-
Trainingarrow_drop_down
- About Training
-
Internationalarrow_drop_down
- About International
- Produce Safety Alliance Grower Training
- Good Fishing Vessel Practices
- Aquaculture Training Programs
- Good Agricultural Practices
- Commercially Sterile Packaged Foods
- Food Inspector Training
- Supply Chain Management for Spices and Botanical Ingredients
- WTO-SPS Professional Development
- Training Data
-
Collaborationsarrow_drop_down
- About Collaborations
-
International Collaborationsarrow_drop_down
- About International Collaborations
- About Collaborative Training Initiatives
- Collaborative Produce Safety Training Initiative
- Bangladesh Aquatic and Aquacultural Food Safety Center
- IICA-JIFSAN Collaborative Training Initiative for the Americas
- India Supply Chain Management for Spices and Botanical Ingredients (SCMSBI)
- Malaysia Ministry of Health Collaborative Framework on Food Safety Capacity Building
- Thailand Center for Commercially Sterile Packaged Foods
- About
- News & Events
- Training
- Research
-
Collaborations
-
International Collaborations
- About Collaborative Training Initiatives
- Collaborative Produce Safety Training Initiative
- Bangladesh Aquatic and Aquacultural Food Safety Center
- IICA-JIFSAN Collaborative Training Initiative for the Americas
- India Supply Chain Management for Spices and Botanical Ingredients (SCMSBI)
- Malaysia Ministry of Health Collaborative Framework on Food Safety Capacity Building
- Thailand Center for Commercially Sterile Packaged Foods
- Partnerships
-
International Collaborations
- Informatics
Internship Projects
The JIFSAN internship program allows undergraduate students at the University of Maryland, College Park to participate in research at FDA facilities, including the Harvey Wiley Building in College Park and the MOD1 & MOD11 facilities on Muirkirk Road in Laurel, MD. Internships require a time commitment of 8-10 hours/week during the semester and 30 hours/week during winterterm and summer.
Internships generally begin in the summer and continue through the subsequent academic year. Currently, projects seeking interns are posted in February and for best consideration, applications should be submitted by March 15. Students may apply by submitting a complete application including: 1) JIFSAN Paid Internship Initial Application, 2) Resume/CV, and 3) Unofficial transcript (including courses for which you are already registered). All three items should be assembled into a single PDF document and uploaded to the webform located at go.umd.edu/JIFSAN2025 . Please do not reach out to FDA mentors directly in regards to JIFSAN internships. All queries and applications should be routed to Dr. Kaci Thompson or the JIFSAN office.
Concentrations
Click on a concentration to jump to projects in that category:
Biological Sciences
Evaluation of the effectiveness of post-harvest treatment of enoki mushrooms for reduction of Listeria monocytogenes
Principle Investigator: Burall, Laurel
Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD (In-Person)
Objective:
- Evaluate the efficacy of various post-harvest treatments, such as boiling or treatment with organic acids, to reduce and/or control the amount of Listeria monocytogenes on enoki mushrooms after harvest.
- Contaminate mushrooms at different points during cultivation determine if earlier or later contamination events alters the efficacy of the treatments at harvest or consumption.
- Evaluate whether storage post-treatment alters the assessment of the treatment’s efficacy by determining whether bacteria grow or return to detectable levels, depending on initial treatment efficacy, during the standard shelf-life of the mushrooms.
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).
Development and Validation of Improved Molecular Detection and Characterization of L. monocytogenes and Listeria spp. in Food and Environmental Matrices
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.
Evaluation of the New Approach Methodologies (NAMs) for Propagation of Cyclospora cayetanensis
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.
Determination of virulence potential of Listeria monocytogenes in relation to its effect on gut barrier function
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.
Evaluating the detection of Salmonella from artificially contaminated cucumbers using Targeted Amplicon Sequencing and Whole Metagenomic Sequencing
Principle Investigator: Patel, Isha
Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD (In-Person)
Objective:
1. Determine limit of detection of artificially contaminated Salmonella when spiked at different CFU in cucumbers using DNA isolated from different kits.
2. Use BAM approved method for Salmonella to confirm the presence of the pathogen in the artificially spiked samples.
Project Needs and Duration:
- Interns from any of the following disciplines would be desirable: microbiology, molecular biology, cell biology, and biochemistry.
