Internship Projects

Principle Investigator: Burall, Laurel

Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD (In-Person)

Objective:

Project Needs and Duration:

Prior experience working in a research environment, especially with Listeria monocytogenes, is preferred. Basic science coursework and lab instruction. Additionally, basic laboratory experience, including: pipetting, ability to make calculations for reagent and solution preparation, serial dilutions, genomic DNA isolation, sequencing library preparations is preferred.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Listeriosis outbreaks have been linked to the consumption of contaminated enoki mushrooms. Post-outbreak evaluation has noted differences in the practices associated with enoki consumption based on region. Additionally, several post-harvest treatments have been proposed to reduce Listeria monocytogenes on the product but full understanding of the efficacy of these treatments, especially how timing of contamination may affect treatment efficacy, is limited. This project will evaluate several proposed interventions, including UV light, organic acid treatment, and different heating protocols, to determine their effectiveness and whether or not contamination timing alters the efficacy (i.e., contamination at harvest versus during mushroom generation).

Principle Investigator: Chen, Yi

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

1. Perform method development and validation of novel molecular screening methods for the detection of Listeria monocytogenes and Listeria spp. in food and environmental matrices.
2. Investigation of the impact of atypical Listeria strains and recently discovered novel Listeria spp. on molecular screening and confirmation methods.
3. Use of a whole-genome-sequencing-based methods for speciation of Listeria spp.

Project Needs and Duration:

Course work and preferably lab course work in microbiology. Prior work experience in a microbiology lab preferred.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

The FDA’s standard procedures for detecting Listeria monocytogenes and Listeria spp. are outlined in the Bacteriological Analytical Manual (BAM). The current isolation method is culture-based and does not include rapid molecular screening. Consequently, there is a critical need to develop and validate more sensitive inhouse molecular screening methods for inclusion in the BAM, leveraging advanced techniques such as real-time PCR, digital PCR, and isothermal amplification.

Additionally, multiplex qPCR approaches should be explored and validated to enable the simultaneous detection of L. monocytogenes and other Listeria species. Non-monocytogenes Listeria spp. serve as important indicators of L. monocytogenes in FDA environmental monitoring programs. However, current identification methods rely on biochemical testing, which can yield inaccurate results for certain strains.

With whole genome sequencing (WGS) now routinely employed in many laboratories, integrating WGS-based speciation would significantly improve the accuracy of species-level identification. Furthermore, the emergence of atypical Listeria strains and newly defined species poses additional challenges for detection and confirmation, potentially interfering with existing molecular protocols. The current BAM method cannot detect some of these newly classified species. Therefore, it is essential to assess the impact of these emerging variants and, where needed, adapt current methodologies to ensure accurate detection and characterization.

Principle Investigator: Cinar, Hediye

Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD (In-Person)

Objective:

1. Assist in the establishment and maintenance of the gut organoids and organ-on-a-chip system.
2. Perform/assist experiments designed to evaluate system parameters for propagation of the apicomplexan parasites.
3. Contribute to data analysis using currently available statistical analysis tools.
4. Contribute to communication of research findings by participating in the preparations of posters and manuscripts.

Project Needs and Duration:

1. Students should have completed at least some General Microbiology courses with laboratory components.
2. Students should have familiarity with computer programs beyond MS Office.
3. Students should be able to work in the laboratory using various experimental procedures, including cell biology and molecular biology methodologies.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Cyclospora cayetanensis is an intestinal protozoan parasite that causes cyclosporiasis, a diarrheal disease of public health importance in humans. In the United States, foodborne outbreaks of C. cayetanensis have been a recurring challenge since the mid-1990s. The absence of reliable animal or cell culture propagation systems prevents assessing the viability of C. cayetanensis oocysts in foodborne contamination events. Establishing an in vitro culture model for C. cayetanensis would be transformative for outbreak response and prevention, while supporting current method development strategies at FDA. However, research progress has been hindered by the limited availability of C. cayetanensis oocysts, which can only be obtained from infected patient stool samples. To overcome this critical barrier, we have initiated the use of Cryptosporidium spp. as model organisms for testing purposes to guide the development of an in vitro propagation system for C. cayetanensis. Cryptosporidium, a coccidian parasite that causes food- and waterborne diarrheal disease, shares key biological and life cycle characteristics with Cyclospora, making it a scientifically relevant model organism. In our previous project, we successfully established C. parvum culture systems using human intestinal organoid monolayers and collected preliminary data using Emulate gut-on-achip platform. These innovative systems replicate the structural and physiological complexity of the human intestinal environment in vitro and provide a robust foundation for exploring C. cayetanensis propagation. This project aims to advance C. cayetanensis research through the application of several New Approach Methodologies (NAMs). This research will fill a critical knowledge gap and directly support the development of strategies to detect, characterize, and control Cyclospora-associated foodborne outbreaks.

