Related Experiment Video
Updated: Jun 25, 2025
05:10
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
9.6K
Computational biology approaches for drug repurposing
Tanya Waseem1, Tausif Ahmed Rajput1, Muhammad Saqlain Mushtaq1
1Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan.
Summary
Computational biology aids drug discovery by organizing complex biological data. This approach, particularly drug repurposing, accelerates development by using approved drugs, saving time and cost.
Area of Science:
- Computational Biology
- Drug Discovery and Development
- Bioinformatics
Background:
- Drug discovery and development (DDD) faces challenges due to complex, heterogeneous biological data.
- Traditional DDD is time-consuming and expensive.
- Drug repurposing offers a faster, cost-effective alternative by utilizing existing drugs with known safety profiles.
Purpose of the Study:
- To explore computational biology techniques for drug repurposing.
- To outline methods and tools for developing drug repurposing profiles.
- To demonstrate how computational biology streamlines drug development.
Main Methods:
- Utilizing computational biology to organize and analyze large biological datasets.
- Applying drug repurposing strategies to identify new therapeutic uses for approved drugs.
- Leveraging existing safety and efficacy data of approved drugs.
Main Results:
- Computational biology provides systematic approaches to manage complex biological data.
- Drug repurposing significantly reduces the time and cost associated with traditional drug development.
- Established computational tools facilitate the creation of effective drug repurposing profiles.
Conclusions:
- Computational biology is essential for efficient drug discovery and development.
- Drug repurposing, enhanced by computational methods, offers a viable strategy to overcome DDD constraints.
- This chapter provides foundational knowledge on computational biology tools for drug repurposing.
Keywords:
BioinformaticsComputationalDisease-targetDrug repositioningDrug-diseaseMachine learningMolecular dynamicsNetwork modelsRepurposingMore Related Videos
08:31Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
5.0K
07:40A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
4.2K
Related Concept Videos
01:28Structure-Activity Relationships and Drug Design
699
Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
699
01:26Drug Discovery: Overview
7.8K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
7.8K
01:14Model Approaches for Pharmacokinetic Data: Compartment Models
91
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Two primary types of compartment models are recognized: mammillary and catenary. The more...
91
01:26Targets for Drug Action: Overview
6.2K
Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
6.2K
01:26Pharmacokinetic Models: Comparison and Selection Criterion
69
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
69
01:12Analysis of Population Pharmacokinetic Data
252
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
252