- Basic laboratory experience in microbiology/molecular biology/cell biology would be preferable. 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:
A major challenge in fresh produce associated outbreaks is to selectively enrich and detect low level foodborne pathogens accurately and rapidly. The short shelf-life and complex microbial environment of fresh produce make source tracking during outbreaks difficult. Recent Salmonella outbreaks linked to cucumbers highlight the need for improved detection methods to protect public health. Current culture-based methods for pathogen detection can be time-consuming, often taking several days to produce results, which is a considerable delay when dealing with perishable foods and potential outbreaks. To address this, we will evaluate two culture-independent sequencing methods: Targeted Amplicon Sequencing (TAS) and Whole Metagenomic Sequencing (WMS). This project will compare the effectiveness of these two approaches for detecting Salmonella on artificially contaminated cucumbers. TAS offers a highly specific approach by amplifying genes unique to the target pathogen, which may enhance the detection of low-level contamination that could otherwise be missed. In contrast, WMS provides a comprehensive view of the entire microbial community, which can be valuable for understanding the broader microbial landscape but may be less sensitive for detecting a specific pathogen in a complex sample. Our goal is to determine which of these sequencing methods, or a combination of both, provides the most sensitive, accurate, and rapid detection of Salmonella on cucumbers. If successful, this research will lead to a validated and highly sensitive detection method that can be implemented to improve food safety surveillance. Development of this rapid genomic screening method will enable field investigators to examine official samples for specific cucumber-related outbreak strains of Salmonella in real-time, an ability we currently lack in field testing at this time.
Expansion of a Targeted Metagenomic Method for the Detection and Identification of Arthropod Contaminants in Diverse Food Matrices
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.
Development of Enhanced Methodologies for Purification, Sporulation and Excystation of Cyclospora cayetanensis Oocysts
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.
Molecular detection of Cyclospora cayetanensis in herbs and soil
Description:
Cyclospora cayetanensis causes a diarrheal illness called cyclosporiasis. Outbreaks of cyclosporiasis have historically affected thousands of persons in the U.S and often occur in multi-state fashion. The outbreaks in the U.S. have been frequently linked to fresh produce. However, there are significant gaps in our knowledge of the epidemiology of C. cayetanensis, and still to date there is not a clear understanding of the relative importance of the sources and routes of transmission of C. cayetanensis infection. The potential of contaminated soil as a source of infection needs to be considered. Cyclospora oocysts are highly resistant in the environment (soil and/or water) and to chemical disinfectants, and to date there is not a clear understanding of the relative importance of the sources and routes of transmission of C. cayetanensis infection. Contact with soil has been found to be a risk factor for C. cayetanensis infection in endemic areas, such as in Peru, Guatemala, and Venezuela, as well as in an outbreak in the U.S. Furthermore, C. cayetanensis has been recently found in soil collected from under the water drippers from vegetable plots in Italy and in soil from commercial berry farms in Mexico. These data suggest that contact with soil may be an important mode of transmission and could play a role in the contamination of foods. Our group recently developed a fast and sensitive method for the detection of C. cayetanensis in soil. This method will be used in the present project for detection of the parasite in soil artificially contaminated with oocysts using the GEN1000 CONVIRON growth chambers, under controlled environmental conditions. The main objective is to determine the effects that the environmental factors (type of soil, temperature, water, humidity, and photoperiod) have in C. cayetanensis detection, and possibly survival/sporulation, in soil and herbs artificially contaminated with the parasite, and to evaluate the seasonality trends. These data will allow FDA to better understand ways of C. cayetanensis transmission and to establish control measures to disrupt the cycle of transmission. This project will also help in filling gaps in risk assessment of C. cayetanensis in soil, which to date has not been performed.
Evaluation of the Performance of the FDA Validated Method for Detection of Cyclospora cayetanensis on Different Water Sources
Description:
Cyclospora cayetanensis is a protozoan parasite that causes a foodborne diarrheal illness called cyclosporiasis which is linked to the consumption of contaminated fresh produce including leafy greens, snow peas, and berries. Since 2013 there has been an increase in the number of domestically acquired laboratory-confirmed cases of cyclosporiasis. The potential use of contaminated water for agricultural purposes poses a significant public health issue to millions of people worldwide and a method for detection of C. cayetanensis in agricultural water was recently validated and published in the FDA’s BAM Chapter 19c. There is a need to evaluate the performance of this method in different water sources such as well water, produce wash water, wastewater, and surface water, among others. There is also a need to develop and apply new generation of molecular markers for detection and for genotyping in environmental samples. This study will provide FDA with tools to accumulate scientific data about the different water matrices and their impact in the transmission of C. cayetanensis.
