Tipranavir (TPV) genotypic Inhibitory Quotient (giq) predicts Virological Response at 48 weeks to TPV-based salvage regimens.

Transcription

1 AAC Accepts, published online ahead of print on December 00 Antimicrob. Agents Chemother. doi:.1/aac.0-0 Copyright 00, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved Tipranavir (TPV) genotypic Inhibitory Quotient (giq) predicts Virological Response at weeks to TPV-based salvage regimens. Daniel Gonzalez de Requena, Stefano Bonora, Andrea Calcagno., Antonio D Avolio Marco Siccardi, Silvia Fontana, Maria Grazia Milia 1, Mauro Sciandra, Silvia Garazzino, Antonio Di Garbo 1, Lorena Baietto, Laura Trentini, and Giovanni Di Perri. Department of Infectious Diseases, University of Turin, Turin, Italy, and 1 Laboratory of Virology, Ospedale Amedeo di Savoia, Turin, Italy. Corresponding Author : Daniel Gonzalez de Requena, PharmD Clinica di Malattie Infettive. Universitá di Torino. Ospedale Amedeo di Savoia. Corso Svizzera, Torino. Italy. Phone: Fax: danifarre@hotmail.com 0 1 1

2 Abstract Background. Virological Response (VR) to tipranavir/ritonavir (TPV/RTV)-based regimen had showed to be associated with number of mutations on the protease gene, use of enfuvirtide (T0) and TPV phenotypic Inhibitory Quotient (IQ). The role of TPV genotypic inhibitory quotient (giq), has not yet been fully investigated. Aim of our study was to evaluate the relationship between TPV giq and -weeks VR to TPV-based salvage regimens. Methods. Patients (pts) placed on regimens containing nucleoside reverse transcriptase inhibitors (NRTI) + TPV/RTV 00/00 mg BID +/- T0 were prospectively studied. Regular follow up was 9 performed over the study period. VR, considered as viral load (VL) decrease 1 log and/or achievement of <0 copies/ml with no VL rebound > 0. log as compared to maximal VL decrease) at week was assessed. Results. Thirty-eight multi-experienced pts were included. At week VL decrease was -1. [-.;-0.], 1 pts (9. %) had VL<0 copies/ml, and CD+ cell count increase was cells/mm [-0; +1]. Twenty subjects (.%) achieved VR. TPV giq and optimized background score (OBS) were independently associated with higher VL decrease. TPV giq and OBS were also independent predictors of VR at week. A TPV giq and OBS cut off values of 0 and, respectively, were associated with a higher rate of VR. Conclusion. TPV giq showed to predict VR at weeks to TPV-containing salvage regimens better than TPV C trough or TPV- associated mutations alone. A possible TPV giq cut off value (0) for reaching VR at week was suggested. Further studies are needed in order to evaluate calculation of TPV giq as a new tool to optimise TPV-based salvage therapy.

