
OpenAI’s Nick Turley Wants ChatGPT to Operate Like an App Platform
October 9, 2025
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PumasAI, a science-first organization that turns data into life-saving decisions faster, has officially launched PumasAide, an intelligent assistant that integrates directly into the pharmacometric workflow. By combining trusted scientific models with built-in artificial intelligence, PumasAide helps researchers analyze data, generate code, and complete routine clinical pharmacology and pharmacometrics tasks with unmatched speed.
PumasAide works inside environments like Visual Studio Code and other IDEs, allowing scientists to run analyses and build models in real time. It works on live data, supports AI from multiple providers, and keeps sensitive information secure by staying fully local.
“PumasAide brings scientists closer to their data and decisions,” said Dr. Vijay Ivaturi, CEO and Co-Founder, PumasAI. “We designed it to help new users get started quickly and to give experienced pharmacometricians a trusted assistant to scale their impact.”
Since its founding, PumasAI has focused on bringing advanced science and automation into clinical pharmacology. The company has released a series of tools that build toward this vision:
Each launch builds on the last, with PumasAide marking a new phase in accelerating insight and reducing bottlenecks across the drug development lifecycle.
Dr. Ivaturi added, “Innovation like this is how we clear the path for scientists to think bigger, move faster, and deliver breakthroughs that improve lives.”
For more information and to receive a demo of PumasAide, visit the official website.
PumasAI is an award-winning global healthcare intelligence company with a vision to accelerate precision healthcare to patients. Proprietary software and AI tools developed by the company include the Pumas suite of products, an integrated modeling and simulation platform designed to multiply productivity across the drug development lifecycle. Scientists at PumasAI provide consulting with leading pharmaceutical innovators in clinical pharmacology, model-informed drug development (MIDD), pharmacometrics, front-end applications, and more.
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