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.
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Title : The impact of metal-decorated polymeric nanodots on proton relaxivity
Paulo Cesar De Morais, Catholic University of Brasilia, Brazil
Title : Hepatotoxic botanicals-shadows of pearls
Consolato M Sergi, Universities of Alberta and Ottawa, Canada
Title : Exploring classical ayurvedic drugs in hypertension
Prashant Bhokardankar, Datta Meghe Ayurved College, India
Title : Principles and standards for managing healthcare transformation towards personalized, preventive, predictive, participative precision medicine ecosystems
Bernd Blobel, University of Regensburg, Germany
Title : Personalized and Precision Medicine (PPM) as a unique healthcare model based on design-inspired biotech- & biopharma-driven applications to secure the human healthcare and biosafety
Sergey Suchkov, N.D. Zelinskii Institute for Organic Chemistry of the Russian Academy of Sciences & InMedStar, Russian Federation
Title : A unique role and and impact of catalytic antibodies (abzymes) in clinical practice: A novel strategy for predicting and preventing relapse in chronic autoimmune conditions
Sergey Suchkov, N.D. Zelinskii Institute for Organic Chemistry of the Russian Academy of Sciences & InMedStar, Russian Federation
Title : The promise of nanotechnology in personalized & precision medicine: Drug discovery & development being partnered with nanotechnologies via the revolution at the nanoscale
Sergey Suchkov, N.D. Zelinskii Institute for Organic Chemistry of the Russian Academy of Sciences & InMedStar, Russian Federation
Title : The promising future of the unique translational tool to manage beta-cell population renewal and regeneration to secure the post-diabetic period
Sergey Suchkov, N.D. Zelinskii Institute for Organic Chemistry of the Russian Academy of Sciences & InMedStar, Russian Federation
Title : Easily injectable, organic solvent free self assembled hydrogel platform for endoscope mediated gastrointestinal polypectomy
Hitasha Vithalani , IIT Gandhinagar, India