2 da fecha no todos los inh dpp4 son iguales (2)
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No todos los Inhibidores de la DPP4 son iguales
Dr. Luis More SaldañaHospital Santa Rosa /Clínica San FelipeEndocrinólogo
Advisory: Eli Lilly Speaker: MSD,Eli Lily,Novartis.Investigador Principal : Novartis ,Covance.Takeda ,Sanofi Aventis PPD,Roche ,Johson&Johnson Astrazeneca,GSK.
Conflicto de Interés
Chemical Class
β-Phenethylamines1 Cyanopyrrolidines Aminopiperidine8 Xanthine
Generic Name
Sitagliptin2,3 Vildagliptin2,4,5 Saxagliptin2,6,7 Alogliptin9,10 Linagliptin11,12
Molecular Structure
DPP-4 Inhibitory Activity (IC50)
9.96 ± 1.03 nM 5.28 ± 1.04 nM 3.37 ± 0.90 nM 6.9 ± 1.5 nM ~1 nM
Half-life 12.4 h ~2–3 h2.5 h (parent)
3.1 h (metabolite)12.4–21.4 h 113–131 h
DPP-4 Inhibitors Differ in Molecular Structures and Pharmacologic Properties
DPP-4=dipeptidyl peptidase-4. IC50 =half maximal inhibitory concentration1. Kim D et al. J Med Chem. 2005;48:141–151. 2. Matsuyama-Yokono A et al. Biochem Pharmacol. 2008;76:98–107. 3. JANUVIA EU-SPC 2010.4. Villhauer EB et al. J Med Chem. 2003;46:2774–2789. 5. Galvus EU-SPC 2010. 6. Augeri DJ et al. J Med Chem. 2005;48:5025–5037. 7. Onglyza EU-SPC 2010. 8. Feng J et al. J Med Chem. 2007;50:2297–2300. 9. Lee B et al. Eur J Pharmacol. 2008;589:306–14. 10. Christopher R et al. Clin Ther. 2008;30:513–527. 11. Thomas L et al. J Pharmacol Exp Ther. 2008;325:175–182. 12. Heise T et al. Diabetes Obes Metab. 2009;11:786–794.
F
F
F O
N
NH2
N NN
CF3
N N
OH3C
O N
CN
NH2
N
O
HH
NCHO
NH2
HO
NH
O
N
NC
N
NO
N
N
N
NN
O
NH2
Química Metabolización Eliminación
Sitagliptina Derivado de β-amino acido No metabolizado Renal (~80% inmodificado)
Vildagliptina Cianopirrolidina Hidrolizado a metabolito inactivo (P450 independent)
Renal (22% como molécula madre, 55% como metabolito)
Saxagliptina Cianopirrolidina Metabolizado en hígado – Metabolito activo (via P450 3A4/5)
Renal (12-29% como madre, 21-52% como metabolito)
Alogliptina Pirimidinediona modificada No metabolizado Renal (>70% inmodificado)
Linagliptina Derivado xantinico No metabolizado Biliar (inmodificado); <6% via renal
Características de los inhibidores DPP-4 (Deacon C, 2010)
Selectivity for DPP-4 vs other enzymes
C. Deacon Diabetes, Obesity and Metabolism 13: 7–18, 2011
Chemical Class
β-Phenethylamines1 Cyanopyrrolidines Aminopiperidine8 Xanthine
Generic Name
Sitagliptin2,3 Vildagliptin2,4,5 Saxagliptin2,6,7 Alogliptin9,10 Linagliptin11,12
Molecular Structure
DPP-4 Inhibitory Activity (IC50)
9.96 ± 1.03 nM 5.28 ± 1.04 nM 3.37 ± 0.90 nM 6.9 ± 1.5 nM ~1 nM
Half-life 12.4 h ~2–3 h2.5 h (parent)
3.1 h (metabolite)12.4–21.4 h 113–131 h
DPP-4 Inhibitors Differ in Molecular Structures and Pharmacologic Properties
DPP-4=dipeptidyl peptidase-4. IC50 =half maximal inhibitory concentration1. Kim D et al. J Med Chem. 2005;48:141–151. 2. Matsuyama-Yokono A et al. Biochem Pharmacol. 2008;76:98–107. 3. JANUVIA EU-SPC 2010.4. Villhauer EB et al. J Med Chem. 2003;46:2774–2789. 5. Galvus EU-SPC 2010. 6. Augeri DJ et al. J Med Chem. 2005;48:5025–5037. 7. Onglyza EU-SPC 2010. 8. Feng J et al. J Med Chem. 2007;50:2297–2300. 9. Lee B et al. Eur J Pharmacol. 2008;589:306–14. 10. Christopher R et al. Clin Ther. 2008;30:513–527. 11. Thomas L et al. J Pharmacol Exp Ther. 2008;325:175–182. 12. Heise T et al. Diabetes Obes Metab. 2009;11:786–794.
