Inhibitory Quotient Research Articles

High-Dose Lopinavir/Ritonavir in Highly Treatment-Experienced HIV-1 Patients: Efficacy, Safety, and Predictors of Response

Objective: To investigate the efficacy and safety of high-dose lopinavir/ritonavir (LPV/r) therapy in multiple protease inhibitor, non-nucleoside reverse transcriptase inhibitor (NNRTI)-experienced subjects. Method: Thirty-six HIV-1-infected subjects were randomized to LPV/r 400/300 mg or 667/167 mg bid in a 48-week, open-label study. Subjects also received investigator-selected nucleoside reverse transcriptase inhibitors (NRTIs). Primary outcomes were the proportion of subjects with HIV-1 RNA levels <50 copies/mL at week 24 and time until loss of virologic response through week 48. Results: Six of 17 (35%) and 10 of 19 (53%) subjects in the 400/300 and 667/167 groups, respectively, completed 48 weeks of treatment. Median durations of follow-up in discontinued subjects and all subjects were 15 weeks and 32 weeks, respectively. Forty-four percent of subjects achieved HIV-1 RNA <50 copies/mL at least once; 18% (400/300 mg) and 21% (667/167 mg) of subjects achieved HIV-1 RNA <50 copies/mL at week 24 (intent-to-treat analysis). Corresponding results at week 48 were 18% (400/300 mg) and 26% (667/167 mg). No statistically significant differences in adverse event incidence occurred between treatment groups, except for a higher vomiting rate in the 400/300 mg dose group. Predictors of response included baseline LPV inhibitory quotient and number of active NRTIs. Conclusion: Higher doses of LPV/r may provide substantial antiviral activity in multiple class-experienced subjects.

Therapeutic drug monitoring of the HIV protease inhibitor atazanavir in clinical practice

Therapeutic drug monitoring (TDM) is being applied for a number of antiretroviral agents. Little is known about the use of TDM for atazanavir. This is a retrospective cohort analysis on the use of TDM of atazanavir at three clinical sites in The Netherlands. Patients were divided into three groups: (i) all patients with evaluable data of plasma atazanavir concentrations and its relationship with hyperbilirubinaemia; (ii) patients who started atazanavir without documented evidence of protease inhibitor (PI) mutations; (iii) patients who started atazanavir with documented evidence of PI mutations. The genotypic inhibitory quotient (GIQ) was calculated by dividing the mean atazanavir plasma trough concentration by the number of PI mutations. A total of 108 patients were included; 70 (65.8%) were using atazanavir/ritonavir (300/100 mg once daily). No significant relationship was observed between atazanavir plasma trough concentration and antiviral response in patients starting atazanavir without PI mutations (group 2; n = 82). In contrast, a significant relationship was observed between atazanavir GIQ and treatment response in patients starting atazanavir while having PI mutations (group 3; n = 26). The cut-off value for GIQ most predictive of virological failure was 0.23 mg/L/mutation: patients (n = 8) with a GIQ equal to or below this value had 50% virological failure whereas patients (n = 18) with a GIQ above 0.23 mg/L/mutation had only 11% virological failure (chi(2): P = 0.030). Atazanavir plasma trough concentrations were significantly related with the occurrence of increased total bilirubin concentrations. TDM of atazanavir might be beneficial for patients with documented PI resistance or patients with hyperbilirubinaemia.

