Therapeutic antibodies have become one of the fastest growing classes of drugs in recent years. Antibodies are central to the body’s response to a viral infection. They work by recognizing and sticking to antigens in order to remove them from the body. Monoclonal antibodies are laboratory-made proteins that have become very prevalent during the COVID-19 pandemic in fighting the virus and protecting from future infections. The market for therapeutic monoclonal antibody drugs has grown tremendously as new drugs have been approved by the US FDA to treat many cancers, autoimmune, metabolic and infectious diseases. Monoclonal antibodies are now the best selling form of drugs in the pharmaceutical area with a reported global market value of USD 145.7 Billion in 2021. Although using monoclonal antibodies to target tumors seems like a simple concept, drug efficacy is dependent on many physiological characteristics. Both the tumor environment and biochemical properties of the antibody such as its ability to bind to an antigen play a large role in tumor penetration. The goal of this project is to design a new antibody based molecule to improve transport into a tumor. By reviewing existing literature on antibody tumor transportation and reproducing existing models on MATLAB, we can develop and improve on our antibody-tumor model and identify parameters which have been observed to impact antibody tumor distribution. From this we will design experiments to test the outcome of the model which is predicted to improve efficacy.