The current thesis work consists of two projects presenting the pharmacometric analyses in drug exposure and response data. The first project applied population pharmacokinetic modeling approach to estimate the in vivo inhibition constant (Ki) across different CYP2C9 genotypes. In the second project, a model-based meta-analysis was performed to describe the time-course of virologic response in hepatitis C clinical trials across current approved treatments. The inhibition constant (Ki) of an inhibitor is usually estimated from in vitro experiments. Given the differences between in vivo and in vitro experiments, the in vitro Ki may not truly reflect the inhibitor-enzyme interaction in vivo. A previous study demonstrated that the in vitro Ki of fluconazole varied across different CYP2C9 genotypes, suggesting the inhibitor potency of interacting with CYP2C9 in vivo also depends on enzyme genotypes. The current study presented a population model-based approach to determine the in vivo Ki of fluconazole across three CYP2C9 genotype groups (*1*1, *1*3 and *3*3) with the CYP2C9 substrate, flurbiprofen. An integrated model was developed describing the pharmacokinetic profile of the flurbiprofen and competitive inhibition of fluconazole on flurbiprofen metabolism through CYP2C9. The estimates of in vivo Ki was 14.7 µM for CYP2C9 *1*1, 18.7 µM for CYP2C9*1*3 and 32.9 µM for CYP2C9*3*3. The estimates of in vivo Ki of fluconazole are comparable to those estimates from in vitro studies. The result suggests the presence of CYP2C9*3 is associated with diminished interaction between fluconazole and enzyme. In addition, the contribution of CYP2C9 mediated metabolic clearance to the total flurbiprofen clearance is less significant in CYP2C9*3 group than CYP2C9*1*1 group. The magnitude of overall in vivo drug interaction was also quantitatively evaluated. Patients with CYP2C9*3 is less susceptible to fluconazole inhibition. The present findings showed the potential of metabolism-based drug interaction could be different across individuals featured with various metabolic enzyme polymorphisms. The recommendation on dosing adjustment due to the overall effect of drug interaction on metabolism, accordingly, should take into consideration genotypes of metabolizing enzyme, elimination pathways of the substrate and inhibitor potency. In the second project, a model-based meta-analysis was performed to quantitatively assess the time course of longitudinal virologic response across currently approved hepatitis C treatments including peginterferon plus ribavirin (PR), telaprevir plus PR therapy and boceprevir plus PR therapy. A total of 18 studies with 47 treatment arms were enrolled in the current analysis. The information collected in the analytic dataset included numbers of responders whose hepatitis C viral RNA level is undetectable at a given time, treatment strategy and patient population characteristics. The analysis was firstly conducted in NONMEM 7 to obtain maximum likelihood estimates. However, the initial model had several limitations and ran into computational difficulties when trying to incorporate random effects at multiple levels. One of major limitations is that the model did not account for the potential decrease in the response rate which was observed during later phase of treatment in some treatment arms. To overcome these limitations, the meta-analysis was implemented in a Bayesian framework using Markov Chain Monte Carlo algorithm. The response rate model was developed incorporating the component of possibility of response reverse. The analysis found the telaprevir had the fastest response onset, followed by boceprevir and PR therapy alone. The maximum response rates were lower in treatment arms with greater proportion of genotype 1 patients, black patients and prior null-responders. In the model, the SVR rate was compared to the response rate at the end of treatment. Their ratio was associated with the therapy and duration of the treatment. The probability of having a response reverse event increased quite slightly over time in triple therapy with telaprevir or boceprevir, compared to PR therapy alone.