F
F
F O
N
NH2
N NN
CF3
N N
OH3C
O N
CN
NH2
N
O
HH
NCHO
NH2
HO
NH
O
N
NC
N
NO
N
N
N
NN
O
NH2
Química Metabolización Eliminación
Sitagliptina Derivado de β-amino acido No metabolizado Renal (~80% inmodificado)
Vildagliptina Cianopirrolidina Hidrolizado a metabolito inactivo (P450 independent)
Renal (22% como molécula madre, 55% como metabolito)
Saxagliptina Cianopirrolidina Metabolizado en hígado – Metabolito activo (via P450 3A4/5)
Renal (12-29% como madre, 21-52% como metabolito)
Alogliptina Pirimidinediona modificada No metabolizado Renal (>70% inmodificado)
Linagliptina Derivado xantinico No metabolizado Biliar (inmodificado); <6% via renal
Características de los inhibidores DPP-4 (Deacon C, 2010)
44
Sitagliptin: Dose reduction is based on PK data
AUC=area under the curve; CrCl=creatinine clearance; GM=geometric mean.1. Data on file, MSD.
<2-fold AUC increasewith mild renal insufficiency
vs normal renal function
Dose adjustmentsCrCl <30 mL/min: ¼ dose
CrCl 30–50 mL/min: ½ doseCrCl >50 mL/min: full dose
Do
se-A
dju
sted
(to
50
mg
) A
UC
, μM
/h
0
4
8
12
16
20
24
28
Creatinine Clearance, mL/min10 30 50 70 90 110 130 150 170 190 210 230
GM of healthy subjects
2× GM ofhealthy subjects
APaT, Excluding Data After Initiation of Glycemic Rescue Therapy
Sitagliptin vs Glipizide in Patients With Type 2 Diabetes Mellitus and Chronic Renal Insufficiency: Change From Baseline in Estimated GFR1
GF
R E
stim
atio
n M
DR
D (
mL
/min
/1.7
3m2 )
C
han
ge
Fro
m B
asel
ine
(Mea
n ±
SE
)
Week0 6 12 18 30 42 54
1
0
-1
-2
-3
-4
-5
Sitagliptin Glipizidea
APaT=All Patients as Treated ; GFR=glomerular filtration rate; SE=standard error.aMean dose of glipizide was 7.7 mg per day.1. Data on file, MSD.
Selectivity for DPP-4 vs other enzymes
C. Deacon Diabetes, Obesity and Metabolism 13: 7–18, 2011
FDA requirement
24-hour Weighted Mean Glucose Change From Baseline at Day 28
Sitagliptin, Linagliptin compared to placebo
Ref.: clinicaltrials.gov
* P < 0,001 vs placebo
n=40 n=39
-19.8 ± 2.9*-26.1 ± 2.8
Sitagliptin
100 mg/day
Linagliptin
5 mg/day
Change from Baselineat Week 24 (Primary End Point)
–30,0
–25,0
–20,0
–15,0
–10,0
–5,0
0,0
5,0
24 h
- W
eigh
ted
Mea
n G
luco
se[u
nits
: m
g/d
L] M
ean
± S
D
7.32 ± 0.59
7.17 ± 0.44 Baseline-HbA1c
Placebo
7.47 ± 0.53
0.1 ± 3.0
n=38
n=39n=40
Fasting Plasma Glucose Change From Baseline at Day 28
Sitagliptin, Linagliptin compared to placebo
Ref.: clinicaltrials.gov
* P = 0.0283 vs placebo
n=40 n=39
-10.9 ± 3.5 *-15.6 ± 3.1
Sitagliptin
100 mg/day
Linagliptin
5 mg/day
Change from Baselineat Week 24 (Primary End Point)
–20,0
–15,0
–10,0
–5,0
0,0
5,0
FP
G[u
nits
: m
g/d
L]M
ean
± S
D
7.32 ± 0.59
7.17 ± 0.44 Baseline-HbA1c
Placebo
7.47 ± 0.53
-0.1 ± 3.6
n=38
n=39n=41
Head to Head StudyLinagliptin versus glimepride, both on top of metformin
EMA/ European public assessment report Linagliptin
-0,60%
-0,50%
-0,40%
-0,30%
-0,20%
-0,10%
0,00%
52 weeks 104 weeks
Glim
Lina
Full Analysis Set
Non-inferiority margin:0.35%
0,22% 0,20%
- 0.
