PumasAI, an AI-powered clinical pharmacology and pharmacometrics company, has unveiled scientific software package Pumas 2.9.
Pumas 2.9 introduces enhancements that improve computational performance, estimation stability, reproducibility, and support for increasingly sophisticated pharmacometric workflows.
“Pumas was built to help scientists solve increasingly complex problems without adding unnecessary complexity to their workflows,” said PumasAI cofounder and CEO Dr Vijay Ivaturi. “Pumas 2.9 continues that mission by strengthening the core modelling platform with faster computation, greater stability, and expanded capabilities that allow researchers to spend more time generating scientific insight.”
The release builds on Pumas 2.8, strengthening the scientific engine that powers modern model-informed drug development. It also delivers improvements across estimation methods, model flexibility, diagnostics, distributed computing and user experience, helping pharmaceutical and biotechnology organisations analyse complex data with greater confidence and efficiency.
Major enhancements include:
- Expanded advanced estimation, with continued enhancements to the experimental Monte Carlo Expectation Maximisation (MCEM) and Variational Expectation Maximisation (VEM) estimation methods improve stability, reliability, and support for increasingly complex nonlinear mixed-effects models.
- Improved computational performance, incorporating new multithreading capabilities, distributed computing enhancements, and intelligent load balancing accelerate simulations, diagnostics, inference, and estimation across demanding modelling workflows.
- Greater reproducibility, bringing improvements to deterministic calculations and reproducible inference across parallel computing environments help ensure greater consistency and confidence in scientific results.
- Expanded modeling flexibility, with new support for ordered parameter domains, enhanced covariate selection, richer prediction outputs, expanded error model capabilities and additional inference tools provide scientists with greater flexibility when building sophisticated pharmacometric models.
- Enhanced user experience, including Improved diagnostics, clearer documentation, expanded error reporting and numerous workflow refinements simplify model development while helping users identify and resolve issues more efficiently.
“Every release of Pumas is driven by the same objective,” added Ivaturi. “Our responsibility is to give scientists the most advanced computational tools available while making those tools faster, more reliable, and easier to use. As clinical pharmacology continues to evolve, we remain committed to delivering innovations that help researchers ask better questions, explore more possibilities, and accelerate the development of new therapies.”
By eliminating fragmented workflows across multiple software platforms, organisations can reduce operational complexity, accelerate analyses, and dedicate more time to scientific decision-making throughout the drug development lifecycle.
