Browsing by Subject "Antiviral therapy"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Intrahepatic HBV DNA as a predictor of antivirus treatment efficacy in HBeAg-positive chronic hepatitis B patients
    (Baishideng Publishing Group, 2007-05-28) Lu, Hai-Ying; Zhuang, Li-Wei; Yu, Yan-Yan; Ivan, Hadad; Si, Chong-Wen; Zeng, Zheng; Li, Jun; Hou, Dong-Ming; Chen, Xin-Yue; Han, Zhong-Hou; Chen, Yong; Department of Medicine, IU School of Medicine
    AIM: To evaluate the effect of antiviral agents on intrahepatic HBV DNA in HBeAg-positive chronic hepatitis B patients. METHODS: Seventy-one patients received treatment with lamivudine, interferon alpha (IFN-alpha 2b) or sequential therapy with lamivudine-IFN-alpha 2b for 48 wk. All subjects were followed up for 24 wk. Serum and intrahepatic HBV DNA were measured quantitatively by PCR. HBV genotypes were analyzed by PCR-RFLP. RESULTS: At the end of treatment, the intrahepatic HBV DNA level in 71 patients decreased from a mean of (6.1 +/- 1.0) log10 to (4.9 +/- 1.4) log10. Further, a larger decrease was seen in the intrahepatic HBV DNA level in patients with HBeAg seroconversion. Intrahepatic HBV DNA level (before and after treatment) was not significantly affected by the patients' HBV genotype, or by the probability of virological flare after treatment. CONCLUSION: Intrahepatic HBV DNA can be effectively lowered by antiviral agents and is a significant marker for monitoring antivirus treatment. Low intrahepatic HBV DNA level may achieve better efficacy of antivirus treatment.
  • Thumbnail Image
    Item
    Multiscale Model of Antiviral Timing, Potency, and Heterogeneity Effects on an Epithelial Tissue Patch Infected by SARS-CoV-2
    (MDPI, 2022-03-14) Gianlupi, Juliano Ferrari; Mapder, Tarunendu; Sego, T.J.; Sluka, James P.; Quinney, Sara K.; Craig, Morgan; Stratford, Robert E., Jr.; Glazier, James A.; Medicine, School of Medicine
    We extend our established agent-based multiscale computational model of infection of lung tissue by SARS-CoV-2 to include pharmacokinetic and pharmacodynamic models of remdesivir. We model remdesivir treatment for COVID-19; however, our methods are general to other viral infections and antiviral therapies. We investigate the effects of drug potency, drug dosing frequency, treatment initiation delay, antiviral half-life, and variability in cellular uptake and metabolism of remdesivir and its active metabolite on treatment outcomes in a simulated patch of infected epithelial tissue. Non-spatial deterministic population models which treat all cells of a given class as identical can clarify how treatment dosage and timing influence treatment efficacy. However, they do not reveal how cell-to-cell variability affects treatment outcomes. Our simulations suggest that for a given treatment regime, including cell-to-cell variation in drug uptake, permeability and metabolism increase the likelihood of uncontrolled infection as the cells with the lowest internal levels of antiviral act as super-spreaders within the tissue. The model predicts substantial variability in infection outcomes between similar tissue patches for different treatment options. In models with cellular metabolic variability, antiviral doses have to be increased significantly (>50% depending on simulation parameters) to achieve the same treatment results as with the homogeneous cellular metabolism.