Preliminary safety and efficacy data of brecanavir, a novel HIV-1 protease inhibitor: 24 week data from study HPR10006

Brecanavir, a novel protease inhibitor (PI), has sub-nM in vitro antiviral activity against multi-PI-resistant HIV-1 and in vitro is >100-fold more potent than previously marketed PIs and approx. 10-fold more potent than the recently marketed PI, darunavir. HPR10006 is an open label, single-arm, descriptive 48 week study, with 8 and 24 week interim analyses. Thirty-one HIV-1-infected patients were enrolled and received brecanavir/ritonavir 300 mg/100 mg twice daily, with two nucleoside reverse transcriptase inhibitors, based on history and genotype. At baseline, 25/31 had PI-sensitive virus and 6/31 had PI-resistant virus (median of two primary PI and five secondary PI mutations). Median baseline HIV-1 RNA was 5.0 and 4.2 log(10) copies/mL, respectively. Four patients discontinued prior to Week 24. At Week 24, 77% (24/31) had HIV-1 RNA <50 copies/mL regardless of screening genotype, including 5/6 patients with PI-resistant virus (6/6 had HIV-1 RNA <400 copies/mL). Brecanavir/ritonavir was well tolerated with no serious adverse events or clinically concerning changes in laboratory parameters. Of 31 patients, 10 (32%) experienced drug-related Grade 2-4 adverse events [most frequent events were fatigue (13%), dyspepsia (10%) and nausea (10%)]. Baseline isolate brecanavir IC(50) values for all patients ranged from 0.1 to 0.2 nM. Median plasma trough concentration at Week 4 was 150 ng/mL. Correcting the IC(50) (0.2 nM) value for protein binding (6-fold increase in vitro with 50% human serum) gives a corrected inhibitory quotient of 180. Brecanavir/ritonavir was well tolerated and showed potent antiviral activity in HIV-1-infected patients harbouring both PI-sensitive and PI-resistant virus, following 24 weeks of dosing.

Combining resistance and pharmacology for optimum patient care

Therapeutic drug monitoring is now incorporated into the treatment guidelines of many countries. In this review, we describe the use and limitations of therapeutic drug monitoring, and how added benefit might accrue from integrating therapeutic drug monitoring with resistance testing in the form of inhibitory quotients. Although the unselected use of therapeutic drug monitoring in current (ritonavir-boosted) protease inhibitor or nonnucleoside reverse transcriptase inhibitor-containing regimens has yet to be established, therapeutic drug monitoring is likely to be useful in selected groups of patients, such as children, pregnant women, patients with malabsorption, or in specific clinical scenarios, such as liver impairment, drug interactions, suspected toxicity, assessing adherence or treatment failure. One problem with therapeutic drug monitoring is that efficacy targets relate mainly to drug-sensitive virus. Inhibitory quotients may be a better predictor of response in treatment-experienced patients. In this review, we discuss the different derivations of inhibitory quotients. Inhibitory quotients have been shown to be predictive of virological response in heavily pretreated patients receiving lopinavir, amprenavir, saquinavir, atazanavir and tipranavir. Lack of standardization and consensus on which inhibitory quotient to use are major factors which limit their introduction into clinical practice.

Inhibitory quotient as a prognostic factor of response to a salvage antiretroviral therapy containing ritonavir‐boosted saquinavir. The CIVSA Study*

