<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>39(1)</volume><submitter>Wang HC</submitter><pubmed_abstract>In order to develop an integrated pharmacokinetic/viral dynamic (PK/VD) model to predict long-term virological response rates to daclatasvir (DCV) and asunaprevir (ASV) combination therapy in patients infected with genotype 1 (GT1) chronic hepatitis C virus (HCV), a systematic publication search was conducted for DCV and ASV administered alone and/or in combination in healthy subjects or patients with GT1 HCV infection. On the basis of a constructed meta-database, an integrated PK/VD model was developed, which adequately described both DCV and ASV PK profiles and viral load time curves. The IC&lt;sub>50&lt;/sub> values of DCV and ASV were estimated to be 0.041 and 2.45 μg/L, respectively, in GT1A patients. A sigmoid E&lt;sub>max&lt;/sub> function was applied to describe the antiviral effects of DCV and ASV, depending on the drug concentrations in the effect compartment. An empirical exponential function revealed that IC&lt;sub>50&lt;/sub> changing over time described drug resistance in HCV GT1A patients during DCV or ASV monotherapy. Finally, the PK/VD model was evaluated externally by comparing the expected and observed virological response rates during and post-treatment with DCV and ASV combination therapy in HCV GT1B patients. Both the rates were in general agreement. Our PK/VD model provides a useful platform for the characterization of pharmacokinetic/pharmacodynamic relationships and the prediction of long-term virological response rates to aid future development of direct acting antiviral drugs.</pubmed_abstract><journal>Acta pharmacologica Sinica</journal><pagination>140-153</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC5758672</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Integrated pharmacokinetic/viral dynamic model for daclatasvir/asunaprevir in treatment of patients with genotype 1 chronic hepatitis C.</pubmed_title><pmcid>PMC5758672</pmcid><pubmed_authors>Qiu Y</pubmed_authors><pubmed_authors>Zheng J</pubmed_authors><pubmed_authors>Ren YP</pubmed_authors><pubmed_authors>Lu W</pubmed_authors><pubmed_authors>Li GL</pubmed_authors><pubmed_authors>Wang HC</pubmed_authors><pubmed_authors>Zhou TY</pubmed_authors><pubmed_authors>Hu CP</pubmed_authors><pubmed_authors>Li L</pubmed_authors></additional><is_claimable>false</is_claimable><name>Integrated pharmacokinetic/viral dynamic model for daclatasvir/asunaprevir in treatment of patients with genotype 1 chronic hepatitis C.</name><description>In order to develop an integrated pharmacokinetic/viral dynamic (PK/VD) model to predict long-term virological response rates to daclatasvir (DCV) and asunaprevir (ASV) combination therapy in patients infected with genotype 1 (GT1) chronic hepatitis C virus (HCV), a systematic publication search was conducted for DCV and ASV administered alone and/or in combination in healthy subjects or patients with GT1 HCV infection. On the basis of a constructed meta-database, an integrated PK/VD model was developed, which adequately described both DCV and ASV PK profiles and viral load time curves. The IC&lt;sub>50&lt;/sub> values of DCV and ASV were estimated to be 0.041 and 2.45 μg/L, respectively, in GT1A patients. A sigmoid E&lt;sub>max&lt;/sub> function was applied to describe the antiviral effects of DCV and ASV, depending on the drug concentrations in the effect compartment. An empirical exponential function revealed that IC&lt;sub>50&lt;/sub> changing over time described drug resistance in HCV GT1A patients during DCV or ASV monotherapy. Finally, the PK/VD model was evaluated externally by comparing the expected and observed virological response rates during and post-treatment with DCV and ASV combination therapy in HCV GT1B patients. Both the rates were in general agreement. Our PK/VD model provides a useful platform for the characterization of pharmacokinetic/pharmacodynamic relationships and the prediction of long-term virological response rates to aid future development of direct acting antiviral drugs.</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Jan</publication><modification>2024-11-13T07:35:49.202Z</modification><creation>2019-03-26T22:26:46Z</creation></dates><accession>S-EPMC5758672</accession><cross_references><pubmed>28880015</pubmed><doi>10.1038/aps.2017.84</doi></cross_references></HashMap>