Development and enhancement of structure-searchable toxicology databases derived from FDA in-house toxicity data
Description:
The intern will assist with the collection of toxicology data from OFAS legacy records for incorporation into the Chemical Evaluation and Risk Estimation System (CERES). Updated and detailed toxicology information in CERES is used by OFCSDSI scientists to support their scientific evaluations of food additives and packaging materials through read across, filling data gaps, and computational toxicology analyses. Utilizing legacy data in this manner is in line with the 3Rs (Replacement, Reduction, and Refinement) as it reduces the need for additional testing potentially involving animal studies.
Database and predictive models for skin permeability of chemicals
Description:
Understanding dermal absorption is important for risk assessment of cosmetic ingredients. Skin permeability is a key parameter to predict the absorption and disposition of chemicals through skin into systemic circulation. A reliable prediction of skin permeability of chemicals can support the development of a physiologically based pharmacokinetic (PBPK) model after dermal exposure; which would predict an internal dose to facilitate a toxicological risk assessment. Predictive modeling of transdermal absorption started in the early 1940s. With advancements in computational modeling, different types of algorithms and models, such as Potts-Guy model, Cleek-Bunge model, Wang-Kasting-Nitsche model, etc., were reported. Compilation of a well-curated database that includes permeability data for chemicals of interest to cosmetics risk assessment would be beneficial for both research and regulatory use to create reliable predictive models for skin permeation. The Modernization of Cosmetics Regulation Act of 2022 (MoCRA) indicates the sense from Congress that animal testing should not be used for the purposes of cosmetic safety assessment (with the exception of appropriate allowances). In addition, given that animal testing is being banned in a number of jurisdictions and cosmetics are marketed internationally, it is critical that validated alternative methods are developed. Therefore, reliable and robust skin permeability data will be needed to predict the toxicity from exposure to cosmetics. A database of skin permeation data and a repository of skin permeability predictive models would support dermal exposure assessment of cosmetic ingredients and potential impurities in cosmetic products. In the 2024-2025 project, we developed a user-friendly interface for the database and commonly used predictive models for skin permeability executable locally and online (https://dermal-permeability.onrender.com/), and added key experimental parameters by reviewing in vivo and in vitro skin permeability guidances from EFSA, OECD and WHO. In the 2025-2026 project, we will focus on adding skin permeability data from publications to the database with assistance from generative artificial intelligence (AI). Additionally, we will identify AI/Machine Learning (ML) and/or mechanistically based models to predict skin permeability.
Horizon Scanning and Trend Analysis in Agricultural Biotechnology
Description:
Plant genetic engineering and genome editing are rapidly advancing, making it possible for a growing number of plant biotechnology developers to bring food crops with innovative new traits to the market. The Innovative Foods Staff in FDA’s Office of Food Chemical Safety, Dietary Supplements, and Innovation (OFCSDSI), works with developers to ensure that food from new plant varieties developed with biotechnology are safe and lawful. To be successful in their mission to protect public health while supporting scientific innovation, it is important that members of this team are prepared for future developments in the use of plant biotechnology in the food supply.
Horizon scanning is a process intended to gather information to help anticipate and prepare for future developments. This project is a horizon scanning activity that involves monitoring publicly available news and scientific literature for information about the use of plant biotechnology in plants used as food. Information about potential plant biotechnology pipeline products will be added to an internal database for future reference and to enable trend analysis.
The Innovative Foods Staff has an internal “plant biotechnology pipeline monitoring” database. This database has been updated manually by our previous and current JIFSAN Interns. To make the process more efficient, we plan to establish an automatic system through a machine learning approach by partnering with HFP’s WILEE team. The goal is to train WILEE to identify relevant news and scientific literature from publicly available databases and to extract information from those articles for populating the “plant biotechnology pipeline.” This will help OFCSDSI and the agency understand new trends, identify emerging developers, and track global developments in food and agricultural biotechnology.
