Bio-Lab
Bio-Lab
CLIENT
Design Challenge for GenBio AI
Design Challenge for GenBio AI
TIME
1 week
1 week
SKILL
Dashboard, UX Design, UI Design
Dashboard, UX Design, UI Design
TOOL
Figma
Figma
MY ROLE
Product Designer
Product Designer
TEAM
n/a, this is a one-person project
n/a, this is a one-person project
This design challenge was for GenBio AI, an AI-powered biotech startup pioneering multi-scale models for diverse scientific applications. The goal was to translate their core technology into user value by aligning with researchers’ needs and incorporating a conversational user interface. As the sole designer in this 1-week sprint, I led everything from product strategy and UX to visual design—owning every pixel from start to finish..
While I didn’t join the team due to a restructuring of their product organization, I received positive feedback on the work and walked away with valuable reflections and learnings that I’m excited to share.
This design challenge was for GenBio AI, an AI-powered biotech startup pioneering multi-scale models for diverse scientific applications. The goal was to translate their core technology into user value by aligning with researchers’ needs and incorporating a conversational user interface. As the sole designer in this 1-week sprint, I led everything from product strategy and UX to visual design—owning every pixel from start to finish..
While I didn’t join the team due to a restructuring of their product organization, I received positive feedback on the work and walked away with valuable reflections and learnings that I’m excited to share.
PROBLEM
PROBLEM
Bringing a Multi-Purpose Interface to Life
The core strength of this company lies in its ability to provide multi-scale biological models—ranging from RNA and DNA to cell performance, tissue-level behavior, and even whole-organism dynamics. While the product is initially designed for researchers, the long-term vision is to expand access to a broader range of users, amplifying its impact across the bio-AI community.
With this foundation, the product should aim to accomplish 4 key goals:
Bringing a Multi-Purpose Interface to Life
The core strength of this company lies in its ability to provide multi-scale biological models—ranging from RNA and DNA to cell performance, tissue-level behavior, and even whole-organism dynamics. While the product is initially designed for researchers, the long-term vision is to expand access to a broader range of users, amplifying its impact across the bio-AI community.
With this foundation, the product should aim to accomplish 4 key goals:
PROCESS
PROCESS
To address the problem, I began by immersing myself in the domain—learning how research is conducted in practice. This helped me uncover key design challenges and make informed design decisions grounded in real user insights.
To address the problem, I began by immersing myself in the domain—learning how research is conducted in practice. This helped me uncover key design challenges and make informed design decisions grounded in real user insights.
Light
Research
Light Research
How are research conducted?
To understand how target users might use this product, I conducted a light desktop research, spoke with 3 researchers and asked them to walk me through their research and/or experiment process.
Here’s what I learned.
How are research conducted?
To understand how target users might use this product, I conducted a light desktop research, spoke with 3 researchers and asked them to walk me through their research and/or experiment process.
Here’s what I learned.
Insight 1
The D-B-T Cycle
At the heart of scientific inquiry is an iterative cycle: researchers design hypotheses, build models or experiments, and test outcomes, constantly refining along the way.
In addition, I learned that this loop sits within a larger journey:
First, they define the research objective or problem space.
Finally, they finalize findings into shareable results, validated models, or next-phase experiments.
In addition, I learned that this loop sits within a larger journey:
First, they define the research objective or problem space.
Finally, they finalize findings into shareable results, validated models, or next-phase experiments.
A single project often involves multiple Design–Build–Test loops, each linked to different threads or subgoals. This modular, parallel experimentation can create complexity in tracking progress and maintaining alignment.
A single project often involves multiple Design–Build–Test loops, each linked to different threads or subgoals. This modular, parallel experimentation can create complexity in tracking progress and maintaining alignment.
Insight 2
Rigor in Process Control
Additionally, the process itself matters—researchers want control over the design phase, as it directly impacts cross-experiment consistency and collaboration.
One researcher emphasized,
Insight 2
Rigor in Process Control
Additionally, the process itself matters—researchers want control over the design phase, as it directly impacts cross-experiment consistency and collaboration.
One researcher emphasized,
"If I can’t control how the experiment is set up, I can’t trust the results or share them with my collaborators. It’s not just about the outcome—it’s about how we got there.”
