From Complexity to Clarity – Visualizing Medical Data with AI

When you're juggling biotech boardrooms, funding rounds, and scientific chaos, sometimes clarity is the most radical innovation.

Simon Haworth, a creative strategist and biotech leader, joined AI Upgrade for Creative Professionals to navigate the fast-evolving landscape of AI in life sciences. What he built during the program—an AI-powered tool for visualizing genomic data—isn’t just clever. It has the potential to accelerate drug discovery and help researchers focus on breakthrough solutions instead of drowning in spreadsheets.

“I should have joined this course long ago. It has given me an overview of what is possible, what is coming and what it means to us all—and galvanised me to catch up.”

The Problem: Genomic Overload in Medical Research

Modern medicine is powered by data—massive, intricate datasets filled with genetic markers, protein targets, and treatment pathways. But accessing this data is a slow, manual grind. Researchers often spend weeks combing through CSV files to find a single signal worth pursuing.

Worse still, human bias tends to dominate—favoring familiar hypotheses over novel discoveries. For Simon, this was more than inefficient—it was a barrier to innovation.

“When I go to biotech events, I’m the economics guy in a room full of scientists,” Simon shared during his capstone. “I needed to find ways that AI could help me belong in those spaces.”

The Solution: AI That Maps, Models, and Simulates

Simon’s capstone reimagines how researchers interact with genomic data. His tool leverages multiple AI systems to:

• 🧬 Extract relevant gene data automatically

• 🧠 Visualize disease pathways, highlighting complex interrelationships

• 🧪 Simulate digital twins for drug interaction modeling—before real-world trials

These aren’t static graphs. They’re interactive, real-time visual insights that help scientists ask better questions, faster.

“Someone said we had to do a creative image,” Simon joked. “So I did one better—I made the data itself visual.”

The Build: Tools and Iteration

To bring his system to life, Simon used:

• MindStudio for AI workflow orchestration

• ChatGPT for refining complex queries

• Custom GPT agents for confidentiality-aware data handling

Along the way, he ran into roadblocks—especially with large-scale genomic queries that overwhelmed most models. His solution?

“I broke the problem into smaller parts,” he said. “Once I started chunking the data, I got results I could actually use.”

This iterative mindset—build, break, rebuild smarter—is at the core of AI Upgrade’s teaching.

The Impact: From Bottlenecks to Breakthroughs

Simon’s tool helps researchers:

• 📈 Access insights in hours, not weeks

• ⚖️ Minimize bias by surfacing unexpected patterns

• 💸 Save money by simulating trials before investing in lab work

And it’s already finding application in treatment research for diseases like lung cancer and tuberculosis—where speed and accuracy are everything.

What’s Next: Scaling the Digital Twin

Simon is now developing Phase 3 of his system: scaling digital twin simulations for pharmaceutical companies. This would allow R&D teams to test drug interactions virtually, unlocking faster clinical progress and safer outcomes.

“What I’ve seen today,” Simon said during one of our sessions, “I would have predicted was five or ten years away—and it’s on my screen.”

Data Meets Design, Powered by Creative Thinking

Simon’s project is more than a scientific tool. It’s proof that when creatives embrace technical fluency—and technologists embrace design thinking—real transformation happens.

For anyone working in complex industries—healthcare, finance, policy—this kind of AI-assisted clarity is not just helpful. It’s essential.

Want to build something equally bold?
Join the next AI Upgrade for Creative Professionals cohort and build your future, your way.