In silico modeling employs computational methods to predict drug behavior, thereby significantly economizing both time and resources. Through the utilization of molecular docking simulations, this approach meticulously analyzes drug-target interactions, providing valuable insights into predicting therapeutic efficacy. In silico models systematically evaluate ADME properties, adeptly identifying potential issues at the early stages of drug development. Additionally, chemoinformatics facilitates the identification of lead compounds and refines molecular structures, while QSAR models quantitatively correlate chemical structure with pharmacological activity, offering a nuanced understanding of drug behavior. In the broader scope of pharmacology, computational methodologies contribute to personalized medicine by scrutinizing genetic and molecular data, tailoring drug treatments to individual profiles. The invaluable application of in silico methods in drug repurposing identifies existing drugs with untapped therapeutic potential against novel targets.
Vladlen Slepak
University of Miami, United States
Yong Xiao Wang
Albany Medical College, United States
Axel H Schonthal
University of Southern California, United States
Consolato M Sergi
Universities of Alberta and Ottawa, Canada
Madhav Bhatia
University of Otago, New Zealand
Luis Jesus Villarreal Gomez
Universidad Autónoma de Baja California, Mexico
Saad Tayyab
UCSI University, Malaysia
Lan Wang
Paretor LLC, United States
Ravi P Sahu
Wright State University, United States
Tanuja Tummala
Harrisburg University of Science and Technology, United StatesSubmit your abstract Today
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Consolato M Sergi, Universities of Alberta and Ottawa, Canada
Title : Development of novel drug delivery pathways enabled by perillyl alcohol (NEO100), A monoterpene with multifaceted biomedical applications
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Luis Jesus Villarreal Gomez, Universidad Autónoma de Baja California, Mexico