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AACR-Think Forward Foundation Career Development Award

American Association for Cancer Research (AACR)

The Think Forward Foundation and AACR are proud to announce the AACR-Think Forward Foundation Career Development Award This grant mechanism seeks to support early-career researchers to pursue impactful research focused on advancing precision medicine in breast cancer treatment.

Each grant provides $300,000 over 3 years for expenses related to the research project. Grant funds may be used for research expenses attributable to the project, which may include supplemental salary support, equipment, research/laboratory supplies, and other research expenses.

Research Project Criteria

This grant is designed to support innovative research focused on advancing precision medicine in breast cancer treatment. Our goal is to accelerate the development of tailored therapeutic strategies that address individual genetic profiles, molecular markers, and biomarkers to enhance treatment efficacy while minimizing adverse effects.

Applicants are encouraged to incorporate artificial intelligence (AI) to analyze large datasets, identify research correlations, and accelerate access to precision medicine—ultimately improving patient outcomes and transforming breast cancer care.

Grant Amount$300,000 USD

Grant Term3 Years

Start of Grant TermJuly 1, 2026

Letter of Intent DeadlineDecember 18, 2025 1:00 PM (ET)

Letter of Intent Notification DateFebruary 2026

Application DeadlineApril 7, 2026 1:00 PM (ET)

Decision DateJune 2026

Additional InformationAdditional details regarding this grant can be found in the Program Guidelines and Competitive Letter of Intent Instructions. Final determinations of eligibility will not be completed until the AACR is in receipt of the submitted Competitive Letter of Intent.

AI Based Application Success Predictor

1. Strong preliminary data

AACR panels expect high-quality, convincing pilot data. Successful applicants demonstrate:

Mechanistic feasibility

Biological signal

Proof-of-principle in at least two systems (e.g., cell line + in vivo)

Biomarker rationale where relevant

Weak or minimal preliminary data is the most common rejection cause.

2. Clear translational potential

AACR heavily values clinical relevance:

Patient-driven hypotheses

Biomarker-driven trial concepts

Therapeutic target potential

Realistic proximity to clinical application
Funding tends to favor proposals that can impact patients within 3–7 years.

3. Cancer relevance that is explicit and justified

A common failure mode: cancer linkages that feel “tacked on.”
Winning applicants explicitly:

show pathway relevance to cancer biology,

outline patient populations,

reference tumor heterogeneity,

map existing clinical unmet need.

4. Track record of productivity

Successful applicants typically demonstrate:

1–3 first-author cancer manuscripts (recent)

Co-authorship in diverse oncology subfields

Conference abstracts (ASCO, AACR, ESMO)

Even early-career winners have measurable momentum.

5. Feasible scope within award duration

Panels flag:

overly ambitious aims,

multi-omics everything-everywhere plans.

Winning applications present:

clear milestones,

2–3 aims,

defined decision points.

6. Strong mentorship (for early-career awards)

Predictors:

active publication record of mentor

demonstrated prior mentoring success

multiple mentors (computational, clinical, basic)

Weak mentorship statements correlate with low scores.

7. Institutional environment

AACR reviewers value:

core facilities access,

tumor biobank availability,

genomics platforms,

animal facilities,

clinical trial access.

Letters confirming facility access improve panel confidence.

8. Innovation that’s grounded, not speculative

Winning proposals tend to:

address mechanistic novelty,

leverage cutting-edge platforms,

avoid “hand-wave” future benefits.

Innovation must be operationalizable.

🧫 Theme Areas That Score Higher

Historically stronger funding rates for projects involving:

Tumor immunology & microenvironment

Resistance mechanisms to targeted therapies

Biomarker discovery + validation

Single-cell / spatial biology approaches

Computational oncology with validation

Drug repurposing with mechanistic rationale

🔍 Project Designs That Often Win

Predictive design elements include:

Patient-derived samples / organoids

Clinically annotated cohorts

Mechanism → biomarker → targeted therapy progression

🧨 Common Reviewer Critiques (from rejection summaries)

“Unclear how results would change clinical practice”

“Lacks specificity in experimental design”

“Unrealistic number of aims”

“Weak contingency plan”

“Cancer relevance insufficiently justified”

🧪 Experimental Rigor Predictors

Panels reward:

attention to replicates,

power calculations,

batch effect mitigation,

blinded scoring methods.

Rigor & reproducibility paragraphs make or break applications.

👥 Collaboration Signals

Successful applications often show:

access to clinician collaborators,

biostatistics support,

immunology partnerships,

computational co-investigators.

“Solo silo science” is penalized.

💰 Budget Predictors

AACR reviewers are sensitive to:

overpriced consumables,

excessive personnel allocations,

irrelevant equipment purchases.

Lean budgets with central facility usage score higher.

🧵 Diversity & community impact (emerging predictor)

Recent cycles show:

emphasis on disparity-focused work,

access inequity,

demographic representation,

under-studied cancers.

Proposals that engage diverse populations score better.

🧑‍🔬 Applicant Profile Patterns

Typical successful profiles display:

consistent productivity,

early independence signals (co-PI, first-/senior-author),

integrated cancer seminar participation,

AACR meeting involvement.

Many winners previously presented at AACR conferences.

📉 Weak predictors / low-conversion approaches

Historically poor performance:

purely computational studies with no wet-lab validation

purely descriptive omics

overly incremental projects

indirect cancer hypotheses

🎯 AACR Reviewer Value Hierarchy (inferred)

Translational relevance

Preliminary data strength

Project feasibility

Mechanistic depth

Applicant trajectory

Innovation

Environment

Budget efficiency

In that rough order.

🧰 Meta-Predictor: Clinical Integration

Projects that connect:

experimental biology
→ biomarkers
→ trial pathways
→ therapeutic decision-making

score extremely well.

🏁 Summary: Strongest Predictors

A competitive AACR application generally has:

✅ clear clinical unmet need
✅ rigorous preliminary data
✅ mechanistic innovation
✅ translational biomarker strategy
✅ strong mentors/collaborators
✅ feasible, milestone-driven aims
✅ environment with cancer infrastructure
✅ attention to rigor & reproducibility

At the start of the grant term (July 1, 2026), applicants must:

  • Hold a faculty position with the title of assistant professor, instructor, research assistant professor, or the equivalent.
    • If eligibility is based on a future position, the position must be confirmed at the time of submission and CANNOT be contingent upon receiving this grant.
    • If the future position is at a different institution than the applicant’s current institution, the applicant must contact AACR’s Research and Grants Administration Department (AACR’s RGA) at grants@aacr.org before submitting their Letter of Intent for information on additional verification materials/signatures that may be required.
  • Have started their first independent faculty position within the past 6 years from the grant start date (i.e. cannot have held an independent faculty position before July 1, 2020).
  • Have independent laboratory space as confirmed by their institution.
  • Work at an academic, medical, or research institution anywhere in the world.

Sponsor Institute/Organizations: American Association for Cancer Research (AACR)

Sponsor Type: Corporate/Non-Profit

Address: 615 Chestnut St., 17th Floor Philadelphia, PA 19106-4404 USA Telephone: 215-440-9300 Email: aacr@aacr.org

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Grant, Award

Letter Of Intent Deadline:

Apr 07, 2026

Final Deadline:

Apr 07, 2026

Funding Amount:

$300,000

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