What the FY2027 request buys
Verbatim from the R-2A exhibit for project LF1 of PE 0601384BP. This is the budget justification's own description of work that has not happened yet — the one thing no other level of the budget carries.
- Organoid Technology – Continue investigating cellular toxicity and metabolic profiles in organoids and evaluate relevance to safety/efficacy model data. Determine inflammatory signaling in models that are relevant to human cells. Evaluate and develop alternative models that mimic human response for rapid drug development, which can speed up future Food and Drug Administration (FDA) approvals. - Pathogenesis – Continue to evaluate small molecule inhibitor on viral gene expression in vivo. Evaluate how Ribonucleic acid (RNA) viruses alter biological activity of hosts during accurate and persistent infection. - Structural biology – Continue investigate efficacy of inhibitor molecule in an organ-on-chip platform. Initiate training models to predict structural features for small molecules based on experimental data. - Artificial Intelligence (AI) for Early Drug Discovery – Continue to characterize promising protein binding candidates based on model predictions. Validate predictive models ability to identify specific metabolic properties to enhance host immunity. Applying multi-learning prediction to molecular binding to expand general application drug design. Develop of artificial intelligence/machine learning (AI/ML) for identification of broad spectrum antivirals and small molecule libraries guided by AI/ML. - Biomarkers – Evaluate machine-learning model to predict strain specific binding targets. Complete machine-learning architecture and sampling for iterative experimental design and begin validation of amino acid sequence capture. - Inflammation Mapping – Evaluate inflammatory pathways activated by chemical exposure using multiple characterization techniques. Validate potential medical countermeasure candidates in an in vitro nerve model.
Minor change due to routine program adjustments.
FY2025–FY2026: what came before
Prior-year accomplishments and current-year plans from the same exhibit. Context for the FY2027 plan, not a series — an activity partitions its project exactly in the request year, but can under-cover it in earlier years.
- Organoid Technology – Complete metabolic modeling and evaluate relevance to human cells. This research informs the end goal of developing better models for drug development, which can speed up future Food and Drug Administration (FDA) approvals. - Pathogenesis – Validate small molecule inhibitor on viral gene expression and begin structural analysis of protein complexes and quantify inhibitors in viruses. Understanding what stops viral replication can help to develop future therapeutics. - Structural biology – Begin testing efficacy of small molecules and antimicrobial peptides. Continue training models to predict structural features for small molecules based on experimental data. Understanding how various molecules can affect bacteria can help develop future therapeutics. - Artificial Intelligence (AI) for Early Drug Discovery – Characterize multivalent countermeasures and evaluate binding profiles. Continue to validate predictive models’ ability to identify specific metabolic properties to enhance host immunity. Apply multi-learning prediction to molecular binding to expand general application drug design. Begin development of standard framework to identify novel signatures of host response to pathogens. Develop methodology to test experimental data across multiple data platforms. AI efforts require training and validation before they can be used to make predictions, these efforts cross several divisions and affect multiple future capabilities. - Biomarkers – Begin material characterization by spectroscopy and measure biosensor sensitivity. Develop algorithms to enhance multi-dimensional geometry and begin to evaluate sensitivity design and performance. Contributions to biomarker sensitivity enables earlier disease detection, improves diagnostic capability, and effective treatments. - Inflammation Mapping – Begin to correlate data to existing chemical exposures. Begin inflammation marker analysis using multiple molecular processes. Understanding key indicators of inflammation can help to treat various diseases and chemical exposures.
- Organoid Technology – Continued investigating cellular toxicity and metabolic profiles in organoids and evaluate relevance to safety/efficacy model data. Determined inflammatory signaling in models that are relevant to human cells. - Pathogenesis – Evaluated small molecule inhibitor on viral gene expression in vivo. Evaluated how hemorrhagic fever viruses alter biological activity of host cells. - Structural biology – Investigated efficacy of inhibitor molecule in an organ-on-chip platform. Began training models to predict structural features for small molecules based on experimental data. - Artificial Intelligence (AI) for Early Drug Discovery – Characterized promising protein binding candidates based on model predictions. Validated predictive models ability to identify specific metabolic properties to enhance host immunity. Applied multi-learning prediction to molecular binding to expand general application drug design. - Biomarkers – Evaluated machine-learning model to predict strain specific binding targets. Completed machine-learning architecture and sampling for iterative experimental design and began validation of amino acid sequence capture. - Inflammation Mapping – Evaluated inflammatory pathways activated by chemical exposure using multiple characterization techniques. Validated potential medical countermeasure candidates in an in vitro nerve model.
Three years, and no five-year plan
An R-2A activity publishes the prior year, the current year and the budget year. The FYDP outyears exist at project and program-element level and are deliberately absent here rather than inferred. Estimate types are colored and never summed into one figure.
| Fiscal Year | Estimate Type | Amount ($M) |
|---|---|---|
| FY2025 | Actual | 20.4 |
| FY2026 | Enacted | 17.7 |
| FY2027 | Request | 16.1 |
This activity is 100% of project LF1's FY2027 request and 59% of PE 0601384BP's. In the request year the activities under a project sum to it exactly; in the current year they under-cover it in about 9% of cases, so an activity's delta can legitimately exceed its parent's and the two must not be compared row to row.
1 activity in project LF1
Every R-2A line of this project, largest FY2027 request first. Linked where the activity has enough of its own narrative to carry a page; the rest are shown in full on the project page.