60%
- 0.
38%
- 0.
36%
- 0.
16%
Per protocol analysis (more robust)Differences: 0.26% 0.28%
HbA
1c
redu
ctio
n
Linagliptin PK interacionsEfects of coadministered drugs on linagliptinUS- PI 2011
EMA webside
EMA Scientific discussion
Linagliptin Phase III Meta-analysis:Linagliptin Phase III Meta-analysis:Cardiovascular EndpointsCardiovascular Endpoints
Secondary Endpoints: Hazard Rate Estimates
0.15 0.34 0.75
0.125 0.25 0.5 1 2 4
0.33 0.55 0.94
0.17 0.36 0.78
Ratio (95% CI) of linagliptin to control
Favors Linagliptin
Favors Comparators
CV death, MI, or stroke
All CV events*
FDA-custom MACE†
ADA 2011 Poster 30-LB
*All major CV events include CV death, MI, stroke, transient ischemic attack, UAP, and stable angina pectoris.†FDA-custom MACE includes 34 unadjudicated MedRA preferred terms for MI and stroke.
Linagliptin Product information Canada
G. Schernthaner et al. Diabetes, Obesity and Metabolism 2012
Lina CV safety
G. Schernthaner et al. Diabetes, Obesity and Metabolism 2012
FDA requirement
Conclusion Linagliptin
Only limited clinical experience
Less indications
No RCTs in patients with moderate/severe renal failure and dialysis
Xanthin based molecule: HR increase, proarrythmic?
No CV benefit over Placebo in pooled safety analysis
Why inhibit FAP?
Glucose lowering efficacy? (Lina/Sita 24h WMG study)
Vildagliptin
Main points to note:– Need to check hepatic enzymes– BID dosing– No CV outcome trial– Poorer in vitro selectivity than other DPP4 inhibitors– Pre-clinical tox issues - maybe due to DPP8 and DPP9
inhibitory activity
The Marfella issue
• Repeat nonsense* until it is believed
• * retrospective analysis of as much data as possible until you find a difference that probably occured by chance
• The only way to compare compounds is with appropriately powered, prospective randomised clinical trials
Cross-Sectional Study: Sitagliptin vs Vildagliptin in Patients With Type 2 Diabetes Uncontrolled on
Metformin
Journal of Diabetes and Its Complications, Marfella R, Barbieri M, Grella R, et al., Effect so vildagliptin twice daily vs. sitagliptin once daily on 24-hour acute glucose fluctuations, Vol. 24(2),79-83 (2010),
Marfella et al J Diabetes Complication 2009
Inta
ct G
LP-1
(pm
ol/L
)
30
20
10
0
** * *
**
***
Breakfast Lunch Dinner (+5 h) (+ 10 h)
0 180 300 0 180 300 0 180 300 min
80
60
40
20
Pla
sma
gluc
agon
(m
g/dL
)
* ***
* **
** **
**-60
-40
-20
0G
luco
se c
hang
es (
mg/
dL) } } } }FPG PPG MPG MAGE
*
Inadequate glycaemic control while on max metformin (3000 mg/d)
Sitagliptin (100 mg qd; n=20)
Vildagliptin (50 mg bid; n=18)
MAGE = mean amplitude of glycaemic excursion, determined from arithmetic mean of differences between consecutive glycaemic peaks and nadirs
Effects of vildagliptin twice daily vs sitagliptin once daily on 24-hour acute glucose fluctuations Marfella R et al.
