AR-67 is a lipophilic third generation camptothecin analogue, currently under early stage clinical trials. It acts by targeting Topoisomerase 1 (Top1), a nuclear enzyme essential for DNA replication and transcription and is present in two forms, the pharmacologically active lipophilic lactone and the charged carboxylate. In oncology patients participating in a phase I clinical trial, AR-67 lactone was the predominant species in plasma. Similarly to other camptothecins, the identified dose-limiting toxicities for AR-67 were neutropenia, thrombocytopenia and fatigue. In addition, in vitro metabolism studies indicated AR-67 lactone as a substrate for CYP3A4/5 as well as the UGT1A7 and UGT1A8 enzymes localizing in the liver and the gut. Numerous studies have demonstrated the over-expression of transporters in certain tumor types. Here, the effect of interactions between AR-67 and efflux or uptake transporters on the antitumor efficacy of AR-67 in vitro was studied. We showed that BCRP and MDR1 overexpression confers resistance to AR-67. Moreover, we demonstrated the therapeutic superiority of protracted dosing over more intense dosing regimens of AR-67 using xenografts models. Our studies indicated the schedule-dependent expression of Top1 and the preferential partitioning of AR-67 in the tumor tissue. We reason that these are factors that need to be taken into consideration when designing dosing schedules aiming to maximize efficacy. As most cytotoxic drugs, AR-67 has a narrow therapeutic window. Thus, it is essential to identify the variables influencing exposure to this camptothecin analogue. A thorough compartmental pharmacokinetic analysis was performed on the patient data obtained in a phase 1 clinical trial on AR-67. Moreover, sources of intersubject variability associated with obtaining pharmacokinetic parameter estimates were identified and a population covariate pharmacokinetic model was developed. In conclusion, the drug development of AR-67 is a work in process. Findings presented above provide an insight on the factors contributing to its efficacy and toxicity when given to cancer patients.

Mathematical models provide unique insights to real-world problems. Within the context of infectious diseases, models are used to explore the dynamics of infections and control mechanisms. Human papillomavirus (HPV) globally infects about 630 million people, many of these infections develop into cancers and genital warts. Vaccines are available to protect against the most prevalent and devastating strains of HPV. The introduction of this vaccine as part of a national immunization program in Canada is a complex decision for policy-makers in which mathematical models can play a key role. We use the current recommendations provided by the World Health Organization to explore the integral role mathematical models have in the decision to incorporate the HPV vaccine within a national immunization program. We then provide a review of the literature discussing the role of mathematical models in the decision to include a vaccine in a national immunization program within the context of the HPV vaccine. Next, we evaluate the current standing of mathematical models used within the context of HPV immunization, to highlight the types of models used, underlying assumptions and general recommendations made about these immunization programs. Then, we create and analyze a model to explore the possibility of bettering the current HPV vaccine strategy in Canada. We focus on the effects of the grade of vaccination and the number of doses required to eradicate the targeted strains of HPV.

Mathematical models provide unique insights to real-world problems. Within the context of infectious diseases, models are used to explore the dynamics of infections and control mechanisms. Human papillomavirus (HPV) globally infects about 630 million people, many of these infections develop into cancers and genital warts. Vaccines are available to protect against the most prevalent and devastating strains of HPV. The introduction of this vaccine as part of a national immunization program in Canada is a complex decision for policy-makers in which mathematical models can play a key role. We use the current recommendations provided by the World Health Organization to explore the integral role mathematical models have in the decision to incorporate the HPV vaccine within a national immunization program. We then provide a review of the literature discussing the role of mathematical models in the decision to include a vaccine in a national immunization program within the context of the HPV vaccine. Next, we evaluate the current standing of mathematical models used within the context of HPV immunization, to highlight the types of models used, underlying assumptions and general recommendations made about these immunization programs. Then, we create and analyze a model to explore the possibility of bettering the current HPV vaccine strategy in Canada. We focus on the effects of the grade of vaccination and the number of doses required to eradicate the targeted strains of HPV.