Quantitative Structure-Activity Relationship (QSAR) Modeling: A Recent Trend in Drug Design

QSAR, Computer-Aided Drug Design, CADD, Molecular Modeling, Drug Discovery, Pharmaceuticals, Computational Chemistry, Minitab Software, Regression Modeling, Energy Minimization, Pharmacophore Modeling, Pharmaceutical Development, Molecular Simulation, Rational Drug Design, Force Field, QSAR Modeling, Correlation Coefficient, Model Validation, Computational Approaches, Drug Properties, Pharmaceutical Research

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MODE
Virtual (Google Meet)

TYPE
Self Paced

LEVEL
Moderate

DURATION
1 Month

VIDEO LENGTH
1

About

The Unveiling the Power of QSAR: Pioneering Trends in Computer-Aided Drug Design program is a comprehensive educational event designed to immerse participants in the world of Quantitative Structure-Activity Relationship (QSAR) modeling and its contemporary applications in Computer-Aided Drug Design (CADD). This program is meticulously crafted to provide a deep understanding of the intricate interplay between computational science and pharmaceutical research, offering a roadmap to harness the potential of QSAR in the drug development process.

Aim

The aim of this program is to empower participants with the latest insights and practical knowledge in Quantitative Structure-Activity Relationship (QSAR) modeling and its applications in Computer-Aided Drug Design (CADD). Through interactive sessions and hands-on experience with Minitab software, participants will gain a comprehensive understanding of how QSAR techniques enhance the drug development process.

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Courses Objectives

Introduction to CADD and QSA: Provide a foundational understanding of Computer-Aided Drug Design (CADD) and Quantitative Structure-Activity Relationship (QSAR) modeling.
Hands-On QSAR Skills: Equip participants with practical skills, including QSAR modeling using Minitab software and data analysis techniques.
Real-World Applications: Illustrate the practical applications of QSAR in pharmaceutical research and drug development through case studies.
Enhanced Problem-Solving: Foster critical thinking and problem-solving abilities in the context of drug design and computational chemistry.
Career Advancement: Empower participants with knowledge and skills to advance their careers in pharmaceuticals, computational chemistry, and related fields.

Courses Structure

Day 1:

CADD and Molecular Modeling
Why CADD and Molecular Simulation
Force Field and Energy minimization
Drug Development Process
Process of CADD and Technology Impact
Phases of CADD, methodology and Strategies

Day 2:

QSAR and Drug Design
Steps in QSAR
QSAR Modeling importance in CADD
QSAR Data Analysis
Potential Drug Properties
Pharmacophore Modeling

Day 3:

Introduction of Minitab software
Multiple Linear Regression Model
PRESS, SSY and Leave one out (LOO)
Applications of QSAR
Correlation coefficient and Model Validation
Applications of QSAR in pharmaceutical development

Participant’s Eligibility

Pharmaceutical Researchers, Medicinal Chemists, Chemoinformaticians, Pharmacologists, Bioinformaticians, Academics and Students, Data Scientists and Computational Biologists, Regulatory Affairs Professionals, Entrepreneurs and Startups, Pharmaceutical Marketers: Marketing, Chemistry and Biology Students

Important Dates

Registration Ends

2023-11-03
Indian Standard Timing 07:00 PM

Courses Dates

2023-11-03 to 2023-11-05
Indian Standard Timing 08:30 PM

Courses Outcomes

Proficiency in QSAR Modeling: Participants will gain hands-on experience and proficiency in using QSAR modeling techniques to predict and optimize drug properties.
Understanding of CADD Principles: Participants will acquire a solid understanding of Computer-Aided Drug Design (CADD) principles, including molecular modeling and simulation.
Real-World Application: Participants will be able to apply QSAR methods to real-world pharmaceutical challenges, enhancing their problem-solving abilities.
Enhanced Career Prospects: Attendees will leave the program with valuable skills and knowledge that can boost their career opportunities in pharmaceuticals, computational chemistry, and related fields.
Networking and Collaboration: The program will provide a platform for networking and collaboration with experts and peers in the field, fostering professional relationships and knowledge sharing.

Fee Structure

Student

INR. 1199
USD. 40

Ph.D. Scholar / Researcher

INR. 1499
USD. 45

Academician / Faculty

INR. 1999
USD. 50

Industry Professional

INR. 2499
USD. 75

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