Method: Not a prospective, randomized, blinded clinical trial
Why don’t we like this analysis
Small study Not sufficiently powered Retrospective analysis SD is a more typical measure of variability We have no problems convincing SLs about the weakneses
of this study – but primary health care physicians??
65
0
10
20
30
40
50
60
70
80
90
100
Percent Plasma DPP-4 Inhibition*
Mea
n P
erce
nt
Inh
ibit
ion
of
DP
P-4
A
ctiv
ity
(S
E)
Hours
Sitagliptin 100 mg QD
Vildagliptin 50 mg BID **
Saxagliptin 5 mg QD
Vildagliptin 50 mg QD **
Placebo
* Single day dosing** Vildagliptin is not approved in the US
Once-Daily Dosing of JANUVIA Delivers Maximal
DPP-4 Inhibition Over 24 Hours
0 5 10 15 20 25
OPTIMA : Optimized Glycemic Control With Vildagliptin vs. Sitagliptin - Study Design1
CGM=continuous glucose monitoring.1. Guerci B et al. French Diabetes Society (SFD) Congress. Nice, France. 2012. Poster 299.
R
Inclusion Criteria:•Age > 18 yrs•HbA1c between 6.5 and 8.0% •BMI between 22 and 45 kg/m2
•Currently on stable, maximum tolerated metformin dose
8 Weeks
Vildagliptin + Metformin (N=19)
Sitagliptin + Metformin (N=19)
CGM for 3 days
CGM for 3 days
CGM for 3 days
2-4 Weeks
OPTIMA : Optimized Glycemic Control With Vildagliptin vs. Sitagliptin - Study Objectives1
Primary Objective:– Change in mean amplitude of glycemic excursions (MAGE) after 8
weeks of treatment Secondary Objectives:
– Time spent in the optimal glycemic range, ≥ 70 and ≤ 140 mg/dL – Time spent in hyperglycemic range, ≥140 and ≥180 mg/dL– Time spent in hypoglycemic range, < 70 mg/dL
67
1. Guerci B et al. French Diabetes Society (SFD) Congress. Nice, France. 2012. Poster 299.
OPTIMA : Optimized Glycemic Control With Vildagliptin vs. Sitagliptin - Patient Characteristics1
Sitagliptin 100 mg QD(N=19)
Vildagliptin 50 mg BID(N=19)
Mean age, yrs 53.5 59.1
Males, n (%) 11 (57.9) 10 (52.6)
Body Weight, kg 87.6 86.1
BMI, kg/m2 30.9 31.2
Mean HbA1c, % 7.09 7.16
Mean metformin dose, mg/day 2113 2115
Duration of disease, yrs 6.3 7.6
68
BID=twice daily; QD=once daily.1. Guerci B et al. French Diabetes Society (SFD) Congress. Nice, France. 2012. Poster 299.
OPTIMA : Glycemic Variability Results Were Similar Between Sitagliptin and Vildagliptin Treated Groups1
69
At baselineAt 8 weeks
BID=twice daily; MAGE=mean amplitude of glycemic excursions; MODD=mean of daily differences; QD=once daily; SD=standard deviation. 1. Guerci B et al. French Diabetes Society (SFD) Congress. Nice, France. 2012. Poster 299.
SD of 24-h Mean Glycemia
MAGE
Varia
ble,
mg/
dL
MODD
P=0.61
P=0.83
P=0.89
2 abstracts/posters published in 1Q/2012
Poster at ATTD meeting – Barcelona, Spain.February 2012
Poster at SFD congress in France March 2012 (arguably the most important national diabetes congress in France)
Methods
A multicentre, prospective, randomised, open label study with blinded endpoint.
Type 2 patients who were treated with either vilda or sita as an add-on to metformin in patients with starting HbA1c levels in rage 6.5-8.0.
