PumasAI to showcase AI pharmacometrics program at ACoP 2026

PumasAI will bring a full-day AI-in-pharmacometrics workshop, four scientific posters and Booth #5 to the American Conference on Pharmacometrics in Maryland Oct. 11-14, 2026. The company is using the conference to push its case that AI and scientific machine learning can speed drug-development decisions.

Why it matters: - PumasAI is positioning AI and scientific machine learning as practical tools for pharmacometrics teams that need faster and better drug-development decisions. - The ACoP 2026 program puts the company in front of pharmacometrics leaders, R&D decision makers and quantitative scientists at a major industry conference. - The company is linking its research portfolio to both current pharmacometric work and emerging modeling methods.

What happened: - PumasAI announced its scientific program for the American Conference on Pharmacometrics, taking place Oct. 11-14, 2026, at the Gaylord National Resort & Convention Center in Maryland. - The company will host a full-day pre-conference workshop on Oct. 11 from 9 a.m. to 5 p.m. EST. - Dr. Niklas Korsbo will lead the workshop, titled "AI in Pharmacometrics: A Strategic Vision for the Next Five Years." - PumasAI will also staff Booth #5 throughout the conference.

The details: - The workshop is designed for pharmacometrics leaders, R&D decision makers and quantitative scientists. - The session will cover the strategic and technical foundations of machine learning in pharmacometrics. - PumasAI said the workshop will focus on how AI and machine learning can support pharmacometric thinking, decision making and future modeling strategies. - The company will present four scientific posters at ACoP 2026. - The poster topics include population pharmacokinetic analysis of taletrectinib in healthy subjects and patients with ROS1-positive non-small cell lung cancer. - Another poster examines DeepNLME and its performance against expert-specified pharmacokinetic functions for mosunetuzumab. - Two additional posters focus on an oral meloxicam formulation, MR-107A-02, in healthy volunteers and surgical patients, plus exposure-response of pain relief in post-surgery patients. - PumasAI will discuss pharmacometrics, MIDD, AI and Scientific Machine Learning with attendees at Booth #5. - More information and workshop registration are available here. - PumasAI describes itself as an award-winning global healthcare intelligence company with software and AI tools built to accelerate precision healthcare. - The company says its Pumas suite is an integrated modeling and simulation platform designed to multiply productivity across the drug-development lifecycle. - PumasAI also provides consulting in clinical pharmacology, model-informed drug development, pharmacometrics and front-end applications. - Additional company information is available at www.pumas.ai.

Between the lines: - PumasAI is using ACoP to showcase not just software, but a broader strategy that ties conference science, consulting and product positioning together. - The workshop theme suggests the company sees AI adoption in pharmacometrics as a near-term strategic shift, not a distant possibility. - The mix of poster topics points to an effort to show credibility across traditional population pharmacokinetics and newer AI-enabled approaches. - Dr. Vijay Ivaturi said ACoP brings together people shaping the future of pharmacometrics and model-informed drug development. - Ivaturi also said the company wants to help scientists move from increasingly sophisticated models to faster development decisions.

What's next: - PumasAI will deliver the workshop, present the posters and meet attendees during ACoP 2026. - The company is likely to use the event to drive interest in its platform, consulting services and AI-focused approach to pharmacometrics. - Conference conversations may help set up follow-on interest from pharmaceutical teams evaluating AI-enabled modeling workflows.

The bottom line: - PumasAI is turning ACoP 2026 into a showcase for its argument that AI can reshape how pharmacometrics supports drug development.