P.Clevenbergh , J.Durant, R.Garraffo, P. Halfon, P. del Giudice, P. Simonet, N. Montagne, CAB Boucher, JM Schapiro and

1. Persisting long term benefit of genotypic guided treatment in HIV infected patients failing HAART and Importance of Protease Inhibitor plasma levels .Viradapt study, week 48 follow up and Pharmacological data. P.Clevenbergh, J.Durant, R.Garraffo, P. Halfon, P. del Giudice, P. Simonet, N. Montagne, CAB Boucher, JM Schapiro and P. Dellamonica

2. Background • An increasing number of retrospective studies link the presence of resistance mutations with a rebound in viral load . • Two prospective studies (GART and Viradapt) showed a short term benefit of genotypic adaptation in patients failing combination therapy

3. VIRADAPT: Trial Design Inclusion Criteria: HIV-RNA> 10.000 copies/ml PI > 3 months, NRTI > 6months Randomization N= 65 N= 43 GENOTYPICGroup CONTROL Group Clinical and Laboratory Evaluation (CD4, HIV-RNA,Genotype ,) If virological failure, ARV adaptation according to Randomization Analysis M3 M6 M12

4. 12 months Follow up Study • We report the 12 months follow-up of the patients participating in the Viradapt study • First 6 months: randomized study with 2 arms • After 6 months, patients in both arms received treatment changes based on genotyping results which were performed every three months

5. Patients and Methods Randomized Open study study Genotypic arm  Control arm M0 M3 M6 M9 M12  Genotyping treatment  Standard of care

6. Patients and Methods: Statistical Analysis for the first 6 months randomized study • Primary End-point: HIV-RNA variation from baseline at Month 3 and 6 (log10 transformed) • Secondary End-Point • Proportion of patients with HIV-RNA < 200 copies/ml • CD4 cell count • Statistics • Intent to treat analysis (dropout equal failure) • LOCF

7. 6 - 12 month follow-up study:Patients and Methods • Primary End-point HIV-RNA changes from baseline at Month 9 and 12 • Secondary End-Point Proportion of patients with HIV-RNA < 200 copies/ml • Statistics On treatment analysis

8. Genotyping Technology

9. Mutations - Drug Resistance Table

10. Baseline Characteristics :Demographic data • Characteristic Control Adapted to p Genotype 43 65 • Age 40.1±7.5 39.4±8.2 0.43 • Sexe Male/Female34/9 47/18 0.64 • Risk Factor :18/24/1 30/34/1 0.48 IVDU/Sexual/Others • HIV1-RNALog10 4.8±0.5 4.7±0.6 0.45 (range) (3.7-6) (3.4-6.2) • CD4 x106 201.7±22 220.8±18 0.49 • Stade CDC:A/B/C5/16/22 16/14/35 0.11

11. Prior Antiretroviral Treatment

12. Baseline Characteristics-Frequency of Primary and Secondary RT mutations

13. Baseline Characteristics-Frequency of primary and secondary P mutations

14. Results • 41/43 and 40/43 pts in the control arm were evaluable at month 3 and 6 • 62/65 and 59/65 pts in the genotypic arm were evaluable at month 3 and 6 • 103/108 (95.4%)pts and 99/108 (91.6%) evaluable at 3 and 6 months • 92/108 (85,2%) were evaluable at 12 months and included in the analysis.

15. Mean changes in plasma HIV-RNA from baseline throughout 12 months in Control and Genotypic arms

16. Percentage of patients with plasma HIV-RNA below the limit of detection (200 copies/ml) in Control and Genotypic arms

17. Correlation of baseline primary protease mutations and randomization arm with changes in HIV RNA

18. Conclusions • Virologic response 1.15 log sustained with genotypic guided therapy throughout 1 year ( heavily experienced population) • Performance of genotypic guided therapy may have contributed to additional viral load reduction seen in control patients • Presence of primary protease mutations and performance of genotypic guided treatment, both independently effect virological response

19. Importance of Protease Inhibitor plasma levels in patients treated with Genotypic adapted therapy 

20. Background • Multiple factors determine the response to antiretroviral therapy and causes other than drug resistance must be considered • Poor efficacy may be due to pharmacological parameters resulting in suboptimal drug exposure

