G-Di-Perri

Aspetti di Farmacocinetica e Farmacodinamica nei
STRs (Single Tablet Regimens) per il Trattamento
dell’Infezione da HIV-1
Gianni Di Perri
Clinica di Malattie Infettive
Università degli Studi di Torino
Ospedale Amedeo di Savoia
Ospedale Amedeo di Savoia
L’evoluzione della Farmaceutica, ovvero delle modalità di
elaborazione di preparati per uso medico, è in necessario
parallelismo con:
• L’evoluzione Farmacoterapica, ovvero degli avanzamenti in
tema di disponibilità di nuovi principi attivi efficaci, sicuri e
tollerati
• L’evoluzione della comprensione dei principi della
Farmacodinamica e dell’applicazione degli stessi (come
perseguire il miglior possibile risultato con le risorse
disponibili)
• L’evoluzione del paziente, nel senso dell’aumento della
potenzialità di cura e controllo di numerosi disordini acuti e
cronici, e quindi dell’aumento della durata della vita
In the FDC and/or STR conception one assumption and
two main reasons are recognizable
for pursuing co-formulation:
The assumption:
For whatever reason (synergy, genetic barrier, …), more
than one drug is required for treating the disease
The two main reasons:
1. More than 1 drug is required to treat the disease,
and co-formulation might ensure that 2/3 or the
entire therapy is taken;
1. A reduced n. of pills has the potential to improve
adherence
In the FDC and/or STR conception one assumption and
two main reasons are recognizable
for pursuing co-formulation:
The assumption:
For whatever reason (synergy, genetic barrier, …), more
than one drug is required for treating the disease
The two main reasons:
1. More than 1 drug is required to treat the disease,
and co-formulation might ensure that 2/2 or the
entire therapy is taken;
1. A reduced n. of pills has the potential to improve
adherence
NRTI monotherapy
NRTI dual therapy
HAART
2NRTIs +
HAART
NNRTI or PI/r or II
2NRTIs + PI (single)
HIV-RNA/mL Log10
1
HIV-RNA/mL Log10
1
1
2
2
3
3
5
5
6
6
P24 Antigen
2
3
5
6
1987 - 1994
1996 - 2000/1
1994 - 1996
1996 - now
HIV RNA copies/mL
Malattie da Infezione: Polichemioterapia
Virus
Micobatteri
Parassiti
•
•
•
•
• M.tuberculosis
• M.leprae
• MAC & other atypical
•
•
•
•
•
HIV
HBV
HCV
CMV
P.falciparum
P.vivax
P.ovale
E.histolytica
W.bancrofti
Batteri convenzionali
Funghi
• P.aeruginosa
• Cryptococcus sp.
• Aspergillus spp.
• Candida sp.
•
•
•
•
•
ESbL producers (e.g. KPC)
Endocardite
Infezioni polimicrobiche
Terapia empirica/razionale
H.pylori
Motivi del ricorso a più farmaci
• Modifica di 1 o più parametri di efficacia
Sinergico / Additivo
Antagonista / Indifferente
• Barriera genetica
Coalistico
Potenziante / Riduttivo
• Copertura di spettro
• Copertura compartimentale
• Controllo epidemiologico / ambientale (“altruista”)
[B]
The shape of equal inhibition lines in the dose-dose space
defines the interaction between the drugs
Suppression
Antagonism
Synergy
Growth rate
Growth rate
[A]
MIC
Minimal Inhibitory Concentration
“Coalistic” Interaction
Michel,Yeh, et al. – PNAS 2008
In the FDC and/or STR conception one assumption and
two main reasons are recognizable
for pursuing co-formulation:
The assumption:
For whatever reason (synergy, genetic barrier, …), more
than one drug is required for treating the disease
The two main reasons:
1. More than 1 drug is required to treat the disease,
and co-formulation might ensure that 2/3 or the
entire therapy is taken;
1. A reduced n. of pills has the potential to improve
adherence
N/NtRTIs
N/NtRTIs // NNRTIs
Combivir
Atripla
September 1997
AZT/3TC
July 2006
TDF/FTC/EFV
Trizivir
Eviplera
November 2000
AZT/3TC/ABV
August 2011
TDF/FTC/RPV
Truvada
Triomune
August 2006
TDF/FTC
June 2001
d4T/3TC/NVP
Kivexa
Duovir-N
August 2004
ABV/3TC
July 2003
AZT/3TC/NVP
Kaletra
September 2000 (Meltrex 2005)
LPV/RTV
N/NtRTIs // IIs
Stribild
August 2012
EVG/COBI/TDF/FTC
Triumeq
August-Sept 2014
DGV/ABV/3TC
Darunavir without ritonavir is 37% bioavailable
Primary resistance to darunavir leads to
significant in class resistance
Darunavir package insert
SQV/RTV simultaneously
RTV – 4 hs - SQV
SQV – 4 hs - RTV
In the FDC and/or STR conception one assumption and
two main reasons are recognizable
for pursuing co-formulation:
The assumption:
For whatever reason (synergy, genetic barrier, …), more
than one drug is required for treating the disease
The two main reasons:
1. More than 1 drug is required to treat the disease,
and co-formulation might ensure that 2/3 or the
entire therapy is taken;
1. A reduced n. of pills has the potential to improve
adherence
Adherence: on-time pharmacy refills
by number of tablets per day
Single-tablet regimen
P <0.01
Multi-tablet regimen
50
44.8%
41.3%
P <0.01
40
Patients, %
11% more pts with
≥80% adherence to STR
vs. MTR:
70% vs. 59%
P <0.01
28.4%
30
P <0.01
25.3%
23.2%
17.6%
20
11.6%
10
0
6.6%
122
690
<60%
427
1686
60%–79%
824
2454
80%–94%
465
1044
N
95%–100%
Adherence to antiretroviral therapy
Cohen C, et al. EACS 2011. Belgrade, Serbia. Poster PE7.5/7.
