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Quantitative systems pharmacology: a promising approach for translational pharmacology
Drug Discovery Today: Technologies, 2016Biopharmaceutical companies have increasingly been exploring Quantitative Systems Pharmacology (QSP) as a potential avenue to address current challenges in drug development. In this paper, we discuss the application of QSP modeling approaches to address challenges in the translational of preclinical findings to the clinic, a high risk area of drug ...
K, Gadkar +3 more
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A quantitative systems pharmacology model of hyporesponsiveness to erythropoietin in rats
Journal of Pharmacokinetics and Pharmacodynamics, 2021Recombinant human erythropoietin (rHuEPO) is effective in managing chronic kidney disease and chemotherapy-induced anemia. However, hyporesponsiveness to rHuEPO treatment was reported in about 10% of the patients. A decreased response in rats receiving a single or multiple doses of rHuEPO was also observed.
Ly Minh Nguyen +3 more
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Quantitative Systems Pharmacology for Rare Disease Drug Development
Journal of Pharmaceutical Sciences, 2023Though hundreds of drugs have been approved by the US Food and Drug Administration (FDA) for treating various rare diseases, most rare diseases still lack FDA-approved therapeutics. To identify the opportunities for developing therapies for these diseases, the challenges of demonstrating the efficacy and safety of a drug for treating a rare disease are
Jane Pf, Bai +4 more
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Educational Needs for Quantitative Systems Pharmacology Scientists
2022There is a demand for scientists trained in quantitative systems pharmacology (QSP) that has yet to be met by changes in graduate education. The multidisciplinary nature of QSP is not unlike its predecessor, pharmacokinetics (PKs) and pharmacodynamics (PDs) that have now become firmly established in many educational programs.
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Future Directions for Quantitative Systems Pharmacology
In this chapter, we envision the future of Quantitative Systems Pharmacology (QSP) which integrates closely with emerging data and technologies including advanced analytics, novel experimental technologies, and diverse and larger datasets. Machine learning (ML) and Artificial Intelligence (AI) will increasingly help QSP modelers to find, prepare ...Birgit, Schoeberl +2 more
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Boolean Modeling in Quantitative Systems Pharmacology: Challenges and Opportunities
Critical Reviews in Biomedical Engineering, 2019Drug research and development has a high attrition rate, with many promising drugs failing for efficacy or safety in the clinic. Increased use of detailed modeling approaches like quantitative systems pharmacology (QSP) may help in reducing overall failure rate, by helping the industry in decisions to fail early and cheaply, or to focus on patients and
Matthew, Putnins, Ioannis P, Androulakis
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A systems approach to quantitative pharmacology a review of the authors' methodology
European Journal of Pharmacology, 1970Abstract A systems approach to data-handling is described and its application to a number of pharmacological screening tests is illustrated. Its use has led to more effective utilization of our data resources, more immediate control over the research process, and greater predictive power.
P J, Lewi, C J, Niemegeers
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Quantitative Systems Pharmacology and Machine Learning
Journal of Pharmacology and Experimental Therapeutics, 2023As pharmaceutical development moves from early-stage in vitro experimentation to later in vivo and subsequent clinical trials, data and knowledge are acquired across multiple time and length scales, from the subcellular to whole patient cohort scale.
Tindall, Marcus John +3 more
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A Framework for Quantitative Systems Pharmacology Model Execution
A mathematical model can be defined as a theoretical approximation of an observed pattern. The specific form of the model and the associated mathematical methods are typically dictated by the question(s) to be addressed by the model and the underlying data.Victor, Sokolov +2 more
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