Principle Investigator: Khuda, Sefat

Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD (In-Person)

Objective:

1. Assist in establishing an experimental model
2. Assist in optimizing the parameters for treatments
3. Assist in assessing cellular epithelial barrier integrity
4. Assist in analyzing experimental samples for in vitro tight junction function in response to treatments

Project Needs and Duration:

- Basic laboratory calculations such as dilutions, normality, molarity, and preparing various reagents, pipetting techniques
- Skill to utilize laboratory equipment, computer programing to perform assays and manage records
- Lab experience in the area of general biochemistry, cellular and molecular biology, food chemistry/science, biological effect of foodborne pathogens

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Listeria monocytogenes (Lm) is a foodborne pathogen that causes human listeriosis. It is known that Lm strains found in fresh produce supply chains and foods vary in their degree of virulence. Although Lm has been well studied, there are gaps in our understanding of its virulence potential. Lm can breach the gut epithelial barrier through intracellular mechanisms and compromising paracellular routes leading to gut barrier dysfunction. For paracellular translocation, Lm uses Listeria Adhesion Protein (LAP) to disrupt tight junctions that normally seal gaps between intestinal cells. High LAP-secreting Lm strains increase epithelial cell junction permeability more than low-secreting strains. Research gaps exist on whether strain-dependent variation in virulence potentially affects gut barrier permeability and Lm paracellular translocation through the epithelial barrier. Based on the results from our pilot study, we hypothesize that more virulent Lm strains will cause greater damage to gut barrier permeability than less virulent strains, thereby providing a quantitative method to assess virulence potential of Lm strains. An important factor in maintaining the barrier integrity is the gut microbiome that includes bacteria like Lactobacillus and Bifidobacterium and therefore, it will also be investigated whether these bacteria can mitigate paracellular translocation of Lm. The proposed research will develop an in vitro cell-based bioassay to: 1) evaluate how different Lm strains, including outbreak-associated strains and their virulence factors, impact gut barrier integrity and function, which can be quantitatively measured; and 2) assess the effect of dietary live microbials on gut barrier protection against Lm translocation. In this study, our goal is to use this phenomenon of gut barrier function disruption by Lm to develop a quantitative method for determining the virulence potential of Lm strains.

The objective of this research project is to develop an in vitro cell based method as an alternate to live animal testing of Lm strains for risk evaluation of Lm strains as they emerge in the food supply chain.

Principle Investigator: Pava-Ripoll, Monica

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

1. Perform DNA extraction and quality control from diverse food products.
2. Prepare genomic libraries and apply target enrichment protocols for next-generation sequencing (NGS).
3. Conduct PCR amplification of insect DNA from spiked food samples or food products.
4. Analyze sequence data using in-house bioinformatic pipelines to classify insect species.
5. Present findings at group meetings and prepare materials for potential conference abstracts/posters.

Project Needs and Duration:

- Coursework in general biology, genetics, molecular biology, or entomology.
- Laboratory experience using micropipettes, DNA extraction, PCR.
- Familiarity with computational biology, data analysis, or bioinformatics is a plus.
- Strong organizational skills and interest in food safety and regulatory science.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

This project applies targeted metagenomics, an advanced DNA-based sequencing approach, to detect and identify arthropods, such as insects, in food products. By enriching insect mitochondrial DNA and analyzing results with FDA-developed software pipelines, this project helps modernize the “Filth” program by creating an efficient, high-throughput tool that supports regulatory decision-making.