3 INTRODUCTION Tipranavir (TPV) is a non-peptidic protease inhibitor with potent in-vitro activity against most HIV-1 strains resistant to other protease inhibitors (PIs) (1, 1, 1). In vitro data have shown that resistance to TPV develops slowly (). When co-administered with ritonavir (RTV) as a booster, TPV has shown potent antiviral activity in multiexperienced patients (,, 9, 1). In RESIST-1 and RESIST- studies, efficacy and safety of TPV/RTV (00 mg/00 mg twice daily) in 9 highly treatment-experienced HIV-1-positive patients was assessed. Forty-eight-week analysis showed that TPV/RTV-containing regimens significantly improved immune and virological responses as compared to RTV-boosted comparator protease inhibitor (CPI) plus optimized background regimen (OB) (,,). Different factors have been found to be associated with virological and immunological response: lower viral load at baseline, use of enfuvirtide as a part of OB, presence of two or more active drugs in the latter (optimized background score, OBS, ) (,,), and baseline numbers of specific TPV- associated mutations (TPV-RMs) (). Moreover, TPV Ctrough and phenotypic Inhibitory Quotient (IQ) have been also shown to be associated with virological response at week (Valdez H, McCallister S, Kohlbrenner V, Mayers D., presented at the rd IAS Conference on HIV Pathogenesis and Treatment, Rio de Janeiro; July 00, and Naeger L, Zheng J, and Struble K. Presented at 1th Conference on Retroviruses and Opportunistic Infections, Denver, CO, February 00) Genotypic IQ (giq), as the ratio between PI Ctrough and number of PI-associated mutations, is simpler to derive in the clinical setting than IQ. GIQ has previously been shown to be a predictor of therapeutic response to PI-based salvage regimens, e. g. lopinavir or fosamprenavir (,,,1). Preliminary data showed that TPV-gIQ correlated with early and mid virological response (Bonora S, Gonzalez De Requena D, Calcagno A, Milia MG, D'Avolio A, Sciandra M, Garazzino S, Siccardi M, Sinicco A, and Di Perri G.: Presented at 1th Conference on Retroviruses and

4 Opportunistic Infections, Denver, CO, February 00, and Bonora S, Gonzalez de Requena D, Calcagno A, Milia MG, D Avolio A, Sciandra M, Garazzino S, Siccardi M, Sinicco A, Di Perri G. Lisboa: Presented at the th International Workshop on Clinical Pharmacology of HIV therapy, Lisboa, April 00). However, no data are yet available on the predictive value of TPV-gIQ on the long term efficacy of TPV-based regimens. Therefore, aim of our study was to perform a pharmacokinetic/pharmacodynamic evaluation of predictors of virological response (VR) at week to salvage TPV-containing regimens in the clinical setting. PATIENTS AND METHODS Study Design Patients enrolled in the TPV Expanded Access Program (EAP) study and administered with regimens containing NRTIs + TPV/RTV 00/00 mg BID +/- enfuvirtide (T0) were prospectively evaluated. Criteria for the inclusion in the final analysis were baseline plasma HIV- RNA >00 copies/ml, HIV genotypic analysis and Virtual Phenotype performed in the last months before initiation of TPV-based regimen, regular follow up through week, availability of at least one TPV Ctrough measurement, and self-reported adherence more than 90% in last days before each visit. HIV-RNA and CD+ cell count were assayed by RT-PCR (Cobas Amplicor HIV- 1 monitor test v 1., Roche Molecular Systems, Switzerland) and flow citometry, respectively, at baseline and at weeks 1, and as an indicator of early, mid- and long term-response, respectively. 1 Study end points. Virological response (VR) was considered as HIV-RNA decrease 1 log and/or achievement of HIV-RNA < 0 copies with no HIV-RNA increase > 0. log as compared to the maximal viral load decrease. Intention To Treat (ITT) Last Observation Carried Forward method (LOCF) was used. In this ITT approach, in subjects who discontinued TPV before week for reasons other than

5 virological failure (VF) last HIV-RNA and CD+ cell count record before TPV withdrawal were considered for further analysis Calculation of the Optimized Background Score Optimized Background Score (OBS) was calculated by relying on the Genotypic Sensitivity Score (GSS). It was calculated by using Virtual Phenotype, version. (Virco). Drugs included in the background regimen reported to have full or partial susceptibility, by Virtual Phenotype were scored as 1, while drugs reported to be inactive by the latter were scored as 0. OBS was defined as the sum of such genotypic sensitivities scores of all drugs included in the regimen. In subjects administered with enfuvirtide, this drug was considered to be inactive if previously administered to the subject and discontinued after virological failure. Genotypic Resistance Test Genotypic resistance test was performed at baseline in subjects with VL>00 copies/ml by using ViroSeq HIV-1 Genotyping System (Celera Diagnostics, LCC, Alameda, CA, USA) with an automatic sequencer (ABI PRISM 0, PE Biosystems, Foster City, CA, USA). Genotype interpretation was made accordingly to the mutation score recently proposed (), and used in the - weeks combined analysis of RESIST 1 and RESIST trials (). According to this score, amino acid changes within the protease gene at positions LV, I1V, K0M/R/V, LF, EG, MI, KT, ML, IV, IA/M/V, QE, H9K, TP, VL/T, ND, and IV were considered as TPV Resistance Mutations (TPV-RMs). Pharmacokinetic Analysis. Blood samples were collected into lithium heparin tubes before morning dose, and plasma was separated by centrifugation at 000 rpm, refrigerated at C for min and then stored at 0 C until analysis. At time of blood sampling, patients were asked about time of last TPV dose intake.

