FDA In Silico Modeling Fellowship
*Applications will be reviewed on a rolling-basis.
An opportunity is available at the U.S. Food and Drug Administration (FDA), Center for Drug Evaluation and Research (CDER) located at the University of Maryland, Baltimore.
In silico analysis of chemicals and biological targets can assist in identifying potential risks and benefits of new pharmaceuticals. In the Office of Clinical Pharmacology (OCP), several ongoing projects analyze the effects of drug structure, molecular target, biological process, and patient characteristics on the safety and efficacy of newly-identified chemical substances, drugs under review, and marketed drug products. Multiple opportunities are available to utilize computational modeling, including machine learning, quantitative systems pharmacology (QSP), systems biology, and (quantitative) structure-activity relationships ((Q)SARs), to evaluate potential drug adverse events, identify secondary drug targets, assess the public health risks of new drugs of abuse, and predict the toxicological profiles of other components of drug products.
Under the guidance of a mentor, the participant will have the opportunity to learn:
- how to use public and proprietary knowledgebases, including proprietary software used by government agencies and pharmaceutical companies to evaluate drug safety
- how to develop and design text-mining queries for obtaining relevant information out of public and proprietary documents
- about current regulatory (Q)SAR, QSP, and/or biological models used to predict a compound’s risk to public health and to build and evaluate new (Q)SAR, QSP, and/or biological models or other risk prediction models
- about best practices for the application of these methodologies to support regulatory decision-making
Qualifications
The qualified candidate should 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.
Knowledge of chemical and biological data mining, statistics, computational modeling, pharmacology, or drug toxicity is desired.
If you have questions, send an email to ORISE.FDA.CDER@orau.org. Please include the reference code for this opportunity (FDA-CDER-2020-0516) in your email.