How to write winning grant applications: Part 2

At the start of the year, we launched our “fresh look” grant editing service. We have already started working with many of you and look forward to learning the outcome of your proposals later in the year. Meanwhile, IEL’s Director and senior editor Dr. Neil McCarthy has put together a three-part blog on “How to write winning grant applications”.

About Neil

Before finding out what Neil has to say in part one of his blog, let’s find out why he is ideally placed to provide IEL clients with some useful hints and tips on successful grant writing!

Many of you will know Neil as a senior editor with Insight Editing London (IEL), but he is also a Lecturer in Immunology / MRC Career Development Fellow in the Faculty of Medicine at Queen Mary University of London. Neil is Research Lead in The Blizard Institute’s Centre for Immunobiology, as well as Infection and Inflammation Lead in the cross-faculty Centre for Predictive in vitro Models. He has secured more than £1M in personal research funding to date, including research council grants, via charitable sources, and through various commercial projects. Let’s hear what Neil has to say, in part two of his blog, “Time – Team – Tools“.

Time – Team – Tools

“A key component of biomedical grant writing is clearly outlining the important scientific or clinical problem that you are ultimately trying to ‘fix’. In your proposal, you will need to convince a reviewer that this is the best possible time, team, and tools you could need to tackle this issue. For conventional project grants, this involves identifying a major current challenge in biomedicine, breaking this down into competent parts, and then securing the best possible collaborative partners and research tools to address each separate element.

If your own research team lacks a key skill, it is important to forge links with other labs that have the required track record to cover that need. In an ideal situation, each project aim will also be linked but not dependent on the others, so that if any one aspect of the study fails there will still be useful outputs from other areas. At the same time, a compelling grant proposal will also have a clear ‘narrative arc’ that ties the individual pieces together, thereby appearing to build towards your ultimate goal of ‘curing disease x’ (or at least making some progress in this direction).”

Stay tuned for part two that discusses the importance of the “Person, Project, and Place”!

At the start of the year, we launched our “fresh look” grant editing service. We have already started working with many of you and look forward to learning the outcome of your proposals later in the year. Meanwhile, IEL’s Director and senior editor Dr. Neil McCarthy has put together a three-part blog on “How to write winning grant applications”.

About Neil

Before finding out what Neil has to say in part one of his blog, let’s find out why he is ideally placed to provide IEL clients with some useful hints and tips on successful grant writing!

Many of you will know Neil as a senior editor with Insight Editing London (IEL), but he is also a Lecturer in Immunology / MRC Career Development Fellow in the Faculty of Medicine at Queen Mary University of London. Neil is Research Lead in The Blizard Institute’s Centre for Immunobiology, as well as Infection and Inflammation Lead in the cross-faculty Centre for Predictive in vitro Models. He has secured more than £1M in personal research funding to date, including research council grants, via charitable sources, and through various commercial projects. Let’s hear what Neil has to say, in part one of his blog, “The Wisdom of Crowds“.

The Wisdom of Crowds

“An excellent piece of advice for all aspiring grant writers is to START EARLY. On too many occasions, I have been asked to provide feedback on a rough draft proposal when the planned submission date is only a week or two away! Constructing an excellent grant takes a lot of time, and ideally a large amount of feedback from both specialist and non-expert reviewers collected along the way. This is vital to ensuring that you put forward the best possible case for support.

Following on neatly from this last point – do not listen to ALL the advice you are given simply because it has been offered. This may seem counter-intuitive, but remember that not all input you receive will be *good* advice. An important part of your job as the applicant is to discern the difference between a constructive / valid point and other comments that may be less valuable or even harmful to your case. When writing my own fellowship proposal, I received feedback ranging from ‘this looks great / submit right now!’ all the way to ‘you should start again with a blank sheet of paper’ (in both cases, these were comments on the final proposal that was ultimately submitted and funded). So, always be wary of extreme opinions – whether strongly positive or negative – since often these are unlikely to provide much useful information to help enhance your application.”

Stay tuned for part two that discusses the importance of “Time, Team and Tools”!

Can we really use AI to write research papers?

 

As an editor, writer, and scientific researcher, I am following with interest the gaining momentum of artificial intelligence (AI) programs in the context of scientific writing.

AI tools are certainly causing a stir and even leading journals Nature and Science are at loggerheads over the best way forward.

Once I learned that Nature journal were accepting submissions that acknowledged AI-assisted writing tools, I decided it was time to check it out for myself. After reading various opinions on the subject, I decided that for the time being, these algorithms are likely best used for creating the “filler” text: introductions, summaries.

I initially asked one-such prominent AI tool (ChatGPT) to compose an introduction for a review paper on acute kidney injury (AKI) in children. I was pretty impressed – within a few seconds I had some fairly decent prose written in the style of a review article introduction. Sentences perfectly formed. A native tone. Ideal.

