Imported from TheAppMakerPro/baddassapp (src/process/resources/skills-library/bodies/skills/writing/grant-proposal-writing/SKILL.md). Install upstream with npx skills add TheAppMakerPro/baddassapp --skill grant-proposal-writing. Copyright stays with the author (Apache-2.0).

Grant Proposal Writing

When to Use

Use this skill when:

• The user asks to write, draft, or revise a grant proposal or funding application for a research project
• The user needs help with a specific aims page, research strategy, significance, innovation, approach, or budget justification section
• The user is applying to a funding agency -- NIH (R01, R21, R03, K awards, P awards), NSF (CAREER, standard grants, collaborative research), private foundations (Robert Wood Johnson, Gates, Wellcome Trust, American Cancer Society), or institutional mechanisms (internal pilot grants, bridge funding)
• The user wants to respond to reviewer critiques for a resubmission (A1 or A2 cycles at NIH; resubmissions at NSF and foundations)
• The user needs to write a specific section in isolation -- a specific aims page, a significance section, or a budget justification -- as a standalone deliverable
• The user wants to assess the strength of an existing proposal and identify weaknesses before submission
• The user needs to adapt a funded grant from one mechanism or agency to another (e.g., converting an R21 to an R01, or adapting NIH content for a foundation application)
• The user is writing for a team science, multi-PI, or center grant (P01, U19, SPORE) and needs to coordinate aims across investigators

Do NOT use this skill when:

• The user wants a business proposal or investor pitch -- use a business writing skill instead
• The user wants a scholarship or fellowship personal statement or research statement (these use entirely different rhetorical structures and evaluation criteria)
• The user wants to write a manuscript or research paper reporting completed work -- use research-paper-structure
• The user wants a consulting proposal, statement of work, or service contract -- these are commercial documents with different conventions
• The user is asking about grant compliance, regulatory approvals, IRB/IACUC protocols, or institutional administrative requirements -- these are process questions, not writing questions
• The user wants only a literature review without a research proposal attached -- this is a background synthesis task, not grant writing
• The user is writing a letter of support, reference letter, or biosketches for other investigators -- use a letter-writing skill

Process

Step 1: Gather the Funding Context Before Writing a Single Word

Every grant proposal is written to a specific audience operating under specific constraints. Collect all of the following before drafting:

• Funding agency and program: NIH vs. NSF vs. private foundation determines page limits, section names, scoring rubrics, and reviewer pool composition. NIH uses the five scored criteria (Significance, Investigators, Innovation, Approach, Environment). NSF uses Intellectual Merit and Broader Impacts. Private foundations often use their own rubrics but structurally resemble NIH.
• Mechanism and activity code: An NIH R01 allows 12 pages of Research Strategy. An R21 allows 6. An R03 (small grant) allows 6 and capped at $50,000/year direct costs. An NSF CAREER award requires a substantial education and outreach plan alongside the research plan. A K99/R00 requires a mentored phase and an independent phase. Getting the mechanism wrong invalidates everything.
• Funding opportunity announcement (FOA) or program solicitation: Read it in full. Note any required sections, required attachments, page limits, font size (NIH requires 11-point Arial, Georgia, Helvetica, or Palatino, with 0.5-inch margins), and deadline. Some FOAs require specific response to particular scientific priorities -- proposals that do not address the FOA themes are triaged.
• Study section or review panel: NIH proposals are reviewed by standing study sections (e.g., INIA, RPHB, BCHI) or special emphasis panels. Knowing the study section tells you the reviewers' scientific background and what they expect. NSF panels are program-specific. Foundation panels vary.
• Budget range and project period: NIH R01 budgets over $500,000 direct costs per year require prior permission from the program officer. Most R01s run at $200,000-$400,000 direct costs per year for 4-5 years. R21s are capped at $275,000 total direct costs over 2 years. Under-scoping a budget signals poor planning; over-scoping signals inexperience.
• Preliminary data status: What does the PI already have? Published papers, pilot data, unpublished data, relevant prior training? The answer shapes how much of the approach is de-risked vs. speculative.
• Resubmission history: First submission or A1 resubmission? NIH allows one resubmission. If the prior summary statement is available, the resubmission must address every scored concern. NSF allows multiple resubmissions but each must meaningfully respond to review.

Step 2: Write the Specific Aims Page -- The Single Most Important Page

The specific aims page is read by every reviewer, by program officers, and sometimes by advisory council members. The research strategy may be read fully only by the primary and secondary reviewers. The specific aims page must function as a complete argument that stands alone.

• Opening hook (lines 1-3): State the public health, scientific, or societal problem at its maximum legitimate scale. Use a specific statistic -- not "cancer is a major problem" but "pancreatic cancer has a 5-year survival rate of 11%, and 90% of patients present with unresectable disease." The first sentence must make the reviewer feel the urgency.
• State of the field paragraph: What is currently known? What has the field tried? Keep this to 3-4 sentences. This is not a review -- it is the setup for the gap.
• The gap sentence: One to two sentences stating specifically what is NOT known and why that gap matters. "Despite [what is known], it remains unknown whether [specific unknown]." The gap must be real, significant, and fillable by this project.
• Central hypothesis and general approach: "We hypothesize that [specific, testable claim]. To test this, we will [general strategy in one sentence]." The hypothesis must be falsifiable. Avoid "we will investigate" or "we will examine" -- these are fishing expeditions. State what you expect to find.
• Aims (typically 2-3): Each aim is one paragraph. Format: "Aim X: [Action verb] [what you will do] using [key method or approach]. We expect to find [specific outcome]. This aim will [why it matters]." Aims should address different aspects of the hypothesis, not be sequential steps of the same experiment. A failed Aim 1 should not preclude completion of Aim 2.
• Impact statement (last 2-3 sentences): What changes about science, medicine, policy, or practice if this project succeeds? This must be specific -- not "this will advance the field" but "these findings will provide the first mechanistic basis for why X drug works in population Y but not Z, enabling precision prescribing."
• Page discipline: One page, no exceptions. NIH reviewers will stop reading at the page boundary. Target 500-600 words. Use the space efficiently -- no unnecessary headers, no figures on the aims page, no wasted white space.

