ArticleDelaware journal of public health2026
Model-Informed Drug Development: Addressing the Critical Need for Training in the Promising New Field.
Article in Delaware journal of public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Authors and funding
3 authors.
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Abstract
The pharmaceutical industry faces a major challenge in drug discovery and development, with overall success rates of only 10-20%, often due to reductionist approaches that fail to account for complex biological networks. To address this challenge, industry and regulatory agencies, including the FDA, are increasingly adopting Model-Informed Drug Development (MIDD) and Quantitative Systems Pharmacology (QSP) to improve dose optimization, trial design, and decision-making throughout the drug development pipeline. At the same time, pharmaceutical investment in the United States, particularly in the greater Delaware region, is rapidly expanding, increasing the demand for a highly skilled workforce trained in advanced modeling and simulation. However, the widespread adoption of MIDD and QSP methodologies is hindered by a shortage of trained scientists, as traditional Biomedical Engineering curricula often lack the advanced mathematical and computational modeling preparation required by industry. To address this gap, the Biomedical Engineering department at the University of Delaware has integrated MIDD principles into its graduate curriculum and launched the nation's first Master's program dedicated to QSP, providing structured, industry-aligned training to prepare students for careers in the pharmaceutical and biotechnology industries.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.