# 1) Life Sciences

**R-2A activity** of project LF1 — Life Sciences (Basic Research)  
**Program element:** 0601384BP — Chemical and Biological Defense Program  
**Component:** Defense-Wide · **Budget Activity:** 1  
**Vintage:** President's Budget PB2027  
**Canonical URL:** https://hitchintel.com/programs/0601384BP/LF1/a0  
**Parent:** https://hitchintel.com/programs/0601384BP/LF1

## Summary

This activity requests $16.1M in FY2027, 100% of project LF1, down 8.7% on FY2026. The R-2A exhibit describes it across FY2025–FY2027, including what the FY2027 money is planned to buy.

## What the FY2027 request buys

**FY2027 planned work.** - 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.

**FY2026 to FY2027 change.** Minor change due to routine program adjustments.

## Before the request year

**FY2026 plans — current year.** - 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.

**FY2025 accomplishments.** - 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.

## Funding

| Fiscal Year | Estimate Type | Amount ($M) |
|---|---|---|
| FY2025 | Actual | 20.4 |
| FY2026 | Enacted | 17.7 |
| FY2027 | Request | 16.1 |

> Prior, current and budget year only — an R-2A activity carries no five-year plan. It sums exactly into its project in the request year and not necessarily in any other.

## Source & machine access

- **Source:** FY2027 Office of the Secretary of Defense RDT&E Budget Justification, Exhibit R-2A, PE 0601384BP project LF1 (PB PB2027). Narrative is the government's own text.
- **No marks, no contractors at this grain** — congressional marks land on the program element and R-3 performers on the project.
- **MCP:** `mcp.hitchintel.com` — `budget_get_activity`.

*HitchAI is an independent intelligence service, not affiliated with the U.S. Department of Defense. Budget figures are requests/estimates, not obligations.*