QSAR Modeling & Machine Learning

Mikael Kristiadi, S.Si., M.Si.

LOC 35
Higher Education 📅 13-15 Oktober 2025
🕘 19.00 - 21.00 WIB

Harga Course
Rp.300,000


Min. requirements

Course Overview

Quantitative Structure–Activity Relationship (QSAR) modeling is a cornerstone of modern computer-aided drug design (CADD). Combined with machine learning approaches, QSAR enables prediction of biological activity, toxicity, and pharmacokinetic properties of compounds with high efficiency.

This course, led by Mikael Kristiadi, S.Si., M.Si. (Bioinformatics Research Center – INBIO), provides a comprehensive foundation in QSAR concepts, molecular features, and the integration of machine learning techniques. Participants will gain hands-on experience in building, validating, and interpreting QSAR models for drug discovery.

Sub-topics

  • Introduction to QSAR & Molecular Features: Introduction to QSAR, Molecular Descriptors & Feature Extraction, The QSAR Modeling Pipeline
  • Machine Learning for QSAR: Overview of Machine Learning in Drug Discovery, Key Machine Learning Algorithms, Model Evaluation and Validation
  • Hands-On Session: Dataset Preparation, Descriptor Calculation, QSAR Model Building, Model Validation & Interpretation

Course Components