Introduction:
In the ever-evolving landscape of clinical research and drug development, the intersection of standards and automation has paved the way for remarkable advancements. Since its inception in 2007, Iris has been at the forefront of the rise of data standards and witnessed the subsequent surge in automation initiatives. This article emphasizes the crucial role of human review of electronic data submissions in an era of increasing automation.
The Power of Standards and Automation:
Data standards have heralded a new era in the field of clinical research, opening doors to unprecedented automation opportunities. The streamlined data lifecycle, from collection to eSubmission preparation, has revolutionized how the industry approaches data management and programming. As health authorities, including the FDA, integrate these standards into their toolkits, the burden on new drug and biologic evaluations is considerably reduced. Notably, the FDA’s exploration of artificial intelligence (AI) further underscores the potential for enhanced streamlining.
AI in Digital Health Technologies:
The intersection of AI and clinical research is a burgeoning field that holds immense promise. The #PHUSE working group, AI in Digital Health Technologies, is dedicated to exploring the potential of AI. A quick search of the PHUSE archives for “AI” reveals several papers can be found on this topic including the use of AI in handling unstructured data, case report form (CRF) design, and validation.
The Human Element in Drug Evaluation:
While the prospect of AI-driven drug evaluations may not be too distant, the current responsibility of assessing the safety and efficacy of new medicines rests in the hands of human reviewers. Despite the industry’s best efforts mistakes happen. Crafting a flawless marketing application remains an aspiration rather than a reality.
Elevating the Burden of Deliverables:
The surge in automation does not diminish the responsibility of sponsors to deliver data packages that are not only machine-readable but also comprehensible to human reviewers. In fact, automation amplifies this responsibility. Clear data definition, meticulously formatted documentation, and information consistency is imperative. Seemingly minor errors, such as incorrect page numbers, document titles, or references, can consume hours of a reviewer’s time. Transparency regarding hard coded data values, dosing mistakes, and validation issues in reviewer’s guides can save a lot of work and time spent responding to information requests. The value of a well-constructed data traceability diagram cannot be overstated. A double check by a human of these elements and more is imperative.
Iris: Nurturing Human-Ready Submissions:
As a pioneer in the field, Iris has emerged as a beacon of expertise in Electronic Data Submission Package Evaluation. With a wealth of experience evaluating numerous data packages for studies and marketing applications, Iris plays a pivotal role in ensuring that they are ready for the human review process. This final step, prior to pressing the proverbial button to submit data, instills sponsors with the confidence that their submissions are primed for the rigors of health authority review.
Conclusion:
The synergy between standards and automation has undeniably revolutionized drug, biologic, and device development. As the industry continues to evolve and AI’s role becomes more pronounced, it’s crucial to remember that the ultimate arbiter of a new medicine’s safety and efficacy remains the human reviewer. The imperative for sponsors to deliver human-readable data packages that reflect clarity, consistency, and transparency has never been more paramount. In this dynamic landscape, Iris stands as a testament to the harmonious blend of technology and human expertise, ensuring that data submissions are poised for a successful human review.
A shout-out to ChatGPT for my second draft of this article. It was the first time I used generative AI, I was not disappointed. Author: Lisa K Brooks and #ChatGPT