NB Starting HbA1c is 7.1 – compared to Marfella study (8.3-8.4 Blood glucose was continuously monitored over two 72-hour periods:
– First Observation – pts on metformin alone– Second Observation - eight weeks after the addition of either vildagliptin
(n=14) or sitagliptin (n=16). CGM recordings were centrally analysed in a blinded fashion
Results Primary Endpoint – Glycaemic Variability (eg MAGE)
– Both vilda and sita significantly improved MAGE, SD and MODD– No differences between vilda and sita
Secondary Endpoints – Effect on HbA1c was similar with both compounds: Sita: decrease of 0.34 from a
baseline of 7.12, Vilda decrease of 0.49 from a baseline of 7.14– Time spent in the optimal glycaemic range (70-140 mg/dL) increased significantly by
vilda, although no difference between the 2 inhibitors is evident– Time spent at hyperglycaemic levels (AUC Total: AUC>/=100 mg/dl over the full 24-hour
period; • Reduced by 37% by vildagliptin Sig (level?)• Reduced by 9% on sitagliptin, NS• Again, no difference was observed between the 2 inhibitors
– Time spent at hyperglycaemic levels (>/= 140 mg/dL) • Poster: Only patients in the vildagliptin group had a significant decrease in time spent above 140
mg/dL. Decrease observed with sitagliptin was not sinificant• Again, the between-group difference did not achieve statistical significance.
Glycemic Variability Results Were Similar Between Sitagliptin and Vildagliptin Treated Groups1
73
At baselineAt 8 weeks
BID=twice daily; MAGE=mean amplitude of glycemic excursions; MODD=mean of daily differences; QD=once daily; SD=standard deviation. 1. Guerci B et al. Poster.
SD of 24-h Mean Glycemia
MAGE
Varia
ble,
mg/
dL
MODD
P=0.61
P=0.83
P=0.89
Sitagliptin and Vildagliptin Increased the Time Patients Spent in the Ideal Glycemic Range at 8 Weeks1
74
At baselineAt 8 weeks
Tim
e, m
inut
es
Glucose levels 70 – 140 mg/dL Glucose levels >140 mg/dL
BID=twice daily; QD=once daily. 1. Guerci B et al. Poster.
P=0.11
P=0.09
Sitagliptin Reduced HbA1c Levels at a Similar Rate From Baseline Compared With Vildagliptin1
75
N=16 N=14
-0.34a
-0.49b
7.12 7.14Mean Baseline HbA1c
P=0.42aP=0.09 .bP<0.001.1. Guerci B et al. Poster.
Other Notes/Questions
Publication of full paper: Within one year (Valensi – personal communication to Elisabeth Eymard)
Some (secondary?) endpoints quoted on posters do not appear to have been pre-specified – ie retrospective data analysis
No incretin or pancreatic endocrine data presented – it is unclear whether the protocol includes measurement of these hormones.
One imagines an attempt will be made to link this data to differences in binding of the two inhibitors (although we have commented publically on the limitations of this linkage)
Study was small – statistical power calculation?
Saxagliptin Was Noninferior to Sitagliptin in Reducing HbA1c at 18 Weeks
Primary End Point (Per-Protocol Population; on background of metformin therapy)
Mean baseline HbA1c, %
Cha
nge
From
Bas
elin
e in
A
djus
ted
Mea
n H
bA1c
(SE)
, %
0.09 (95% CI: –0.01, 0.20)a
(Prespecified noninferiority margin=0.30%)
Sitagliptin 100 mg + metformin
Saxagliptin 5 mg + metformin
In the FAS population, numerically greater
HbA1c reductions from baseline were observed
for sitagliptin 100 mg compared with saxagliptin 5 mg. Difference between groups: 0.17% (95% CI:
0.06, 0.28)
7.69 7.68
–0.62(95% CI: –0.69, –0.54)
–0.52(95% CI: –0.60, –0.45)
–0.60
–0.45
–0.30
–0.15
0.00
–0.75
CI=confidence interval; FAS=full-analysis-set; SE=standard error.aDifference in adjusted change from baseline vs sitagliptin + metformin.Scheen AJ et al. Diabetes Metab Res Rev. 2010;26(7):540–549.
n=343 n=334
Thank you
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