Previous Article | Next Article 
Antimicrobial Agents and Chemotherapy, April 2000, p. 1051-1058, Vol. 44, No. 4
0066-4804/00/$04.00+0
Copyright © 2000, American Society for Microbiology. All rights reserved.
The Triple Combination
Indinavir-Zidovudine-Lamivudine Is Highly Synergistic
Stuart
Snyder,1
D. Z.
D'Argenio,2
Owen
Weislow,1
John A.
Bilello,1,3 and
G. L.
Drusano3,*
SRA Life Sciences, Rockville
Maryland1; Albany Medical College,
Albany, New York3; and University of
Southern California, Los Angeles, California2
Received 28 January 1999/Returned for modification 21 October
1999/Accepted 15 January 2000
 |
ABSTRACT |
Administration of the combination of
indinavir-zidovudine-lamivudine has been demonstrated to cause a large
fraction of treated patients to have a decline in human
immunodeficiency virus type 1 (HIV-1) copy number to below the
detectability of sensitive assays. A recent investigation (G. L. Drusano, J. A. Bilello, D. S. Stein, M. Nessly, A. Meibohm,
E. A. Emini, P. Deutsch, J. Condra, J. Chodakewitz, and
D. J. Holder, J. Infect. Dis. 178:360-367, 1998)
demonstrated that the durability of the antiviral effect was affected
by combination chemotherapy. Zidovudine-lamivudine-indinavir differed
significantly from the combination of zidovudine plus indinavir. We
hypothesized that the addition of lamivudine might alter the regimen,
producing a synergistic anti-HIV effect. In vitro analysis of drug
interaction demonstrated that zidovudine-indinavir interacted
additively. The addition of lamivudine in concentrations which
suppressed viral replication by 20% or less by itself demonstrated marked increases in the synergy volume, increasing the synergy volume
20-fold with the addition of 320 nM lamivudine (which does not
suppress HIV by itself) and 40-fold with the addition of 1,000 nM
lamivudine (20% viral inhibition as a single agent). A fully parametric analysis with a newly developed model for three-drug interaction confirmed and extended these observations. The interaction term (
IND,AZT,3TC) for all three drugs showed the
greatest degree of synergy. This marked synergistic interaction among
the three agents may explain some of the clinical results which
differentiate this regimen from the double-drug regimen of zidovudine
plus indinavir.
 |
INTRODUCTION |
The course of human immunodeficiency
virus (HIV) disease changed dramatically with the introduction of the
HIV type 1 (HIV-1) aspartyl protease inhibitors. Prior to their advent,
antiretroviral chemotherapy frequently produced changes in HIV copy
number on the order of 0.5 to 1.0 log10 units
(7). With the use of the inhibitors, changes of 1.5 to 2.5 log10 units became attainable. Unfortunately, although
potent, use of the HIV protease inhibitors as single agents rapidly
resulted in the emergence of clones of virus resistant to the drug,
causing failure of therapy. Work by Drusano et al. (2)
demonstrated that the length of time until the protease inhibitors lost
their retroviral suppressive effect, when used as single agents, was a
function of the depth to which the HIV copy number could be driven by
monotherapy. Patients whose copy numbers remained above 500/ml had a
76% hazard of emergence of resistance over the first 24 weeks of
therapy. For patients whose copy numbers had declined below assay
detectability, this hazard was 16%.
In a further analysis, these authors examined the impact of combination
chemotherapy on the hazard of emergence of resistance. Surprisingly,
after correcting for the change in hazard of resistance induced by the
reduction in copy number, the specific combination regimen played a
significant role in further explaining the duration of the anti-HIV
effect. Indinavir was combined (in three separate studies) with
zidovudine, zidovudine plus didanosine, and zidovudine plus
lamivudine. In the final analysis, only the regimen of
indinavir-zidovudine-lamivudine significantly altered the hazard of
emergence of resistance relative to indinavir monotherapy after the
change in HIV copy number was factored into the evaluation.
