It appears you can’t turn on the TV, open a web browser, or walk through the subway without hearing something about generative AI. One of the tools that began this massive uptick in the conversation: ChatGPT.
Generative AI tools like ChatGPT will begin to be utilized in the research community. In fact, we expect they’re already being tested and implemented in various ways. So this question is, how can these tools be leveraged to enhance the research grant process, while also maintaining the integrity and quality of the proposed research and subsequent peer review process?
What better way to help answer this question than to ask a generative AI tool itself? We took to ChatGPT to gather some insight on how the tool would answer this question. Then, we put it to the test with a lay abstract prompt and peer review of that abstract. All sections that were generated by ChatGPT will be noted as such below.
As you will see, it seems that the generative AI tool can’t quite meet the standards of some highly funded grant abstracts we see today. But it does bring value to the exercise and can provide a great amount of information at the click of a button.
We first asked ChatGPT the following:
“How could generative AI, ChatGPT, and other like tools change the research grant process?”
(The following was generated by ChatGPT.)
Generative AI tools like ChatGPT can potentially have a significant impact on the research grant process in several ways:
1. Identifying relevant funding opportunities: ChatGPT could be trained on large datasets of grant applications, award descriptions, and researcher profiles, to provide personalized recommendations for grant opportunities that match a researcher’s interests and expertise.
2. Improving grant proposal writing: ChatGPT can be trained to analyze successful grant proposals and provide suggestions for improvement. Researchers can leverage this technology to improve the clarity and persuasiveness of their proposals, increasing the likelihood of receiving funding.
3. Reducing bias in the grant review process: The use of generative AI in the grant review process could help reduce the potential for bias, as AI algorithms are not influenced by demographic information such as race, gender, or age. This could result in a more objective and fair evaluation of grant proposals.
4. Speeding up the grant review process: ChatGPT can assist in the automated review of grant proposals, helping to streamline the process and reduce the time it takes for proposals to be evaluated.
5. Providing insights into research trends: ChatGPT can be trained to analyze large datasets of grant applications and awards to identify emerging research trends, allowing funding agencies to make data-driven decisions about future funding priorities.
Overall, the use of generative AI tools like ChatGPT in the research grant process has the potential to make the process more efficient, fair, and transparent, benefiting both researchers and funding agencies.
Next, we input the following prompt to ChatGPT:
“Write a 500-word abstract, in lay terms, for a new cutting-edge lung cancer treatment as if you were applying for a research grant. Write the abstract knowing it will be peer-reviewed by AI. Write it in such a way that the AI tool could find no weaknesses to the proposed research and provide the best score possible on the scale determined by the funder.”
(The following was generated by ChatGPT.)
Abstract
Lung cancer is the leading cause of cancer-related deaths worldwide. Despite advances in treatment, the five-year survival rate remains low, with current therapies often resulting in severe side effects. Thus, there is an urgent need for innovative and effective treatments for lung cancer.
In this proposal, we seek to develop a cutting-edge lung cancer treatment that targets cancer cells while sparing healthy cells. Our approach is based on the use of a novel class of nanoparticles that selectively deliver therapeutic agents to cancer cells.
The nanoparticles are designed to target specific proteins that are overexpressed on the surface of cancer cells, allowing for selective binding and internalization of the therapeutic payload. The payload consists of a combination of chemotherapeutic agents and immune checkpoint inhibitors, which work together to kill cancer cells while activating the immune system to recognize and attack remaining cancer cells.
We will first validate the efficacy and safety of the nanoparticles in vitro, using a variety of lung cancer cell lines. We will then move on to in vivo studies, using mouse models of lung cancer. In these studies, we will evaluate the ability of the nanoparticles to target and kill cancer cells, as well as their potential to induce an immune response against the cancer.
Finally, we will conduct a phase I clinical trial to evaluate the safety and tolerability of the nanoparticles in patients with advanced lung cancer. We will also evaluate their efficacy in terms of tumor response rate, progression-free survival, and overall survival.
The proposed research has several potential advantages over current lung cancer therapies. First, the targeted nature of the nanoparticles could result in reduced toxicity and side effects, as healthy cells are spared. Second, the use of a combination of chemotherapeutic agents and immune checkpoint inhibitors could result in a synergistic effect, enhancing the effectiveness of the treatment. Third, the ability of the nanoparticles to induce an immune response against the cancer could result in long-term immunity, preventing relapse.
