Author: [AUTHOR] Published on 2/4/2026 3:35:00 PM
CALL FOR PAPERS
Clinical Pharmacology & Therapeutics: Pharmacometrics and Systems Pharmacology (PSP), an official journal of the American Society for Clinical Pharmacology & Therapeutics (ASCPT), is inviting submissions for a special collection on Transformative Approaches in Artificial Intelligence for Pharmacometrics and Systems Pharmacology scheduled to open in 2026.
This special collection will advance a vision for how Artificial Intelligence (AI) and Machine Learning (ML) can provide a transformative impetus in reshaping pharmacometrics and systems pharmacology to improve the development of new patient diagnostics, novel therapies, and medical devices with the ultimate goal of enhancing patient care through precision medicine.
The past decade has seen advancements in AI/ML in conjunction with classical modelling and simulation methodologies to enhance the scope and application of model-informed drug discovery and development (MID3). In this special collection, the emphasis will be placed on approaches that could result in a step change in how pharmacometrics and systems pharmacology models can be developed and/or applied. Taken together, the special collection aims to highlight emerging paradigms while promoting good practices to avoid potential risks and ultimately help chart the research agenda aimed at making greater impacts in improving human health.
The “Transformative Approaches in AI” special collection welcomes the submission of topics that highlight recent advances in using AI/ML algorithms and/or models to:
- Develop, calibrate, or validate pharmacometrics and quantitative systems pharmacology models in ways that could significantly increase their adoption and the scope of their impacts in drug discovery and development.
- Advance translational modeling with AI/ML, by using in-vitro and in-silico data to predict human-relevant outcomes, thereby reducing the need for animal experiments.
- Leverage multiple data sources (e.g., omics, imaging, or other content-rich modalities) via quantitative models, such as exposure-response or disease models, to support new diagnostics, novel therapies, and patient care.
- Enable data-driven mode discovery with improved predictivity and other quantitative attributes as compared to current modeling paradigms, with the potential to change the status quo.
- Accelerate the creation of simulation models for rapidly advancing novel modalities (e.g., cell and gene therapy, antisense oligonucleotides, mRNA therapeutics, siRNA, bi-/tri- specifics, etc.).
- Discover potential causal relationships and generate novel insights from complex longitudinal data.
- Create virtual patients, digital twins, and in silico trial platforms to simulate disease progression, treatment response, and variability across populations.
- Leverage pharmacometrics and/or quantitative systems pharmacology models within agentic AI workflows to support new diagnostics, novel therapies, and patient care.
The objective of this issue is to highlight the role of AI/ML in expanding the capabilities and influence of PSP to support new diagnostics, novel therapies, and patient care.
Original research articles are encouraged. Submissions may also include reviews/mini-reviews, tutorials, position/white papers, PSP case reports, and perspectives from regulatory agencies, academia, societies, and industry. Please contact alaina@ascpt.org for details about manuscript types and format requirements.
To be considered for publication in this special collection, manuscripts should be submitted via the online submission and tracking system by September 1, 2026.