But the text was superficial. The introduction comprised just 126 words, of which a third described what the review would be about (based on the text I input).

Perhaps these algorithms needed more input than I thought. So, giving it the benefit of the doubt, I gave the algorithm a bit more information, asking it to include a discussion on the genetic basis of AKI in children.

I gained just 20 words on the original.

First impression – a good starting point but certainly not relieving me of the task of writing my introduction.

On to its next test. “Can you include some references in the introduction you have written?”, I asked. “Certainly!”, it boldly responded.

The same introduction came back but now with three reference citations repeatedly dotted about the text. I was shocked, as on first glance, we now had something approaching the full package. A fully referenced piece of novel, grammatically correct, text. The references were absolutely plausible – the journals were well known for the field, I knew the author names and the subject area matched their expertise. There was nothing to suggest anything was wrong.

But the editor and researcher in me checked these three references out. I could not find them anywhere.

So I asked ChatGPT directly, “Are these real references?”. The reply was adamant. “Yes, the references cited are genuine articles that have been published in the scientific literature…” The only concession ChatGPT made was that being a language model, it does “not have the ability to independently verify the accuracy of validity of the content of these references” (a perhaps even more important issue for a later discussion).

I searched again, and again came up with nothing. I asked ChatGPT three times and each time it maintained that the references were genuine, though it conceded that perhaps the citations contained typographical errors hence leading to my problem to find them. On the fourth attempt telling ChatGPT that the references were non-existent, the response was unexpected, to say the least.

ChatGPT returned to me the 200 words or so of introductory text, but this time with a disclaimer that the references referred to “are fictional and provided as an example only”.

Fourth time lucky. It took me half an hour to create some 200 words of falsely referenced text, and half an hour to get ChatGPT to admit it. Could I even trust those 200 words now?

Armed with this knowledge, I repeated the experiment on a different subject area. The same thing happened. This time, two out of three references were invented by ChatGPT. Now knowing how to probe ChatGPT for the truth, I quickly got the response that “the references were generated based on commonly cited sources in the scientific literature” and that “they do not appear to be accurate or credible sources of information”. But I had to probe for this answer many times before the truth came out.

My discovery, therefore, is quite profound. ChatGPT lied. Several times. Here, no harm was caused but I was committed to checking and double checking. Will everyone using these tools to save time be so persistent? In the real world, misattributing statements of fact to actual real researchers is dangerous and misleading. Moreover, if the content these tools create is also false, and then attributed to an active researcher…then what? The repercussions could be serious.

I have no doubt that these prototypes are going to develop into highly sophisticated tools that will have enormous benefits, uses and applications. But I urge caution, especially in the context of the biomedical sciences. As with most things, there are pros and cons with these tools, and while we are in the early days of their development, I suggest that you trust your own abilities rather than a computer to write your papers.

*My tests were based on ChatGPT Jan 30 Version. Free Research Preview. These tests were conducted in February, 2023.

Perfecting your presentation

So far, we have thought about how to select a review topic and reach out to a target journal. Now that you have your structure, bibliography, and potential target journal in place – you are finally ready to write your review! In this final blog post, I will share with you a few tips and tricks to write a clear, concise and effective review article.

All the principles of good science writing apply, but ensuring clarity and concision are at the top of my list. It is tempting to write a thesis on your favourite subject, but consider your audience, their attention span and their time available to read your review. An effective review is often around 3,000-5,000 words (although some journals accept longer). If you think you will greatly exceed this word count, then perhaps your topic is too broad or you have started to diverge away from your original topic. The good news is that this might mean you have enough material to write another review later down the track!

Primary research articles are exciting and interesting because they are full of new data with supporting figures and tables. Make sure you bring the same level of interest to your review article. Blocks of unbroken text are daunting and off-putting to read. Aim for at least one display item to accompany each main section of your review: perhaps a cartoon, schematic, table, graph, or information box. Whatever you create, make it novel, informative and interesting. Remember – display items from reviews are often heavily recycled in conference talks and posters, and so serve as great advertising for your article and your research team!

Research articles condense the excitement of unraveling new data: how can you bring that level of intrigue to a review article? While a review article doesn’t necessarily include new data, you can still offer your unique opinion. Much of your audience will have chosen to read your review because of your authoritative position in the field, and others might be looking for inspiration. So, create a buzz by offering some speculation and suggesting new avenues for research and development in the field. Just make sure you explain that this is just your opinion (of many alternatives) and not necessarily consensus!

Finally, you should consider who is going to co-author your review if you choose not to fly solo. Review articles tend to include just a handful of authors who are ideally from different labs, representing different opinions and expertise. Including your entire research group is discouraged — rather, your audience will want to see that your review has been crafted by a select group of experts. To avoid arguments, think about this sooner rather than later!

We hope you found this series of blog posts on writing un-commissioned reviews helpful. The IEL team look forward to seeing what you produce over the coming year.