The addition of a low dose of ritonavir to protease inhibitors (PIs) has become a widespread strategy to improve PI pharmacokinetics. As resistance is a major barrier to long-term suppression, in salvage therapy genotype and/or phenotype scoring is currently used to predict the response. We evaluated the relationship between the saquinavir (SQV) inhibitory quotient (IQ) (virtual and genotypic) and virological response. Eligible patients were on a PI-containing highly active antiretroviral therapy (HAART) regimen excluding SQV and had a viral load >5000 HIV-1 RNA copies/mL. The PI was switched to SQV/ritonavir (RTV) 1000/100 mg twice a day (bid) and the same two backbone nucleoside reverse transcriptase inhibitors (NRTIs) were maintained at least until week 4, when the resistance test results became available. Genotype and virtual phenotype were determined at baseline, while the SQV trough plasma concentration was determined at week 4. Fifty-three patients were included in the study. Mean baseline viral load and CD4 count were 137,693 copies/mL and 263 cells/microL, respectively, the mean number of previous PIs was 2.3 and the mean number of protease gene mutations (PGMs) was 4.1. Using an on-treatment analysis, at week 16 the mean increase in CD4 count was 70.9 cells/microL, viral load was <200 copies/mL in 17 out of 37 patients (45.9%), and 30 out of 45 patients (66.7%) were considered virological responders (VRs) (viral load <200 copies/mL or viral load declined > or =1 log(10) at week 16). Median virtual phenotype was 1.3 (0.6-6.9). Baseline differences were detected between VR and non-VR populations: the mean numbers of PGMs were 3.2 and 5.8 (P<0.05), the mean numbers of SQV-associated mutations were 2 and 3.8 (P<0.05), and the mean CD4 counts were 365.9 and 184.3 cells/microL (P<0.05), respectively. Mean SQV trough concentrations at week 4 were 1.1 and 1.0 microg/mL (not significant), and mean virtual IQs were 0.7 and 0.1 (P<0.01), respectively. Multivariate analysis showed that baseline PGMs >5 or SQV-associated mutations>5, virtual phenotype, baseline viral load >50,000 copies/mL, and virtual IQ <0.5, but not genotypic IQ, were the variables independently associated with non-VR. In heavily pretreated patients, the use of SQV virtual IQ or alternatively virtual phenotype, as well as PGMs, is a useful tool for the prediction of virological response.

Interpretation of Genotype and Pharmacokinetics for Resistance to Fosamprenavir-Ritonavir-Based Regimens in Antiretroviral-Experienced Patients

In this study, named the Zephir study (Telzir-pharmacokinetics), 121 antiretroviral-experienced human immunodeficiency virus (HIV) patients failing on highly active antiretroviral therapy (HAART) were included in a prospective cohort and received a fosamprenavir-ritonavir (700 mg/100 mg twice a day)-based regimen. The impact of baseline HIV type 1 (HIV-1) mutations, pharmacokinetic (PK) parameters, and genotype inhibitory quotient (GIQ) on the virological response at week 12 (W12) was assessed. HIV reverse transcriptase and protease were sequenced at W0. The response at W12 was defined as<2.3 log10 HIV-1 RNA copies/ml or a virus load decrease of>or=1 log10 copies/ml. W4 amprenavir PK were determined by high-performance liquid chromatography. Patients had a median of nine previous treatments over 8 years. Median W0 values were as follows: 295 CD4+/microl, 4.4 log10 HIV-1 RNA copies/ml, and 6 protease- and 5 nucleotide reverse transcription inhibitor-related mutations. Respective values for minimum concentration of drug in serum (Cmin) and area under the concentration-time curve (AUC) from 0 to 24 h were 1,400 ng/ml and 35 mg.h/ml. At W12, 52% of the patients were successes, with a median decrease of -0.7 log10 HIV-1 RNA copies/ml. The Zephir mutation score included 12 IAS protease mutations associated with poorer virological response: L10I/F/R/V, L33F, M36I, M46I/L, I54L/M/T/V, I62V, L63P, A71I/L/V/T, G73A/C/F/T, V82A/F/S/T, I84V, L90M, and polymorphism mutations I13V, L19I, K55R, and L89M. Comparing<4 versus>or=4 mutations, HIV-1 RNA decreases were -2.3 log10 copies/ml versus -0.1 log10 copies/ml (P<10(-4)) with 93% versus 19% successes (P<10(-4)), respectively. This score predicted W12 failure with 94% sensitivity, versus 31% for the ANRS 2005 algorithm. Cmin (<1,600 ng/ml), AUC (<40 mg.h/ml), and GIQ (<300) values were associated with failure (all P values were <10(-4)). The need to test genotype-based algorithms using different patient databases before their implementation in clinical practice is highlighted. Specific mutations, PK and GIQ, provide relevant information for monitoring fosamprenavir-ritonavir-based HAART.