Principle Investigator: Sahu, Surasri

Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD (In-Person)

Objective:

1. Assist in purification of C. cayetanensis oocysts from available samples using the discontinuous sucrose density gradient and/or cesium chloride concentrations and centrifugation protocols.
2. Assist in development of enhanced methodologies for the excystation of purified oocysts of C. cayetanensis.
3. Assist in imaging studies using fluorescence microscopy and Scanning Electron Microscopy (SEM).
4. Perform molecular detection assays such as qPCR and ddPCR.
5. Contribute to data analysis using currently available statistical analysis tools.
6. Contribute to communication of research findings by participating in the preparations of posters and manuscripts.

Project Needs and Duration:

a. Students should have completed at least some General Microbiology courses with laboratory components.
b. Students should have familiarity with computer programs beyond MS office.
c. Students should be able to work in the laboratory using various experimental procedures, including cell biology and molecular biology methodologies.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Cyclospora cayetanensis, an intestinal protozoan parasite, can cause diarrheal illnessnamed cyclosporiasis in humans, which is characterized by anorexia, nausea, flatulence, fatigue, abdominal cramping, diarrhea, low-grade fever, and weight loss. Cyclosporiasis is primarily associated with food-borne and water-borne outbreaks in endemic and epidemic patterns worldwide. In the US, food-borne outbreaks of C. cayetanensis have been an ongoing public health problem since mid-1990s. As of August 2024, 24 states, reported a total of 2,622 laboratory-confirmed cases of cyclosporiasis, of which 1261 cases were acquired domestically.

Individuals infected with cyclosporiasis excrete unsporulated oocysts through their feces. These oocysts are non-infectious and require a period of one to two weeks in the environment to transform into sporulated oocysts. Only the sporulated form is infectious to susceptible individuals. When consumed by the host, sporozoites are released from the sporocysts within the sporulated oocysts to infect the intestinal epithelial cells. The biological processes governing sporulation of the Cyclospora oocysts and required environmental conditions are poorly understood. Although several purification methods are available to isolate oocysts from human stool samples, none of these methods are evaluated for their applications in downstream assays requiring viability of oocysts, such as cultivating methods including 3-D cell cultures, and micro-physiological systems. Further research is required to address these critical knowledge gaps to optimize our detection methods for this pathogen and generate data to prevent or mitigate foodborne outbreaks of C. cayetanensis.

Principle Investigator: Butler, Karen

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

- Prepare QC standard mixtures and food sample extracts.
- Compare accuracy of results and data analysis throughput for the analysis of QC compounds across multiple software tools for NTA and SSA data.
- Evaluate SSA software tools for accuracy, reproducibility, reliability, and potential limitations for LC/HRMS data using a large compound list.
- Assist with designing and proposing standardized workflow for monitoring QC compounds as part of processing NTA and SSA LC/HRMS data for food safety applications.

Project Needs and Duration:

- Good academic standing.
- Coursework in general, organic, and analytical chemistry required.
- Basic laboratory skills, including the ability to weigh and accurately measure chemicals and perform basic pipetting, required.
- Computer skills, including proficiency with Microsoft Office (Excel, PowerPoint, Word) required. Basic programming skills (R, Python) preferred but not required.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

