The Artos Blog

While structured databases are designed for easy querying, and generative AI has made great strides in handling unstructured text, the life sciences faces a significant gap in terms of what data automated systems can handle. At Artos, we call this Ossified Data—data that was once structured but has been trapped in PDFs, RTFs, or other unstructured formats due to legacy systems, regulatory requirements, or internal data ownership complexities.

Regulatory submissions in life sciences are undergoing a transformation. As the volume and complexity of clinical and regulatory data grow, structured submissions have become essential for efficiency, accuracy, and compliance. The HL7 Fast Healthcare Interoperability Resources (FHIR) standard, widely adopted in clinical data exchange, is now being explored for its potential role in structured submissions under the electronic Common Technical Document (eCTD) framework.

In biotech and pharma, precision and consistency are critical. Regulatory submissions and clinical documentation demand high-quality outputs that meet stringent standards. As AI becomes essential to these processes, standardization plays a key role in ensuring efficiency and reliability. However, over-standardization can stifle productivity, while too little structure leads to inconsistency. Striking the right balance is essential for AI to thrive.

As enterprises increasingly explore AI, tools like ChatGPT provide accessible, flexible options for generating text and running basic functions like table creation or visualization. And, at Artos, we absolutely love tools like ChatGPT, Claude, and Perplexity.

In the rapidly evolving landscape of generative AI, curiosity and hands-on experimentation are some of the most powerful tools we have to unlock its potential. At Artos, we’ve seen how experimentation not only builds an intuitive understanding of what AI can achieve but also reveals the often-underestimated complexities involved in building robust, scalable AI solutions. Here, we’ll dive into why experimentation with generative AI is vital, from uncovering AI’s unique strengths and limitations to understanding the true challenges of scaling these technologies effectively.

At Artos, we believe that AI is uniquely suited to transform the field of medical and regulatory writing—and to make its experts even more essential in the process. AI’s capacity to streamline repetitive, detail-intensive tasks offers a chance for medical writers to shift their focus from low-level work to high-level, strategic contributions that can drive real value for life sciences companies.