1
5
Caratteristiche e Proprietà delle
Singole Componenti di un
Regime STR
Integrase Inhibitors (IIs): main clinical trials
Raltegravir (RAL)
Elvitegravir (ELV)
Dolutegravir (DGV)
BENCHMRK
Study 102 (vs
EFV/FTC/TDF [atripla])
SPRING 1, 2 (vs RAL &
EFV)
Study 103 (vs ATV/r)
SINGLE (vs
EFV/FTC/TDF [atripla])
SWITCHMRK
*
STARTMRK
STRATEGY - PI
ARDENT (ACTG 5257)
VIKING I, II, III (RAL-R)
STRATEGY - NNRTI
QDMRK (QD vs bid)
SAILING (vs RAL, IIsnaïve pts)
Treatment-naïve pts
Treatment-experienced patients
Switch studies (not for failure)
Superiority:
at week 48;
FLAMINGO (vs DRV/r)
* At week 156
PHARMACODYNAMICS
IC50: 2.7 nM,
IC50 in PBMC: 0.51 nM
RAL IC50: 3.3 nM
EVG IC50: 6.0 nM
Kobayashi M, et al. Antimicrob Agent Chemother 2011; 55: 813-21
Dissociation from integrase-DNA complexes: mean dissociation rate constant ((koff) [s-1 x 10-6]
Drug
Wild-Type HIV
Q148 mutation
DTG
2.7
37
RAL
22
1160
EVG
71
1130
EVG, elvitegravir; IC50, 50% inhibitory concentration; PBMC,
peripheral blood mononuclear cells; RAL, raltegravir
Hightower KE, et al. Antimicrob Agent Chemother 2011; 55: 4552-9
RELATIONSHIP BETWEEN DTG TROUGH CONCENTRATION
AND VIRAL LOAD REDUCTION
Phase IIa, dose-ranging, placebo-controlled, 10-day monotherapy study
C (µg/mL)
Day 11 log10 viral load change from
baseline
0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
–3.5
Subjects with
HIV-1 RNA <50 c/mL
are represented by
orange-bordered
circles
–3.0
–2.5
–2.0
–1.5
–1.0
Placebo
2 mg QD
–0.5
10 mg QD
0
50 mg QD
0.5
Model fit: Emax = –2.6, IC50 – 0.036 µg/mL
Open circles with lines
denote mean standard
deviation
1.0
DTG is associated with a well characterised, predictable
exposure-response relationship
c/mL, copies/mL; Emax, maximum effect; RNA, ribonucleic acid
Adapted from Min S, et al. AIDS 2011; 25:1737–45
DTG: 90%
Proportion (%)
DRV/r: 83%
86%
100
Percent of Patients With
HIV RNA < 50 Copies/mL
A favorable finding
associated to the
therapeutic use of IIs in
treatment-naïve patients is
a much quicker viral fall
then comparators (both
NNRTIs and PIs/r
80
82%
60
Non-Inferiority
P Value < 0.001
40
Raltegravir 400 mg BID*
Efavirenz 600 mg QHS*
20
0
024
8 12 16
24
Weeks
32
40
48
Does it matter?