These results raise a number of questions about the relative
effectiveness of different combination regimens. Clearly,
zidovudine-didanosine-indinavir might be expected to have
problems with compliance because of the need to separate the indinavir
administration from that of didanosine, because of the buffer in
didanosine. The question of why indinavir-zidovudine-lamivudine
(IND-AZT-3TC) was a superior regimen relative to indinavir-zidovudine
was the impetus for this in vitro investigation. One hypothesis we
decided to investigate was that IND-AZT-3TC was significantly more
synergistic than IND-AZT.
 |
MATERIALS AND METHODS |
The method of Weislow et al. (8) was the starting
point for the assay used and was modified for three drug combinational analysis as described below.
Cells and virus.
CEM-SS cells (a generous gift from Peter
Nara [5]) are routinely used as targets for HIV-1
infection. Target cells were maintained in exponential growth in RPMI
1640 medium without phenol red and with 5% fetal calf serum, 2 mM
glutamine, and 1% penicillin-streptomycin by appropriate subculture
and were split 1:4 the day before initiating experiments. On the day of
the experiments, cells were counted and resuspended in fresh medium at
a density of 125,000 per ml.
HIV-1rf (obtained from the National Institute of Allergy
and Infectious Diseases [NIAID] AIDS Reagent Repository Program) was
characterized prior to use in combination experiments on the basis of
killing; i.e., before initiation of any combination experiments, a
dilution of the particular virus preparation used was identified which
resulted in 90 to 95% killing of target cells. On the day of the
experiment, frozen virus stock was thawed and diluted as appropriate
immediately prior to infection.
Anti-HIV drugs.
3TC, AZT, and IND were obtained from the
NIAID or National Cancer Institute (NCI) Drug Repository for use in
these studies. Stock solutions of each were made using dimethyl
sulfoxide (DMSO) and were stored at
20°C; AZT and IND stocks were
made at a concentration of 5 mM, and 3TC stock was made at a
concentration of 50 mM. On the day of the experiment, stock solutions
of drugs were diluted in media, using 10-fold serial dilutions, to five
times the high test concentrations. These working solutions of drugs
were then serially diluted using 0.5 log10 dilutions in
media. AZT and IND high test concentrations were 107 M,
whereas the 3TC high test concentration was 106 M; six
dilutions were made of AZT and 3TC and seven of indinavir.
Assay.
The plates were set up in the following manner.
Sixteen microliters of medium or diluted drug was added to wells of
384-well microtiter plates. On each plate, AZT was added as the
vertical drug and IND was added as the horizontal drug. We added 3TC at a single concentration per plate; seven plates per experiment were set
up, each using a different concentration of 3TC or medium only. After
all of the media, phosphate-buffered saline (PBS), or diluted drug was
added, 16 µl of cell suspension (2,000 cells per well) was added to
each well. Finally, diluted virus was added to appropriate wells of
each plate. Cultures were incubated at 37°C, 5% CO2, and
95% humidity for 6 days and then were stained as described below.
XTT tetrazolium staining.
Six days postinfection, cell
viability was assessed using
2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT)-phenazine methosulfate (PMS) staining. XTT (final concentration, 1 mg/ml) was dissolved in warm medium (without fetal bovine serum [FBS]), and a small volume of a working solution of PMS dissolved in
PBS was added for a final PMS concentration of 20 µM; 20 µl of the
XTT-PMS solution was then immediately added to all wells of the test
plates and reincubated for 4 to 5 h at 37°C.
Data acquisition and analysis.
After 4 to 5 h of
incubation, plates were read on a Tecan Spectra plate reader using a
450-nm absorbance filter and a 650-nm reference filter. Absorbance
values were corrected for nonspecific XTT reduction using the average
of medium-only wells. After correction, absorbance values were pasted
into the MacSynergyII spreadsheet, which had been modified to
accommodate replicates of four on one plate.
