Simplification of therapeutic drug monitoring for twice-daily regimens of lopinavir/ritonavir for HIV infection

Prevalence and virologic consequences of transmitted HIV-1 drug resistance in Uganda

Few reports have examined the impact of HIV-1 transmitted drug resistance (TDR) in resource-limited settings where there are fewer regimen choices and limited pretherapy/posttherapy resistance testing. In this study, we examined TDR prevalence in Kampala and Mbarara, Uganda and assessed its virologic consequences after antiretroviral therapy initiation. We sequenced the HIV-1 protease/reverse transcriptase from n=81 and n=491 treatment-naive participants of the Uganda AIDS Rural Treatment Outcomes (UARTO) pilot study in Kampala (AMU 2002-2004) and main cohort in Mbarara (MBA 2005-2010). TDR-associated mutations were defined by the WHO 2009 surveillance mutation list. Posttreatment viral load data were available for both populations. Overall TDR prevalence was 7% (Kampala) and 3% (Mbarara) with no significant time trend. There was a slight but statistically nonsignificant trend indicating that the presence of TDR was associated with a worse treatment outcome. Virologic suppression (≤400 copies/ml within 6 months posttherapy initiation) was achieved in 87% and 96% of participants with wildtype viruses versus 67% and 83% of participants with TDR (AMU, MBA p=0.2 and 0.1); time to suppression (log-rank p=0.3 and p=0.05). Overall, 85% and 96% of study participants achieved suppression regardless of TDR status. Surprisingly, among the TDR cases, approximately half still achieved suppression; the presence of pretherapy K103N while on nevirapine and fewer active drugs in the first regimen were most often observed with failures. The majority of patients benefited from the local HIV care system even without resistance monitoring. Overall, TDR prevalence was relatively low and its presence did not always imply treatment failure.

Limited-sampling strategies for anti-infective agents: systematic review

BACKGROUND

Area under the concentration-time curve (AUC) is a pharmacokinetic parameter that represents overall exposure to a drug. For selected anti-infective agents, pharmacokinetic-pharmacodynamic parameters, such as AUC/MIC (where MIC is the minimal inhibitory concentration), have been correlated with outcome in a few studies. A limited-sampling strategy may be used to estimate pharmacokinetic parameters such as AUC, without the frequent, costly, and inconvenient blood sampling that would be required to directly calculate the AUC.

OBJECTIVE

To discuss, by means of a systematic review, the strengths, limitations, and clinical implications of published studies involving a limited-sampling strategy for anti-infective agents and to propose improvements in methodology for future studies.

METHODS

The PubMed and EMBASE databases were searched using the terms "anti-infective agents", "limited sampling", "optimal sampling", "sparse sampling", "AUC monitoring", "abbreviated AUC", "abbreviated sampling", and "Bayesian". The reference lists of retrieved articles were searched manually. Included studies were classified according to modified criteria from the US Preventive Services Task Force.

RESULTS

Twenty studies met the inclusion criteria. Six of the studies (involving didanosine, zidovudine, nevirapine, ciprofloxacin, efavirenz, and nelfinavir) were classified as providing level I evidence, 4 studies (involving vancomycin, didanosine, lamivudine, and lopinavir-ritonavir) provided level II-1 evidence, 2 studies (involving saquinavir and ceftazidime) provided level II-2 evidence, and 8 studies (involving ciprofloxacin, nelfinavir, vancomycin, ceftazidime, ganciclovir, pyrazinamide, meropenem, and alpha interferon) provided level III evidence. All of the studies providing level I evidence used prospectively collected data and proper validation procedures with separate, randomly selected index and validation groups. However, most of the included studies did not provide an adequate description of the methods or the characteristics of included patients, which limited their generalizability.

CONCLUSIONS

Many limited-sampling strategies have been developed for anti-infective agents that do not have a clearly established link between AUC and clinical outcomes in humans. Future studies should first determine if there is an association between AUC monitoring and clinical outcomes. Thereafter, it may be worthwhile to prospectively develop and validate a limited-sampling strategy for the particular anti-infective agent in a similar population.

Sensitive analysis of anti-HIV drugs, efavirenz, lopinavir and ritonavir, in human hair by liquid chromatography coupled with tandem mass spectrometry

A highly sensitive and selective method using liquid chromatography coupled with tandem mass spectrometry (LC/MS/MS) was developed and validated for the measurement of three antiretroviral agents, efavirenz, lopinavir and ritonavir, in human hair. Hair samples from adherent HIV-infected patients on antiretroviral therapies were cut into about 1 mm length segments and drugs were extracted by first shaking the samples with methanol in a 37 degrees C water bath overnight (>14 h), followed by methyl tert-butyl ether/ethyl acetate (1:1) extraction under weak alkaline conditions. The extracted lopinavir and ritonavir were separated by reversed-phase chromatography and detected by tandem mass spectrometry in electrospray positive ionization mode with multiple reaction monitoring (MRM), while efavirenz was monitored in negative ionization MRM mode. This method was validated from 0.01 to 4.0 ng/mg hair for ritonavir and 0.05-20 ng/mg hair for lopinavir and efavirenz by using 2 mg of a human hair sample. The interday and intraday assay precision (coefficients of variation, CV) for spiked quality control (QC) samples at low, medium and high concentrations were within 15% and accuracy ranged from 89% to 110%. Assay reproducibility was also demonstrated by analysis of incurred hair QC samples (CV <14%). No significant matrix ionization suppression was observed. This developed method allowed for the monitoring of these target medications in the hair samples of HIV-infected women on antiretroviral therapy in an observational study using small amounts of hair.

Limited-sampling strategy for the prediction of boosted hard-gel saquinavir exposure at a dosage of 1000/100 mg twice daily in human immunodeficiency virus-infected individuals

Area under the concentration time curve (AUC) over a dosing interval is considered to be the best estimate of drug exposure in a patient. However, determination of this parameter is costly and often impractical, requiring multiple samples and a great deal of time and resources. A limited-sampling strategy (LSS) may overcome some of these issues, making pharmacokinetic studies easier to perform, particularly in a limited-resource setting. The aim of this work was to develop and validate a pragmatic LSS for the accurate and precise prediction of boosted saquinavir AUC0-12 (AUC over the 12-hour dosing interval) at a dosage of 1000/100 mg twice daily. Pharmacokinetic data were obtained from 34 human immunodeficiency virus (HIV)-infected individuals stable on saquinavir/ritonavir-containing therapy, randomly split into two sets (n = 17 per set). One set was used to construct prediction models using univariate and multivariate analysis (development set), and the second was used to determine the predictive performance of the models (validation set). For single samples, 6- and 10-hour concentrations correlated best with saquinavir AUC0-12 (r2: 0.913 and 0.911, respectively), yet all single samples failed to produce precise and unbiased predictions. However, combinations at 2, 6; 0, 2, 6; 0, 4, 10; 0, 4, 12; and 2, 4, 6 hours achieved good predictive performances, and both precise [root mean squared relative prediction error (%RMSE): 6.4% to 11.9%] and unbiased [mean relative prediction error (%MPE), 95% CI: -2.7%, (-0.8)-2.7 to 1.6%, (-1.8)-4.7] estimations of saquinavir AUC0-12. Of these models, concentrations obtained at 0, 2, 6 and 2, 4, 6 hours are more practical in a clinical setting and are therefore the LSS with most potential. Provided that the technique is validated in specific patient populations, an LSS approach is a potentially useful tool to evaluate the AUC0-12 of saquinavir in resource-limited settings, reducing both costs and volumes of blood taken. It may also aid the choice of sampling times for population analysis.