Diffusion intra-amygdalienne et pharmacodynamies comparées de la roxithromycine, de la clarithromycine et de la 14-OH hydroxyclarithromycine

The purpose of the present work was to evaluate the intra-tonsillar concentrations of roxithromycin (ROX), clarithromycin (CLR) and 14-OH-CLR at steady state in children, and then to compare them with their respective MICs against group A Streptococci. It was a monocenter, pharmacokinetic study in children hospitalized for a tonsillectomy and receiving in a randomized manner either roxithromycin 3 mg/kg bid, or clarithromycin 7.5 mg/kg bid, for three days. The last dose in both groups was randomly administered either 2, or 4 or 12 hours before the bilateral tonsillectomy. The tissue sample was concomitent to a blood sample. Blood and tissue concentrations of macrolides were performed by HPLC. Results Mean blood (mg/l) and tissue (mg/kg) concentrations are as follows (mean+/-SD) : serum concentrations (mg/L) (mg/kg) (mean, SD), as decreasing from 2 d to 12 th hour, are respectively 7.51±4.28 to 2.34±0.67 for ROX, of 1.83±1.15 to 0.62±0.53 for CLR and of 0.81±0.35 à 0.51±0.16 for 14-OH-CLR. For tonsils decreasing concentrations at the same sampling times were 0.81±0.48 to 0.29±0.14 for ROX, of 1.81±0.48 to 0.78±0.14 for CLR, of 0.78±0.49 to 0.51±0.14 for 14-OH-CLR. The areas under the serum concentrations curves (AUC) for ROX and CLR+ 14-OH-CLR (CLRtot) were respectively 53.8 and 22.5 μg.h.ml-1. The corresponding values for the tonsils were respectively 7.0 and 26.15. The rate of penetration as determined by the AUC serum/AUC tissue ratios are 13% and 116.2% for ROX and CLR tot respectively. As a consequence in terms of antibacterial activity, and as far as CLR and 14-OH-CLR MICs are regularly four times lower than those of ROX, and considering that intra-tonsillar concentrations of CLRtot vs ROX were 3.6 (2 h), 2.3 (4 h) and 4.4 (12 h) times higher than those of ROX, the resulting inhibitory quotients are up to 13-18 times higher for CLR, without taking into account the synergy that is likely to occur between CLR and 14-OH-CLR. Conclusion The better antibacterial activity and tonsillar pharmacokinetics of CLR and its active metabolite 14-OH-CLR confer to these components pharmacodynamic properties which are more in adequation with the pre-requisites correlating with a suitable bacterio-clinical efficacy when compared with ROX.

The use of drug resistance algorithms and genotypic inhibitory quotient in prediction of lopinavir–ritonavir treatment response in human immunodeficiency virus type 1 protease inhibitor-experienced patients

Background Different approaches using genotypic, pharmacokinetic parameters or combination of both have been recently developed to monitor antiretroviral treatment in HIV-1-infected individuals. Their uses in clinical practice may improve the benefit of protease inhibitor-based salvage therapy while reducing treatment toxicity and emergence of viral resistance. Objectives To assess the prediction of genotypic inhibitory quotient (GIQ) using different genotypic drug resistance interpretation's algorithms and lopinavir plasma concentration in PI-experienced patients treated by lopinavir/ritonavir (LPV/r). Genotypic susceptibility score (GSS) was also evaluated. Study design Forty-seven HIV-1 PI-experienced, but LPV naïve patients were included in a retrospective cohort study. Plasma HIV-1 viral load (VL), CD4 cell count and LPV plasma concentrations were assessed at weeks (W) 12 and 24. Interpretation of baseline resistance genotype was achieved according to four different algorithms and GSS calculated using two expert systems. GIQ was defined as the ratio of LPV concentration to the number of LPV resistance mutations at day 0 (D0) and patients classified by units of GIQ. The end point of the study was the virological response expressed in HIV VL median decrease from D0 to W24. Results The overall median VL decrease from D0 to W24 was −2.42 log 10 copies/mL and 60% of patients had VL below 400 copies/mL. The LPV mutation score was predictive of response for all algorithms whereas plasma concentrations of LPV were not. Mean VL decrease was greater for higher GIQ classes and difference reached statistical significance at W24. When considering virological response at W24, GSS calculated with ANRS and Stanford system were good predictor scores as areas under the receiver operating characteristics (ROC) curves were 0.76 for both. Conclusion GIQ was found to be a useful drug-monitoring tool which could be helpful in targeting LPV concentrations in order to achieve long-term undetectable viral load, particularly in genotypic resistant patients.