My answer is probably yes, I
would say for two reasons:
a. Greater genetic barrier
BL
4
8 12
16
24
Week
36
48
b. Pharmacodynamic T/2 likely
to be longer than
pharmacokinetic T/2
Infections with a high bacterial density at the initiation of antibiotic therapy
may present a therapeutic problem, including a higher risk for the emergence
of resistance due to the larger number of bacteria present and the higher
probability of having at least one resistant bacterial cell within a large initial
inoculum (CFUo)
Johnson, C. C., L. Livornese, M. J. Gold, P. G. Pitsakis, S. Taylor, and M. E. Levison. 1995. Activity of cefepime
against ceftazidime-resistant gram-negative bacilli using low and high inocula. J. Antimicrob. Chemother.
35:765-773.
1000 in 109
100 in 108
10 in 107
1 in 106
Shen l, et al. Letter Nature Medicine 14, 762 - 766 (2008) Published online: 15 June 2008
Log (fa/fu) = m log(D/IC50)
Fraction of the viral
population affected
by the drug
Fraction of the viral
population
unaffected by the
drug
Steepness of the curve
The parameter m determines
the sigmoidicity of the
concentration-response curve
m1
m2
m3
Drug
concentration
Drug concentration inhibiting
the 50% of viral growth
The effect of the virus is
measured in a singleround infectivity assay in
vitro as infected cells (%)
rather than as HIV-RNA
fall per time unit (clinical
studies)
BL
4
8
RAL 100 mg BID.
RAL 200 mg BID.
12 RAL
16400 mg
24 BID.
Week
RAL 600 Weeks
mg
BID.
EFV 600 mg QD
Percent of Patients With
HIV RNA < 50 Copies/mL
Proportion (%)
DRV/r: 83%
86%
100
DTG: 90%
80
82%
60
Non-Inferiority
P Value < 0.001
40
Raltegravir 400 mg BID*
Efavirenz 600 mg QHS*
20
0
36
024
48
8 12 16
24
Weeks
32
40
48
EFV
RAL
These are the
facts…….
Shen l, et al. Letter Nature Medicine 14, 762 - 766 (2008) Published online: 15 June 2008
Experimentally measured antiretroviral IC50s are determined by
These parameters may also depend on the
three factors:
virus-producing cell type.
1. intrinsic drug properties (e.g. drug-target binding)
•
•
•
•
how well it is taken up,
complexes with,
inhibits its target,
how easily the reverse process takes place
Previously reported IC50s of five RT
inhibitors in macrophages are on average 3
fold lower than IC50s measured using a
similar and compar- able single round
infection assay in CD4+ T cells
2. kinetics of the HIV life cycle
• the longer the drug-susceptible state exists the lower the IC50, because
there is more time for the drug to act and affect target cells
Enhancing ARV activity through
pharmacologic interventions that
3. kinetics of drug-inhibited infected cells prolong the drug-susceptible state; eg
additional antiretroviral drugs (synergy)
HIV requires an average
of 52 h between two
sequential generations;
Most of this time is
taken by reverse
transcription (RT, 33 h)
NEAT 001/ANRS 143
Primary endpoint at W96 by baseline
characteristics
Overall analysis: RAL + DRV/r non inferior to TDF/FTC + DRV/r
Overall
RAL + DRV/r
TDF/FTC +
DRV/r
-1.1
8.6
n = 805
Baseline HIV-1 RNA
< 100,000 c/ml
n = 530
> 100,000 c/ml
-3.9
n = 275
3.5
-0.05
19.3
RAL + DRV/r
TDF/FTC +
DRV/r
17.4 %
13.7 %
7%
7%
36 %
27 %
p = 0.09*
Baseline CD4+
< 200/mm3
n = 123
> 200/mm3
n = 682
4.7
-3.4
30.8
6.3
39.0 %
21.3 %
13.6 %
12.2 %
p = 0.02*
9
-10
0
10
20
30
Difference in estimated proportion (95% CI) RAL – TDF/FTC; adjusted
* Test for homogeneity
Virological Efficacy at W24
Proportion of patients with HIV RNA <50 cp/mL
MonoDTG
28 pts
25/28 VL <50 cp/mL
100%
90%
• All <50 cp/mL
• All <20 cp/ml except
37 cp/mL (1)
• 1 blip W4 (52 cp/mL)
80%
3 virological failures
40%
• W12: 1 pt
30%
– VL 138/469 cp/mL
• W24: 2 pts
– VL: 2220 cp/mL
