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The search for a cure: A drug discovery perspective on HIV eradication “A game of hide and...
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Transcript of The search for a cure: A drug discovery perspective on HIV eradication “A game of hide and...
The search for a cure: A drug discovery perspective on HIV eradication
“A game of hide and sleep”
Daria Hazuda, Merck and Co
Why can’t we cure HIV with ARV DrugsWhere is the virus and how is it maintained in the
face of “suppressive” therapy?
Defining the problem…..
The Reservoir of Latently Infected Cells Decays Slowly and is replenished?
Siliciano et al., Nat Med (2003) 9:727
Decay of Latent Reservoir in Patients with full HAART suppression for 3-7 years
• HIV Integrates into cells with extremely long biological half-life
• Integrated HIV persists in patients on HAART
• Latent reservoir makes HIV infection incurable
• Potential for clonal expansion of latently infected cellsand proliferation
Persistent low level viremia can be detected in nearly all patients on HAART
Plasma HIV RNA (log)
Perc
en
tile
2.5
Nelfinavir
0
20
40
60
80
100
-0.5 0 0.5 1 1.5 2
Lopinavir/Ritonavir
Maldarelli, Palmer, et al. PLoS Pathogens 2007
Median 3.1 copies RNA/mL at week 60
T cell activation declines, but remains abnormal even after many years of HAART
Hunt PW, et al. J Infect Dis. 2003;187:1534-1543 and unpublished
% C
D38
+H
LA
DR
+C
D8+
T C
ells
0
20
40
60
80
HIVNegative(n=82)
Non-Controller
(n=65)
HAART(n=132)
P < 0.001
P < 0.001
The size of the HIV reservoir (defined by RNA/DNA ratio) is associated with frequency of activated
CD4+ T cells in rectal tissues
Hunt, Yukl and Wong
2
Effect of raltegravir-containing intensification on HIV burden and T-cell activation in multiple gut sites of HIV-positive adults on suppressive antiretroviral therapy.Yukl, Steven; Shergill, Amandeep; McQuaid, Kenneth; Gianella, Sara; Lampiris, Harry; Hare, C; Pandori, Mark; Sinclair, Elizabeth; Gunthard, Huldrych; Fischer, Marek; Wong, Joseph; Havlir, Diane
AIDS. 24(16):2451-2460, October 23, 2010.DOI: 10.1097/QAD.0b013e32833ef7bb
Fig. 2 . Change in cell-associated unspliced HIV RNA (a, b) and HIV DNA (c) per 106 CD4+ T cells. HIV copy numbers were measured by real-time PCR, normalized for the total cell input into the PCR (by [mu]g RNA or DNA), and then normalized to the percentage of all cells that were CD4+ T cells (by flow cytometry). (b) Shows the HIV RNA values in the ileum for each participant at weeks 0 and 12. In (a) and (c), column heights indicate the average of the changes (week 12-week 0) in HIV copy number per 106 CD4+ T cells, as measured from peripheral blood mononuclear cells or total gut cells (obtained by collagenase digestion of endoscopic biopsies) from each of the four gut sites. Error bars indicate the standard error of measurement (SEM).
Is tissue the issue?
Cervicovaginal Fluid Exposure mean percent of blood plasma
600%
500%
400%
300%
200%
100%
75%
50%
25%
0%
TDF (110%)
3TC (400%)
FTC (375%)
ZDV (235%)
ddI (21%)
ABC (8%)
d4T (5%)
DLV (20%)
NVP (80%)
EFV (0.4%)
N(t)RTIs NNRTI PI Entry Inhibitors
MVC (410%)
IDV (200%)
APV (50%)
RTV (26%)
ATV (18%)
LPV (8%)SQV (ND)
Integrase Inhibitors
AUC GT = AUC BP
RAL (93%)
Dumond,J et al. AIDS 2007
Why can’t we cure HIV with ARV DrugsWhere is the virus and how is it maintained in the
face of “suppressive” therapy?
Residual replication (Sanctuaries; drug penetration)
Persistent HIV expression
Immune dysfunction
Latently infected reservoir
Homeostatic Proliferation
Inflammation
These are not mutually exclusive mechanisms; will multiple approaches be required?
A game of hide and sleep?
