Presentation Type

Oral Presentation

Abstract

Cancer has long been a significant problem that has affected our world’s population for years and continues to this day. With the number of cases expected to increase annually there is a societal pressure to find effective treatment methods for eliminating cancer. Current forms of cancer treatment tend to cause detrimental effects to the human body and are usually quite expensive and long lasting, some costing upwards of $30,000 over an 8 week period. A more recently established form of cancer treatment known as photodynamic therapy is an effective treatment option for ridding cancers that lie on or just below the surface of the skin. Photodynamic therapy is usually done as an outpatient procedure, on average costing between $2,500-3,000 and can eliminate all traces of cancer in as little as a single visit. A major drawback to this form of cancer treatment is the lack of efficient photosensitizers, the light absorbing organic compounds which initiates the destruction of cancer cells. Our research is based on establishing a computational strategy for predicting the effectiveness of new photodynamic therapy photosensitizers. We focus our study on a specific photosensitizer from the boron dipyrromethene family of dyes, where we calculate the properties that can be used to classify the performance of a photosensitizer. This study will help future scientists approach the issue of finding top candidates for use as photosensitizers in photodynamic therapy through a rational design process rather than a repetitive trial and error based approach.

Start Date

6-5-2017 2:45 PM

End Date

6-5-2017 3:00 PM

Genre/Form

presentations (communicative events)

Subjects - Topical (LCSH)

Photosensitizing compounds; Photochemotherapy; Cancer--Treatment; Cancer--Research

Type

Event

Format

application/pdf

Language

English

COinS
 
May 6th, 2:45 PM May 6th, 3:00 PM

A Computational Approach to Studying the Properties of Photosensitizers in Photodynamic Therapy

Miller Hall

Cancer has long been a significant problem that has affected our world’s population for years and continues to this day. With the number of cases expected to increase annually there is a societal pressure to find effective treatment methods for eliminating cancer. Current forms of cancer treatment tend to cause detrimental effects to the human body and are usually quite expensive and long lasting, some costing upwards of $30,000 over an 8 week period. A more recently established form of cancer treatment known as photodynamic therapy is an effective treatment option for ridding cancers that lie on or just below the surface of the skin. Photodynamic therapy is usually done as an outpatient procedure, on average costing between $2,500-3,000 and can eliminate all traces of cancer in as little as a single visit. A major drawback to this form of cancer treatment is the lack of efficient photosensitizers, the light absorbing organic compounds which initiates the destruction of cancer cells. Our research is based on establishing a computational strategy for predicting the effectiveness of new photodynamic therapy photosensitizers. We focus our study on a specific photosensitizer from the boron dipyrromethene family of dyes, where we calculate the properties that can be used to classify the performance of a photosensitizer. This study will help future scientists approach the issue of finding top candidates for use as photosensitizers in photodynamic therapy through a rational design process rather than a repetitive trial and error based approach.