Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.

Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.



Access Type

Open Access Thesis

Document Type


Degree Program

Chemical Engineering

Degree Type

Master of Science (M.S.)

Year Degree Awarded


Month Degree Awarded



Current chemotherapeutic treatment schedule prediction methods rely heavily on PK/PD-based models and overlook the important contribution of tissue-level transport and binding. Tissue-level transport and binding phenomena are essential to understanding drug delivery and efficacy in tumors. Drugs with desirable PK/PD properties often fail in vivo due to poor tissue-level transport. We developed an in silico method to predict the effect of treatment schedule on efficacy that couples PK/PD with tissue-level transport. Treatment schedules were implemented on theoretical drugs with different PK/PD and transport properties. For each drug with a given clearance rate, diffusivity, and binding, treatment schedules consisting of one to 20 doses were simulated. Results show that at binding constants around one, high diffusivities, and high clearance rates, implementation of a treatment schedule becomes more significant. At low clearance rates, regardless of tissue-level transport and binding, one dose was predicted to be most efficacious. Tissue Drug Exposure (TDE) was shown to be to a crucial factor for treatment schedule efficacy. Efficacy was improved by increasing TDE. Implementation of a treatment schedule with more doses than one curbed the effect of poor retention with drugs. This model investigates the effect of treatment schedule on a tissue transport model and shows implementation of a proper dosing regimen is crucial to maximize TDE and chemotherapeutic efficacy.


First Advisor

Neil S Forbes