Drug discovery is one of the most attractive subjects of today's early pharmaceutical research. The traditionally available drug discovery process constitutes the identification of target, as well as the most promising drug molecule, and then optimization of this, in-vitro, in-vivo and in pre-clinical studies to decide whether the compound has suitable characteristics to be developed as a drug molecule. Drug discovery, evaluation, and development are complex, lengthy, costly and laborious processes. There are many computational tools available to reduce the number of potential compounds which could be studied for drug discovery and which could lead to reducing costs, time, and human resources.
The aim of this Research Topic is to explore new approaches, using Quantitative Systems Pharmacology (QSP) to develop new drugs with respect to ‘small molecules’ and biopharmaceuticals (please note, manuscripts referencing natural products will not be accepted in this section Topic). A fast-growing interest in the application of QSP for drug dosing and trial decision-making in clinical development has made QSP a well-recognized tool in drug development. These methodologies are playing an ever-increasing role in preclinical and clinical drug development that are critical in the cost-effective identification of promising drugs.
Quantitative systems pharmacology is an emerging interdisciplinary field that integrates systems biology and pharmacometrics, with an emphasis on dynamic modelling, to quantitatively predict the effects of clinical interventions and their combinations under a variety of genetic, biophysical, biochemical, physiological, and biomechanical conditions.
Several modelling approaches for QSP have been developed, including statistical (Bayesian), agent-based, Boolean, temporal (ordinary differential equations), spatio-temporal (partial differential equations, integrative, empirical curve fitting, and machine learning that enable integrating molecular pathways with clinical results and pharmacology.
This Research Topic welcomes submissions from researchers in the field of computational drug discovery and design, including original research and review articles related to the Quantitative Systems Pharmacology approaches used in drug discovery. Any In silico original research data must be supported with experimental research. The topics to be covered in this Research Topic can include, but are not limited to:
-Quantitative Systems Pharmacology Modelling to drug development
-Quantitative Structure-Activity/Property relationship (QSAR/QSPR)
-Cardiovascular, metabolic, and oncology drug development
-Cancer therapy
-Target site delivery
-Immuno-Oncology applications
-Molecular docking
-Translational pharmacology
-CNS research and development
-Chemotherapy induced neutropenia
-Metabolic bone disorder
-Low-density lipoprotein cholesterol regulation in the human body
-Improving nano-therapy using image-guided systems pharmacology
-Toxicology
-Optimal dosing of COVID-19 vaccines
Please note: We will not accept original research manuscripts containing in silico studies only.
Furthermore, this Research Topic is hosted in the section Experimental Pharmacology and Drug Discovery and will not accept manuscripts referring to traditional remedies or other natural products.
Drug discovery is one of the most attractive subjects of today's early pharmaceutical research. The traditionally available drug discovery process constitutes the identification of target, as well as the most promising drug molecule, and then optimization of this, in-vitro, in-vivo and in pre-clinical studies to decide whether the compound has suitable characteristics to be developed as a drug molecule. Drug discovery, evaluation, and development are complex, lengthy, costly and laborious processes. There are many computational tools available to reduce the number of potential compounds which could be studied for drug discovery and which could lead to reducing costs, time, and human resources.
The aim of this Research Topic is to explore new approaches, using Quantitative Systems Pharmacology (QSP) to develop new drugs with respect to ‘small molecules’ and biopharmaceuticals (please note, manuscripts referencing natural products will not be accepted in this section Topic). A fast-growing interest in the application of QSP for drug dosing and trial decision-making in clinical development has made QSP a well-recognized tool in drug development. These methodologies are playing an ever-increasing role in preclinical and clinical drug development that are critical in the cost-effective identification of promising drugs.
Quantitative systems pharmacology is an emerging interdisciplinary field that integrates systems biology and pharmacometrics, with an emphasis on dynamic modelling, to quantitatively predict the effects of clinical interventions and their combinations under a variety of genetic, biophysical, biochemical, physiological, and biomechanical conditions.
Several modelling approaches for QSP have been developed, including statistical (Bayesian), agent-based, Boolean, temporal (ordinary differential equations), spatio-temporal (partial differential equations, integrative, empirical curve fitting, and machine learning that enable integrating molecular pathways with clinical results and pharmacology.
This Research Topic welcomes submissions from researchers in the field of computational drug discovery and design, including original research and review articles related to the Quantitative Systems Pharmacology approaches used in drug discovery. Any In silico original research data must be supported with experimental research. The topics to be covered in this Research Topic can include, but are not limited to:
-Quantitative Systems Pharmacology Modelling to drug development
-Quantitative Structure-Activity/Property relationship (QSAR/QSPR)
-Cardiovascular, metabolic, and oncology drug development
-Cancer therapy
-Target site delivery
-Immuno-Oncology applications
-Molecular docking
-Translational pharmacology
-CNS research and development
-Chemotherapy induced neutropenia
-Metabolic bone disorder
-Low-density lipoprotein cholesterol regulation in the human body
-Improving nano-therapy using image-guided systems pharmacology
-Toxicology
-Optimal dosing of COVID-19 vaccines
Please note: We will not accept original research manuscripts containing in silico studies only.
Furthermore, this Research Topic is hosted in the section Experimental Pharmacology and Drug Discovery and will not accept manuscripts referring to traditional remedies or other natural products.