 Routine analytical methods for food safety applications are commonly targeted towards the detection of specific compounds or compound classes, limiting the scope of what may be detected within a single analysis. As chemical hazards continue to evolve and the food supply becomes increasingly global, there is a greater need for food-safety methods that can detect unknown or unexpected compounds across a broader range of chemicals. Liquid chromatography coupled with high resolution mass spectrometry (LC/HRMS) allows for the detection of hundreds to thousands of compounds in a single sample, facilitating the potential detection and identification of a wider range of compounds than targeted approaches; these methods are commonly referred to as non-targeted and suspect screening analysis (NTA and SSA, respectively). NTA data sets from food matrices are information-rich and their inherently varied chemical complexity requires the use of robust quality controls (QCs) to ensure features are reproducibly and reliably extracted from the data. One way to address this need is using QC standard mixtures that exhibit a wide range of physicochemical properties and diverse chemical compositions representative of compounds to mimic potential compounds of concern to evaluate method performance. This project will interrogate several software tools with a QC mixture to determine the optimal data analysis pipeline for needed QC checks. Each software tool will also be evaluated for SSA performance against a large list of compounds to enable higher throughput analyses of generated data sets.

Principle Investigator: Carter, Jake

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

1. Learn applied atomic spectroscopy theory to better understand potential pitfalls between different atomic spectrometry techniques and different plasma sources.
2. Learn how to quantitatively prepare samples for atomic spectrometry analysis. Working at trace element concentrations requires more attention and detail than what is taught in general chemistry laboratory experiments. Example: Sample massing, sample transfer to digestion vessels, reagent massing and transfer to digestion vessels, gravimetric dilutions, clean chemistry—working in a clean room environment.
3. Prepare samples spanning the AOAC Food Triangle (i.e. foods with varying amounts of fats, protein, and carbs) for acid extraction. Quantitatively perform microwave assisted digestions of all samples and quality control materials for the project.
4. Prepare external standard calibration curves for quantitative analysis on plasma OES instruments.
5. Perform daily instrument checks and calibrations. Maintain instruments throughout the project (e.g., cleaning plasma torches, changing pump tubing, calibrating instrument spectrometer).
6. Perform instrumental analyses of all validation foods to meet the definition of single lab validation in the Chemical Methods Food Validation Guidelines.
7. Process all instrumental data to convert instrument response to element mass fractions.

Project Needs and Duration:

- Demonstrated success in quantitative chemical analysis coursework and lab exercises.
- Research in a lab environment involving quantitative sample preparation and instrumental analysis.
- Soft skills related to the intern’s ability to operate both in independent work within the lab under the advisor’s guidance and in a team environment within the branch.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

EAM 4.4 is a recently updated method covering up to 23 elements in foods using inductively coupled plasma optical emission spectrometry (ICP-OES). Currently undergoing a multilaboratory validation, EAM 4.4 has been single lab validated and shown to be fit for purpose for regulatory analysis. ICP-OES is a workhorse technique for atomic emission spectrometry with multielement capabilities based on the energy rich, Ar supported plasma.

Recent research has shown novel plasma sources are capable of quantitative atomic emission spectrometry at lower cost. Of note is the microwave-sustained, inductively coupled, atmospheric-pressure plasma (MICAP), where MICAP optical emission spectrometry (MICAPOES) is tolerant of potentially harsh matrices routinely encountered during food regulatory analyses. Prior results demonstrated suitable accuracy for nutrient elements in organic solvents and high salt solutions. In addition to its ruggedness, the N2 supported plasma leads to lower operational costs compared to the traditional Ar ICP. Therefore, if proved to be suitable for nutrient element analysis via a successful single lab validation, MICAP-OES may be an efficient alternative for regulatory analysis of nutrients in food compared to the traditional ICP-OES instrumentation commonly found in FDA field labs.

OLOAS/OCT/DBC/CCB has recently purchased and installed a MICAP-OES for testing and validation. The data gathered from the project will determine the metrics of performance of the new technique and suitability of the platform for regulatory analysis where accuracy and low uncertainty are required in addition to cost efficiency.

Principle Investigator: Fiedler, Katherine

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

- Design experiments to determine optimal method parameters for each LFIA
- Prepare poppy seed samples at known concentrations of morphine, codeine, and thebaine
- Perform the previously developed method on poppy seed samples using the different LFIAs
- Analyze the results to determine which LFIA performs the best by evaluating method performance characteristics such as sensitivity, specificity, precision, threshold, false positive rate, false negative rate, minimum detectable concentration, and ruggedness/robustness.