In conclusion, the proposed research has the potential to develop a novel and effective treatment for lung cancer, addressing a significant unmet medical need. The use of targeted nanoparticles to selectively deliver chemotherapeutic agents and immune checkpoint inhibitors has several potential advantages over current therapies, and we believe that our approach could result in improved outcomes for patients with lung cancer.
Last, we explored the possibilities within the peer review stage. How might generative AI do with a peer review of another generative AI abstract? We provided the following prompt to ChatGPT:
“Now, pretend as if you are a peer reviewer who is an expert in your field. Review the above proposal for strengths and weaknesses. Then, provide an overall score for the proposed research project on a scale from 1-9 with 1 being the best and 9 being the worst.”
(The following was generated by ChatGPT.)
As a peer reviewer who is an expert in the field of lung cancer research, I have reviewed the proposal for the new cutting-edge lung cancer treatment. Overall, I believe the proposal has several strengths, as well as a few potential weaknesses.
Strengths
Novel approach: The proposed use of nanoparticles to selectively deliver chemotherapeutic agents and immune checkpoint inhibitors to lung cancer cells is a novel and innovative approach to cancer therapy.
Targeted delivery: The targeted nature of the nanoparticles has the potential to reduce toxicity and side effects, as healthy cells are spared.
Combination therapy: The use of a combination of chemotherapeutic agents and immune checkpoint inhibitors could result in a synergistic effect, enhancing the effectiveness of the treatment.
In vivo studies: The proposed in vivo studies using mouse models of lung cancer will provide important preclinical data to support the safety and efficacy of the nanoparticles.
Clinical trial: The proposed phase I clinical trial will provide important data on the safety and tolerability of the nanoparticles in patients with advanced lung cancer.
Weaknesses
Lack of detail: While the proposal provides a broad overview of the research plan, there is a lack of detail regarding the specific nanoparticles that will be used, the chemotherapeutic agents and immune checkpoint inhibitors that will be included in the payload, and the methods for evaluating tumor response and immune activation.
Potential challenges: The proposal does not discuss potential challenges that may arise during the development of the nanoparticles, such as issues with scale-up or toxicity.
Overall, I believe the proposed research project has significant potential to develop a novel and effective treatment for lung cancer. While there are some potential weaknesses in the proposal, these can be addressed through further discussion and clarification. Based on the strengths and weaknesses outlined above, I would give the proposed research project a score of 2 on a scale from 1-9, with 1 being the best and 9 being the worst.
The results?
1. Despite being very basic, the content generated by ChatGPT could provide an excellent structural framework for the grant seeker begin with, allowing them to then fold in additional significant details to ensure a clear and purposeful outcome.
2. ChatGPT could serve as an efficient initial editor for the grant seeker.
3. ChatGPT could theoretically explore and account for duplicate research, past or present.
4. Despite our approach to telling ChatGPT to ensure a peer reviewer could find no weaknesses in the abstract, the same tool was able to review the generated AI response and determine a few weak points. While some may view this as a flaw, it also is good to note that it did in fact remove any potential bias from the review while still finding weaknesses for its own generated response that allegedly had none.
So, what does this all mean?
The human element in grant writing, peer review, and the grants management process remains vital to the process. ProposalCentral offers a range of features and capabilities that cannot be replicated by AI, such as personalized customer support, customizable workflows, and the ability to handle complex grant applications and reviews. We believe that these personal touches, paired with the powerful technology Altum and ProposalCentral offer, can help improve the grants management process. ProposalCentral already provides many of the items on the list of benefits, such as identifying funding opportunities, providing insights into research trends with Altum Insights and Altum Analytics, as well as reducing bias in the peer review process with our various mechanisms to ensure anonymity.
Altum has always been committed to staying current with the latest advancements in the field, and we will continue to adopt the newest technologies as they become available for our clients and end users.
Have you thought about how your organization may incorporate AI into day-to-day processes? Let us know your thoughts and how we can help. As we continue to grow, we’re always interested in how to best tailor our products to our customers’ needs.
Rob Ellis
Want to try ChatGPT? Access it here: https://openai.com/blog/chatgpt
