From the Fringes to the Mainstream: What WCP Melbourne Told Me About the Future of Pharmacology

There are some conferences where you leave with pages of notes, a long list of new papers to read, and perhaps a few new collaborations. And then there are conferences where you leave with the feeling that something has shifted.

For me, the World Congress of Basic and Clinical Pharmacology (WCP) in Melbourne was one of the latter. I attended WCP in Glasgow in 2023, so returning to the Congress in Melbourne this year gave me an interesting opportunity to compare the two experiences. Of course, every conference is shaped by its programme, speakers, and the scientific questions receiving attention at that time. But one difference stood out to me: quantitative pharmacology seemed much more visible and much more embedded within the broader pharmacology conversation.

Dr. Aida Kawuma poses for a photo at WCP 2026.

There was considerably more discussion around population pharmacokinetic (PopPK) modelling, physiologically based pharmacokinetic (PBPK) modelling and even quantitative systems pharmacology (QSP). Importantly, these approaches did not feel like isolated topics belonging exclusively to a small community of modelers. They were increasingly being presented as tools for addressing mainstream pharmacological questions. How does drug exposure relate to response? Why do patients respond differently? How might physiological differences affect drug disposition? How can we translate findings between populations? How can we integrate knowledge across different biological systems?

And I think that tells us something important about where pharmacology is heading. Pharmacometrics is no longer sitting on the fringes! Therefore, what waits to be seen is how quantitative pharmacology will reshape the way pharmacology itself is practiced.

The increasing visibility of these approaches suggests that quantitative pharmacology is becoming less of a specialized add-on and more of an essential component of modern drug research and development.

Dr. Aida Kawuma giving a presentation on leveraging pharmacometrics to bridge evidence gaps in lactation pharmacology. Photo by Catriona Waitt

And then there was AI. Everywhere!

If quantitative pharmacology was one of the themes that stood out to me, the other was impossible to miss: artificial intelligence.

It seemed that almost every symposium had a session or presentation in which AI made an appearance. What was particularly interesting was the breadth of applications. AI was being discussed in education, from preparing examination questions and assessments to supporting grading and other aspects of teaching. At the same time, it was being discussed as a tool to aid research, including applications in PK/PD modelling and drug development. That breadth is significant.

We often talk about AI as though it is a single technology that affects particular or isolated aspects of science. But what I saw at WCP suggested something different. AI is beginning to influence the entire scientific ecosystem: how we teach, how we learn, how we analyse data, how we build models and potentially how we make scientific decisions.

Aida at WCP 2026 in Melbourne, Australia. Photo by Catriona Waitt

And so, we must think carefully about what scientific expertise actually means in an AI-enabled environment. The pharmacologist of the future will not necessarily need to become a pharmacometrician, a machine-learning specialist or an AI engineer. But they will increasingly need to be comfortable working alongside these disciplines. And the same is true in the other direction.

Pharmacometricians need to understand the pharmacology behind the models. Data scientists need to understand the scientific questions behind the data. AI specialists working in drug development need to appreciate the biological and clinical context in which their tools are being applied.

In short, the boundaries between disciplines like pharmacology, mathematical modeling and AI are becoming increasingly porous.

Aida Kawuma

Pharmacometrician