.0

-27.0

-26.0

-25.0

-24.0

-23.0

-22.0

-21.0

-20.0

26-Nov-16 6-Mar-17 14-Jun-17 22-Sep-17 31-Dec-17 10-Apr-18 19-Jul-18

13C δ (‰)

T A E 5a 5b PD

ca. 3 years

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

26-Nov-16 6-Mar-17 14-Jun-17 22-Sep-17 31-Dec-17 10-Apr-18 19-Jul-18

∆δ

PD-T PD-A PD-E PD-5a PD-5b


Isotopic Module

SD < 0.7 ‰

IRMS data are stable


Isotopic Module

A Et T

5aAdiol 5bAdiol PD


Steroid Module

2 Laboratories involved

2 Laboratories involved

-28.0

-27.0

-26.0

-25.0

-24.0

-23.0

-22.0

-21.0

-20.0

-19.0

23-Oct-15 18-Aug-16 14-Jun-17 10-Apr-18 4-Feb-19

13C δ(‰)

T A E 5a 5b PD

-26.0

-24.0

-22.0

-20.0

-18.0

-16.0

16-Dec-16 6-Mar-17 25-May-17 13-Aug-17 1-Nov-17

13C δ (‰)

T A E 5a 5b PD

(ca. 1 year) (ca. 2 years)


Isotopic Module


Steroid Module

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

31-Jan-16 18-Aug-16 6-Mar-17 22-Sep-17 10-Apr-18 27-Oct-18

∆δPD-T PD-A PD-E PD-5a PD-5b

-31.0

-29.0

-27.0

-25.0

-23.0

-21.0

31-Jan-16 18-Aug-16 6-Mar-17 22-Sep-17 10-Apr-18 27-Oct-18

13C δ (‰)

T A E 5a 5b PD


Isotopic Module


Isotopic Module

A Et T

5aAdiol 5bAdiol PD


Isotopic Module


……. But the steroid module of the ABP has some additional information

Conclusions and Future Perspectives

IRMS Bayesian model:

Improves the sensitivity for the detection of doping with

pseudo endogenous steroids

The simplicity and the same approach used for the Steroid

Profile Adaptive Model should allow an easy inclusion in the

Athlete Biological Passport

The use of IRMS should be extended not only to

confirmations


Future

Greater harmonization among Laboratories is needed

Study of potential confounding factors needed

Acknowledgments

My IRMS colleagues @ the Laboratorio Antidoping FMSI

Italian Ministry of Health (“Ministero della Salute,Commissione per la vigilanza sul doping e sulla tutelasanitaria delle attività sportive”) for the financialsupport of the initial part of the project

World Antidoping Agency (WADA) for financial support


Documents

Application of GC-C-IRMS in the ABP - wada-ama.org · Xavier de la Torre. Application of GC-C-IRMS in the ABP. Athlete Biological Passport Symposium. 5-7 November 2018. Rome, Italy