Background

Aeon Biomarkers is a longevity health tech startup innovating advanced tools for clinicians to monitor and reverse biological aging.

Working closely with the CEO and medical advisors, I was responsible for shaping how clinicians would explore interconnected biomarkers for age-related health planning, turning conceptual medical goals into a usable product

Role
Lead UX & Visual Designer

Client
Aeon Biomarkers LLC

Medium
Web App & Website

Tools
Figma

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What's being solved

Longevity is the future of healthcare and professionals lacked a clear, intuitive way to understand how biomarkers interact, track changes over time, and connect those shifts to biological aging.

Issues

  • Biomarker relationships are complex – Clinicians struggled to see how biomarkers influence each other over time.
  • No visual representation existed – The system lacked an intuitive network view of biomarkers.
  • Data was difficult to compare – Users needed to track biomarkers against population data and see trends over time.
  • Filtering and searching were clunky – Clinicians needed a way to zoom in, focus on specific biomarkers, and search effectively.

UX Goal: Design an interactive visualisation that enables users to explore biomarker data intuitively, filter relationships, and track aging-related changes.

Patient Biomarker Map for Age Reversal

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Final Design and Outcomes

  • Used in seed fundraising round
  • Influenced product roadmap pivot
  • Helped non-technical stakeholders understand the product vision
  • Set foundation for MVP development
  • Onboarded initial users

Interactive Biomarker Map

  • Analyse patient ageing across time
  • Visualise healthy and unhealthy biomarkers
  • AI suggest trajectory & interventions

Patient Insights

  • AI medical history analysis
  • Age profiles
  • Patient data records
  • Trial results

Clinical Trial Input & Search

  • Add and find clinical trials
  • Compare data and results
  • AI written results analysis & papers
  • Demographic comparison

Users

Clinicians

in longevity and preventative health

Biohackers

and health-conscious consumers

Researchers

interested in population-level biomarker & aging trends

Design Process

Step 1: Analyse requirements

  • Look at user needs and business objectives
  • Identify potential solutions and requirements
  • Create user actions and tasks

Step 2: Low-Fidelity Wireframes

  • Sketched early layouts to test navigation & interaction patterns.
  • Focused on biomarker grouping, relationships, and data hierarchy.

Step 3: High-Fidelity Prototypes

  • Designed an interactive prototype in Figma.
  • Created motion effects to make biomarker connections more intuitive.

Step 4: Usability Testing & Iteration

  • Conducted feedback sessions with test users (clinicians & health researchers).
  • Iterated on usability issues, such as label clarity, zoom functions, and filter controls.

Goal - Visualise patient biomarker insights over time

  1. Visualise all human biomarkers
  2. Show category and relationships
  3. Change over time
  4. Health of each biomarker
  5. AI based interventions and predictions

Map prototyping - a journey through wireframes

1. Initial Ideas

Analysed what kinds of maps/graphs work for relationships between nodes.
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The type of biomarkers, their attributes and how they are categorised
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How timelines could affect the visualisation of nodes.

2. All elements on a screen

a - An idea of how the map, biomarker nodes, categorisation, timeline (age), search, filter and information could work.

b - Looked at previous design and changed elements based on existing age data and categorisation.

c - Age timeline based on data entry points and future trajectory (AI prediction).

3. Biomarker age design and categorisation

a - Age visualisation of biomarker nodes - youth, good, at risk and aged making it easy for the clinician to mentally snapshot the profile reducing cognitive load

b - Biomarker grouping and categories into easily identifiable types e.g. antioxidants, nicotine

c - Snapped timeline and zoom to bottom for space usage

4. Enhanced node design & biomarker relations

a - Removal of node values to make each biomarker clearer - moved to hover over states to minimise clutter while retaining interactivity

b - Lighter node colours to have lower load on eye and to enhance scanning

c - Changed category names to cloud hotspots

d - Added more accurate line relationships to show links between categories

e - Designed various states to show hover over, selected, searched item etc

5. AI based interventions & predictions

a - Side panel that opens when you click a biomarker for progressive disclosure of clinical data

b - Shows patient current values and data for that biomarker and all linked biomarkers

c - AI predicts the trajectory of the biomarker based on all patient data

d - AI automates the interventions based on all patient data and longevity research

e - Population comparisons are available to compare individual results

Biomarker map in action

Additional Screens

Patient Records

Goal: Use AI to record all medical history so biomarkers, biological age and interventions can be more accurate.

AI Medical Records

  • Upload of medical record history
  • AI parses data and creates entry records
  • Medical record deep dive

Patient

  • Age profiles
  • AI biological age calculation based on all data
  • Intervention protocols

Clinical Trials

Goal: Find and add clinical trials. Write information on trials and produce research papers

Find, participate and create trials

  • Search a database of clinical trials by date, name, category
  • Create trials
  • Recruit participants

AI written trials, results analysis & papers

  • Leverage AI to write trial info based on data input
  • AI analysis of results and findings
  • Creation of research papers

Reflection & Learning

This project strengthened my ability to design in ambiguity, translating a visionary product concept into an intuitive interface without access to user data. I worked closely with a scientific founder and clinical experts to build a tool for exploring biomarkers tied to biological age, focusing on clarity, scalability, and future usability.
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It challenged me to interpret complex health data into usable UX patterns, apply best practices in healthtech design, and prototype interfaces for an emerging field where no standard exists. This experience deepened my confidence in driving UX strategy for early-stage, innovative products.

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