The data were analyzed with a modified version of Prichard and
Shipman's MacSynergy II software using the Independent Effects
method
(
6); on the plates, IND was the horizontal drug, AZT
was the
vertical drug, and 3TC was the third, overlay
drug.
This program examines drug interaction using either Bliss Independence
or Loewe Additivity as the null reference model for
additivity.
Confidence bounds are set up about the data from the
data replication.
If the confidence bounds (95%, 99%, etc.) do
not overlap the
theoretical additive surface, then the interaction
is significantly
different from additive, either synergistic (above
the additive
surface) or antagonistic (below the additive surface).
Areas of the
interaction surface can be synergistic while others
are additive or
antagonistic. The program also provides the ability
to quantify the
volume of areas which differ significantly from
additivity. Finally, by
mathematically subtracting the theoretical
additive surface, the
synergy or antagonism areas can be displayed
graphically.
Synergy modeling as a function of 3TC concentration.
Volumes
of synergy at the 95% confidence level (output from the MacSynergyII
program) served as the dependent variable in a sigmoid Emax effect
analysis, where 3TC concentrations served as the independent variable.
The model was fitted to the data by using the ADAPT II software of
D'Argenio and Schumitzky (1).
Fully parametric analysis of drug interaction.
Because it is
impossible to truly understand the interaction of drugs and to use this
understanding for experimental and clinical trial design purposes
without examining all three drugs simultaneously, we developed a fully
parametric model for all drugs using Loewe Additivity as a definition
of additive interaction (3). The derivation followed the
intellectual process of Greco et al. in the derivation of their
two-drug interaction equation. Interested readers should refer to this
paper (4) for the derivation approach. The full model is as
follows:
where IC
50 is the 50% inhibitory concentration. The
model was fitted to the data employing the ADAPT II software of
D'Argenio
and Schumitzky (
1).
 |
RESULTS |
Each plate was independently analyzed, and the initial results are
presented in Fig. 1 through 5. In Fig. 1
and 2, the full-effect surface and the
synergy surface for 3TC at 0 and at 1.0 × 10
6
M, respectively, are presented. Figure
3 displays the synergy surfaces for other
concentrations of 3TC. The data were reformatted to allow analysis
of each drug as the third, independent drug. The results of the
subsequent two analyses are presented in Fig. 4 (indinavir as the third drug) and
5 (AZT as the third drug).

View larger version (59K):
[in this window]
[in a new window]
|
FIG. 1.
Full-effect surface (A) and synergy surface (B) for the
interaction of indinavir and zidovudine in the absence of 3TC.
|
|

View larger version (68K):
[in this window]
[in a new window]
|
FIG. 2.
Full effect surface (A) and synergy surface (B) for the
interaction of indinavir and zidovudine, in the presence of 1.0 × 10 6 M 3TC.
|
|

View larger version (75K):
[in this window]
[in a new window]
|
FIG. 3.
Synergy surfaces for increasing concentrations of 3TC
together with indinavir-AZT. (A) 0 M; (B) 1.0 × 10 7
M; (C) 3.2 × 10 7 M; (D) 1.0 × 10 6 M.
|
|

View larger version (81K):
[in this window]
[in a new window]
|
FIG. 4.
Synergy surfaces for increasing concentrations of
indinavir together with AZT-3TC. (A) 0 M; (B) 1.0 × 10 8 M; (C) 3.2 × 10 8 M; (D) 1.0 × 10 7 M.
|
|

View larger version (78K):
[in this window]
[in a new window]
|
FIG. 5.
Synergy surfaces for increasing concentrations of AZT
together with 3TC-indinavir. (A) 0 M; (B) 1.0 × 10 8
M; (C) 3.2 × 10 8 M; (D) 1.0 × 10 7 M.
|
|
The synergy volumes from Fig. 1 through 3 are displayed as a function
of 3TC concentration in Fig. 6. The
relationship developed was as follows: synergy volume = 44.6 + {[2,243 × (3TC)1.25]/[(3TC)1.25 + 0.5981.25]}, r2 = 0.999, P < 0.001, where 44.6 is the synergy volume at
a 3TC concentration of 0.0 M, 2,243 is the Emax synergy volume, 0.598 µM is the 3TC concentration at which the synergy volume is half maximal, and 1.25 is the slope parameter.