Step 3: Write Significance -- The Argument, Not the Textbook Chapter

The Significance section establishes why the proposed research deserves federal investment. It must read as an argument, not a literature review.

• Establish the scientific and clinical landscape in 1-2 paragraphs: What does the field understand well? What are the dominant theories, treatments, or frameworks? Use citations efficiently -- cite the landmark papers, not every paper ever written.
• Identify the specific gap with precision: "Current models of [X] assume [Y], but this assumption has never been tested in [context]. The consequence of this assumption is [downstream problem]." Precision here separates strong proposals from weak ones.
• Explain why the gap has persisted: Was it a technical limitation? A conceptual blind spot? A lack of the right patient population or biological model? This explains why no one has solved this before and why now is the right time.
• Name the populations or systems that bear the consequences of this gap: Who is harmed by not knowing? Who benefits from knowing? Ground the scientific gap in real-world consequences.
• Address NIH's scored criterion directly: The review criteria ask whether the proposed project addresses "an important problem or critical barrier to progress." Use language that maps to this criterion. The section should explicitly name the "critical barrier" the project will remove.
• Keep it to 1.5-2 pages for an R01: Every sentence must either establish context, identify the gap, or argue for impact. Cut anything that is review for its own sake.

Step 4: Write Innovation -- Name What Is Genuinely New

Innovation is the most commonly misunderstood section. "New" must be real -- not incremental extensions of existing work.

• Differentiate the types of innovation: Conceptual innovation (new theoretical framework, overturns a dominant paradigm); methodological innovation (new technique, new measurement, new model organism or system); translational innovation (first application of a known concept to a new disease, population, or context); technological innovation (new tool, platform, or instrument). Name which type applies.
• Be explicit and specific: "This is the first study to use [method] in [context]. Prior work has used [alternative method], which cannot [specific limitation]. Our approach overcomes this limitation by [specific mechanism]." Do not say "innovative" without saying why.
• Differentiate from your own prior work: If this is a renewal or builds on your published work, explain what is new relative to your own prior grants. Reviewers who know your work will look for this.
• Differentiate from competitors: Know the field. If another group has published something that looks like your innovation, explain why your approach is different, superior, or complementary.
• Keep to 0.5-1 page: If you need more than one page to explain what is new, the proposal is probably trying to be innovative in too many directions simultaneously, which weakens rather than strengthens the claim.

Step 5: Write the Approach -- The Technical Heart of the Proposal

The approach section must convince a sophisticated reviewer in the field that you have the right plan, that you have thought through the risks, and that you can execute.

• Lead each aim with preliminary data: Before describing the methods, show that you already have evidence the approach works. Present pilot data, relevant published findings from your lab, or proof-of-concept results. Preliminary data is the single strongest de-risking element in a proposal. For NIH, preliminary data from your own lab is expected for R01s; for R21s (exploratory/developmental), it is less required but still strengthens the proposal.
• Describe methodology with enough specificity to be reproducible: Sample sizes must be justified with a power calculation that specifies the effect size (from preliminary data or published literature), alpha (typically 0.05), and desired power (typically 80% or 80%; NIH expects 80-90%). State the primary statistical analysis for each aim -- not "appropriate statistical tests" but "linear mixed-effects models with random effects for subject and site, with shift length as the fixed predictor."
• Potential pitfalls and alternative approaches: For every aim, dedicate a subsection (or clearly labeled paragraph) to what could go wrong and what you will do if it does. Be specific: "If the knockout mouse fails to display the expected phenotype (as seen in 20% of conditional knockouts in our pilot), we will [specific alternative: use shRNA knockdown, use a pharmacological inhibitor, use a different Cre driver]." Reviewers who are experts will think of these problems -- preempting them signals rigor and experience.
• Timeline: Include a Gantt chart or timeline table showing when each major activity in each aim occurs across the project period. The timeline must be internally consistent -- you cannot complete Aim 3 by Month 18 if Aim 2's reagents require 6 months of development first.
• Data management, sharing, and rigor: NIH now requires explicit attention to scientific rigor. Address: how you will handle blinding and randomization, how you will account for sex as a biological variable (SABV), what the criteria for excluding data points will be (pre-specified, not post-hoc), and how you will share data (in alignment with the NIH Data Management and Sharing Policy, effective January 2023).
• Interpretation of results: After expected outcomes for each aim, include a brief "Interpretation" section: "If we find [result A], this supports [interpretation X]. If we find [result B], this supports [interpretation Y]. If the result is [unexpected C], this would suggest [explanation] and would lead us to [next step]." This shows the reviewer you understand your own experiment.