6 Only plasma samples obtained between to 1 hours post dose were considered for Ctrough analysis. TPV concentrations were determined by using a validated High Performance Liquid Chromatography method with UV detection which was linear over the range of ng/ml Intra-day (CV%) and inter-day (CV%) precision ranged from 0.9 to.% and from.0 to.%, respectively. Limit of quantification and limit of detection were 90 ng/ml and ng/ml, respectively (). In subjects with more than one PK measurement, mean value of all available Ctroughs throughout the study period was considered. GIQ was calculated for each patient as the ratio between mean TPV Ctrough and the baseline number of TPV-RMs. GIQ was expressed as ng/ml/mutation. Statistical analyses Linear and logistic regression analyses were used to investigate factors associated with higher HIV- RNA decrease and VR. Variables showing p value < 0.0 at univariate analysis were considered for multivariate analysis forward conditional method. Receive Operator Characteristics (ROC) curve was used to explore possible cut off values for variables predictive at logistic regression analysis. Chi-square test was used to analyse the association between categorical variables. Statistical significance was considered as p <0.0. Statistical analysis was performed using SPSS software (00, version 1.0, SPSS Inc., Chicago, Ill). RESULTS Study population characteristics. Thirty-eight subjects (.% male) were included in the study. Eight (1%) patients were coinfected with HCV. Median [IQR] numbers of previous PIs and NRTIs were [-] and [-], respectively. Subjects had previous failures to a median [IQR] of [-] PI-based regimens. OB included a median (range) of (-) drugs. Twenty out of subjects were administered with enfuvirtide, of whom were enfuvirtide-experienced and had had previous VF to a regimen

7 including this drug. Median (range) OBS, based on Vph interpretation, was (0-). Complete study population characteristics are reported in Table Virological and immunological outcomes. Median [IQR] CD+ cell counts increase was [-9; 1], 0 [-1; ], and [-0; 1] at 1,, and weeks, respectively. Median [IQR] plasma HIV-RNA decay was.0 logs [-.; -0.], -.1 logs [-.9; -0.], and -1. logs [-.; -0.], at 1,, and weeks, respectively. VR was observed in (0.%), (.%), and 0 (.%) subjects at 1,, and weeks respectively, being VL <0 copies/ml in 1 (.1), 1 (.%), and 1 (9.%) subjects. Immuno-virological outcomes are reported in table. Pharmacokinetic and Genotypic analyses A total of 190 plasma samples from subjects were collected for pharmacokinetic analysis. A median [IQR] of [-] samples were obtained from each subject. Overall mean (±SD) of all available TPV Ctrough measurements through weeks was 1.9 (±1) ng/ml (Table ). Median [IQR] number of TPV-RMs was [-]. No TPV-RMs were detected in subjects. Specific amino acid changes at specific protease codons are reported in Figure 1. Overall median [IQR] TPV giq was 9 [9-19] ng/ml/mutation Pharmacological determinants of virological response. At univariate linear regression analysis, higher VL decrease at week was associated with higher OBS (R=-0., p=0.01) and higher giq (R=-0.91, p=0.01), while association with lower number of TPV-RMs showed a trend toward significativity (R=0.0, p=0.0). At multivariate analysis, only OBS (R=-0., p=0.0), and giq (R=-0., p=0.0) were confirmed to be independent predictors of higher VL decrease.