View larger version (16K):
[in this window]
[in a new window]
|
FIG. 6.
A sigmoid Emax effect model relating the synergy volume
seen with AZT-3TC-indinavir to the concentration of 3TC.
|
|
The results from the fully parametric model are displayed in Table
1. Examination of the interaction terms
(the
's) indicates (in concordance with the above analysis) that
indinavir and zidovudine are almost exactly additive in their
interaction. Indinavir and lamivudine are also additive but
barely miss being synergistic on a statistical basis (the 95%
confidence interval barely overlaps 0.0). Zidovudine and lamivudine, as
has been seen previously, are synergistic in their interaction.
However, as is clear only in the fully parametric analysis, the real
power of the regimen comes from the interaction of all three drugs,
which has by far the largest
(8.94). It should also be appreciated
that the lower end of the 95% confidence interval is above the upper
end of the 95% confidence interval for the
zidovudine-lamivudine
, indicating that it is significantly
larger.
 |
DISCUSSION |
The question being investigated here is whether there is
significant synergy among the drugs of the three-drug combination IND-AZT-3TC and to compare this interaction to that seen with the
two-drug combination of IND-AZT.
In examining Fig. 1B, it is clear that, except for a small area of
synergy, the interaction of IND-AZT is best characterized as additive.
While additive interaction is acceptable, one would prefer to have the
drugs interact synergistically. It should be noted that this panel (and
its paired full-interaction surface) was created from data where no
lamivudine was added.
It is difficult to display the resultant activity of three drugs in a
graphical way. Concentrations of each drug vary along a separate axis,
with a fourth axis representing the drug effect. The information exists
fully only in four dimensions. We have chosen to present the
experiments as traditional three-dimensional graphics, with two of the
drugs displayed on the x and y axes, and with the
z axis representing drug effect. The third drug is "invisible" in this sort of treatment, but a full response surface and synergy surface can be generated for each concentration of the
"invisible" drug evaluated in vitro, which allows easy comparison to the base two-drug regimen surfaces.
Further, presenting the data in this way corresponds to the traditional
method of avoiding three-dimensional graphics for two-drug interaction
data by taking isoboles of effect, which display planes cutting through
a three-dimensional response surface parallel to the XY (drug
concentration) plane at different levels of effect. In this instance,
however, we are taking cuts through a four-dimensional surface with
planes through constant concentrations of the "invisible" drug,
resulting in three-dimensional surfaces.
With the addition of lamivudine, one starts to see changes in the
effect and synergy surface, with major changes starting at
approximately 100 nM lamivudine. The synergy volume calculated by
MacSynergyII can be modeled as a function of lamivudine concentration, using a sigmoid Emax model. The fit of the model to the data was excellent (r2 = 0.999 [see Fig.
6]), and it is clear that relatively low, clinically achievable
concentrations of lamivudine produce large changes in synergy volume.
Does this change in synergy volume with the addition of
lamivudine represent true synergy? The answer is provided by the
knowledge that major changes in synergy volume (ca. 20-fold
increase relative to the synergy volume in the absence of
lamivudine) are produced by concentrations of lamivudine (320 nM)
which do not cause any inhibition of the virus, and a further increase
to approximately 40 times the synergy volume without lamivudine is
provided by 1 µM lamivudine, which inhibits the virus by about 20%
(data not shown), indicating true synergy.
Compared to the two-drug interaction surface and synergy surface of
IND-AZT, the addition of even modest, clinically achievable (9) concentrations of lamivudine markedly improves the
effect seen.
The same sort of analysis can be generated by making either zidovudine
or indinavir the "invisible" drug. When looked at in this fashion,
it is clear that the interaction between indinavir and lamivudine (Fig.