"If I can’t control how the experiment is set up, I can’t trust the results or share them with my collaborators. It’s not just about the outcome—it’s about how we got there.”
This highlights the importance of transparency and flexibility in the setup phase, reinforcing the need for tools that support deliberate, user-driven workflows from the start.
This highlights the importance of transparency and flexibility in the setup phase, reinforcing the need for tools that support deliberate, user-driven workflows from the start.
This prompted me to take additional factors into account during the design process. As a result, I established 3 key considerations to guide my approach.
This prompted me to take additional factors into account during the design process. As a result, I established 3 key considerations to guide my approach.
Design
Challenge #1
Design Challenge #1
Planning Scenarios
Given the complexity of the product’s capabilities, I outlined the core features as potential solutions to key user problems—ensuring they not only addressed the user needs but also came together seamlessly as a cohesive product experience.
Planning Scenarios
Given the complexity of the product’s capabilities, I outlined the core features as potential solutions to key user problems—ensuring they not only addressed the user needs but also came together seamlessly as a cohesive product experience.
In addition, by mapping out key user scenarios and walking through them using low-fidelity product concepts, I ensured that the product structure and features could support a range of experimental settings and research workflows.
In addition, by mapping out key user scenarios and walking through them using low-fidelity product concepts, I ensured that the product structure and features could support a range of experimental settings and research workflows.
Design
Challenge #2
Design Challenge #2
Defining the Visual
Another design decision I made was defining the visual style of the dashboard. Drawing inspiration from the ever-changing nature of life patterns—and the common association of “organic” with green—I created a series of gradient blends that reflect the complexity, ambiguity, and beauty inherent in living systems.
Defining the Visual
Another design decision I made was defining the visual style of the dashboard. Drawing inspiration from the ever-changing nature of life patterns—and the common association of “organic” with green—I created a series of gradient blends that reflect the complexity, ambiguity, and beauty inherent in living systems.
SOLUTION
SOLUTION
Step 1. Set Up A Project
Users begin by creating a project and defining a goal. This foundation enables project-level management and allows AI to tailor the experience as the work evolves.
Step 1. Set Up A Project
Users begin by creating a project and defining a goal. This foundation enables project-level management and allows AI to tailor the experience as the work evolves.
Step 2. Design Studio - design & build
In this module, users can update their setup, request AI to generate input data, and manage variables extracted from those inputs.
Step 2. Design Studio - design & build
In this module, users can update their setup, request AI to generate input data, and manage variables extracted from those inputs.
Step 3. Stimulate Lab - test your build
In this module, users can monitor multi-scale simulations and explore details as needed. They can add a new stimulation directly through the chat interface.
Step 3. Stimulate Lab - test your build
In this module, users can monitor multi-scale simulations and explore details as needed. They can add a new stimulation directly through the chat interface.
Step 4. Looping Between
If users want to explore the data further, they can iterate on the experimental setup directly through the chat interface and view the updated simulation as a new version of the lab results.
Step 4. Looping Between
If users want to explore the data further, they can iterate on the experimental setup directly through the chat interface and view the updated simulation as a new version of the lab results.
REFLECTION
REFLECTION
Although this was a time-intensive project completed in just one week, I truly enjoyed the process. The complexity and back-and-forth nature of the work pushed me to exercise and expand my systemic thinking skills.
If I had more time, I would have further developed the Dashboard feature—currently represented as an icon in the tab structure. This module is envisioned as a project management hub, enabling users to conduct in-depth analysis of test results, transition seamlessly into the next experiment or wet lab setup, and generate reports for documentation or collaboration. It’s designed to support lab staff and researchers in managing their workflows more effectively.
Although this was a time-intensive project completed in just one week, I truly enjoyed the process. The complexity and back-and-forth nature of the work pushed me to exercise and expand my systemic thinking skills.
If I had more time, I would have further developed the Dashboard feature—currently represented as an icon in the tab structure. This module is envisioned as a project management hub, enabling users to conduct in-depth analysis of test results, transition seamlessly into the next experiment or wet lab setup, and generate reports for documentation or collaboration. It’s designed to support lab staff and researchers in managing their workflows more effectively.