21. Background • In contrast to nucleoside reverse transcriptase inhibitors, significant correlations between antiviral activity and plasma drug concentration have been demonstrated for HIV protease inhibitors • Low plasma PI drug levels have been significantly related to the rebound of viral load

22. Study Objective • To correlate Protease Inhibitors plasma levels with the changes in HIV RNA • To determine the multiple factors contributing to the efficacy of antiretroviral therapy in treatment experienced patients

23. Methods • Serial protease inhibitor drug levels were analysed in patients participating in the Viradapt study • pharmacological substudy N= 87 • Control group: standard of care (until 6mns) • Genotypic Group : genotypic guided therapy • Serial PI plasma trough levels were performed in both arms throughout the 12 months study.

24. Methods • Levels of PIs determined by HPLC • Samples collected before morning dose • Analysis was performed on batched frozen samples • Levels determined for all 4 PI ’s utilized in study (saquinavir, nelfinavir, ritonavir, indinavir) • Data analysed only for patients with at least 3 levels obtained

25. Results • 81 patients evaluated: mean age 39.7±8 years, 59 males, stage CDC C (52,7%) • 604 PI plasma levels obtained • Similar to the parent study, the 2 groups were comparable in terms of: risk factor, age, sex, previous treatment, CD4 cells count and baseline HIV RNA

26. PI drug levels

27. Correlation HIV-RNA and plasma level 6,5 7 6 6 5,5 5 5 4,5 4 4 3,5 3 3 2,5 2 2 1,5 1 1 -1 0 1 2 3 4 5 6 -1 0 1 2 3 4 5 6 7 8 9 10 Saquinavir (n= 289, p= .0007) Nelfinavir (n=85, p= .038) 6,5 6,5 6 6 5,5 5,5 5 5 4,5 4,5 4 4 3,5 3,5 3 3 2,5 2,5 2 2 1,5 1 1,5 -5 0 5 10 15 20 25 30 35 -2 0 2 4 6 8 10 12 Ritonavir (400 mg bid, n =62, p= .051) Indinavir (n=21, p= .012)

28. Pharmacokinetic data of P.I

29. Optimal Drug Concentrations • Sub optimal concentration (SOC):  2 levels less than 2x IC95 • Optimal concentration (OC): No more than 1 level less than 2x IC95 • SOC = 32%, OC = 68%

30. Results

31. Efficacy analysis based on drug levels and randomization arm • Patients were categorized in 4 groups: G1 = SOC/Control (n = 13) G2 = OC/Control (n = 22) G3 = SOC/Genotype (n = 13) G4 = OC/Genotype (n = 33)

32. Efficacy analysis based on drug levels and randomization arm

33. Percentage of patients with plasma HIV-RNA below the limit of detection (200 copies/ml)

34. Predictive factors of virological response OR 95%Confidence p Interval PI Concentration 2.37 [0.02-0.7 ] 0.017 > IC95 x 2 Genotypic therapy 2.24 [1.22-19.56 ] 0.025 Primary mutations 2.47 [0.03-0.567 ] 0.014for PI

35. Conclusions • Drug exposure inversely correlated with plasma HIV RNA (all 4 PI) • Genotypic guided therapy, PI concentration, and primary protease mutations: independently effect response to therapy • Assays to determine drug levels and resistance mutations may both improve responses in experienced patients

36. Acknowledgements • R.Garraffo: Department of Pharmacology,Nice, France • P.Halfon.Alphabio laboratory, Marseille, France. • V.Mondain, P.Puglièse, V.Rahelinirina, I.Perbost, C.Pradier, L.Bentz, H.Etesse: Infectious Diseases Department,Nice,France • the study nurses ( M.Massard, J.Charlier, G.Valentini, C.Rascle) • E.Dohin: Produits Roche France • C.Sayada, M.Andriamanamihaja : ACT Gene and Visible Genetics Europe • J.Stevens, R. Gilchrist : Visible Genetics Canada E.Counillon,P. Del Giudice : Bonnet Hospital, Frejus, France • P.Simonet, N.Montagne. Cannes Hospital France • C.A.B Boucher:Department of Virology, University Hospital Utrecht, Netherlands • J.M.Schapiro National Hemophilia Center, Tel Hashomer, Israel