5) can best be characterized as mostly additive and the interaction
between zidovudine and lamivudine (Fig. 4) as somewhat more
synergistic. While the synergy surfaces all grow as increasing
concentrations of the "invisible drug" are added, they do not
exactly recapitulate the surfaces shown for IND-AZT with lamivudine as
the third drug (Fig. 1 through 3). This is because we are only
taking slices through the full four-dimensional effect and synergy
surfaces and, by changing the "invisible drug," we are
changing the orientation of the slice and hence see a different three-dimensional representation.
In order to examine the interaction in the most quantitative way
possible, we have also developed a fully parametric model for the
interaction of all three drugs simultaneously. These results (Table 1)
show a pleasing concordance with the graphical approach of the
MacSynergyII analysis. Clearly, the fully parametric method identified
the zidovudine-indinavir interaction as almost entirely additive
(
IND,AZT = 0.00013). As seen in the clinical arena, the zidovudine-lamivudine interaction is statistically significantly synergistic (
AZT,3TC = 0.9692; 95% confidence
interval = 0.9417 to 0.9966), as the 95% confidence interval
about the point estimate does not overlap 0.0. Perhaps of greatest
importance was the fact that the largest degree of synergy was found in
the interaction term for all three drugs. This correlates with and
actually supersedes the analysis displayed in Fig. 6.
We can see by examining Fig. 2A, the full-effect surface for IND-AZT
with 1 µM of lamivudine, that quite large anti-HIV effects can be
maintained in the presence of relatively low concentrations of IND and
AZT, as long as lamivudine is present at this concentration. This may
be the reason for the success of this regimen in preventing the
emergence of resistance. Because of the way in which the analysis of
Drusano and colleagues (2) was performed, the effect of combination therapy was significant, independent of the overall drop in
copy number in the blood. This raises two possibilities to explain the
impact of the synergy seen in this investigation. The first is that the
synergy seen with this combination allowed a drop in HIV copy number in
a body compartment distant from the blood which decreased the
rate of emergence of resistance. One could speculate that a
profound copy number decrease in the lymph node might explain such a
finding. The second possibility is that the synergy allows suppression
of more-resistant subpopulations wherever they may be, in
blood or lymph nodes, preventing such clones from growing up and taking
over the population. These hypotheses cannot be differentiated on the
basis of the data presented here and should lead to further clinical
investigations to answer this question.
Because the second analysis is fully parametric, hypotheses can be
tested quantitatively. For instance, one could simply test the
hypothesis that the dosing interval for indinavir makes a difference
with respect to viral suppression by simulating a steady-state dosing
interval and placing the concentrations for each of the drugs in the
appropriate spot in the fully parametric equation. This would, in
effect, change the concentration-time curves for the three drugs into
an effect-time curve. Such an effect-time curve could be easily
integrated over a steady-state interval to demonstrate the differences
between administration schedules for the protease inhibitor. To achieve
a method for comparing the regimens statistically, a large Monte Carlo
simulation could be performed.
In summary, we have demonstrated significant synergy among
the drugs in the three-drug combination of IND-AZT-3TC, which differs from the mainly additive interaction seen with the combination of
IND-AZT. This finding may help explain the difference in duration of
effect seen with different combinations of agents (all of which included indinavir) (2). Further investigation into the
mechanism by which this may occur is warranted.
 |
ACKNOWLEDGMENT |
This investigation was supported, in part, by NIH grant P41 RR01861.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Division of
Clinical Pharmacology, Departments of Medicine and Pharmacology, Albany Medical College, 47 New Scotland Ave., Albany, NY 12208. Phone: (518)
262-6761. Fax: (518) 262-6330. E-mail: GLDRUSANO{at}AOL.COM.
 |
REFERENCES |
| 1.
|
D'Argenio, D. Z., and A. Schumitzky.
1997.
ADAPT II user's guide: pharmacokinetic/pharmacodynamic systems analysis software.