Step 6: Write the Budget Justification -- Connect Every Dollar to the Science

The budget justification is not a financial document -- it is a scientific document. Every line item must be tied to a specific aim, a specific activity, or a specific scientific need.

• Personnel (typically 60-75% of a research budget):

  • For each person, state: name (if known), role, percent effort, what they will do on the project, and why that level of effort is appropriate.
  • PI effort must be at least 10% (for NIH R01s; some mechanisms require more). Reviewers notice when a PI lists 5% effort on a complex R01 -- it signals the PI is overextended.
  • Postdoctoral salaries should follow NIH NRSA stipend levels as a floor (currently $56,400 for Year 0 postdocs in 2024) unless institutional scales are higher.
  • Graduate student budgets vary by institution -- use the institution's current tuition and stipend rates, including tuition remission.
  • If personnel are TBD, still justify the level of expertise needed and why.

• Equipment: Anything over $5,000 (NIH threshold) requires individual justification. State what the equipment will be used for, which aims require it, and why existing institutional or shared equipment cannot meet the need.

• Supplies: Break down by category -- molecular biology reagents, animal purchase and maintenance, cell culture consumables, computing resources. Give unit costs and estimated quantities. "Lab supplies: $15,000/year" is insufficient -- "$3,000 for oligonucleotide synthesis for Aim 1 (estimated 60 primers at $50 each), $5,000 for qPCR reagents, $7,000 for cell culture media and plasticware" is acceptable.

• Travel: Justify by scientific purpose. "One PI trip to annual Society for Neuroscience meeting ($1,800 registration + $400 flights + $600 hotel x 1 PI = $2,800/year) for presentation of results and collaboration with [named collaborator lab]."

• Other direct costs: Participant incentives (justify per the IRB-approved protocol -- IRB approval should be pending or obtained), publication costs (including open access fees, currently $2,000-$12,000 per paper for many journals), animal per diems (calculate using institutional per diem rates and estimated animal census), and consulting fees (name the consultant and justify their role).

• Modular vs. detailed budgets: NIH R-mechanisms under $250,000 direct costs per year use modular budgets (in $25,000 modules). Anything over $250,000 requires a detailed budget. Always confirm the threshold for the current fiscal year.

Step 7: Integrate Reviewer Psychology Into the Structure

Grant writing is persuasion directed at a specific reader: a peer-reviewer with expertise in the field who is reading 6-10 proposals in a compressed timeframe.

• Primary and secondary reviewers read the full proposal. Other reviewers may read only the specific aims and the scores assigned by the primaries. Write the specific aims page for the entire panel, not just the experts.
• Signpost relentlessly: NIH reviewers fill out a structured critique form that maps to each scored criterion. Make it easy for the reviewer to find the information that answers each criterion. Use explicit headers. "Significance" should not require the reviewer to hunt for why the project matters -- it should be stated directly in the opening paragraph of that section.
• Avoid jargon in the specific aims and significance sections. Reserve technical language for the approach section, where a domain expert is doing the reading.
• Score inflation for resubmissions: When submitting an A1, study section reviewers compare the revision to prior critiques. A proposal that addresses every critique systematically, with a clear introduction page (1 page maximum for NIH A1s) that maps each change to each critique point, typically scores higher than a proposal that simply rewrites sections without acknowledging prior feedback.
• Program officer consultation: Before any major submission, the PI should have contacted the NIH program officer to confirm the FOA fit and get intelligence on study section composition. If the user has not done this, mention it as a critical preparatory step.

Step 8: Final Review Against Scored Criteria

Before finalizing the proposal, conduct a structured self-critique:

• NIH review criteria: Score each of the five criteria (Significance, Investigators, Innovation, Approach, Environment) on a 1-9 scale from the reviewer's perspective. Identify the weakest criterion and strengthen it.
• Page limit compliance: Count pages for every section. NIH page limits are hard stops -- overlength proposals are returned without review.
• Internal consistency check: Do the aims in the specific aims page match the aims as numbered in the approach? Do the personnel in the budget justification match the personnel listed as key personnel? Does the timeline fit within the proposed project period?
• Specificity audit: Read every occurrence of the words "explore," "investigate," "examine," and "assess." Each of these verbs in the aims or approach signals a fishing expedition -- replace with verbs that imply a directed test: "test," "measure," "determine," "quantify," "compare."
• Preliminary data coverage: Can each aim point to at least one piece of evidence (pilot data, published literature from your lab, or a collaborator's published data) that it is feasible?
• Independence of aims: Run this thought experiment: if Aim 1 completely fails, can you still write a meaningful completion report for Aims 2 and 3? If not, restructure.

Output Format

When producing grant proposal content, use this structure as a template. Adapt section labels to match the specific agency and mechanism.

## Grant Proposal: [Full Project Title]

**Principal Investigator:** [Name and credentials]
**Agency:** [NIH / NSF / Foundation name]
**Mechanism:** [Activity code and name, e.g., R01 Research Project Grant]
**FOA/PA Number:** [e.g., PA-20-185]
**Project Period:** [e.g., 5 years, September 2025 -- August 2030]
**Total Direct Costs Requested:** [$XXX,XXX/year | $X,XXX,XXX total]
**Study Section (if NIH):** [e.g., Risk, Prevention, and Health Behavior (RPHB)]

---

### SPECIFIC AIMS (1 page maximum)

[PARAGRAPH 1 -- THE HOOK]
[Sentence 1: Quantified statement of the problem and its scale.]
[Sentence 2: What the field has done and what has been achieved.]
[Sentence 3: The specific gap -- what is not known and why it matters.]