“Shock and Kill” ApproachRationale and Goal
Hypothesis– Reactivation of HIV-1 within latent reservoirs in the
presence of HAART will lead to elimination of latent reservoirs through a combination of cytopathic viral and immune mechanisms
Goal– Use small molecule(s) to reactivate latent HIV-1 genomes,
purge the reservoir and elicit a “sustained virologic response” in the absence of continued antiretroviral therapy
Induction/eradication
“Open” HistonesAcetylated Histone tails
Reduced Higher Order StructureAccess to Transcription Factors
Transcription Enabled
“Closed”NucleosomeHypo-Acetylated Histone tails
Stable, Compact ChromatinLess accessible to Transcription Factors
Transcription Repressed
deacetylated
acetylated
HIV lives within chromatinLatency restriction at transcription initiation
Proposed mechanisms to affect latent proviral HIV-1 expression
Adapted from Richman et al, 2009
Me
MTInhibitor
MT
MeMT
HIV LatencyCell Culture Models
Integrated LTR-reporter constructs– Advantages: amenable to screening– Disadvantages: highly reductionist
Chronically infected, inducible cell lines– Advantages: complete integrated HIV genome– Disadvantages: clonal, a single integration site
Retroviral vectors – Advantages: Mixed population– Disadvantages: heterochromatin; mixed population
Ex-vivo infected primary resting CD4+ T cells Resting CD4+ T cells from HIV+ aviremic patients
throughput
biological relevance
Research & Discovery Process
FDA Review 1
5,000 – 10,000 Compounds
250 Compounds
5 Compounds
Drug Discovery
ClinicalTrials
Post-Marketing
Preclinical
2
Years
Phase IIIn=1000-5000
Phase IIn=100-500
Phase In=20-100
1DiMasi JA, Hansen RW, Grabowski HG Journal of Health Economics 22 (2003): 151-185
6
1.5
5
Incr
easi
ng b
iolo
gica
l com
plex
ity
Screening Millions of Compounds
Merck High Thoughput Screen Assay for Activators of Latent HIV-1 Gene Expression
24 hours
Add Compounds
Hela P4/R5 cells
24 hours
b-Galactosidase Assay
E.coli lacZHIV LTR polyA
b-galactosidaseUninfected cell
E.coli lacZHIV LTR polyA
b- galactosidase
Uninfected cell + compound
~ 1.5 million compounds (MRL Library)
~ Confirmed 104 compounds (not known HDACIs)
~ 92 compounds that did not activate T-cell
~ 83 compounds with potential novel mechanism
LTR-bGal screen
NFAT Jurkat cell assay
HDAC activity assay (novel HDACis)
ToxicityChemical attractivenessFurther chacterization eg ACH-2, J1.1, primary cells, ex vivo
Non-mechanism based screening can identify novel HIV-1 activators
Characterizing known vs novel activators
^ TW Chun; D Margolis; * Planelles et al, 2008; Yang et al, 2010; Tyagi et al, 2010; In-house Merck data** Archin et al, 2009; Kutsch et al, 2002; Reuse et al, 2009; Williams et al, 2004; Burnett et al, 2010 # In-house Merck data
+/-
Are these meaningful differences or a reflection of the spectrum of relevant biology?
Patient cells Ex Vivo Jurkat line Hela Toxicity
HDACi VPA
HDACiSAHA
pTEFbHBMA
NFkBProstratin
NFkBTNF
Novel ????
Induction and eradication
Will induction lead to eradication?
Following removal of induction stimuli, cells can return to resting state in vitro
The inability to eradicate HIV-1 infection in the face of suppressive ARV therapy is a consequence a dynamic, latently infected reservoir and an anergic immune response.
Induction and eradication
Will induction lead to eradication?
Following removal of induction stimuli, cells can return to resting state in vitro
The inability to eradicate HIV-1 infection in the face of suppressive ARV therapy is a consequence a dynamic, latently infected reservoir, persistent viremia and an anergic immune response.
Eradication will require multiple approaches in combination
Can you “reset” the immune system without therapy intensification and shutting off persistent antigen production?
InflammationActivationProliferation
Latent reservoir Residual Replication
1) Inductioneg HDACis
2) Immune modulation/eradicationeg Thx vaccine, anti-PD1
3) Therapy intensification?eg, replication in reservoirs (gut, brain?), persistent antigen production
Other approaches?
Potential Modalities and Timelines
Now– Induction therapy: SAHA– Negative Regulators: anti-PD1– Immune modulators: IFN, others– Therapeutic vaccination
Future– Combination induction therapies– Antibodies to other negative regulators– Other approaches?
What do we measure and how do we claim success?
How do we test this hypothesis?From the test tube to humans
In vitro tools Compound or Target identification
Cell-based assays, siRNAs
Compounds/drug leads (One or more MOA?)
Animal modelsPD markers; Efficacy
Human studiesBiomarkers/clinical surrogates
HIV-1 Latency Pre-clinical In Vivo Models
Animal models are critical for understanding viral persistence and testing novel concepts– Can model HAART in HIV-infected humans (eg, RTIs and InSTIs)– Time of infection & HAART initiation can be standardized.– It is possible to evaluate reservoirs in tissues eg, GALT & CNS– Viral rebound as an critical endpoint can be monitored.
– Rodent and Macaque Models
Approaches that delay or decrease viral rebound can provide information for the design of novel and/or combination clinical trials and help validate surrogate endpoints.
Is it the same in all patients?
Time from infection (acute vs chronic)– Initiation of therapy and nadir CD4
Route of infectionAgeGenetic factors, including
– Race– Ethnicity– Gender
ARV regimenOther, eg., co-infection with HCV, HCMV etc.
%T
CM c
ells
am
ong
HIV
+ c
ells
= 0.66p = 0.004
%T
TM
+E
M c
ells
am
ong
HIV
+ c
ells
= -0.64p = 0.006
CD4 count (cells/µl) CD4 count (cells/µl)200 700 1200
0
20
40
60
80
100
200 700 12000
20
40
60
80
100
TCM contribution TTM contribution
The HIV Reservoir Varies with CD4 Count
Courtesy of N. Chomont
Summary and Outstanding Issues
Multiple and perhaps “inter-dependent” processes contribute to the inability to eradicate HIV with ARV therapy– Will any one approach be sufficient for eradication? – Will the same combination of interventions work for all patients?
Various interventions which can address at least some of these issues are being explored including small molecules which may activate latent viral gene expression– Activators can manifest differential activity in different cell based assays; do these
differences reflect a spectrum of biologically relevant mechanisms?– HDACIs appear to be among the most “robust”, may provide an anchor for
combinations?– Will activation therapy be sufficient without modulation of the immune response?– Can the immune response be modulated without blocking persistent viremia?
Evaluating approaches individually and in combination in well validated animal models will be critical to understand many of these issues– What model or models will most accurately reflect HIV-1 persistence
(reservoirs/sanctuaries depend on virus, species, immune response, choice of ART)? – What data is required to justify clinical evaluation?– What surrogates can be used to provide an early signal of efficacy and would be
sufficiently robust to trigger therapy interruption?