Development of a Rapid Targeted Amplicon Next Generation Sequence-Based Detection Method for Foodborne Pathogens in Leafy Green Produce
Description:
A major challenge in fresh produce associated outbreaks is to selectively enrich and detect low level foodborne pathogens accurately and rapidly. The short shelf-life of leafy greens makes source tracking difficult. Currently, established WGS methods using the Illumina MiSeq take up to 3 days to sequence and analyze the data once the isolate is selectively enriched. We propose a targeted amplification method followed by metagenomic sequencing approach using the Oxford Nanopore GridION. The GridION offers a unique, scalable sequencing approach that enables direct near real-time sequencing and an overall reduction in the time to obtain results. This is an advantage over the current Illumina based methods that take up to 2 days for the sequencing run to end. With GridION, data analysis can be performed while sequencing is in progress and therefore eliminates the need to wait for the sequencing to be completed thus saving on time. Our goal is to target and amplify pathogen specific genes to improve the detection of those pathogens present in lower amounts that may go undetected due to the abundance of microflora in metagenomic samples. If successful, the outcome of this research will be a highly sensitivity method capable of detecting low-level pathogens in leafy greens and produce. In addition, with near real-time information using the GridION, the response time and source attribution during outbreaks is expected to save at least 2 days. All this goes toward supporting FDA’s regulatory role in protecting public health.
A Metagenomic Approach using Target Enrichment-based Next Generation Sequencing for Detecting and Identifying Insect Fragments in Food
Description:
Developing a metagenomics method for identifying arthropods in food products.
Food products can be adulterated with insects. Insect fragments in food are currently detected by removing them from the food matrix and then quantifying and taxonomically identifying them via microscopic analysis. For regulatory purposes, both identification and quantification are pertinent because they offer details about the degree and source of insect adulteration (field pests versus storage pests, for instance). Nevertheless, taxonomical identification of the insect fragments through microscopy takes a long time and requires a high level of expertise from the analysts. It also doesn't always yield resolution down to the species level.
The study of metagenomics makes it possible to create new methods for more accurately identifying eukaryotes, like insects, in food samples. Because eucaryotic species have multiple copies of their mitochondrial DNA, metagenomics becomes extremely sensitive when paired with mitochondrial sequencing.
This project uses shotgun metagenomics to develop and validate a new method for detection and identification of insect fragments in food products. Once validated, this method will be applied in labs to identify more insects found in food and stop food that contains avoidable insect contamination from getting to consumers.
Evaluation of the use of a gut-on-a-chip system for in vitro Propagation of Cyclospora cayetanensis
Description:
Cyclospora cayetanensis, a microscopic intestinal parasite, causes food-borne and water-borne infections in endemic and epidemic fashion worldwide. In the US, food-borne outbreaks of C. cayetanensis have been an ongoing public health problem since mid-1990s. Current scientific knowledge suggest that this parasite is human specific, causes an intestinal disease called cyclosporiasis. Previous studies were unable to show propagation of C. cayetanensis in in vivo or in vitro systems. Also, due to the lack of animal models, the only source for oocysts for the research program to propagate C. cayetanensis in vitro, would be the oocysts obtained from patient stool samples. Scarcity of these samples renders such research impossible. To overcome this hurdle, we propose to use other related apicomplexan organisms such as Cryptosporidium spp., Toxoplasma gondii, and/or Eimeria spp., that could serve as a model for evaluating the gut-on-a-chip model, prior to testing C. cayetanensis. Cryptosporidium oocysts are the only commercially available oocysts, making these organisms amenable for starting this research projects. The organ-on-a-chip technology emulates the complexity of human gut structurally and physiologically in vitro, providing a viable research platform for challenging scientific problems such as in vitro propagation of C. cayetanensis.
