How to Improve the Speed and Accuracy of Patient Communications in Clinical Development
According to Phesi, more than a quarter of clinical trials conducted in 2023 were canceled during Phase II.
As clinical research teams struggle with patient recruitment and engagement under tight deadlines and immense regulatory pressure, patients also grapple with confusion around the documentation they receive, the complexities of the enrollment process, their concerns about data privacy, and more. To bridge this gap between researchers and patients, medical writers play a crucial role in facilitating accurate and clear communication to diverse audiences. With rapidly evolving regulatory guidelines and medical research, complex topics to communicate, and time constraints, medical writers face their own administrative burdens. They need support—and that’s where emerging technologies come into play.
Generative artificial intelligence (GenAI) and machine translation (MT) are revolutionizing the life sciences industry globally, including the potential for addressing these key pain points for clinical teams, patients, and their medical writers. With this in mind, let’s dive into the top three use cases for GenAI and MT in improving the speed and accuracy of patient communications.
Automated Clinical Content Creation
In clinical trials, medical writers are required to create key patient-facing documentation, including lengthy informed consent forms (ICF), patient information leaflets (PIL), lay summaries, study brochures and flyers, and newsletters detailing updates on the progress of the trial—just to name a few. These documents are essential, since they inform patients of the study, their rights, the risks, and everything to expect. Currently, clinical document creation is handled and updated throughout the trial manually by each medical writer, resulting in unstructured and inconsistent content comprised of free-form text, figures, and tables. If medical writers can’t interpret clinical trial data, how can they clearly communicate it to patients?
To reduce the time and risks of inefficiencies involved in the manual document creation process, GenAI can be leveraged as an automatic authoring tool to enable content reuse, dynamic templates, and efficient content development procedures. Using this optimization, documents are generated with simplicity, accuracy, and in the right format in just a few seconds. With the time saved from this application, clinical teams can prioritize higher-value tasks for better patient outcomes, such as diverse participant recruitment and patient interviews throughout the trial.
Localization and Personalization
With the increasing trend of global clinical trials, regulatory bodies require clinical trial documentation to be submitted in their official language for approval. To enhance patient participation and retention in clinical studies, documentation must be accessible and culturally appropriate in a participant’s preferred language. Furthermore, without participants from different backgrounds, a trial could miss out on life-saving research and breakthroughs from underrepresented groups.
To achieve this goal, localization goes beyond the process of a one-to-one, verbatim translation. The process of localization adapts clinical content to the linguistic and cultural nuances as well as regulatory requirements of the target patients and market. By translating with context, AI-powered machine workflows can automatically translate industry-specific jargon and increase readability across documentation, no matter where the patients are located. Additionally, an expert human linguist and medical writer should always be kept in the loop during the post-editing process. By working together to bridge language barriers, the linguist and writer can verify the accuracy of the machine translation, customize the content to the participant’s patient profile, and expand medical knowledge to diverse communities around the globe.
Data Quality Assurance and Integration
Clinical teams collect, analyze, and distribute vast volumes of medical information through every step of the clinical trial process. However, if the initial data collection is filled with errors or uncertainties, these issues can transfer to the final versions of clinical documentation.
As a first step, bringing GenAI into the fold within a centralized, secure workflow streamlines the process of converting unstructured data into structured data. Human oversight is essential throughout every step of the process for data supervision, quality assurance, and HIPAA compliance reviews, since there are bias, accuracy, and transparency risks with solely using GenAI. Once this high-quality data is isolated, AI workflows can proactively flag variable outliers and automatically input missing values, further ensuring accuracy in areas that may have been overlooked by human reviewers. To optimize its personalized communications, GenAI can integrate data from electronic health records to automatically create patient summaries, follow-up instructions in the trial landscape, and targeted reminders. By analyzing patient feedback data, GenAI workflows can offer up-to-date information on the patients’ current health status and refine its outputs based on their needs, offering medical writers a treasure trove of resources to effectively customize their content.
Conclusion
Through the use of transformative GenAI and machine translation technology, medical writers and their clinical teams can improve the speed and accuracy of their processes, resulting in enhanced patient outcomes.
TransPerfect Life Sciences has developed AI-enabled tools to help global clinical teams streamline the author-to-archive development of their documentation. If you’re interested in how these AI and machine translation solutions can help your team navigate the complexity in clinical content, reach out today to learn more.