[PARAGRAPH 2 -- THE SOLUTION]
[Sentence 1: What this project will do (general approach).]
[Sentence 2: The central hypothesis, stated as a testable claim.]
[Sentence 3: Why your team / your approach / your preliminary data makes this project feasible now.]

**Aim 1: [Active verb + scientific content, e.g., "Determine the molecular mechanism by which X regulates Y in Z cell type"]**
Using [key method], we will [specific activity] in [specific population/model]. We expect to find [specific outcome]. This aim will establish [why it matters to the central hypothesis].

**Aim 2: [Active verb + scientific content]**
[Same structure as Aim 1]

**Aim 3 (if applicable): [Active verb + scientific content]**
[Same structure as Aim 1]

[IMPACT STATEMENT -- 2-3 sentences]
[What changes about science, medicine, or policy if this project succeeds. Specific, not general.]

---

### RESEARCH STRATEGY

**Page limits:** [Confirm from FOA -- e.g., 12 pages total for R01, 6 pages for R21]

#### A. Significance

[Paragraph 1: State of the field -- what is known. 3-5 sentences citing landmark work.]

[Paragraph 2: The critical barrier -- what is not known, why the gap exists, and what the consequences are.]

[Paragraph 3: Who bears the consequences. Patient populations, clinical systems, scientific fields.]

[Paragraph 4: How this project addresses the critical barrier and why removing it matters.]

*NIH review language:* Explain how the proposed project addresses an important problem or critical barrier to progress in the field.

#### B. Innovation

[Paragraph 1: What the current state of the art is in approach, method, or conceptual framework.]

[Paragraph 2: What is specifically new about this proposal -- name the type of innovation (conceptual / methodological / translational / technological).]

[Paragraph 3: How this innovation advances beyond incremental progress.]

*NIH review language:* Explain how the application challenges and seeks to shift current research or clinical practice paradigms.

#### C. Approach

**Preliminary Data**
[Summary of key preliminary findings that demonstrate feasibility of each aim. For each piece of data: what you found, how you measured it, and which aim it supports. Include figure references if submitting actual proposal.]

---

**Aim 1: [Full title]**

*Rationale:* [Why this aim is the right first step. 2-3 sentences.]

*Preliminary data supporting Aim 1:* [Specific findings from pilot work. "In our pilot study of N=[X], we found [result, with effect size or p-value]."]

*Experimental design:*
- **Subjects/Samples/Model:** [Specific population, N, inclusion/exclusion criteria]
- **Intervention or Manipulation:** [What will be done to subjects/samples]
- **Measures:** [Primary and secondary outcome measures with validation status]
- **Sample size and power:** [Power calculation: effect size = [X], alpha = 0.05, power = 80%, required N = [Y] per group. Accounting for [Z]% attrition, we will enroll N = [W].]
- **Statistical analysis:** [Specific test or model, with covariates named. "Primary analysis: [method] with [specific covariates]. Secondary analysis: [method]."]
- **Timeline:** Months [X]-[Y]

*Expected outcomes:* [What you expect to find, quantified where possible.]

*Interpretation of results:*
- If [result A]: This supports [interpretation X].
- If [result B]: This supports [interpretation Y].
- If [unexpected result C]: This suggests [explanation] and will lead us to [next step].

*Potential pitfalls and alternative strategies:*
- **Pitfall 1:** [Specific risk]. **Alternative:** [Specific contingency].
- **Pitfall 2:** [Specific risk]. **Alternative:** [Specific contingency].

---

**Aim 2: [Full title]**
[Same structure as Aim 1]

---

**Aim 3 (if applicable): [Full title]**
[Same structure as Aim 1]

---

**Timeline**

| Quarter | Aim 1 | Aim 2 | Aim 3 | Key Milestones |
|---------|-------|-------|-------|----------------|
| Y1 Q1-Q2 | [Activity] | -- | -- | [Deliverable] |
| Y1 Q3-Q4 | [Activity] | [Activity] | -- | [Deliverable] |
| Y2 Q1-Q2 | [Activity] | [Activity] | -- | [Deliverable] |
| Y2 Q3-Q4 | [Activity] | [Activity] | [Activity] | [Deliverable] |
| Y3 Q1-Q2 | [Activity] | -- | [Activity] | [Deliverable] |
| Y3 Q3-Q4 | -- | -- | [Activity] | [Deliverable] |

---

### BUDGET JUSTIFICATION

**PERSONNEL**

| Name | Role | % Effort | Y1 Salary | Fringe | Total Y1 |
|------|------|----------|-----------|--------|----------|
| [PI Name] | Principal Investigator | [%] | $[X] | $[X] | $[X] |
| [Name or TBN] | Postdoctoral Fellow | [%] | $[X] | $[X] | $[X] |
| [Name or TBN] | Graduate Research Assistant | [%] | $[X] | $[X] | $[X] |

[For each person: 2-3 sentences explaining their role and which aims they support.]

**EQUIPMENT**
[Item]: $[Cost]. Needed for [specific aim and activity]. [Name of instrument]. Existing [institutional resource] cannot meet this need because [specific limitation].

**SUPPLIES**
[Category]: $[Cost]/year. Breakdown: [itemized list with unit costs].

**TRAVEL**
[Conference or purpose]: [Attendees] x [Cost breakdown] = $[Total]/year. Purpose: [Specific scientific justification].