Therapeutic Drug Monitoring: A Tool to Individualize Highly Active Antiretroviral Therapy in HIV Infected Patients

In HIV-infection, therapeutic drug monitoring (TDM) has been proposed to optimize highly active antiretroviral therapy (HAART) response. Pharmacokinetics of protease inhibitors (PI) and non-nucleoside reverse transcriptase inhibitors (NNRTI) efavirenz and nevirapine have been proved suitable for monitoring their plasma drug levels. In contrast, nucleoside reverse transcriptase inhibitors (NRTI) contain lack of a certain correlation between plasma levels and drug efficacy. Currently, TDM under HAART is limited by some uncertainty which pharmacokinetic predictor to prefer and on which drug concentration or range to rely on. In a therapy naive patient trial (ATHENA) on indinavir or nelfinavir based drug regimens, the study arm with use of TDM resulted in prevention of virological failure or treatment discontinuation due to drug toxicity. Current data ascribed increasing importance to TDM in ritonavir boosted PI combinations especially for lopinavir, atazanavir and fosamprenavir. Besides, further applications are proposed in selected patients groups (i.e. children, pregnancy, renal or hepatic dysfunction, weight loss) to confirm adequate drug concentrations and manage drug-drug- interactions. PI double-boosting in salvage regimens in patients with multiple NRTI associated mutations should also require TDM for handling dose adjustments, moreover, treatment experienced patients might benefit from TDM in combination with viral resistance testing. Limitations to the application of TDM are considered as non standardized procedures or techniques permitted to correlate pharmacological and virological data therefore, an approach towards standardization is needed. So far the inhibitory quotient (IQ) (necessitating phenotypical resistance testing) or the genotypic inhibitory quotient (GIQ) (referring to the number of viral mutations using a genotypic resistance test), could become increasingly important in this context. In assessing adherence, TDM allows to confirm the correct medication intake, but only the last few doses taken by a patient will be reflected. Without TDM, numerous interactions by co-administered drugs (antibiotics, antacid drugs, hypnotics, herbals, life-style drugs) turn out to possibly lead to obscure interpretations and individual medical care remains elusive. Currently, the interpretation of PI and NNRTI drug levels is based on increasing experience using TDM. Even though TDM in HAART is not the gold standard of care, yet, it provides security in guiding patients on an individual therapy and might be linked with pharmacogenomics in resource-rich countries. Keywords: Therapeutic Drug Monitoring, HAART, PI, NNRTI, HIV

An Update on Therapeutic Drug Monitoring for Antiretroviral Drugs

There is an increasing uptake of TDM of antiretroviral drugs, particularly in Europe. There is consensus that current antiretroviral drugs meet most of the criteria of drugs that can be considered as candidates for a TDM strategy. This review examines the pharmacokinetic-pharmacodynamic relationship for protease inibitors and non nucleoside reverse transcriptase inhibitor, give an overview of the published randomised clinical trials and then summarises the scenarios for use of TDM. Finally the development of the inhibitory quotient (IQ) concept is discussed.

