2027 Collaborative Research Development Grant – Microsoft AI for Good Lab

The 2027 Collaborative Research Development Grant (CRDG-AI) from the Ovarian Cancer Research Alliance, in partnership with Microsoft AI for Good Lab, funds high-impact ovarian cancer research integrating artificial intelligence (AI) and machine learning (ML). The program provides up to $900,000 over three years plus Microsoft Azure cloud computing credits. Collaborative, interdisciplinary teams with strong clinical expertise are encouraged to submit a Letter of Intent.

Overview

The 2027 Collaborative Research Development Grant (CRDG-AI) is a competitive funding program designed to accelerate innovation in ovarian cancer research through artificial intelligence and machine learning.

The grant supports interdisciplinary research teams that combine oncology, data science, computational biology, epidemiology, and health services research.

Projects must place AI or ML at the core of the research design and demonstrate direct relevance to ovarian cancer or related gynecologic cancers.

Grant start date: January 1, 2027
Application stage: Letter of Intent (LOI)

Funding Structure and Benefits

Total Funding Amount

• Up to $300,000 USD per year
• Duration: 3 years
• Maximum total: $900,000 USD
• Funds awarded to the Principal Investigator’s institution

Additional Support

• In-kind Microsoft Azure cloud computing credits
• Direct collaboration with Microsoft AI for Good Lab
• Formal contract with Microsoft for Azure services

Reporting and Deliverables

Awardees must:

1. Submit activation deliverables before project launch

2. Provide annual narrative and financial reports

3. Publish peer-reviewed research findings

4. Acknowledge OCRA support in all publications

Research Focus Areas

Eligible projects must demonstrate clear and direct relevance to ovarian cancer, including related gynecologic cancers.

Strong preference is given to high-impact and innovative research in:

1. Screening and Early Detection

AI-driven diagnostic models, predictive risk algorithms, imaging analysis, biomarker identification.

2. Etiology and Prevention

Data analytics to study genetic, environmental, and lifestyle risk factors.

3. Therapeutics and Precision Medicine

Machine learning for drug discovery, treatment optimization, and response prediction.

4. Cancer Biology and Genetics

AI-assisted genomic analysis, tumor biology modeling, molecular pathway mapping.

5. Epidemiology and Health Services Research

Population-level predictive modeling and health system optimization.

6. Quality of Life and Survivorship

AI tools to monitor symptoms, outcomes, and survivorship metrics.

Core Requirement: AI or ML must be a central and substantive component, not an add-on tool.

Key Definitions

Artificial Intelligence (AI): Computational systems capable of pattern recognition, prediction, and decision support.

Machine Learning (ML): A subset of AI where algorithms learn from structured or unstructured data to improve performance.

Microsoft Azure: A cloud computing platform that supports large-scale data processing, storage, analytics, and secure research environments.

Principal Investigator (PI): The lead researcher responsible for scientific oversight and grant compliance.

Who Is Eligible?

Eligible Institutions

• Accredited academic institutions
• Non-profit research entities
• Research hospitals and scientific institutes

Not Eligible

• For-profit companies
• Consulting firms
• Non-research organizations

Investigator Requirements

Each team must:

• Designate one Principal Investigator
• Ensure all lead investigators hold full-time faculty or equivalent appointments
• Include at least one physician with expertise in ovarian or related gynecologic cancers

Additional Rules

• One LOI per PI per grant cycle
• Only one active OCRA grant at a time
• International applicants and collaborations are welcome

Collaboration Model

The CRDG-AI program is built for collaborative research teams working:

• Within a single institution
• Across multiple institutions

The program encourages interdisciplinary collaboration between clinicians, data scientists, AI engineers, epidemiologists, and translational researchers.

Why This Grant Matters

1. Addresses Unmet Clinical Needs
   Ovarian cancer often lacks effective early detection tools. AI can identify subtle patterns in imaging, genomics, and clinical datasets.

2. Accelerates Translational Research
   Machine learning models can shorten the path from data discovery to clinical application.

3. Enables Large-Scale Data Analysis
   Microsoft Azure supports scalable computing for high-dimensional genomic and imaging data.

4. Promotes Global Collaboration
   International teams can leverage shared cloud infrastructure for cross-border research.

How to Apply – Step-by-Step Process

Step 1: Build a Qualified Team

• Confirm institutional eligibility
• Identify interdisciplinary collaborators
• Include at least one ovarian cancer physician

Step 2: Develop an AI-Centered Research Plan

Your proposal must clearly define:

• Research question
• AI/ML methodology
• Data sources
• Expected clinical or scientific impact
• Azure cloud integration plan

Step 3: Submit a Letter of Intent (LOI)

The LOI should include:

• Project summary
• Scientific rationale
• AI/ML integration strategy
• Investigator roles and expertise

Step 4: Invitation to Full Proposal (If Selected)

Shortlisted applicants may be invited to submit a detailed full application.

Step 5: Post-Award Requirements

• Execute agreement with OCRA
• Sign Azure credit contract with Microsoft
• Submit required activation materials

Common Mistakes to Avoid

1. Treating AI as a Secondary Tool
   The AI/ML component must be central to the research design.

2. Weak Ovarian Cancer Relevance
   The proposal must clearly focus on ovarian or related gynecologic cancers.

3. Missing Required Clinical Expertise
   At least one qualified physician investigator is mandatory.

4. Ineligible Institutional Status
   Confirm nonprofit or accredited academic status before applying.

5. Lack of Cloud Integration Planning
   Azure computing use must be clearly explained and justified.

Frequently Asked Questions (FAQs)

1. What is the maximum funding available?

Up to $900,000 USD over three years, distributed as $300,000 annually.

2. When do funded projects begin?

All funded projects start on January 1, 2027.

3. Is artificial intelligence mandatory?

Yes. AI or machine learning must be a clearly defined and substantive core component of the research.

4. Are international researchers eligible?

Yes. International applicants and collaborations are permitted if eligibility criteria are met.

5. Can for-profit biotech companies apply?

No. Only accredited academic institutions and nonprofit research entities are eligible.

6. What additional support is provided beyond financial funding?

Funded teams receive in-kind Microsoft Azure cloud computing credits and formal collaboration with Microsoft AI for Good Lab.

7. How many applications can a Principal Investigator submit?

A PI may submit only one Letter of Intent per grant cycle and may hold only one active OCRA grant at a time.

Conclusion

The 2027 Collaborative Research Development Grant (CRDG-AI) represents a major investment in AI-driven ovarian cancer research. With up to $900,000 in funding and Microsoft Azure cloud support, the program empowers interdisciplinary teams to develop scalable, data-driven solutions in early detection, therapeutics, genomics, and survivorship.

Research teams with strong clinical expertise and advanced AI capabilities should prepare a clear, impact-focused Letter of Intent to compete for this high-value funding opportunity.