Biomedical Simulations Resource, Los Angeles, Calif.
|
| 2.
|
Drusano, G. L.,
J. A. Bilello,
D. S. Stein,
M. Nessly,
A. Meibohm,
E. A. Emini,
P. Deutsch,
J. Condra,
J. Chodakewitz, and D. J. Holder.
1998.
Factors influencing the emergence of resistance to indinavir: role of virologic, immunologic, and pharmacologic variables.
J. Infect. Dis.
178:360-367[Medline].
|
| 3.
|
Greco, W. R.,
G. Bravo, and J. C. Parsons.
1995.
The search for synergy: a critical review from a response surface perspective.
Pharmacol. Rev.
47:331-385[Medline].
|
| 4.
|
Greco, W. R.,
H. S. Park, and Y. M. Rustum.
1990.
Application of a new approach for the quantitation of drug synergism to the combination of cis-diaminedichloroplatinum and 1- -D-arabinofuranosylcytosine.
Cancer Res.
50:5318-5327[Abstract/Free Full Text].
|
| 5.
|
Nara, P. L., and P. J. Fischinger.
1989.
Quantitative infectivity assay for HIV-1 and -2.
Nature
332:469-470.
|
| 6.
|
Prichard, M. N., and C. Shipman, Jr.
1990.
A three-dimensional model to analyze drug-drug interactions.
Antivir. Res.
14:181-205[CrossRef][Medline].
|
| 7.
|
Rhone, S. A.,
R. S. Hogg,
B. Yip,
C. Sherlock,
B. Conway,
M. T. Schechter,
M. V. O'Shaughnessy, and J. S. Montaner.
1998.
Do dual nucleoside regimens have a role in an era of plasma viral load-driven antiretroviral therapy?
J. Infect. Dis.
178:662-668[Medline].
|
| 8.
|
Weislow, O. S.,
R. Kiser,
D. L. Fine,
J. Bader,
R. H. Shoemaker, and M. R. Boyd.
1989.
New soluble-formazan assay for HIV-1 cytopathic effects: application to high-flux screening of synthetic and natural products for AIDS-antiviral activity.
J. Natl. Cancer Inst.
81:577-586[Abstract/Free Full Text].
|
| 9.
|
Yuen, G. J.,
D. M. Morris,
P. K. Mydlow,
S. Haidar,
S. T. Hall, and E. K. Hussey.
1995.
Pharmacokinetics, absolute bioavailability, and absorption characteristics of lamivudine.
J. Clin. Pharmacol.
35:1174-1180[Abstract].
|
Antimicrobial Agents and Chemotherapy, April 2000, p. 1051-1058, Vol. 44, No. 4
0066-4804/00/$04.00+0
Copyright © 2000, American Society for Microbiology. All rights reserved.
This article has been cited by other articles:
-
Lim, T.-P., Ledesma, K. R., Chang, K.-T., Hou, J.-G., Kwa, A. L., Nikolaou, M., Quinn, J. P., Prince, R. A., Tam, V. H.
(2008). Quantitative Assessment of Combination Antimicrobial Therapy against Multidrug-Resistant Acinetobacter baumannii. Antimicrob. Agents Chemother.
52: 2898-2904
[Abstract]
[Full Text]
-
Seigneres, B., Martin, P., Werle, B., Schorr, O., Jamard, C., Rimsky, L., Trepo, C., Zoulim, F.
(2003). Effects of Pyrimidine and Purine Analog Combinations in the Duck Hepatitis B Virus Infection Model. Antimicrob. Agents Chemother.
47: 1842-1852
[Abstract]
[Full Text]
-
Pereira, C. F., Paridaen, J. T. M. L., van de Bovenkamp, M., Middel, J., Verhoef, J., Nottet, H. S. L. M.
(2003). APHS can act synergically with clinically available HIV-1 reverse transcriptase and protease inhibitors and is active against several drug-resistant HIV-1 strains in vitro. J Antimicrob Chemother
51: 1181-1189
[Abstract]
[Full Text]