The genotypic inhibitory quotient and the (cumulative) number of mutations predict the response to lopinavir therapy

For 95 protease inhibitor-experienced HIV-1-infected patients, the genotypic inhibitory quotient (GIQ; trough level/number of mutations) was calculated for lopinavir. Three different sets of mutations showed equal predictive value. However, the use of cumulative numbers of mutations for calculation of the GIQ showed significantly better association with the virological response. Furthermore, the predictive value of the GIQ was no different from that of the number of mutations alone.

Different Methods to Calculate the Inhibitory Qoutient of Boosted Single Protease Inhibitors and Their Association With Virological Response

Different Methods to Calculate the Inhibitory Qoutient of Boosted Single Protease Inhibitors and Their Association With Virological Response

Ability of different lopinavir genotypic inhibitory quotients to predict 48-week virological response in highly treatment-experienced HIV-infected patients receiving lopinavir/ritonavir

The genotypic inhibitory quotient (GIQ) is the ratio between drug concentration and the number of resistance mutations. However, as different resistance scores can be calculated for the same protease inhibitor, the ability of a GIQ to predict the virological outcome may vary depending on the resistance score used as the denominator. Forty-four highly treatment-experienced HIV-infected patients failing on their current regimen were treated with a lopinavir/ritonavir-containing combination for at least 48 weeks. Three GIQs were calculated for each patient: the denominator of the first (GIQ-A) was the lopinavir/ritonavir score calculated using the mutations listed by IAS-USA as being related to lopinavir/ritonavir resistance; the denominator of the second (GIQ-B) was the total number of mutations related to resistance to any protease inhibitor as reported by IAS-USA; and the denominator of the third (GIQ-C) was the lopinavir/ritonavir score proposed by Parkin et al. The median (IQR) of the GIQ-A, B, and C was 4.69 (3.83-9.76), 0.97 (0.74-1.62), and 1.02 (0.68-2.52), respectively. At week 48, the median decrease in HIV-RNA was 1.09 (0.32-2.34) log(10) copies/ml (P < 0.0001), with 13 subjects (29.5%) attaining undetectable levels. All of the GIQs independently predicted the change in viral load from baseline and undetectable HIV-RNA at week 48. The partial R(2) of GIQ-C was greater than that of GIQ-B, which was greater than that of GIQ-A. All of the GIQs were independent predictors of the 48-week virological response. The predictive value of the GIQ for lopinavir/ritonavir may vary depending on the algorithm used to score drug resistance.

Prediction of early and confirmed virological response by genotypic inhibitory quotients for lopinavir in patients naïve for lopinavir with limited exposure to previous protease inhibitors

Objective To determine the impact of genotypic inhibitory quotient (GIQ) for lopinavir (LPV) in patients failing HAART with limited antiretroviral exposure. Design Retrospective analysis of a prospective trial. Methods Lopinavir GIQ was calculated as the ratio between the mean trough concentration ( C trough) and the number of protease mutations using eight different HIV drug resistance mutation lists or algorithms. Early (by week 12) and confirmed (up to week 24) virological response (HIV-RNA < 400 copies/mL, ECVR) was used as dependent variable in logistic regression model. Results Seventy-one of 109 (65%) patients achieved ECVR. At multivariable logistic regression analysis, each μg/mL increase of GIQ was correlated with increasing probability of ECVR as far as the following mutations were computed: multi-protease inhibitor (PI) associated mutations listed by IAS (OR = 1.17; 95% CI = 0.99–1.39; P = 0.058), mutations associated with LPV resistance by ANRS algorithm (OR = 1.21; 95% CI = 1.02–1.44; P = 0.03), major mutations associated with LPV resistance by Stanford database (OR = 1.16; 95% CI = 1–1.35; P = 0.05), and the whole set of mutations associated with LPV resistance in the same database (OR = 1.22; 95% CI = 1.02–1.46; P = 0.03). Using ROC curve method, a specific threshold GIQ was assessed, above which this parameter could predict ECVR with the highest sensitivity (74.6% with GIQ obtained through Stanford LPV mutations) or specificity (89.5% with GIQ obtained through ANRS LPV mutations). Conclusions Our results suggest that increasing GIQ can improve virological outcome even in patients with limited exposure to PIs. Further studies are necessary to understand what HIV protease mutations should be considered and whether such mutations should be weighted differently to improve LPV GIQ predictive value.

