Modeling Clinical Phenotype Variability: Consideration of Genomic Variations, Computational Methods, and Quantitative Proteomics

Advances in biomedical and computer technologies have presented the modeling community the opportunity for mechanistically modeling and simulating the variability in a disease phenotype or in a drug response. The capability to quantify response variability can inform a drug development program. Quan...

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Bibliographic Details
Published in:Journal of pharmaceutical sciences 2023-04, Vol.112 (4), p.904-908
Main Authors: Bai, Jane P.F., Yu, Li-Rong
Format: Article
Language:English
Subjects:
Biological Variation, Population
Computation
Drug Development
Genomic variation
Genomics
Phenotype
Proteomics
Quantitative proteomics
Quantitative systems pharmacology
Virtual patient population
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Summary:Advances in biomedical and computer technologies have presented the modeling community the opportunity for mechanistically modeling and simulating the variability in a disease phenotype or in a drug response. The capability to quantify response variability can inform a drug development program. Quantitative systems pharmacology scientists have published various computational approaches for creating virtual patient populations (VPops) to model and simulate drug response variability. Genomic variations can impact disease characteristics and drug exposure and response. Quantitative proteomics technologies are increasingly used to facilitate drug discovery and development and inform patient care. Incorporating variations in genomics and quantitative proteomics may potentially inform creation of VPops to model and simulate virtual patient trials, and may help account for, in a predictive manner, phenotypic variations observed clinically.
ISSN:0022-3549
1520-6017
DOI:10.1016/j.xphs.2022.10.016