Evaluation of the use of a gut-on-a-chip system for in vitro Propagation of Cyclospora cayetanensis
Description:
Cyclospora cayetanensis, a microscopic intestinal parasite, causes food-borne and water-borne infections in endemic and epidemic fashion worldwide. In the US, food-borne outbreaks of C. cayetanensis have been an ongoing public health problem since mid-1990s. Current scientific knowledge suggest that this parasite is human specific, causes an intestinal disease called cyclosporiasis. Previous studies were unable to show propagation of C. cayetanensis in in vivo or in vitro systems. Also, due to the lack of animal models, the only source for oocysts for the research program to propagate C. cayetanensis in vitro, would be the oocysts obtained from patient stool samples. Scarcity of these samples renders such research impossible. To overcome this hurdle, we propose to use other related apicomplexan organisms such as Cryptosporidium spp., Toxoplasma gondii, and/or Eimeria spp., that could serve as a model for evaluating the gut-on-a-chip model, prior to testing C. cayetanensis. Cryptosporidium oocysts are the only commercially available oocysts, making these organisms amenable for starting this research projects. The organ-on-a-chip technology emulates the complexity of human gut structurally and physiologically in vitro, providing a viable research platform for challenging scientific problems such as in vitro propagation of C. cayetanensis.
Chemistry
Improved data analysis pipelines for global chemical screening approaches
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.
Single Lab Validation of a Nitrogen Sustained Microwave Inductively Coupled Plasma Optical Emission Spectrometer for Nutrient Element Analysis of Foods
Principle Investigator: Carter, Jake
Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)
Objective:
- Learn applied atomic spectroscopy theory to better understand potential pitfalls between different atomic spectrometry techniques and different plasma sources.
- 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.
- 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.
- Prepare external standard calibration curves for quantitative analysis on plasma OES instruments.
- Perform daily instrument checks and calibrations. Maintain instruments throughout the project (e.g., cleaning plasma torches, changing pump tubing, calibrating instrument spectrometer).
- Perform instrumental analyses of all validation foods to meet the definition of single lab validation in the Chemical Methods Food Validation Guidelines.
- 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.
Multi-laboratory Validation of a LC-MS/MS Method for the Quantification of Morphine, Codeine, and Thebaine on Poppy Seeds
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.
Investigation of PFAS in Foods
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.
Developing a food packaging additive/contaminant mass spectral database
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.
Single Laboratory Validation of Commercial Allergen ELISA Test Kits
Principle Investigator: Panda, Rakhi
Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)
Objective:
- Preparation of model allergen incurred/spiked food materials.
- Analysis of allergen spiked/incurred materials by commercial ELISAs.
- Data analysis and evaluation of method validation parameters.
Project Needs and Duration:
Basic pipetting skill, skills of weighing and measuring accurately, knowledge of food product preparation. Courses in Analytical Chemistry and Basic Food Science would be beneficial.
Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.
Description:
Food allergy affects approximately 6% of adults and children in the United States, requiring strict avoidance of allergen containing products. Enzyme-linked immunosorbent Assays (ELISAs) are routinely used for analysis of allergens in foods and dietary supplements. FDA relies on commercial ELISA test kits for analysis of allergens in regulatory samples. However, many commercial test kits are used based only on the kit company’s internal validation studies. FDA Foods Program Chemical Method Validation guidelines require that methods are single laboratory validated for routine regulatory testing. The goal of this study is to complete single-lab validations of commercial ELISA test kits currently being used by FDA for allergen analysis. The intern will be involved in preparation of model incurred/spiked food materials, and analysis of these materials by commercial ELISA test kits to support the validation study. The intern will also be involved in data analysis and evaluation of validation parameters.
Quantitation of gluten in fermented or hydrolyzed foods by a multiplex competitive ELISA
Description:
Celiac disease (CD) affects approximately 1% of the world’s population and is triggered by the interaction of gluten (from wheat, rye and barley and possibly oat) with the intestinal mucosa of sensitive individuals. Currently there is no treatment available for CD, and the only option to avoid a serious reaction is to follow a lifelong gluten-free diet. Reliable and accurate quantitation of gluten in foods and ingredients is paramount to meet this goal as well as to comply with the gluten-free regulations enacted by the regulatory bodies throughout the world. Accurate quantitation of gluten in fermented or hydrolyzed foods is challenging due to the lack of appropriate calibrants and variable proteolysis. Recently, it was possible to accurately quantitate gluten in dairy products and sourdough using gluten-incurred yogurt as a calibrant with a multiplex-competitive ELISA. Further, an intact gluten calibrant has been evaluated, and the calibrant is currently being used with the multiplex-competitive ELISA to quantify gluten in dairy products and sourdough, to provide information on ppm “intact gluten equivalent” present in the fermented foods. The intern working on this project will use both the intact gluten calibrant and the incurred yogurt calibrant with the multiplex-competitive ELISA to evaluate gluten quantitation in fermented foods such as alcoholic cider, cheese, kombucha, beer, and vinegar. The intern will be involved in the preparation of gluten incurred model fermented or hydrolyzed foods, analysis of the products by the multiplex-competitive ELISA, and assist with the validation process of the method.
