Innovation in Clinical Trial Design Award

The Innovation in Clinical Trial Design Award from the Mayo Clinic Center for Clinical and Translational Science (CCaTS) offers funds to support investigators in the development and evaluation of new clinical trial designs. Goals for these designs include:

  • Reducing sample size.
  • Lowering clinical trial costs.
  • Limiting on-site visits.
  • Substituting artificial intelligence (AI) alternatives for in-person data collection, with the intention of facilitating clinical study protocols that consider the burden of participation in terms of time and travel.

High-quality proposals will be assured through a collaborative review process with CCaTS biostatistics, epidemiology and research design resources. Proposals that incorporate AI and digital science approaches to subject recruitment, data collection and analysis are encouraged.

Standard features of the traditional randomized clinical trial, such as control arms, randomization, stratification and blinding, are designed to minimize bias and maximize conclusiveness and interpretability of results. However, the traditional clinical trial design often requires large resource expenditures and usually focuses on narrow research questions.

A proposed innovation represents a deviation from the traditional design and, as such, results in new benefits and potential risks that must be thoroughly discussed, anticipated and tested. While smaller sample sizes are a common goal of innovative clinical trials, an equivalently or slightly larger sample size may help answer broader questions and minimize the risk of a failed trial. For example, the use of historical control information can substantially reduce the size of a trial, particularly for rare diseases. But this advantage requires careful matching of the historical data to the current trial. Otherwise, the trial may impose inferential risks due to mismatches.

General examples of innovative trial designs are flexible sample sizes, enrichment, use of historical information, adaptive trial designs, multiple arm and multiple domain trials, and novel endpoints. Specific examples include:

  • Multiphase optimization strategy (MOST) designs for multicomponent interventions.
  • Pragmatic clinical trials in real-world setting.
  • Clinical research studies to build diverse community partnerships needed to increase research participation by underrepresented participants.
  • Clinical research to overcome major logistical barriers to participation, including the number of on-site visits, time commitment and travel-associated obstacles.
  • Use of electronic consent to provide an option for broad sharing of de-identified data.
  • Development and deployment of citizen science methods to engage diverse and underrepresented populations.
  • Collaborations to identify, evaluate and increase knowledge about best practices for recruitment and retention of research participants.
  • Establishment of new standard outcome measures necessary for data comparisons across trials.
  • Implementation of innovative trial designs with a precision medicine research paradigm.
  • Designs that reduce the number of participants needed, for example N = 1 trials.
  • Designs that utilize remote or AI technologies.
  • Innovative statistical design approaches, especially in trials of one or few individuals.
  • Novel methods to identify appropriate participants, such as those with rare diseases.

The scope of projects supported by this award mechanism may include any step in the development of novel aspects of clinical trial design, including subject participation, outcome measures, data collection and analysis, guidelines, and venues. The successful proposal will develop approaches that can be generalized and serve as a foundation for other studies in unrelated fields.

2023 awardees

Brian J. Arizmendi, Ph.D., L.P., "A User-Optimized Digital Behavioral Health Program To Promote Patient Success in Endoscopic Bariatric Therapy." Dr. Arizmendi and colleagues will incrementally develop and evaluate the creation of a digital psychosocial care delivery platform with an initial application to bariatric surgery.

Cody C. Wyles, M.D., "Leveraging Large Language Models and Clinical Registries to Improve Data Collection Processes for Clinical Trials." Dr. Wyles and colleagues will address on of the barriers to conducting clinical trials — time and expense for data collection — through the development and implementation of a large language model.

Eligibility

All Mayo investigators with an M.D., Ph.D. or other doctoral-level degree are eligible to apply. Eligible positions include:

  • Consultant.
  • Senior associate consultant.
  • Associate consultant.
  • Research fellow.
  • Clinical fellow.
  • Resident.
  • Nurse scientist.
  • Research scientist.
  • Research associate.
  • Allied health staff.

Individuals in the process of transitioning from mentored career development awards to independent awards are encouraged to apply.

Funding

CCaTS anticipates funding up to two awards from this request for applications. Awards provide up to $50,000 in direct costs for study-related expenses for one year, plus indirect costs. Extensions are considered only under extenuating circumstances.

Expenses that are not covered by funding include capital equipment and computers or laptops.

Recipients of grants or awards supported by CCaTS may be asked to review applications for other future CCaTS grants.

Application information

Timeline

Full applications are due by 5 p.m. Central time on June 17, 2024. They must be submitted through the START Application Tool. Log in to the Mayo Clinic network to access.

The anticipated award date is Nov. 1, 2024.

Application requirements

Applicants are required to include the following:

  • Biosketches for faculty team members using the new National Institutes of Health (NIH) biographical sketch format.
  • Brief budget justification.
  • Letter(s) of support, if applicable.

A formal Mayo Integrated Research Information System (MIRIS) budget prepared by the Office of Sponsored Projects Administration (OSPA) is not required at the time of application. If the project is selected for funding, the awardee will work with Susan (Sue) J. Rubow and OSPA to create a MIRIS funding proposal and budget.

Review criteria

CCaTS applies the following criteria when reviewing applications for the Innovation in Clinical Trial Design Award:

  • Scientific merit, with a strong emphasis on:
    • Clinical trial designs that reduce sample size and on-site visits.
    • Use of AI and digital technology in any or all aspects of participant recruitment and data collection or analysis.
    • New or novel outcome measures.
  • Likelihood of future extramural funding.
  • Feasibility within the time and budget proposed.
  • Qualifications of the investigators.
  • Evidence of plans for multidisciplinary collaboration.

Prior approval for research involving human participants

Awardees with projects involving human participants are required to submit information to the National Center for Advancing Translational Sciences (NCATS) to obtain prior approval before conducting any activities related to human participants. Documentation includes a human subject plan. CCaTS staff members guide awardees through the process and provide assistance.

Reporting

Annual progress reports are required for up to two years beyond the end date of the award.

Publications

The NIH Public Access Policy requires that all publications resulting from NIH funding be uploaded to PubMed Central. Recipients of CCaTS awards, including intramurally funded awards, must follow this policy. The Mayo Clinic Public Access Policy intranet site guides awardees through the process of uploading publications. Log in to the Mayo Clinic network to access.

Please remember to cite the Mayo Clinic CCaTS grant in your publication.

Contact

For scientific questions, email Robert J. Pignolo, M.D., Ph.D. For questions about the request for applications or the START Application Tool, email Sue J. Rubow or Tobias C. Wolf.