Second Round of Research Funding Spring 2024

Call for Proposals

The submission period for this funding opportunity has closed. Thank you to everyone who submitted a proposal. We will keeep you apprised of the results and next steps in the selection process.

The Center for Data-Driven Drug Development and Treatment Assessment (DATA), an NSF-funded Industry-University Cooperative Research Center (IUCRC) and a unit of the Michigan Institute for Data Science (MIDAS), in partnership with DATA’s industry members, is pleased to announce its second round of research funding awards, to be distributed in Spring 2024. We are inviting proposals for projects that will apply novel computational methods, data science solutions, artificial intelligence (AI) and machine learning (ML) techniques to solve problems of interest to our industry partners within the focus research areas of the Center, including drug design, drug repositioning, drug treatment assessment, patient phenotyping, and quantitative pharmacovigilance.

Submission information

  • EXTENDED! Submission deadline: Friday March 8, 2024, 11:59 pm EST.
  • Method of submission: Please upload all documents, as described under guidelines below, as a single PDF file using this Google form
  • Eligible applicants: University of Michigan researchers eligible to serve as a U-M Principal Investigator (PI) on sponsored projects (e.g., tenured-track or research faculty) are eligible to apply as the project lead PI or lead co-PI, i.e., the individual(s) responsible for the scientific or technical direction of the project. If a project has several lead co-PIs, the first PI listed on the proposal will hold primary responsibility for the project. 
    • MIDAS affiliate faculty is encouraged to apply.
  • Research topics of interest include but are not limited to:
    • Physiological simulation (organ-on-a-chip)
    • Less-invasive, multimodal methods for clinical data collection
    • Study of systematic integration of AI models/tools into clinical or pharmaceutical processes
    • Risk reduction in (granular) clinical data sharing
    • Simultaneous analysis of multi-omics/multimodal data
    • RNA generative design
    • PP and collaborative tensor models for in-silico perturbation analysis
    • Representing chemical data for training generative AI models
    • Best use cases for privacy-preserving/confidential data sharing technologies
    • Ontological framework for extracting knowledge from confidential data
    • Evaluation of the utility of multivariate time series analysis for treatment assessment

Information Session

A virtual information session was held on Thursday, February 1, 2024 with program representatives. The following materials are available from that session:

Content guidelines

Proposals should include:

   1.  Project description:

    • Problem statement: Description of the problem(s) within the Center’s focus research areas that the project will aim to solve. Please also address the importance of solving the problem(s) to the pharmaceutical and healthcare industries.
    • Methods: Description of the data science, AI, and ML methods and techniques that will be used to investigate the problem(s).
    • Innovation: Discussion of how the proposed methodologies contribute to innovation in the field of drug discovery and/or treatment assessment.
    • Milestones & deliverables: Description of project milestones and proposed deliverables through the anticipated length of the project. 
    • Industry partners: A list of industry sectors within the Center’s focus areas that are expected to participate in and/or benefit from the project. DATA’s industry focus includes pharmaceutical, biotech, healthcare, computing & technology (big tech, startups), AI/ML, and data standardization sectors. Proposals involving multiple industry fields and/or partners are strongly encouraged. DATA-funded projects should be designed to foster active research collaboration between University researchers and the Center’s industry partners (members and affiliates). While not required, applicants who have discussed their project ideas with a DATA member or affiliate should specifically identify their expected collaborators.

Please do not include any proprietary or confidential information and limit your project description to two (2) pages in length.

   2.  References: Please limit your references to two (2) pages.

   3.  Budget

  • While a detailed budget is not required at this time, proposals should include the estimated funding needs by expense category.
  • Eligible expenses include support for research personnel (e.g., students, trainees, post-docs, non-tenured faculty), lab resources (e.g., high performance computing and storage, consumables).
  • Tenured faculty effort or funding for travel may not be included in the budget.
  • Awards are limited to $40,000/project/year, including a 10% indirect cost rate.

   4. Biosketch of the lead PI and each lead co-PI (if any), no more than two (2) pages in length.

Limit on number of proposals

Multiple submissions by the same applicant will be accepted, with a cap of two (2) proposals for which an applicant may serve as a PI or a co-PI.

Selection process & review criteria

A two-tiered evaluation process will be used to select funded projects:

  1. Proposals satisfying the content and submission guidelines will be evaluated by members of the Center’s Industry Advisory Board (IAB), using criteria including (i) significance & relevance of the problem(s) to DATA’s mission, (ii) novelty of the suggested methodological approach, (iii) project team & resources, (iv) a member’s preference for funding the project & interest in active collaboration, (v) the extent to which the project will involve or benefit multiple industries and/or multiple DATA industry partners. Results of the first round of selection will be communicated before DATA’s Spring 2024 IAB meeting (scheduled for May 16-17, 2024).
  2. Applicants with top-rated proposals will be invited to give a brief, 10-minute presentation at DATA’s Spring 2024 IAB meeting, which will be held on May 16-17, 2024, in Ann Arbor, MI (U-M North Campus Research Center). The IAB will make its funding decisions at this meeting or shortly afterwards. Please be available for in-person participation on Thursday, May 16, to deliver the project presentation, and in the morning of Friday, May 17, for a discussion & review session with the IAB.

Award Information

  • Please review the full DATA award terms here.
  • Proposed projects may be designed for multiple years; however, award decisions are made on a year-by-year basis.
  • Proposed projects may not duplicate projects funded by other awards received by the researchers.
  • Intellectual Property: DATA is a pre-competitive consortium of academia and industry. In accordance with NSF rules, DATA’s industry members receive a non-exclusive royalty-free license to intellectual property derived from inventions conceived or first actually reduced to practice within the Center. If you wish to receive more details on the nature of this license, please contact U-M Innovation Partnerships at magnolia@umich.edu. If intellectual property created prior to, or outside the scope of, a Center project is required for a research project selected for funding, U-M Innovation Partnerships will negotiate appropriate agreements as necessary.

Questions?

Please contact DATA staff at data-iucrc@umich.edu.

About DATA

Established in 2022, the Center for Data-Driven Drug Development and Treatment Assessment (DATA) is part of the Industry-University Cooperative Research Centers (IUCRC) Program of the National Science Foundation and a unit of the Michigan Institute for Data Science (MIDAS) at the University of Michigan. DATA advances U.S. competitiveness by working with industry to solve current, emerging, and industry-relevant challenges in drug design, drug repositioning and repurposing, treatment monitoring, assessment and optimization, patient phenotyping, and quantitative pharmacovigilance using novel computational and data science techniques such as metrology, machine learning (ML), and/or artificial intelligence (AI), including generative AI, and by training the next generation of talent in this field. DATA seeks to produce new methodologies and infrastructure for industry-wide collaborative drug discovery and treatment assessment, with the goal of significantly accelerating the pace of drug development to help target the right drug to the right person at the right safe and effective dose while reducing R&D costs.

The advent of generative AI has created an urgent need for stakeholders in all stages of the drug life cycle to come together, share experiences with this revolutionary technology, and jointly address its implications for health care. Thanks to its cross-industrial and cross-disciplinary nature designed to bring together data scientists, mathematicians, biomedical researchers, pharmaceutical companies, healthcare providers and payers, and government agencies, DATA is ideally positioned to catalyze these conversations, identify best practices, and develop solutions to the challenges generative AI brings to the health care sector.