**OTHER DIRECT COSTS**
[Item]: $[Cost]. Justified by [IRB protocol / publication plan / data sharing plan].

---

### INTRODUCTION TO REVISED APPLICATION (A1 resubmissions only, 1 page maximum)

[Summary of prior review strengths and weaknesses]
[Table: Reviewer critique | Section revised | Summary of change]
[Closing statement confirming all concerns have been addressed]

Rules

1. The specific aims page is one page. No exceptions, no appendices, no footnotes. NIH reviewers stop reading at the page boundary. NSF program solicitations may allow 1-2 pages for "Project Summary" plus a separate aims equivalent -- always check the FOA.

2. Each aim must be independently completable. Run the collapse test: if Aim 1 fails entirely, can the project still produce meaningful, publishable findings from Aims 2 and 3? If not, restructure the aims. One common fix is to make Aim 1 a descriptive/characterization aim and Aims 2-3 mechanistic -- the latter can often be initiated in parallel.

3. Never write the Significance section as a literature review. Every paragraph must answer: "Why does this gap matter?" A literature review describes what is known. A Significance section argues why not knowing something is costing us something. The reviewer is evaluating whether the problem is important, not whether you can summarize the field.

4. Power calculations are not optional. Every human subjects or animal study must include a statistical power calculation with: the effect size (sourced from preliminary data or published literature with a citation), the alpha level (0.05 unless justified otherwise), the desired power (80% minimum, 80-90% preferred by most reviewers), and the resulting required sample size with attrition adjustment. "Sample size will be determined based on preliminary data" is not a power calculation.

5. Every pitfall must have a specific, named alternative. "We will troubleshoot as needed" is not an alternative strategy. Name the specific risk, name the specific alternative method or reagent or model, and name one piece of evidence that the alternative is viable. Generic fallback language signals to reviewers that the PI has not thought through the experiment.

6. Budget personnel effort must reflect actual scientific leadership. A PI at 10% effort on a 12-page R01 proposing 3 complex aims signals overcommitment. Reviewers calculate whether the proposed personnel can actually complete the proposed work. If the PI is at 10%, the postdoc must be at 100% and there must be an explicit justification for why 10% PI effort is sufficient.

7. NIH Innovation must describe a paradigm shift or a first. "We will use an established method in a new context" is not innovation -- it is application. Innovation requires: a new method, a new conceptual framework, a new model that challenges a dominant assumption, or first use of an approach in a clinically significant population where the method's use is genuinely novel. Name the specific "first."

8. Sex as a biological variable (SABV) must be addressed in the Approach section for all NIH proposals involving vertebrate animals or human subjects (as of 2016 policy). State whether sex is an independent variable (preferred), whether the study is powered to detect sex differences, or provide a specific scientific justification for why sex is not a relevant variable in this context. Omitting SABV discussion risks a poor Approach score.

9. Resubmission introduction pages must be surgical, not defensive. The A1 Introduction page should: (1) briefly thank reviewers for useful critique, (2) state in 1-2 sentences the overall nature of the revision, (3) use a table or numbered list to map each major critique to a specific revision, and (4) note any changes made proactively beyond reviewer critiques. Reviewers who scored the original proposal often serve on the resubmission panel -- they will look for their concerns to be addressed directly.

10. The NIH Data Management and Sharing (DMS) Plan is now required and reviewed. Since January 25, 2023, all NIH applications requesting $500,000 or more in direct costs in any year, or those that generate scientific data, must include a DMS plan. The plan must specify: what data will be shared, when (by the time of first publication or end of the award period), with whom (specific repository name -- for genomic data, dbGaP; for clinical data, the NIMH Data Archive or similar; for imaging data, OpenNeuro or TCIA), and whether there are any limitations on sharing (e.g., consent language, sovereignty issues, identifiability). "Data will be available upon request" does not constitute a compliant DMS plan.

11. Avoid the "fishing expedition" verb list. Audit every occurrence of: explore, investigate, examine, assess, analyze, look at, characterize, and study. Each of these verbs is appropriate in some contexts but frequently signals that no specific hypothesis or expected outcome exists. Replace with directed verbs when describing aim-level activities: test, determine, quantify, measure, compare, establish, validate, identify.

12. Specific aims language must be accessible to scientists outside the subfield. NIH review panels typically include 15-20 scientists across a broad area. A study section for cardiovascular disease will include basic scientists, clinical trialists, epidemiologists, and behavioral scientists. If the specific aims page requires the reader to know the difference between STEMI and NSTEMI to follow the argument, the proposal will not score well with generalist reviewers. Write the aims for an intelligent scientist two fields away.

Edge Cases

Early-Career Investigators with No Preliminary Data

For junior investigators (without a prior R01 or equivalent), preliminary data is always thinner. Handle this by:

• Framing feasibility through training rather than findings: "Dr. [Name]'s doctoral training in [method X] at [institution] under [mentor] provides direct technical foundation for Aim 1. [Mentor's] lab has successfully applied this method to [analogous problem]."
• Using mentor/co-investigator published data as feasibility evidence when appropriately attributed ("Mentor [Name] published [finding] demonstrating that [method] detects [signal] at the sensitivity required for this study (reference).").
• Selecting smaller mechanisms: R21 (exploratory), R03 (small grant), K99/R00 (career development), or foundation pilot grants. R21s explicitly do not require preliminary data and are designed for innovative/high-risk proposals.
• Proposing one of the aims as a feasibility or optimization aim (Aim 1 = "establish the assay in our target population") -- this converts absence of preliminary data into a scientific aim.