8 At univariate logistic regression analysis, OBS (p=0.0), giq (p=0.0), and the number of TPV- RMs (p=0.0) showed to be predictor of VR. At multivariate analysis, although OBS was the only factor independently predicting VR (p=0.0), giq (p=0.0) was also included in the final model providing better overall prediction of VR than observed in other tested models. Results of these analyses are reported in table and. An OBS cut off value for VR was calculated to be by ROC analysis. It has 90 % sensitivity and % specificity in predicting VR at weeks. At this time point, / (.%) subjects with an OBS showed VR, whereas it was observed in only / (0%) subjects with an OBS< (X =.9, p=0.01). In the same way, a TPV giq cut off value of 0 ng/ml/mutation was calculated by using ROC curve analysis. This cut off provided a sensitivity of 0% and a specificity of 9% in predicting VR at weeks. Ten out of 1 (.%) subjects with a TPV giq>0 ng/ml/mutation achieved VR, whereas the latter was recorded in only / (.%) subjects with a giq 0 ng/ml/mutation (X =., p=0.01). In order to evaluate the interplay between OBS and giq, both VL decrease and VR at weeks were stratified according to these two variables. All values are graphically represented in Figure. In the subgroup of subjects with a TPV giq 0 ng/ml/mutation (n=), plasma HIV-RNA decrease was significantly only in case of optimal OBS ( ). In subjects with a TPV giq >0 ng/ml/mutation (n=1), maximal VL decrease was similarly reached when OBS was. However, differences in magnitude of VL decrease between two groups can be observed. Moreover, in subjects with TPV giq 0 ng/ml/mutation proportion of VR gradually increased according to OBS, achieving the maximal value (0%) when the latter was. Nevertheless, in subjects with TPV giq>0 ng/ml/mutation, proportion of VR was maximal already with OBS=1. Unfortunately, limited sample size of each subgroup makes impossible statistical comparison.

9 DISCUSSION Our study confirmed that TPV-based regimens can be effective salvage options in more than 0% of heavily pre-treated subjects. Moreover, 9% of subjects administered with TPV/RTV had less than 0 HIV-RNA copies/ml at week. These results are consistent with previously published data of the combined analysis of the RESIST 1 and studies. In these big trials,.% of subjects reached VR (defined as more than 1 log decrease of plasmatic HIV-RNA), and 0.% of patients achieved HIV-RNA <00 copies/ml at weeks (). In our population, OBS and TPV giq were shown to be factors associated with VL decrease and VR. The former was a confirmation of results from RESIST trials. In multi-experienced patients administered with TPV, who had limited therapeutic options due to several failures to previous regimens, choice of optimal OB regimen with the highest number of drugs with residual activity is a crucial challenge. In our patients, in fact, OBS was an independent predictor of VR in both multivariate linear and logistic regression analyses. Moreover, subjects with or more active drugs in the OB were more likely to achieve VR than those with less active drugs, confirming the possible OBS cut off previously suggested (,, ). On the other hand, our study was the first to analyse long term response according to TPV giq. This parameter, that integrates pharmacokinetics and pharmacodynamics variables, showed to be a better predictor of both higher VL decrease and VR at weeks than TPV Ctrough value or number of TPV-RMs considered separately. Although number of TPV-RMs, in fact, showed to be associated with higher VL decrease at univariate linear regression analysis, this association was not confirmed at multivariate analyses (Table and Table ). In previous reports from RESIST trials, magnitude of TPV plasma exposure was shown to be crucial for achievement of effective inhibition of HIV strains, according to individual phenotypic IQ. TPV/RTV standard dosing could result in different plasma exposure, due to interindividual variability of TPV pharmacokinetics. As a consequence, achievement of adequate exposure in the single patient could be unpredictable, 9