Role of the Inhibitory Quotient in HIV Therapy

A systemic review is presented of all studies that have evaluated the inhibitory quotient (IQ). The IQ is defined as the ratio between (trough) drug concentration and level of drug resistance of the HIV isolate. From the studies presented, it can be concluded that for protease inhibitors (PIs) and efavirenz, the phenotypic IQ is associated with virological response. The genotypic IQ (GIQ) for PIs was also demonstrated to be associated with virological response. An intrinsic limitation of the GIQ is that it is only applicable for PIs, of which resistance is based on the cumulative effect of mutations. As the IQ can be modified by adjustment of the drug dosage, it may be of clinical value. Its application in patient care should therefore be further investigated.

Overview of the Potency of Moxifloxacin Ophthalmic Solution 0.5% (VIGAMOX®)

Antibiotics have been the mainstay of therapy for infectious diseases since their origins in the 1940s. As microorganisms changed and resistance developed, more advanced antibiotics were ultimately needed to provide adequate coverage and spectrum. By selecting optimal antibiotics and dosing regimens, clinicians can avoid treatment failures and adverse events and can help prevent the emergence of further antibiotic resistance. The fourth-generation ophthalmic fluoroquinolones include moxifloxacin (VIGAMOX®, Alcon Laboratories, Inc., Fort Worth, TX) and gatifloxacin (Zymar, Allergan, Irvine, CA), and they are now approved for the treatment of bacterial conjunctivitis. This review highlights four scientific methods that compare and rank antibiotic potencies and predict their clinical efficacy and their propensity to develop resistance: 1) in vitro assay for minimum inhibitory concentrations, 2) in vivo models for pharmacokinetic and pharamacodynamic properties, 3) therapeutic index or inhibitory quotient, and 4) in vitro assay for mutant prevention concentration. The fourth-generation ophthalmic fluoroquinolones perform well in these assays. Both antibiotics have better in vitro activity against gram-positive bacteria than ciprofloxacin or ofloxacin. Moxifloxacin penetrates better into ocular tissues than gatifloxacin and older fluoroquinolones; in vitro activity of moxifloxacin and gatifloxacin against gram-negative bacteria is similar to that of older fluoroquinolones. Moxifloxacin also has better mutant prevention characteristics than other fluoroquinolones. These findings support the use of the newer fluoroquinolones for the prevention and treatment of serious ophthalmic infections (e.g., keratitis, endophthalmitis) caused by susceptible bacteria.

Virological and pharmacological factors associated with virological response to salvage therapy after an 8‐week of treatment interruption in a context of very advanced HIV disease (GigHAART ANRS 097)

Both highly potent antiretroviral drug rescue multi therapy and treatment interruption (TI) have been suggested to be effective in HIV-1 infected-patients with multiple treatment failure. GigHAART-ANRS 097 was the only randomized trial during which an 8-week TI was beneficial in heavily pre-treated patients with multi-drug resistant virus on resuming a multiple-drug salvage regimen. The aim of this study was to analyze virological and pharmacological factors associated with a virological response. Clonal resistance analysis showed that although the viral population was highly mutated and nearly monoclonal at baseline, the 8-week interruption therapy allowed the re-emergence of more susceptible quasispecies to the subsequent salvage therapy, which were not detected by classical genotypic resistance testing. The fact that not every viral clone harbored all resistance viral mutations could explain a part of the virological response to a six to eight drug regimen for patients enrolled in the TI group. This phenomenon was associated with a transient virological response after the use of a GigHAART therapy, but was followed by the re-emergence of baseline resistance pattern and acquisition of additional mutations in patients failing this strategy. A combined factor of protease inhibitor (PI) concentration and genotypic score, expressed as a genotypic inhibitory quotient (GIQ), was used to assess the importance of genotypic resistance and plasma drug levels in the rate of response to multiple PI combination. The GIQ of each PI used in the regimen was not associated with virological success. However, the sum of PI GIQs was predictive of a virological response. These results suggest that pharmacological enhancement might overcome viral resistance and that there is some benefit in adding the activity of several boosted-PIs to improve the response to a salvage regimen.