Private Foundation Applications (Non-NIH/NSF Format)

Many foundations use a letter of inquiry (LOI) followed by full application format. The principles are the same; the format is different.

• LOIs are typically 2-3 pages and must communicate the gap, the approach, and the impact without the full technical apparatus. Write LOIs as if you are writing the specific aims page plus one paragraph of methods.
• Foundation reviewers are often a mix of scientists and program officers, not a peer-review panel. Write for a sophisticated lay reader who may not be in the exact field.
• Budget formatting varies: some foundations use narrative budgets ("Personnel: $180,000/year covering the PI at 15% effort and one postdoctoral fellow at 100% effort...") rather than itemized spreadsheets.
• Most foundations do not use the NIH's five scored criteria -- look for their mission statement and strategic priorities and write the significance section to their specific interests (e.g., Gates Foundation priorities health equity and scalable interventions; American Cancer Society emphasizes cancer prevention and survivorship).

Resubmissions (NIH A1, NSF Resubmissions)

• Obtain and carefully read the complete summary statement (NIH) or panel summary (NSF) before writing.
• Create a response matrix: list every critique, categorize by concern type (conceptual, methodological, scope, budget, PI qualifications), and plan a specific response for each.
• For NIH, the Introduction page (1 page) is the only place to formally respond to prior review. Do not respond to reviewers in the body of the proposal.
• Score thresholds matter: NIH proposals with a prior impact score between 20 and 40 have the highest success rate on resubmission. A prior score above 50 (poorly reviewed) may warrant reconsidering the scientific scope or mechanism rather than resubmitting without major restructuring.
• In the proposal body, mark all significant changes with a vertical bar in the left margin (common practice) or bold text -- this helps reviewers from the prior panel quickly identify what changed.

Multi-PI and Team Science Grants

• NIH allows multiple PIs on an R01 through the Multiple PD/PI mechanism. Each PI's contribution must be distinct and non-redundant. Reviewers ask: "Why do you need both PIs? Could one PI do this?"
• Include an explicit Multiple PI Leadership Plan that describes: governance structure, decision-making process, conflict resolution, authorship policy, and plans for continuity if one PI leaves the project.
• Budget effort for each PI must reflect actual contribution. If the work divides cleanly by aim, each PI should be named as the aim lead on their respective aims.
• P01 program project grants and U-mechanisms have even more complex structures with cores, projects, and an administrative core. These require internal coordination of 3-5 individual project proposals under a single umbrella. Treat each project as a mini-R01 and the Program Overview as a meta-specific aims page.

Clinical Trial Applications

• NIH clinical trial applications require additional sections: a clinical trial protocol (or protocol synopsis for early-stage trials), a human subjects section addressing risks and benefits, a recruitment plan with milestones, and a data safety monitoring plan for Phase II/III trials.
• The Approach section must include stopping rules -- prespecified criteria under which the trial would be halted for safety or futility. Reviewers in clinical trial study sections expect these.
• For clinical trials, the statistical analysis plan in the Approach must be more detailed than for basic science studies: specify the primary endpoint, the analysis population (intention-to-treat vs. per-protocol), how missing data will be handled, and whether interim analyses are planned.
• Budget justification for clinical trials must account for clinical research coordinator effort (typically 0.5-1.0 FTE per trial), data coordinating center costs (for multi-site trials), and participant reimbursement at rates justified by IRB protocol.

International Collaborations and Foreign Components

• NIH grants with significant activities conducted outside the United States require a "foreign component" designation. This triggers additional administrative review.
• Budget for foreign subawards follows standard subaward procedures, but indirect costs may be limited to direct costs on subawards above the first $25,000.
• Some countries require government approval for international research collaborations -- this must be documented in the proposal or described as a pending step.
• If the collaboration involves sharing of biological specimens, data, or intellectual property across national boundaries, address this explicitly in the approach and note any relevant agreements (material transfer agreements, data use agreements).

Responding to a Specific Program Announcement vs. a Parent Funding Opportunity

• Program Announcements (PAs) indicate that NIH study sections are particularly interested in certain topics but do not guarantee a set-aside of funds. Competing for a PA means competing within the normal review pool.
• Requests for Applications (RFAs) are different: they have a dedicated review panel, a set-aside budget, and often a single receipt date. RFAs are competitive and targeted -- proposals that do not directly respond to the stated scientific priorities in the RFA text are non-competitive.
• For RFAs, map the proposal structure to the RFA's stated objectives. Some RFAs require specific sections (e.g., "Response to Program Objectives") that are not part of standard Research Strategy. Read the RFA as carefully as any other submission requirement.

Example

Input: "I need a Specific Aims page and a draft Approach section for one aim. NIH R01. I study traumatic brain injury. I've found in a pilot study of 45 patients that microglial activation patterns measured by PET imaging at 72 hours post-injury predict 6-month cognitive outcomes, but we don't know what drives the variation in microglial response across patients with similar injury severity."

