QSPR — Property Prediction & Material Analogs — Hands-on

Learn how to apply Quantitative Structure–Property Relationships (QSPR) for small molecules and material like systems. This module covers endpoint selection, data curation, descriptor strategies, model building for key properties such as logP, solubility and stability, and workflows for proposing property optimized material analogs with clear uncertainty and applicability domain.

QSPR — Property Prediction & Material Analogs

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Session Index

Session 1 — QSPR Foundations & Property Endpoints Session 2 — Data Curation for Property Modeling Session 3 — Property Prediction Models & Evaluation Session 4 — Mini Capstone: Property Focused Material Analogs

Session 1

Fee: Rs 8800

QSPR Foundations & Property Endpoints

From QSAR to QSPR: focus on properties rather than potency

structure property relationships continuous vs categorical endpoints single vs multi property views

Common properties modeled in QSPR

logP, solubility, permeability pKa, stability, melting point material like properties (boiling, flash point)

Linking QSPR to discovery and materials decisions

ADMET and developability inputs formulation and PK implications materials selection and replacement

Session 2

Fee: Rs 11800

Data Curation for Property Modeling

Property data sources and extraction

public databases and literature experimental vs predicted records units and conditions

Cleaning, harmonization and outlier checks

duplicate handling and averaging temperature and pH normalization flagging suspicious entries

Transformations and problem framing for QSPR

log transforms and scaling regression vs classification setup thresholds for property classes

Session 3

Fee: Rs 14800

Property Prediction Models & Evaluation

Single endpoint QSPR modeling

linear regression baselines tree based and kernel methods calibration and residual analysis

Multi task and multi property modeling ideas

related properties and shared features multi output regressors tradeoffs vs single task models

Metrics, uncertainty and applicability domain for QSPR

RMSE, MAE, R² for regression calibration curves and prediction intervals distance based domain checks

Session 4

Fee: Rs 18800

Mini Capstone: Property Focused Material Analogs

Selecting a property endpoint and performance target

Theory + Practical

Using QSPR to explore and rank material or scaffold analogs

simple analog enumeration prediction guided triage balancing property windows

Deliverables: property prediction model and analog short list

notebook or script for QSPR ranked list with predicted values explanation of selection criteria

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QSPR — Property Prediction & Material Analogs Training | Physicochemical Properties & Material Design

QSPR — Property Prediction & Material Analogs — Hands-on