Quality & Compliance
Safety & Vigilance
01 december 2023
Machines are evolving from basic instruments that carry out orders into self-taught, self-correcting machines that make judgments as a result of developments in computer science and the growing quantity of data that is accessible. The modern age of artificial intelligence (AI) technology is upon us, with the potential to completely transform how we work and live. AI is rapidly advancing into the medical and healthcare domains and is beginning to impact medical writers’ jobs. Though touted as a solution, AI can provide significant obstacles for every medical writer. This article underlines the significance of keeping up with the AI world, highlights medical writers’ vital role in an AI-driven healthcare system, and explains how AI may empower medical writers in multiple areas (regulatory, medical affairs, and publication).
Newly developed AI algorithms work well with medical images, including, but not limited to, biopsy images, magnetic resonance imaging (MRI), computed tomography (CT), and electrocardiography (ECG). AI reduces errors and increases the sensitivity, specificity, and speed of diagnosis by identifying patterns not identifiable by the human eye. Besides this, there has been an exponential growth in the amount of medical data that can be collected via wearable devices, mobile telephone applications (apps), and other interconnected medical devices (Internet of Medical Things –IoMT). Personalized medicine can be exercised through continuous and remote monitoring in real-time, thus reducing site visits and providing an online support network with quality interactions by using, for example, chatbots and apps that improve patient engagement, management, and compliance. In addition, patients and consumers are becoming more open to constant monitoring by AI-driven healthcare, from wearable devices to robot-assisted surgeries. However, not all healthcare professionals feel comfortable relying on AI-powered software, and this gap needs to be bridged.
It would be helpful to talk about natural language processing (NLP), the AI technology that helps computers understand the natural language of humans beyond the “ones and zeros.” We encounter NLP several times daily: Google Translate, Gmail autocomplete, text processors such as MS Word or Grammarly, and personal assistants such as Siri, Alexa, etc. Medical writers care about the readability of their writing, as this will dictate the written material’s exposure, comprehension, and impact. A good writer pays attention to the audience and knows how to adjust the text to its readers. Thus, the four major elements of readability – content, style, format, and organization – constitute the readability formulas that famous text processors, such as MS Word and Hemingway editor, use to score readability. However, these tools are based only on static metrics like the number of words per sentence, syllables per word, etc., and do not have the ability to understand complex grammar, context, or feelings expressed by the words. Thus, they cannot create original text. An AI tool based on NLP can use the same information as input, teach itself, and produce a variety of texts adapted to different audiences in a fraction of the time, such as nursing narratives or conversion of electronic health records into plain language. NLP algorithms may soon help medical writers replace one of their most time-consuming, tedious tasks, simultaneously offering the highest degree of security: authoring structured content. A large portion of clinical protocols and clinical study reports can be automatically created by AI tools in a matter of hours instead of weeks so that the medical writer can focus on activities that require a higher level of scientific interpretation. Achieving such a high level of productivity, confidentiality, and consistent compliance with regulations is the enormous promise of AI to regulatory writers.
More and more authors of scientific studies are becoming frustrated with the traditional peer review process, highlighting severe problems in fighting bias, slow speed, or lack of transparency. AI tools can give a hand in most of the laborious processes of peer review. For example, AI-based programs can identify and control parallel communication strategies with reviewers until the required number of reviews has been reached. Journals are testing plagiarism, bad reporting, and manipulated image detection tools. Similarly, editing can be automated with AI-based tools that automatically control and amend documents to comply with required styles and formats.
AI tools can scan the vast medical literature and the scattered available networks of physicians and scientists to create a list of key opinion leaders and the best strategy to make contact. AI tools can educate medical writers and medical affairs professionals with the essential information that will be produced automatically by scanning the databases, gathering scientific insights, and producing summaries. To stay on top of one’s work or business, medical writer managers must collect metrics, create graphs, analyze data, and make decisions to improve businesses. An AI-based system can automatically perform these tasks in real time and reduce the burden of performing them manually. As the impact of AI in healthcare grows, so does the hype. As the gatekeepers of accurate translation of medical breakthroughs, medical writers need to understand basic AI concepts to avoid overly optimistic claims. In addition, it is becoming critical that medical writers know how to communicate with AI-based systems in the era of profound transformation. AI is not magic and is only as good as the data quality used to train and test the model. Thus, AI requires strict regulations, appropriate datasets, and specific questions.
AI-powered chatbots and other language generation models based on deep learning techniques can be used for various natural language processing tasks, including medical writing. However, it is essential to note that using AI-generated text in the medical field requires careful consideration and review by medical experts to ensure the accuracy and reliability of the generated text. Some suggested uses of AI-powered chatbots and other language generation models in medical writing include generating reports and summaries of medical research papers and clinical trials, creating patient-specific medical information like discharge summaries and patient education materials, assisting in the writing of medical textbooks and guidelines, generating product labels and package inserts for medical devices and drugs, creating a chatbot or virtual assistant capable of answering medical-related questions, and assisting in highly protocolized letter writing, such as preauthorization letters to insurance companies, work excuses, or letters of recommendation.
Auto GPT, Agent GPT, BabyAGI, and similar tools are being developed to complete complex tasks, like literature reviews, and may be able to do this in the future. ChatPDF and HeyGPT are similar tools that allow you to chat with documents. You can ask these tools to summarize papers, you can search for specific information, you can ask the tools to suggest the following logical questions, etc. HeyGPT has the advantage that it also allows you to chat with websites, while ChatPDF is more specific for PDFs. Be careful not to upload information not already in the public domain. Consensus and HeyScience are AI search engines for scientific research. They only use published, peer-reviewed materials and can show you the best results to answer a question. These tools have the potential to be powerful search tools for medical writers. Assistant by Scite and Jenni are tools that can help you get started with writing. These tools allow you to collaborate on essays and research papers and to find evidence to support claims. Jenni can also produce reference lists and will soon be integrated with citation tools like Zotero.
AI is proving to be a valuable tool in their toolbox, enabling medical writers to expedite these procedures. Although it is improbable that AI would replace medical writers in their work, medical writers who use AI will likely surpass those who do not. However, medical writers ought to accept it for the good of society as much as for themselves. An AI-literate medical writer may effectively report on upcoming medical and healthcare advances and distinguish fact from fiction as a key healthcare stakeholder.
At PLG, we keep one eye on the present and the second on the future. We are vigilant in looking for changes and advancements that can support us in providing better and more reliable services for our clients. AI and the associated technologies are an excellent avenue for this. Whether it be in medical writing or other aspects of the product life cycle, it is always pertinent to stay updated and be cautiously proactive in implementing these advancements. Partner with PLG to learn more about some of the additional technologies we offer our clients, such as Cloud IT solutions.
Go to our Events to register
Go to our News to get insights