– VL: 291 cp/mL
Katlama C, et al. EACS 2015 , Oral PS4/4
70%
100%
100%
CI 95%:
85–100
CI 95%:
85–100
W4
n=23
W8
n=22
96%
CI 95%:
82–99
60%
89%
CI 95%:
72–98
50%
20%
10%
0%
W12
n=28
W24
n=28
Viral suppression at week 24
Dolutegravir-Lamivudine as initial therapy
in HIV-infected ARV naïve patients
First results of the PADDLE trial
ClinicalTrials.gov : # NCT02211482
#
SCR
BSL
DAY 2
DAY 4
DAY 7
DAY 10
W.2
W.3
W.4
W.6
W.8
W.12
W.24
1
5.584
10.909
3.701
383
101
71
< 50
< 50
< 50
< 50
< 50
< 50
< 50
2
8.887
10.233
5.671
318
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
3
67.335
151.569
37.604
1.565
1.178
266
97
53
< 50
< 50
< 50
< 50
< 50
4
99.291
148.370
11.797
3.303
432
179
178
55
< 50
< 50
< 50
< 50
< 50
5
34.362
20.544
4.680
1.292
570
168
107
< 50
< 50
< 50
< 50
< 50
< 50
6
16.024
14.499
3.754
1.634
162
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
7
37.604
18.597
2.948
819
61
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
8
25.071
24.368
6.264
1.377
Not done
268
105
< 50
< 50
< 50
< 50
< 50
< 50
9
14.707
10.832
Not done
516
202
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
10
10.679
7.978
5.671
318
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
11
50.089
273.676
160.974
68.129
3.880
2.247
784
290
288
147
< 50
< 50
< 50
12
13.508
64.103
3.496
3.296
135
351
351
84
67
< 50
< 50
< 50
< 50
13
28.093
33.829
37.350
26.343
539
268
61
< 50
< 50
< 50
< 50
< 50
< 50
14
15.348
15.151
3.994
791
198
98
< 50
61
64
< 50
< 50
< 50
< 50
15
23.185
23.500
15.830
4.217
192
69
< 50
< 50
< 50
Not done
< 50
< 50
< 50
16
11.377
3.910
370
97
143
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
17
39.100
25.828
11.879
1.970
460
147
52
< 50
< 50
< 50
< 50
< 50
< 50
18
60.771
73.069
31.170
2.174
692
358
156
< 50
< 50
< 50
< 50
< 50
< 50
19
82.803
106.320
35.517
2.902
897
352
168
76
< 50
< 50
< 50
< 50
< 50
20
5.190
7.368
3.433
147
56
< 50
< 50
< 50
< 50
< 50
< 50
< 50
< 50
From week 8 onwards all patients had pVL <50 copies/mL
Parasite Clearance according to the PRR48h
Total Parasite Burden
1012
1010
detection limit (50/mL)
108
106
Artesunates
Chl, Amod, Halof
Quin, Mefl, SP
102
105
104
103
10
102
0
Days
0
4
8
12
16
20
24
Differenziazione e
Replicazione asessuata del
Plasmodium falciparum
Le forme inibite dagli
inibitori della DHFR, da
chinino, chinidina e
meflochina
Differenziazione e
Replicazione asessuata del
Plasmodium falciparum
Le forme inibite
dagli artesunati
ELIMINATION HALF-LIFE (T/2)
TDF (ic): 150 h
EFAVIRENZ
EFV: 45 h
FTC (ic): 39 h
0
10
20
30
40
50
60 h
TDF (ic): 150 h
RILPIVIRINE
RPV: 50 h
FTC (ic): 39 h
0
10
20
30
40
50
60 h
TDF (ic): 150 h
FTC (ic): 39 h
ELVITEGRAVIR/COBI
EVG: 12.9 h
0
10
20
30
40
50
60 h
30
40
50
60 h
ABV (ic): 20 h
3TC (ic): 25
h
DOLUTEGRAVIR
http://www.hiv-druginteractions.org
0
10
DGV: 14 h
20
TORINO:
Stefano Bonora
Antonio D’Avolio
Mauro Sciandra
Alessandra Arialdo
Micol Ferrara
Alice Trentalange
Marco Siccardi
Nicole Pagani
Lorena Baietto
Lucio Boglione
Cristina Tettoni
Sarah Allegra
Sabrina Audagnotto
Letizia Marinaro
Jessica Cusato
Margherita Bracchi
Laura Trentini
Andrea Calcagno
Alessandro Turchi
Debora Pensi
Pino Cariti
Paolo Bigliano
Ilaria Motta
Silvia Corcione
Marco Simiele
Maria Laura Stella
Amedeo De Nicolò
Giancarlo Orofino
Anna Lucchini
Acknowledgments
THE UNIVERSITY
of LIVERPOOL
LIVERPOOL:
David Back
Saye Khoo
Andy Owen
Marco Siccardi
Anna Maria Geretti
Valeria Ghisetti
Filippo Lipani
Roberto Bertucci
Agostino Maiello
Bernardino Salassa
Francesco G. De Rosa
Chiara Montrucchio
Chiara Alcantarini
Chiara Cardellino
LONDON:
ROMA:
Marta Boffito
Andrea Antinori
Margherita Bracchi
Emanuele Nicastri
Nicole Pagani
Giuseppe Ippolito