New tool for clinic long-term Parkinson’s disease drug research.
Discovery & Strategy, UX Design, UI Design
Thomas Dyrks
The goal of this project was to design a user-friendly, scalable system tailored to the needs and workflows of doctors conducting long-term research on treatments for Parkinson’s disease. This new system aimed to simplify data collection in research and treatment centers across Europe, ensuring that specialists could document patient visits efficiently while maintaining high research standards. Parkinson’s disease is a progressive neurological disorder that primarily affects movement, often beginning with mild tremors that escalate over time. Given the complexity of managing long-term treatments and tracking patient progress, researchers and clinicians needed a digital tool that could streamline documentation, reduce manual errors, and improve accessibility.
My role
As a Product Designer, I played a crucial role in shaping the platform from conception to execution. My responsibilities included:
Outcome
The development was completed within three months. Throughout the process, we continuously refined our approach, adapting to feedback and prioritizing real-world usability over theoretical design concepts. The system:
Creating digital tools for the medical field is particularly challenging due to the limited access to benchmarks, users (specialists and patients), and documentation. Through initial research, we discovered that most specialists relied on Excel spreadsheets, paper notebooks, or personal tracking systems to log patient data. These inconsistencies made data retrieval cumbersome and increased the risk of errors.
Flexibility in data entry
Standardize data entry while allowing flexibility for different research methodologies.
Target audience
Ensure a high level of usability, even for doctors unfamiliar with modern digital tools.
Device compatibility
Work seamlessly across different devices, including old desktop monitors and mobile tablets, given the outdated equipment in many clinics.
To ensure our solution aligned with real-world workflows, we collaborated with medical consultants to create detailed user profiles representing a diverse range of physician behaviors and preferences. These profiles helped us map out the pain points, motivations, and goals of our target users. We conducted ongoing interviews and feedback sessions with specialists to refine our approach. Early analysis revealed two possible system architectures, leading us to run usability tests to determine the most effective design direction.
Given the time-sensitive nature of a physician’s work, we designed the system to be quick and intuitive, ensuring that data entry would not disrupt daily operations. Throughout the design process, we consistently evaluated usability by asking critical questions:
By continuously testing these factors, we ensured that the system would be intuitive, efficient, and easy to learn for medical professionals.
The visual design of the platform had to account for the realities of hospital and research environments, where outdated hardware and poor screen quality are common. To accommodate this, we:
These design decisions ensured that the system would be accessible and effective for a broad range of users, regardless of their technical background.
Pharma is not just regulated - it’s layered
Designing for clinical research means complying with overlapping standards (e.g., GDPR, local medical data laws, ethical committee approvals). Beyond legal frameworks, each institution had its own governance procedures and digital infrastructure requiring flexibility in both rollout and design.
Progress over perfection
Designing for research often tempts teams into building "the perfect system." But launching with a usable core and iterating with feedback from real-world use enabled faster learning, better adoption, and ultimately stronger long-term impact.
Design must support variability, not force uniformity
Despite the goal of standardizing research data, we quickly learned that different centers had nuanced workflows. Designing a modular, adaptable system allowed us to strike the balance between structured data and local flexibility.