Output:

Grant Proposal: Determinants of Heterogeneous Microglial Activation After Traumatic Brain Injury and Their Relationship to Cognitive Recovery

Principal Investigator: [PI Name], MD/PhD Agency: National Institutes of Health Mechanism: R01 Research Project Grant FOA: PA-21-071 (NIH Research Project Grant Program) Project Period: 5 years (September 2025 -- August 2030) Total Direct Costs Requested: $325,000/year Study Section: Brain Injury and Neurovascular Regulation (BINR)

SPECIFIC AIMS

Traumatic brain injury (TBI) affects 2.8 million Americans annually, and despite equivalent injury severity, outcomes diverge dramatically: 30% of patients with moderate TBI recover to near-baseline cognitive function within 6 months while 40% experience persistent deficits that preclude return to work or independent living. Our group has recently demonstrated, in a cohort of 45 patients, that [18F]-DPA-714 PET-measured microglial activation at 72 hours post-injury independently predicts 6-month cognitive performance (Trail Making Test-B, Montreal Cognitive Assessment) with greater accuracy than injury severity scores alone (AUC 0.84 vs. 0.67; p=0.003). However, patients with near-identical Glasgow Coma Scale scores and CT findings display a four-fold variation in microglial activation magnitude. The biological drivers of this variation are unknown -- a gap that prevents us from targeting neuroinflammation at the right time, in the right patients, to alter recovery trajectories.

We hypothesize that heterogeneity in early post-TBI microglial activation is determined by a combination of pre-injury genomic factors governing baseline microglial reactivity (specifically, TREM2 and CD33 variant burden) and acute metabolic factors reflecting injury-induced mitochondrial dysfunction, and that the relative contribution of each varies systematically with patient age and sex. To test this, we will leverage a nested cohort design within an ongoing prospective TBI registry (n=800 enrolled to date) and apply multi-modal characterization -- PET neuroimaging, plasma neurofilament light (NfL) and GFAP biomarkers, bulk RNA sequencing of circulating monocytes as a microglial proxy, and targeted genomic profiling -- at standardized post-injury timepoints.

Aim 1: Determine the independent and combined contributions of TREM2/CD33 variant burden and acute mitochondrial metabolite profiles to 72-hour microglial activation magnitude in 240 adult TBI patients (moderate-to-severe, GCS 4-12) using [18F]-DPA-714 PET, plasma metabolomics (targeted mitochondrial panel: succinate, fumarate, alpha-ketoglutarate, lactate-to-pyruvate ratio), and whole-exome sequencing. A validated weighted polygenic risk score for TREM2/CD33 microglial reactivity will be computed and tested in a multivariable linear model with microglial activation DVR as the outcome.

Aim 2: Establish whether the relationship between microglial activation and 6-month cognitive recovery is moderated by age and sex, using a prospective longitudinal design in the same 240-patient cohort with cognitive assessments at 72 hours, 3 months, and 6 months post-injury. Interaction terms (microglial activation x age; microglial activation x sex) will be tested in linear mixed-effects models with random effects for recruitment site. This aim will determine whether neuroinflammation-targeted interventions should be stratified by patient demographics.

Aim 3: Identify transcriptomic signatures in circulating monocytes that mediate the relationship between TREM2/CD33 variant burden and microglial activation magnitude, using bulk RNA sequencing at 72 hours post-injury in a subset of 120 patients (60 high-activation, 60 low-activation, matched on GCS and CT lesion volume). Differentially expressed genes will be mapped to the Reactome neuroinflammation pathway database to identify druggable upstream regulators.

If successful, this project will provide the first mechanistic framework explaining patient-level variation in post-TBI neuroinflammation, identify genomic and metabolic biomarkers that can stratify patients for anti-inflammatory clinical trials, and generate transcriptomic targets for precision neuroinflammatory intervention -- directly addressing the failure of prior TBI neuroprotection trials that enrolled heterogeneous populations without neuroinflammatory stratification.

APPROACH (Aim 1 -- drafted in full)

Preliminary Data

In a completed pilot study (n=45 moderate-to-severe TBI, GCS 4-12, mean age 38.4 years, 62% male), we administered [18F]-DPA-714 PET at 72 ± 12 hours post-injury and found mean whole-brain distribution volume ratio (DVR) of 1.43 (SD 0.31, range 0.91-2.18), confirming a four-fold patient-level variation in microglial activation that was not explained by GCS (r=0.18, p=0.23) or CT hemorrhage volume (r=0.22, p=0.15). DVR at 72 hours predicted 6-month MoCA score (beta = 4.2, 95% CI 2.1-6.3, p<0.001) in a multivariable model adjusting for age, sex, and education. Plasma NfL (r=0.61, p<0.001) and GFAP (r=0.58, p<0.001) correlated strongly with DVR, confirming biological validity of the PET signal. These findings are the subject of a manuscript currently under review at Annals of Neurology.

In a separate genomic feasibility study in 22 of these patients, we genotyped TREM2 (rs75932628) and CD33 (rs3865444) and found a nominally significant association between minor allele burden and higher DVR (beta per allele = 0.12, p=0.048, uncorrected). This sample was underpowered for definitive conclusions, providing direct rationale for Aim 1's adequately powered cohort.

