OUTSOURCING


AI for medical writing: assistance, acceleration and augmentation


The promise of AI for the field of medical writing has been apparent for some time, and a number of teams have created tools of varying effectiveness and scope. Dr Barry Drees, senior partner at Trilogy Writing & Consulting, believes that the best AI tool for medical writing will assist, accelerate and augment the job of the medical writer.


stretching far past the use of AI as a jargon word for computer-assisted text creation. Back in the early 1990s, I was involved in discussions at the pharmaceuticals division at Hoechst in Frankfurt, Germany, about streamlining the writing of subject narratives for participants in clinical trials who experienced serious adverse events. At the time, the entire subject narrative was written by a medical doctor, including basic information about the subject’s age, sex and medical history, using the original line listings. This was an arduous, mistake-filled, time- consuming and expensive procedure that was estimated to cost major pharmaceutical companies millions of euros. It occurred to me and several of my colleagues that they could make this process much faster and less error-prone if they simply imported the subject’s basic information directly from the database. This presented the medical doctor, who was writing the subject narrative, with a small table showing all of the baseline information as well as everything about the adverse events – time, duration and intensity, for example – and study status. The doctor then only had to write their medical opinion about the course and how it related to the event in question. This reduced the time of writing by two-thirds, as well as considerably improved the accuracy. Clearly this was a question of both assisting and accelerating the writing process. These days, most medical writing projects use computer-created data tables – the old days of painstakingly searching through


T 6 | Outsourcing in Clinical Trials Handbook


he use of computers to assist the medical writing of documents for regulatory purposes has a surprisingly long history,


pages and pages of subject listings are thankfully largely ancient history. Augmentation, however, is an entirely different


matter. Most people understand augmentation as actual improvement – can an AI system actually improve the quality of regulatory documents above and beyond finalising them more rapidly, and with fewer mistakes? What would true augmentation actually look like? In fact, augmentation implies that there are things that can – and possibly even should – be improved, but what part of clinical documentation needs to be improved?


If it’s not broke, don’t fix it It is a poorly kept secret that reviewers at major regulatory agencies have complained about the poor quality of study report writing for many years. Some organisations still seem to see medical writing as mostly following a style guide and putting the data in the correct place in the ICH template. One can see this in what passes for regulatory writing in many of the study reports submitted to regulatory agencies – where the data from tables are simply repeated in the text with no attempt to say what they mean. I have long felt that this was not medical writing but rather medical repetition. Early in my career, when I asked a colleague about this, I was told that putting the same information in a table and the text ensured that the reader would have the data in whatever form they preferred, for example, tables or text. Laughing at this, I wondered whether there was even a single person on earth that preferred to read numbers in text rather than a well-designed table. Once told that it was important to describe


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