10 especially towards strains carrying a higher number of TPV-RMs. Phenotypic resistance test is complex and not feasible in laboratory practice, therefore phenotypic IQ is not useful for the clinical setting. GIQ calculation, as opposite, is more practical and affordable in such context. Moreover, in our study a giq cut off value of 0 ng/ml/mutation for VR at weeks was suggested. In other words this means that a TPV Ctrough of 0 ng/ml per each TPV-RMs is requested for high probability of VR. In this way, early TPV giq calculation and possible dose individualization could be an option to explore in the difficult setting of deep salvage therapy. Combined analysis of both predictive variables (TPV giq and OBS), showed in figure, suggested further clinical considerations. TPV giq value above 0 ng/ml/mutation was associated with higher virological efficacy as compared to patients with TPV giq below such cut off, showing an additional VL decrease between 1. and 1. log even in association of high OBS (equal or above ). In a similar way, also the proportion of VR increased from 0% to -0% in patients showing TPV giq>0 ng/ml/mutation associated with OBS, as compared to subjects with lower TPV giq. Moreover, although of anecdotical value, VR was also achieved in the only subjects with an OBS of 1 and TPV giq above 0 ng/ml/mutation, whereas in this OBS stratum this was true for only 1% of subjects with lower TPV giq. From a clinical viewpoint, these findings suggested that optimization of TPV giq is worthy to be done in order to increase probability of VR also in patients with expectation of good residual activity of drugs associated with TPV/RTV. In our study use of enfuvirtide as an active drug was considered in the calculation of OBS, whereas it did not result per se an independent predictor of VR as it was in RESIST trials (,, ). This could be due to the limited sample size of our study and/or to a possible unbalance of clinical stage of patients selected for this association. Subjects administered with enfuvirtide, in fact, showed a slightly higher number of TPV-RMs as compared to other patients, although this difference did not reach statistical significance (data not shown). However, sample size was a main limit of our analysis. Although number of subjects included allowed univariate regression and multivariate regression with or less independent variables, some

11 other variable potentially to be analysed in the model remained at borderline significance, such as number of TPV-RMs. Moreover, in the calculation of TPV giq all TPV-related mutations were equally weighed as a unitary value, while they are supposed to affect drug susceptibility in different degrees. However, lack of consensual weighed score of such mutations allowed to this easy and fast interpretation of genotypic results in the clinical setting. Another possible bias could survival effect, due to early discontinuation of failing or intolerant subjects. However, first discontinuation due to intolerance was after days and many patients showing VF were maintained on TPV-containing regimen until availability of new salvage drug. Therefore, survival effect should not significantly affect analysis of -week efficacy. Moreover, also in RESIST trials analysis survival effect was not considered due to study design considerations. In conclusion, our findings suggested that TPV giq is an independent predictor of long term VR to TPV-based regimens. Therefore, the TPV giq cut off value proposed warrant further evaluation in prospective TDM-guided dose modification clinical trials.

12 Table 1. Demographics and baseline characteristics of study population. Total Population Total number of patients Sex (male) 1 (.) Age (years) Weight (kg) Height (cm) [9-9] 9 [0-] 1 [10-0] HCV co infection 1 (1%) Clinical Status (CDC 199 classification) 1 A 1 (.) B 1 (.) C (.9) Pharmacological history N of previous PIs (1-) Nº of PIs with Virological Failure (1-) N of previous NRTIs (-) Nº of NRTIs with Virological Failure (-) Previous TDF 1 (.) TDF with Virological Failure 1(1.) N of previous NNRTIs 1 (0-) Nº of NNRTIs with Virological Failure 1 (0-) Previous Enfuvirtide 1 (1) Enfuvirtide with Virological Failure (1) Optimized background (OB) Regimen Nº of drugs in OB regimen (-) OB regimen with enfuvirtide 1 0 (.) Nº of subjects with previous virological failure to enfuvirtide /0 (0) Nº of drugs in OB considered to be active (OB score, OBS) (0-) Distribution of OBS 1 0 (.9) 1 (.) 1 (.) (.) Distribution of Tipranavir-Resistance Mutations Baseline Immunovirology Log HIV-RNA CD + cells/ml CD % (.9) (.) (1.) (.9) 9 (1.) (1.) 1 (.). [.19-.1] 1 [0-99] 1. [.9-0.] 1 value are expressed as number of subjects (%) 1