Project Needs and Duration:

- Lab bench work experience including use of pipettes and balances
- Analytical chemistry
- Excellent communication skills

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

 The opium poppy plant is a pharmaceutical source of opiate alkaloids; however, the seeds of the opium poppy are also cultivated and harvested for use in food. Poppy seeds contain varying amounts of morphine, codeine, and thebaine because opiate alkaloids can be transferred to the surface of poppy seeds during harvest. The consumption of poppy seed-containing food can cause adverse health effects or lead to the failure of urine opioid tests. In addition, opioid dependence can be developed, or overdose can occur upon consumption of a tea-like beverage that is produced by steeping poppy seeds in water. A lateral flow immunoassay (LFIA) method was developed in a previous proof-of-concept study that uses tap water for opiate alkaloid extraction from poppy seeds to provide a portable, low-cost screening method for the qualitative detection of morphine and codeine on poppy seeds. In this work, LFIAs from various vendors will be evaluated for use in the previously developed screening method to improve the rapid qualitative detection of opiate alkaloids on poppy seeds to ensure the safety of poppy seeds intended for human consumption.

Principle Investigator: Genualdi, Susan

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

1. Homogenize and weigh out samples
2. Become trained in analytical methods and extraction procedures
3. Assist in instrumental and data analysis using LC-MS/MS
4. Organize data using Excel

Project Needs and Duration:

1. Coursework in general and analytical chemistry
2. Familiarity with general laboratory practices such as pipetting and using a balance.
3. Computer skills including excel
4. Interest in working with a team of scientists, learning new techniques and contributing to a team project

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

 The distribution and presence of PFAS in foods has been of interest to the FDA for several years. The FDA developed an analytical method for 30 PFAS in foods that has been used to analyze thousands of food samples. These samples have included total diet study samples, seafood samples, and various food and feed samples for state partners. Over the years the method has been improved, new technologies tested, and the analyte list has expanded. In the current project, the method will be used to analyze samples of interest to the FDA for PFAS including infant formula and samples from state partners. More data is essential for risk assessment calculations and a better understanding of PFAS distribution in food. Additional testing may also include expanding the analyte list and testing of lab grown crop samples, performing a multi-lab validation of the FDA method, and performing a multi-lab validation on a new joint method with the USDA.

Principle Investigator: Lindahl-Ackerman, Luke

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

- Prepare additive/contaminant chemical standards for DART-MS analysis
- Collect DART-MS spectra for additives/contaminants
- Tabulate DART-MS spectral database

Project Needs and Duration:

- BS level General Chemistry AND Organic Chemistry 1 and laboratory course work.
- BS level Quantitative or Analytical Chemistry laboratory OR >1 month part time laboratory orsolutions prep work experience (ie research assistant, stockroom, chemical safety, or laboratoryassistant).
- >1 months paid work experience, including work-study aid.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

There is very little information on the occurrence of different indirect additives and packaging contaminants in the US market. This project is to develop a rapid mass spectrometric method for packaging material and contaminant identification which could be used to generate data to support rapid, post-market survey-based packaging additive/contaminant exposure estimates.

Principle Investigator: Wong, Jon

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

- Maintain inventory of pesticide and other chemical standards.
- Develop high resolution MS/MS libraries and compound databases for pesticides and other chemicals (veterinary drugs and mycotoxins).
- Develop methods to analyze and screen pesticides in different (primarily low moisture and high fat) food types.
- Operate LC-MS instruments and process results.
- Interpret results.

