Technology in Clinical Trials #14 – Transforming Clinical Studies: A Step-by-Step Guide to Implementing GenAI Solutions
Mati Kargren
Technology Consultant in the Clinical Industry ☆ Content Management ☆ Medical Writing ☆ ENTJ ☆ Coffee lover ☕
The landscape of medical writing and medical communication in the clinical industry is undergoing a transformation due to the increasing number of Generative AI (GenAI) solutions in the market. As GenAI tools are implemented in everyday work practices, it is crucial for medical writers, medical communicators, and other clinical study professionals to embrace relevant change management strategies. Building on our previous discussion of general change management principles, this issue of Technology in Clinical Trials delves into the step-by-step process of implementing GenAI solutions including the need to develop GenAI-specific change management practices.
💡 Understanding the GenAI Landscape in Medical Writing and Medical Communication
The integration of GenAI solutions in medical writing and medical communication is reshaping how we approach clinical study documentation, patient education materials, and scientific publications. GenAI tools are now capable of drafting initial versions of clinical and regulatory documents, generating patient-friendly summaries, and even assisting in the creation of regulatory submissions.
For instance, large language models (LLMs) can analyze vast amounts of medical literature to suggest relevant citations for clinical study protocols or help in generating first drafts of clinical study reports or informed consent forms. However, these advancements come with unique challenges. Medical writers must navigate issues of data privacy, ensure regulatory compliance. Moreover, human expertise remains crucial for ensuring accuracy and contextual appropriateness in clinical and regulatory documentation (Thirunavukarasu et al, 2023).
📝 Assessing Organizational Readiness for GenAI Implementation
Before implementing GenAI solutions, it is crucial to evaluate your organization's preparedness. This assessment should consider not only technological infrastructure but also the skills and mindset of your medical writing or medical communication teams.
Key areas to assess include:
Davenport TH’s and Ronanki R’s report from 2018 on Artificial Intelligence for the Real World provides valuable insights into this process. The authors emphasize the importance of a holistic approach that considers both technical and human factors. Their research, based on an analysis of 152 cognitive technology projects across various industries, identified key factors for successful AI implementation, including having a clear AI strategy, fostering a data-driven culture, and developing AI literacy across the organization. They also discuss challenges associated with AI, such as difficulty of integration with existing processes and systems, associated costs, and lack of relevant expertise.
🧠 The GenAI Journey - From Concept to Integration
The journey of implementing GenAI solutions involves several stages, ranging from initial assessment to full integration:
✍🏼 Developing a GenAI-Specific Change Management Strategy
Implementing GenAI in the medical writing or medical communication fields requires a tailored change management strategy. Clear communication is paramount as involved team members need to understand how GenAI will augment their work, NOT replace it. Address team members' concerns about job security by emphasizing how AI will handle routine tasks, allowing writers and communicators to focus on higher-level analysis and creativity.
Set realistic expectations about the capabilities and limitations of GenAI. For example, while AI can generate initial drafts quickly, human expertise remains crucial for ensuring scientific accuracy, maintaining the appropriate tone, and adhering to regulatory standards.
Roppelt JS’, Kanbach DS’, and Kraus S’ systematic literature review from 2023 on Artificial Intelligence in healthcare institutions offers valuable lessons that can be applied to medical writing teams. The group analyzed a total of 130 publications and identified key organizational factors influencing AI adoption, including leadership support, organizational culture, and employee involvement. They emphasize the importance of continuous training and clear communication to alleviate fears and build trust in AI systems.
🔀 Navigating Regulatory and Ethical Considerations in AI-Assisted Medical Writing
The use of GenAI in medical writing raises complex regulatory and ethical questions. How do we ensure that AI-generated content meets the stringent requirements of regulatory bodies? How do we maintain transparency about the use of AI in document creation?
To answer these questions, medical writing teams must develop clear guidelines for the use of GenAI in different types of documents. For example, you might allow AI to generate first drafts of clinical study reports, while maintaining stricter human oversight over finalized versions containing unblinded patient data which will be used for regulatory submissions.
Gerke S’, Babic B’s, Evgeniou T’s, and Cohen Glenn’s publication from 2020 on the regulatory challenges of AI in healthcare provides valuable insights into these issues. The group proposes that AI/ML-based software should be regulated as medical device, considering not just the technology itself but its integration into clinical workflows. For medical writing, this suggests the need for clear guidelines on how AI-generated content is reviewed, validated, and documented.
🎯 Measuring Success and Continuous Improvement in AI-Assisted Medical Writing and Medical Communication
To measure the impact of GenAI on your medical writing and medical communication processes and determine how to further refine relevant processes, develop key performance indicators (KPIs). These might include:
Czarnitzki T’s, Fernandez FP’s, and Rammer’s C’s Brynjolfsson and Jin's work from 2023 on measuring AI adoption impact provides a framework for developing these metrics. Their large-scale study on the impact of AI adoption on firm-level productivity analyzed data from over 5,851 firms across various industries, out of which 409 can be classified as AI users. They found that AI adoption is associated with significant productivity gains, but these gains are not uniform across all firms. For medical writing teams, this suggests the need for a holistic approach to measuring AI impact, considering not just immediate efficiency gains but also longer-term improvements in document quality and team capabilities.
🤝Conclusion – Working hand-in-hand with GenAI solutions
The integration of GenAI into medical writing and communication represents a significant shift in how we approach clinical study documentation and scientific publications. By adopting a strategic, holistic approach to change management, organizations can harness the power of AI to enhance the quality, consistency, and efficiency of produced output. As we adapt our work practices to the integration of GenAI solutions, let's remember that our goal remains unchanged: to communicate complex medical information clearly, accurately, and ethically for the benefit of patients and the advancement of medical science!
⚠️ Disclosure statement ⚠️
Lastly, I would like to point out that I am NOT associated with and am NOT sponsored by any of the organizations or personas I refer to in this edition of the newsletter.