FDA Automated Adhesion Assessment Fellowship
*Applications will be reviewed on a rolling-basis.
A research opportunity is available in the Office of Pharmaceutical Quality / Office of Translational Sciences, Center for Drug Evaluation and Research (CDER), Food and Drug Administration (FDA) in Silver Spring, Maryland.
Currently percent adhesion is visually estimated by trained clinicians, in small-sample controlled studies where subjects are confined to clinical centers. The manual measurement of percent adhesion, even by trained clinicians, adds observer variability and subjectivity in measurement. Furthermore, recent New Drug Applications (NDAs) have illustrated significant disparity in adhesion performance of a product when the product is assessed in the context of a small-sample controlled study and in the context of a study with large sample size and subjects not confined to clinical centers. It is natural to conclude that despite more variability, the large-sample “real world” study was more representative of the actual performance of the product. We aim to establish a statistical method that can automatically measure percent adhesion from color digital photos (taken via an Application on a smart-phone) to more consistently and accurately assess percent adhesion. This project will explore various combinations of factors (e.g. shapes, sizes, color, lighting) that may affect quality of photos taken and algorithms that extract the area of TDS.
The participant will gain understanding of accurate, precise, and automated assessment of the percent adhesion of transdermal and topical systems applied to the body. Under the guidance of a mentor, the participant will be able to utilize R or Python statistical software as well as contribute to development of an iOS or Android app.
Qualifications
The qualified candidate should be currently pursuing or have received a master's or doctoral degree in one of the relevant fields. Degree must have been received within five years of the appointment start date.
If you have questions, send an email to ORISE.FDA.CDER@orau.org. Please include the reference code for this opportunity (FDA-CDER-2020-0526) in your email.