Project Needs and Duration:

- Good academic standing.
- Background in science, engineering (preferably science or engineering majors).
- Strong work ethic, inquisitive, pro-active, comfortable in a laboratory environment.
- Coursework in general and organic chemistry preferred but not required.
- Interested in science or engineering.
- Good computer skills.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

One of the roles of the FDA's food safety program is to monitor for the presence of chemical residues and contaminants such as pesticides in foods. The FDA is responsible to enforce pesticide tolerances that are established by the U.S. Environmental Protection Agency. Since there are many pesticides and food types, improvement of current methods or development of  methods to identify and quantify these potentially harmful chemicals presents many challenges.  This research involves the development of new technology and the expansion of current  procedures to new chemicals and food matrices for monitoring and surveillance. This research will involve the use of liquid chromatography-high resolution mass spectrometry and a non- targeted Data Acquisition for Target Analysis (nDATA) workflow to expand and improve current FDA procedures for the analysis of pesticides and other residues and contaminants (e.g., veterinary drugs, mycotoxins) in FDA regulated products. These applications will result in the  improvement or complement existing procedures by providing rugged, rapid, and robust multiresidue methods suitable for FDA and non-FDA laboratories.

Principle Investigator: Zhang, Kai

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

- Conduct mycotoxin testing in plant-based foods using the FDA Compendial Method C-003: stable isotope dilution assay (SIDA) coupled with LC–MS/MS.
- Analyze survey samples to generate mycotoxin occurrence and concentration data to support risk assessment and dietary exposure studies.
- Develop sample homogenization procedures for complex matrices, with an emphasis on tree nuts.
- Analyze and interpret results, communicate key findings through presentations, and draft scientific manuscripts for publication.

Project Needs and Duration:

- Dedication to food safety
- Interests in food analysis
- Basic understanding of analytical chemistry

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Survey-based occurrence data on mycotoxins in foods are essential for dietary exposure estimation and risk assessment. Reflecting current U.S. dietary patterns and increased consumer focus on health and nutrition, this study targets three priority commodity areas for mycotoxin surveillance: plant-based meat products, apple puree, and tree nuts.

Mycotoxins in plant-based meat alternatives represent a significant yet insufficiently characterized food safety concern because these products rely heavily on plant-derived ingredients (e.g., grains, legumes, and pulses) that may support fungal growth and subsequent mycotoxin formation. Patulin in apple puree and other apple-based foods is another key concern, as these products are commonly consumed by young children and may contribute meaningfully to early-life dietary exposure. Tree nuts (e.g., pistachios) are high-value agricultural commodities and popular snacks, making it important that mycotoxin contamination can be controlled at levels that protect consumers and satisfy importing countries’ regulatory requirements. At the same time, mycotoxin testing in tree nuts presents practical challenges because it is difficult to achieve a homogeneous sample mixture; therefore, there is a need to develop feasible homogenization approaches and subsampling plans that produce representative test portions. Given the continued growth in plant-based meat consumption and the widespread intake of apple- and nut-based foods, robust occurrence data are necessary to address existing data gaps across these commodities. The objectives of this study are to: 1) conduct a matrix extension of Compendial Method C-003 to include plant-based meat alternative foods and tree nuts in accordance with FDA Foods Program Guidelines for the Validation of Chemical Methods, and then analyze commercially available plant-based meat alternative products (collected in coordination with the Office of Post-Market Assessment) and tree nuts to characterize mycotoxin occurrence; 2) survey patulin in commercially available apple puree and related apple-based foods to generate data suitable for estimating dietary exposure among young children who frequently consume apple-based products; and 3) evaluate and develop practical tree nut (e.g., pistachio with shells) sample homogenization tools and subsampling plans to improve the reliability and representativeness of test portions for mycotoxin analysis.

Principle Investigator: Danica DeGroot, Christopher Kampmeyer

Location: Human Foods Program (HFP) University Station, 4300 River Road, College Park, MD In-Person)

Objective:

- Development of standardized AI prompts. Create and refine systematic prompt engineering approaches to evaluate AI-based screening tools for GRAS submissions. Establish consistent methodologies for leveraging AI capabilities in regulatory document review processes.

- Historical Data Analysis. Apply the developed AI prompts to analyze previously submitted GRAS notifications and submissions. Generate comprehensive screening results using AI-assisted methods on existing regulatory datasets.

