Arta Peptidion

Arta Peptidion was not born from competition. It was born from a question — about what it means to learn, to bind, to evolve, whether in molecules or in machines. That question still drives us, every day.

Most corporate “About Us” pages feel like carefully staged parades of titles and keywords — dense with metrics, light on meaning. In the bio‑AI world, where slide decks and acronyms crowd every conversation, we choose a different voice: first‑person, unpolished, and real. Our story doesn’t say “Look what we’ve achieved.” It says “Here’s who we are, if you’re willing to look closer.”

Why? Because the people we work with — researchers, deep‑tech investors, clinicians, engineers — aren’t impressed by noise. They look for vision and substance living in the same place. We aim to offer both.

I’m Antonello Romani, scientist and founder of Arta Peptidion. Patterns have always been my compass — whether in synaptic sparks, in strands of RNA, or in the structure of code. What we build here — AI platforms for designing functional aptamers — is measurable and concrete, yet anchored in a deeper curiosity: When does information become recognition? When does a system begin to reflect on itself?

I’m Aldo Feriani, pure chemist turned computational chemist, co‑founder of Arta Peptidion. I spent four decades at Glaxo Verona, directing Computational Chemistry long before data science had a name. I’m in love with data, a firm skeptic of hype, and convinced that information without evidence is like a house without foundations. My craft is method, precision, and the quiet satisfaction of getting the numbers right.

Our apparent distance — one of us exploring the limits of machine cognition, the other safeguarding the ground truth of empirical rigor — creates a dynamic tension. Antonello pushes models toward new possibilities; Aldo grounds them in what can be verified. In that dialogue, aptamers emerge that are both imaginative and defensible.

This page isn’t a résumé; it’s a threshold. Beyond it you’ll find models, metrics, and results. But here you’ll find what shapes them: questions before claims, structure before spectacle, and the belief that intelligence — biological or artificial — begins by listening, and earns its meaning through understanding.