The normalized inhibitory quotient of boosted protease inhibitors is predictive of viral load response in treatment-experienced HIV-1-infected individuals

The normalized inhibitory quotient (NIQ) has been proposed as a measure for refining the precision of HIV resistance testing when selecting antiretroviral therapy (ART). We undertook an assessment of NIQ and 48-week virological outcome in patients commencing ritonavir-boosted protease inhibitor (PI) regimens. A cohort of 87 HIV-infected individuals who all had extensive prior exposure to ART were assigned a new boosted PI regimen following resistance testing. PI therapy consisted of lopinavir, indinavir, saquinavir and amprenavir at 50, 32, 11 and 6%, respectively. Fold change (FC) for each PI was determined from the resistance test at baseline. Trough drug concentration (Cmin) was determined at week 4. NIQ was derived individually by taking the logarithm of the ratio of Cmin/FC divided by the fixed ratio of population mean trough drug concentration/clinical cut off. Associations between viral load (VL) response over 48 weeks with baseline VL, FC, Cmin, NIQ and selected PI were assessed. Mean change from baseline VL reduced by 0.83 log at week 48. In multivariate analyses, baseline VL and NIQ were the parameters most associated with change from baseline VL at week 48 (P = 0.012 and 0.003, respectively). FC, Cmin and selected PI were not significantly associated with VL changes. In this cohort of highly treatment-experienced individuals treated with boosted PI regimens, baseline VL and NIQ were significantly predictive of virological response over 48 weeks whereas FC and Cmin were not. These results support the use of a NIQ at week 4, as a tool for predicting response to therapy in this setting.

Therapeutic drug monitoring and the inhibitory quotient of antiretroviral drugs: can they be applied to the current situation?

Therapeutic drug monitoring is attracting growing interest as a means of increasing the effectiveness of antiretroviral therapy and of decreasing its toxicity, although data supporting this strategy are still scarce. Currently, nucleoside analog reverse-transcriptase inhibitors (NARTI) are not candidates because their effect depends on their active intracellular form and not on plasma concentration. Protease inhibitors (PI) and non-nucleoside analogue reverse-transcriptase inhibitors (NNARTI) meet the criteria for therapeutic drug monitoring. The main limitations are that the parameters to be monitored in order to measure exposure to the drug and the effective concentration of the drug have not been well defined. The few studies performed in treatment-naive patients have demonstrated that monitoring improves therapeutic efficacy. This strategy will be particularly useful when the risk of subtherapeutic or toxic concentrations is especially high (pharmacokinetic interactions, intestinal malabsorption, adverse effects, virological failure without obvious cause, pregnancy, children). Although it remains to be standardized, the inhibitory quotient integrates pharmacological and virological parameters and is useful in patients with prior virological failure. Any therapeutic drug monitoring program should be accompanied by measures to monitor and improve treatment adherence. There are good reasons to believe that therapeutic drug monitoring can be useful to improve treatment in specific circumstances. However, before its widespread use as a routine method can be recommended, the parameters to be used should be standardized and studies with appropriate methodology should be performed to define the role of therapeutic drug monitoring in distinct clinical situations.

British HIV Association (BHIVA) guidelines for the treatment of HIV‐infected adults with antiretroviral therapy (2005)

British HIV Association (BHIVA) guidelines for the treatment of HIV‐infected adults with antiretroviral therapy (2005)