- Validation Against Expert Review. Conduct comparative analysis between AI-generated screening results and determinations made by experienced FDA regulatory scientists. Quantify the accuracy and reliability of AI-assisted screening relative to established expert review standards.

- Deficiency Detection Assessment. Administrative deficiencies: Missing documentation, formatting issues, incomplete forms. Scientific deficiencies: Inadequate safety data, flawed study designs, insufficient evidence. Regulatory deficiencies: Non-compliance with FDA guidelines, missing required elements, procedural gaps

- Comparative GRAS Assessment. Apply developed AI prompts to compare new submissions against previous GRAS notices that received a “No questions letter” from the FDA. Prompts will assess if the identity of a substance and intended uses align with previous notices to facilitate streamlined review processes where applicable. Efficient utilization of this workflow would streamline identification of submissions that do not require full review because they would be covered by submitted GRAS notices that have already undergone rigorous expert review.

Project Needs and Duration:

- Experience with prompt engineering, natural language processing or model evaluation
- Solid understanding of the basics of biology, chemistry, or physiology
- Major in Computer Science with a biological sciences background would be ideal

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

 The Office of Pre-Market Additive Safety (OPMAS) within the FDA’s Human Foods Program is responsible for administering the Generally Recognized as Safe (GRAS) Notification Program. This program allows stakeholders to voluntarily notify the FDA that a food ingredient is GRAS. To date, FDA has reviewed over 1200 GRAS submissions for a wide variety of food substances, including microorganisms, proteins, fibers, and sweeteners. When a GRAS submission is received by FDA, it is screened by a team of subject matter experts to determine if the submission is suitable to undergo a more comprehensive evaluation. While necessary, this screening process is time-consuming and resource intensive and may have the potential for enhanced efficiency.

Recent advances in artificial intelligence present an opportunity to supplement traditional review methods with automated screening capabilities. The FDA has developed specialized AI-based tools designed specifically for regulatory document analysis, creating a unique opportunity to evaluate their practical application in GRAS submission screening.

The intern will conduct an evaluation of these newly developed AI tools to assess their:

- Overall usefulness in identifying key GRAS submission elements
- Accuracy compared to expert reviewer determinations
- Efficiency gains in processing time and resource utilization

This research will provide critical data to inform future integration of AI technologies into FDA's initial regulatory review processes, potentially improving both the speed and consistency of GRAS submission screening while maintaining the high scientific standards required for food safety evaluation.

Principle Investigator: Hughes, Jamie

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

Data Analysis & Transparency
- Analyze existing datasets to identify trends, patterns, and actionable insights
- Design and build interactive dashboards for organizational performance metrics
- Create data visualizations that make complex information accessible to non-technical stakeholders

Process Automation & Efficiency
- Identify repetitive manual tasks suitable for automation
- Develop automated report generation systems
- Create workflow automation tools and smart templates
- Build automated communication systems for sample and inspection results
- Design routing protocols and alert mechanisms to ensure critical information reaches appropriate personnel immediately

Technical Development
- Develop custom applications and tools based on process needs
- Integrate disparate data systems for seamless information flow
- Document automation processes and create user guides for new tools

Impact & Outcomes
- Reduce time spent on manual administrative tasks
- Improve response times for public health risk identification
- Enhance decision-making through data-driven insights
- Increase organizational transparency and accountability
- Deliver measurable efficiency gains in staff time utilization

Project Needs and Duration:

Technical Skills
- Proficiency in Microsoft Excel for data analysis and manipulation
- Experience with Power BI, Tableau, or similar dashboard/data visualization tools preferred or demonstrated ability to self-teach using open source options
- Experience with Power Automate for workflow automation and automated communications preferred
- Experience with Power Apps for custom application development preferred
- Familiarity with SharePoint for data management and collaboration preferred
- Familiarity with low code syntax, e.g. used in Tableau, PowerBI, Power Apps

Academic Background
- Coursework in computer science, analytics, and/or statistics
- Understanding of data analysis methodologies and statistical concepts

Professional Competencies
- Ability to work both independently, exercise resourcefulness, and serve as a technical lead on small teams
- Problem-solving skills with attention to detail and accuracy
- Ability to translate user needs into technical solutions

Preferred Experience
- Prior experience using PowerBI, Power Automate, and Power Apps or developing tech enhanced tools to provide solutions to project needs
- Demonstrated ability to identify process improvement and tool enhancement opportunities

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Our office in the Human Foods Program, Office of Compliance and Enforcement, is undertaking a transformative initiative to harness the power of data while modernizing how we work. This project addresses two critical needs: making our organizational data more transparent and accessible, and eliminating inefficiencies that consume valuable staff time.