Aim 1: Determine the independent and combined contributions of TREM2/CD33 variant burden and acute mitochondrial metabolite profiles to 72-hour microglial activation magnitude

Rationale: Microglial activation after TBI is not a uniform response -- it reflects the intersection of genetic predisposition and metabolic context. TREM2 is expressed on microglia and modulates their phagocytic and inflammatory responses to damage-associated molecular patterns. CD33 (Siglec-3) is a myeloid inhibitory receptor whose functional variants regulate microglial reactivity. Both genes carry common variants with demonstrated functional effects on microglial behavior in Alzheimer's disease, and our pilot genomics data suggest they contribute to activation variation in TBI. Separately, acute TBI induces mitochondrial dysfunction -- elevated succinate and suppressed succinate dehydrogenase activity stabilize HIF-1alpha, driving pro-inflammatory microglial polarization in preclinical models. Whether this pathway is active in human TBI and contributes to the inter-patient variation we observe has not been tested.

Experimental design:

• Study population: 240 adults with moderate-to-severe TBI (GCS 4-12 at scene or ED; confirmed by CT or MRI), enrolled consecutively from the ongoing [Institution] TBI Registry at two sites (site 1: n=180 projected; site 2: n=60 projected). Inclusion: age 18-70, injury within 6 hours of hospital arrival, CT-confirmed TBI. Exclusion: pre-existing dementia or neurodegenerative disease, prior TBI within 12 months, immunosuppressive therapy (which would confound microglial activation measurement), contraindication to PET.

• [18F]-DPA-714 PET acquisition and analysis: PET scanning will occur at 72 ± 12 hours post-injury using our established protocol (60-minute dynamic scan following injection of 185 MBq [18F]-DPA-714; Logan graphical analysis for DVR calculation using a population-based input function validated in our pilot study). Regional DVRs will be extracted for whole brain, frontal, temporal, and parietal regions. PET preprocessing will follow the BIDS-PET standard pipeline. All scans will be processed blind to genomic and metabolic data.

• Plasma metabolomics: Blood collected at the time of PET (72 ± 12 hours) will undergo targeted metabolic profiling for 21 mitochondria-associated metabolites (succinate, fumarate, alpha-ketoglutarate, malate, acetylcarnitine, lactate, pyruvate, and 14 additional TCA/fatty acid oxidation intermediates) using a validated LC-MS/MS panel (Biocrates MxP Quant 500, with internal standards for all analytes). Coefficient of variation for all analytes < 10% in our quality control samples.

• Genomic profiling: Whole-exome sequencing (30x coverage, Illumina NovaSeq 6000) will be performed on DNA from peripheral blood. A weighted polygenic risk score (wPRS) for microglial reactivity will be computed from 7 TREM2 and CD33 variants with published functional data (rs75932628, rs143332484, rs2234256 for TREM2; rs3865444, rs12459419, rs35112940, rs1354106 for CD33), using weights derived from the Alzheimer's Disease Genetics Consortium (ADGC) microglial activation QTL data. This pre-specified wPRS approach avoids multiple testing inflation from variant-by-variant analysis.

• Primary statistical analysis: Multivariable linear regression with whole-brain DVR (DVR-wb) as the primary outcome. Primary predictors: (1) wPRS for microglial reactivity, (2) 72-hour plasma succinate level (as the lead mitochondrial predictor based on preclinical evidence), (3) wPRS x succinate interaction term. Covariates: age, sex, GCS, CT hemorrhage volume (mL by automated segmentation), time from injury to PET (hours), and recruitment site. Secondary analyses will substitute regional DVR values (frontal, temporal) as outcomes and will test the full 21-metabolite panel using LASSO penalized regression to identify additional metabolic predictors.

• Sample size and power: Our primary analysis tests whether wPRS explains variance in DVR-wb beyond covariates alone. In our pilot (n=45), wPRS explained approximately 12% of DVR-wb variance (R-squared change = 0.12). Assuming this effect size (f-squared = 0.14, consistent with a medium-small effect), alpha = 0.05, and power = 80%, the required n for the multivariable model with 8 predictors is 98. For the wPRS x succinate interaction test (effect size estimated conservatively at f-squared = 0.06, based on gene-environment interaction effects in comparable neuroinflammation literature), required n = 196. We will enroll 240 patients to achieve 80% power for the interaction test with 20% allowance for PET non-completion (scanner malfunction, patient deterioration requiring emergent surgery, or withdrawal -- we observed an 18% non-completion rate in our pilot).

• Timeline: Months 1-36. Patient enrollment begins Month 3 (following IRB amendment approval for the expanded cohort protocol). PET scanning, blood collection, and genomic sample processing will occur continuously. Database lock at Month 34; analysis and manuscript preparation Months 34-42.

Expected outcomes: We expect that wPRS will independently explain 10-15% of variance in DVR-wb, that 72-hour succinate level will independently explain 8-12%, and that the interaction will explain an additional 5-8%, together accounting for approximately 25-35% of the inter-patient variation in microglial activation. If our effect size estimates are accurate, we will identify at least one genomic and one metabolic factor as independent, modifiable contributors to neuroinflammatory heterogeneity.

Interpretation of results:

• If wPRS but not succinate predicts DVR: The dominant driver of variation is pre-injury genetic constitution; metabolic context at injury is secondary. This would support a genetic stratification strategy for clinical trials.
• If succinate but not wPRS predicts DVR: Acute metabolic context drives variation; genetics play a minor role. This would support metabolic intervention (e.g., itaconate supplementation, which suppresses succinate-driven HIF-1alpha stabilization) as a stratification-independent approach.
• If neither wPRS nor succinate independently predicts DVR: The variation is explained by unmeasured factors (injury timing precision, concurrent medications, unmeasured comorbidities). In this case, we will proceed with the full 21-metabolite LASSO analysis and will expand genomic coverage