13 values are expressed as median [IQR] values are expressed as median (range) 1

14 Table. Evolution of immuno-virological parameters and proportion of virological response through week. Baseline Week 1 Week Week HIV-RNA (log). [.19-.1].0 [<1.-.1].1 [<1.-.]. [<1.-.] HIV-RNA variation from baseline -.0[-.;-0.] -.1[-.9;-0.] -1.[-.;-0.] Virological Response 1 (HIV-RNA (0.) (.) 0 (.) decrease >1 log and/or < 0 copies/ml) subjects with <0 copies/ml 1 0 (0) 1 (.1) 1 (.) 1 (9.) CD + cell count (cells/mm) 1 [0-99] [-0] 9 [-9] [1-9] CD+ variation from baseline + [-9;+1] +0 (-1; +] + [-0;+1] 1 value are expressed as number of subjects (%) values are expressed as median [IQR] 1

15 Table. Overall pharmacokinetic analysis analysis. Mean Tipranavir Ctrough is calculated as the mean of all available Ctrough measurements. Plasma samples obtained between -1 hours were considered. Week 1 (n=) 9 (1) Week 1 (n=) (19) Week (n=) 0 () Week 1 1 (n=1) 19 (19) 1 Values are expressed as mean (±SD) ng/ml Week 1 (n=9) 190 (00) Week (n=) 09 (1) Week (n=) 9 (0) Mean TPV Ctrough 1 (n=) (1) 1

16 Table. Summary results of linear regression analysis. Viral Load decrease from baseline to week was considered as a dependent variable, whereas variables listed in the first column of the table were tested as independent variables. Univariate analysis Multivariate analysis Coefficient of regression (R) p value Coefficient of regression (R) p value Baseline Log VL Baseline CD+ cell count OBS TPV-RMs score TPV Ctrough giq Enfuvirtide co-administration Optimized Background Score. Tipranavir Resistance Mutation score. Genotypic Inhibitory Quotient 1

17 Table. Summary results of logistic regression analysis. Virological response at weeks was considered as a dependent variable, whereas variables listed in the first column of the table were tested as independent variables. Univariate analysis Multivariate analysis p value p value Baseline Log VL 0. Baseline CD+ cell count OBS TPV-RMs score TPV Ctrough 0. giq T0 co-administration 0. 1 Optimized Background Score. Tipranavir Resistance Mutation score. Genotypic Inhibitory Quotient 1

18 Figure 1. Frequency of specific aminoacid changes at specific codons in the protease gene. Black bars represent aminoacid changes considered as TPV resistance mutations (TPV-RMs). Number of Subjects F I V V I M R T V F I I F I D I V R I L V A V L V L A M S T V E F E A P I T V S T A P S V I A C F T V I V M L M L I1 K0 A L V L E M K M I G I0 F I Q D0 L A1 G T L V V I L9 L90 I9

19

20 Figure. Mean plasma HIV-RNA decrease (lines) and proportion of virological response at week (bars) stratified according to genotypic inhibitory quotient (giq) and optimized background score. Data from subjects with TPV giq 0 are in black, and those from subjects with TPV giq>0 are in grey. % of subjects with VR (n=) -0. (n=) -0. (n=1) 0-1. (n=1) (n=1) -.9 (n=) 0 1 Optimized Background Score (n=) -.0 (n=) log HIV-RNA decrease 0

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