Proposal

Please observe the page limits by type of grant application:

Standard Grant:        6 pages maximum

Small Grant:              3 pages maximum

If you have a proposal with a low budget ($7,500 or below) and you cannot adequately describe the proposal in 3 pages for a Small Grant application, consider submitting it as a Standard Grant instead if preliminary data exist for your project. Standard Grants have a budget up to $50,000 but no minimum. Please note the features of the two grant types, described earlier. These grant types also differ by review criteria, which are addressed later in this tutorial.

The proposal consists of the following sections, all of which must fit within the page maximum for the grant type:

  1. Preliminary Work, if applicable
  2. Statement of Work
  3. Anticipated Outcome(s)
  4. Anticipated Pitfall(s)

To conserve page space in your application, delete the application instructions from your proposal. If the proposal exceeds the appropriate page maximum, it will be disqualified. An appendix (see next page) may be included as an additional page/s and is not considered part of the page maximum.

Appendix

You may include an appendix at the end of Section D for form documents, such as a questionnaire or a scoring sheet, if this information will support the proposal. The appendix does not count against the page maximum specified for the type of grant in Section D. Proposal.

Please do not use the appendix to extend the description of your proposal, else your application will be disqualified.

 Prelim Work

Preliminary work is a requirement for a Standard grant, but optional for a Small grant.

If you or colleagues have produced preliminary data that may support your proposal, it will be helpful to present this information and show how this work leads in to your proposed study.

For example:

  • Methods to be used may have been previously proven to work in your laboratory.
  • Preliminary data suggest findings that may be confirmed in the proposed study.
  • You demonstrate how your previous experience prepared you for this proposal.

Preliminary data provides a back-up to your proposal. If appropriate, include images, charts, or tables that clarify how your current proposal is a logical next step in your research.

If the preliminary work is not yours, clearly identify the source. Provide a reference if it is published.

If no preliminary work has been done, for example in a Small Grant application, state so in the application.

 Statement of Work

State the research problem and provide background information.

Prepare the reviewers for understanding your goals or the hypothesis you will test and the specific aims you hope to achieve. Persuade the reviewers that your proposal is significant.

Example:

To our knowledge, no studies have been undertaken to directly evaluate if the delivery gas used to administer isoflurane to rodents via nose cone impacts physiologic parameters. Therefore, we propose studies to verify our preliminary findings in mice and rats and to quantify the atelectasis through functional, histological, and imaging techniques.

Remember: only some reviewers may be familiar with your topic. Avoid jargon and provide all the information to help an unfamiliar person understand.

Describe the specific aim.

Consider these examples:

  1. Determine if delivery of isoflurane in 21% oxygen negatively impacts physiological parameters (e.g., body temperature, MAP, PaO2, PaCO2, and time to recovery) compared to delivery in 100% oxygen, in order to make rodent anesthesia guidelines based solidly on physiological data.
  2. Determine the extent of alveolar atelectasis responsible for ventilation/perfusion inequality in rodents receiving inhalation anesthesia delivered in 100% oxygen.

Describe the experimental design, including study methods.

Describe the feasibility of the study and provide statistical justification for the numbers of animals being used. Include in your justification differences of sex and age.

Be clear and logical--you should provide a solid rationale for the use of the GLAS funds. How you justify your approach/methods can determine your success!

Do you have the resources and expertise to conduct the proposed study? Don’t describe equipment here as there is a follow-up section for facilities and equipment.

Describe the methods of data analysis and statistical analysis to be used, if applicable.

A common source of error in experimental design is the selection of an inappropriate statistical method. Often, such errors are not recognized until too late--when the study has been completed and the data are about to be analyzed. This error can lead to a reduction in the power of the statistical analysis, and consequently a lessening or even negation of the statistical significance of your findings. The scientific paper written in that scenario would be weaker than one utilizing the correct statistical method. Possibly, the paper may be flawed and not publishable in a peer-reviewed journal. As a scientific paper is the ultimate product of your research, carefully plan your statistical approach.

Choosing the right statistical method for your analysis is crucial and requires expertise. If possible, consult a statistician. Alternatively, confer with a mentor who is experienced in the same line of scientific inquiry and has a strong publication record.

What is the predicted timeline for completing the study?

A diagram may help others understand the sequence of events for a complex series of experiments.

 Outcomes and Pitfalls

Explain the possible immediate and long-term outcomes (significance) of the study that you predict will impact the laboratory animal science field.

  • How may the expected results support the GLAS mission?
  • Would the results possibly lead to a subsequent research study?
  • Explain possible pitfalls and experimental design weaknesses in your experimental approach.
  • Indicate how the risks of possible pitfalls will be managed.

See the hyperlinked example for how the possible pitfalls are to be managed in the sample proposal.

Sample Section D. 5. Pitfalls