The data transparency component involves analyzing existing datasets to surface insights that currently remain buried in spreadsheets and disparate systems. The intern will develop interactive dashboards that translate complex information into clear, actionable visualizations, enabling stakeholders across the organization to make informed decisions quickly. This work will fundamentally change how we understand our operations, replacing guesswork with evidence-based strategy.

The efficiency component tackles the manual, repetitive tasks that slow our team down and improving real time information sharing. By identifying automation opportunities and developing tech-enhanced tools, the intern will create sustainable solutions that streamline workflows—from automated report generation to smart templates and custom applications. A critical focus will be implementing automated communication systems that ensure samples and inspections indicating potential public health risks are immediately flagged and routed to the appropriate personnel. This automated alerting will eliminate delays in critical information flow, ensuring faster response times when health and safety concerns emerge. These innovations will free staff to focus on strategic work rather than administrative burdens, while simultaneously strengthening our ability to protect public health.

This project offers substantial organizational value while providing the intern with real-world experience in data analysis, dashboard development, and process automation. The deliverables will have immediate, measurable impact: better-informed leadership, transparent performance metrics, and reclaimed staff hours that can be redirected toward mission-critical work.

Principle Investigator: Timme, Ruth

Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)

Objective:

1. Identify isolates collected as part of FDA inspections, beginning with FDA swab isolates from food manufacturing facilities, which are readily identifiable in NCBI.
2. Collect or gain access to the historical inspection records associated with the isolates identified in Objective 1.
3. Develop an approach to standardize these historical records according to the new metadata package, update the corresponding NCBI records, and support development of a standardized process for documenting future sample collection.

Project Needs and Duration:

Bioinformatics, data science, biology, food science, or microbiology.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Pathogen genomic surveillance is a core component of modern public health and regulatory science, supporting the FDA’s mission to ensure food safety and prevent disease outbreaks. FDA leverages genomic technologies to monitor, trace, and mitigate the spread of foodborne pathogens, relying heavily on the National Center for Biotechnology Information (NCBI) database as the public repository for genomic data and associated contextual information.

In collaboration with CDC, USDA, and NCBI, FDA has developed a new metadata package that expands the contextual details captured for each isolate — whether from humans, animals, food products, food facilities, or farm environments. Once fully implemented, this package will be used for FDA’s food samples, facility inspection samples, and farm inspection samples. These additional metadata fields will provide critical, standardized information for risk assessment activities in a format that is easy to access and analyze.

This project focuses on implementing the new metadata package across FDA laboratories in FDA/HFP/ORTS. During the initial rollout, we’ve encountered unique challenges. Many bacterial isolates collected during FDA facility inspections have detailed collection information associated with them, but the documentation is not standardized. Inspectors often record notes and photographs in narrative PDF reports, and laboratorians must interpret and translate these materials into standardized fields—an approach that is time-consuming, inconsistent, and not scalable.

The intern’s project will center on standardizing historical collection data from FDA inspections. FDA inspectors document where they swab within a facility and submit this information as part of the inspection report. These PDFs are not always uniform or easy to extract structured data from. To support full implementation of the new metadata package, we need to digitize, standardize, and organize these historical records.

Our goal is to compile a clean, standardized dataset describing relevant isolates collected during FDA inspections. Once this dataset is assembled, we will integrate these standardized metadata into the NCBI BioSample database, significantly increasing the value of these isolates to FDA, public health partners, and researchers across the U.S.