Analysis of cannabis-derived consumer products by LC-MS
Description:
In the past few years, there has been a growing interest in cannabis-derived products and many diverse product formulations are available to consumers. As the cannabinoid market diversifies and emerging natural and synthetic cannabinoids gain popularity, it is critical to evolve market surveillance capabilities to understand emerging cannabinoid hemp product (CHP) market segments. Traditional approaches use targeted methods to measure concentrations of key bioactives (e.g., cannabinoids), contaminants, and impurities. However, as new formulations of CHPs are brought to the market, a method capable of recognizing all known cannabinoids and structurally related compounds is needed. In the current project, a non-targeted LC-HRMS method and molecular networking workflow will be developed to recognize natural, synthetic, and cannabinoid-derived synthetic byproducts in complex matrices, including foods and products marketed as dietary supplements. This strategy will provide the Agency with a better understanding of emerging CHPs in the current marketplace and offer a robust analytical solution to identify safety signals and inform a new regulatory framework for CHPs.
Nutritional Sciences
Other
Identifying trends in the production and use of cosmetics by analyzing industry and consumer inquiries
Description:
The Modernization of Cosmetics Regulation Act of 2022 (MoCRA) is the most significant expansion of FDA’s authority to regulate cosmetics since the Federal Food, Drug, and Cosmetic (FD&C) Act was passed in 1938. This new law will help ensure the safety of cosmetic products many consumers use daily. With the passage of this new law, we have received an influx of questions from consumers and the regulated industry alike to our Food and Cosmetics Information Center (FCIC) and to our QuestionsAboutMoCRA@fda.hhs.gov email addresses. These questions have provided insights into areas of the law that need further clarification and eventual guidance, as well as letting us know some of industry’s concerns regarding implementation of many of the provisions. In addition to providing customer service to these inquirers, these inquiries provide valuable data, which, when analyzed, will allow FDA to better prioritize use of its limited public health resources. In the 2024-2025 project, we developed metrics and implemented certain process improvements. For the 2025-2026 project, we will refine and enhance the previous metrics using a new process, and measure the success of process interventions using these new metrics.
Public Health
Artificial Intelligence Tools to Screen Food Ingredient Safety Submissions
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.
HFP Data Transparency and Work Plan Efficiency Building
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.
Standardizing Pathogen Genomic Surveillance Data
Principle Investigator: Timme, Ruth
Location: Human Foods Program (HFP) Wiley Building, 5001 Campus Drive, College Park, MD (In-Person)
Objective:
Project Needs and Duration:
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.
Trade Complaint Review Process Development and Implementation
Description:
HFP receives a number of complaints from industry members each year indicating concerns, potential hazards or non-compliant regulatory behaviors. The Office of Compliance (OC) plays a leadership role in managing the review and monitoring the follow-up of these complaints. OC is seeking an intern to assist with re-envisioning the review procedure, automating the process and assisting with the monitoring of complaints received.
Data Generation, Preparation and Cleaning for Machine Learning Applications
Description:
The Warp Intelligent Learning Engine (WILEE) is a Division of Additives and Ingredients initiated project to develop a data product that will provide the Human Foods Program with an advanced data driven risked based decision-making tool. This tool leverages AI technologies to integrate and process a large variety of data sources, generating reports with quick insights that will significantly improve our time-to-results in predicting and analyzing market and regulatory trends that directly affect products under the Program’s regulatory purview. At completion, WILEE will have multiple modules that enhances the Program’s capacity for postmarket surveillance and signal detection.
The intern will generate a large corpus of training data that can be viewed and further refined using expert opinion from CFSAN scientists. These refined training set(s) will be used to train WILEE’s other machine learning predictive algorithms. The project will include using an application that provides easy access to the generated training data and the ability to correctly tag the record, either affirming the prediction made by the machine learning algorithm or indicating that machine learning algorithm needs modification. The intern will also use another user interface developed to help correct misspelled names and merge common items into a single item. The results of this data preparation step will help extract toxicity data for identified substance which WILEE will use in its risk ranking process for identified signals.