Learning from other industries: Why reinvent the wheel?
Many challenges faced in medical writing, data science, and clinical research are not unique. There is immense value in learning from other industries and applying their best practices to our work in medical writing. This mindset led to attendance at the recent PHUSE* event, an industry gathering focused on data science, biostatistics, and regulatory standards. It explored the intersection between medical writing and data science, particularly in areas such as AI adoption, process optimization, and breaking down silos between functions.
The power of people and process
A central theme of the event was the importance of people and process—two elements that drive change and innovation more effectively than technology alone. While the technical details in data science differ from those in medical writing, the fundamental principles remain consistent:
Successful change is driven by people, not just new tools.
Processes must evolve to support innovation and efficiency.
Outsourcing can be beneficial, but companies must retain ownership of their systems and expertise to stay world-class.
This theme resonates deeply within functional service provider (FSP) models in medical writing. Just as pharmaceutical companies reassess their outsourcing models in data science, medical writing must ensure that expertise remains within the organization, even while leveraging external partners.
AI adoption: Medical writing vs Data science
AI was another prominent topic at PHUSE. Both data science and medical writing approach AI with similar skepticism. While there is recognition of AI’s potential, neither field is prepared to fully embrace black-box solutions. Instead, both groups:
Seek to integrate AI into existing workflows (SAS and R for data science; MS Word for medical writing).
Prioritize human oversight, ensuring AI supports—rather than replaces—experts.
Recognize that successful adoption hinges on trust and transparency.
This cautious yet strategic approach is crucial to making AI a useful tool rather than a disruptive force.
Innovation: More than just technology
One of the prevailing misconceptions about innovation is that it always stems from technology. In reality, some of the most impactful innovations come from breaking down silos and enhancing collaboration. A major takeaway from PHUSE, for the intersection between data science and medical writing, was the importance of early medical writer involvement in reviewing Statistical Analysis Plans (SAPs) and mock tables. This collaboration ensures:
Better integration of key messages in Clinical Study Reports (CSRs).
Fewer last-minute revisions and misinterpretations.
A smoother, more efficient writing process.
AI can also contribute to this process—for instance, using AI to summarize tables before finalization can both validate data and assist medical writers in starting their drafts earlier.
Standardization vs Innovation: Finding the balance
The industry is moving toward greater standardization, with initiatives like ICH M11 aiming to digitize protocols and streamline data flow. While this has clear benefits, it is essential to ask:
Does excessive standardization stifle true innovation?
Could rigid guidelines make it more challenging to introduce groundbreaking trial designs?
Are we prioritizing efficiency over scientific advancement?
Innovation is not solely about refining existing processes but also embracing new ideas that challenge the status quo.
The big picture
One of the most thought-provoking moments of the event was a question from an audience member: “What should we be measuring as an industry?” The answer aligns with our vision as an industry:
Bringing truly transformative medicines to market—not just more medicines, but those that meaningfully improve lives.
Reducing the cost of drug development, making innovative treatments accessible and sustainable.
These goals may sometimes conflict, as true breakthroughs require investment, but achieving a balance is crucial for the future of healthcare.
Final thoughts
Attending PHUSE reinforced the importance of cross-functional collaboration, thoughtful AI adoption, and keeping people and process at the core of industry progress. Whether in data science, medical writing, or clinical research, the shared goal remains clear: better medicines, delivered more efficiently. The best path forward involves breaking down silos, embracing innovation, and focusing on what truly matters.
*PHUSE is an independent, not-for-profit organization run by a worldwide team of volunteers. They are a global community and platform for discussing topics encompassing the work of data managers, biostatisticians, statistical programmers, data scientists, and eClinical IT professionals. PHUSE has become the industry voice to regulatory agencies and standards organizations such as the FDA, EMA, and CDISC.