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Chulalongkorn University · Faculty of Pharmaceutical Sciences

Center of Excellence in Natural Products for Ageing & Chronic Diseases

Research and development of natural-product extracts for emerging diseases, chronic conditions, and an ageing society

Leveraging AI-driven drug discovery and nanoformulation, we transform natural-product science into pharmaceutical innovation and precision medicine for an ageing world.

About & History

From natural compound to clinical formulation

The establishment of CE-NPACD and the evolution of its research programme

Entrance to the Center of Excellence in Natural Products for Ageing and Chronic Diseases and the Joint Research Laboratory for China-Thailand Natural Medicinal Chemistry Second-floor entrance to the Center at the Faculty of Pharmaceutical Sciences, Chulalongkorn University Laboratory bench and fume hoods inside the Center

The Center of Excellence in Natural Products for Ageing and Chronic Diseases (CE-NPACD) was established at Chulalongkorn University to advance natural-product research across the full translational pathway, from the isolation of bioactive compounds to the development of formulations with potential for clinical application.

The Center’s research initially focused on classical natural-product chemistry. This was followed by the development of advanced drug-delivery systems, including polymeric, self-assembling, and magnetic nanoparticles.

The current phase integrates artificial intelligence with experimental research, combining virtual screening, deep-learning-based molecular docking, and machine-learning-guided formulation optimization with laboratory studies within a unified research platform.

Core Expertise

Four integrated research pillars

Four core research areas spanning natural product chemistry, delivery, pharmacology, and the AI platform

CE-NPACD research structure: Chemistry & Biopharmaceutics, Nanoformulation, Pharmacology, and AI Platform
Innovation Pipeline

From natural product to AI-driven formulation

How natural-product discovery connects to delivery systems and AI-driven drug discovery

Innovation pipeline: from traditional natural product discovery to delivery systems and AI-driven drug discovery
Traditional Natural Product DiscoveryIsolation and characterization of bioactive compounds from natural sources.
Delivery SystemNanoformulation to improve stability, bioavailability, and targeted delivery.
AI-Driven Drug Discovery & FormulationAI platform accelerates candidate screening and product development.
Our Team

Director, advisory & research members

The Director, advisory members, and research team of CE-NPACD

CE-NPACD team: Prof. Pornchai Rojsitthisak (Director), Advisory Members, and Research Team members
International Collaborators

A research network across borders

Countries with active academic collaboration with the Center

Map of international collaborating institutions across China, Philippines, USA, UK, Japan, Germany, Qatar, Sri Lanka, Singapore, and Malaysia

Collaboration is shown at country level; individual partner institutions are not listed on this page.

AI Solutions & Use Cases

Artificial Intelligence Product Track

Platforms and outputs built on the Center’s AI pipeline

A2A iCAP Platform — Integrated Virtual Screening of Natural Product-Like A2A Receptor Antagonist Candidates Use Case 01 · Live Platform
Drug Discovery · Virtual Screening

A2A iCAP Platform

  • AI-integrated consensus virtual screening for natural-product A₂A receptor antagonists
  • Combines ML activity prediction, GNINA deep-learning docking, and drug-likeness profiling
  • Validated against PDB 3REA crystal structure
Open Platform
CS-ALG Smart Formulator — Machine Learning-Driven Inverse Design of Chitosan-Alginate Nanoparticles Use Case 02 · Live Platform
Nanoformulation · Inverse Design

CS-ALG Smart Formulator

  • Machine learning-driven inverse design of chitosan-alginate nanoparticles
  • Predicts particle size, zeta potential, and encapsulation efficiency from API structure
  • From predictive modelling to interactive web deployment
Open Platform
CXCR4 Inhibitor Discovery — AI-Driven First-in-Class Antagonist Program Use Case 03 · QuickWin Grant
Drug Discovery · CXCR4

CXCR4 Inhibitor Discovery

  • AI-driven first-in-class CXCR4 antagonist discovery program
  • Cloud-based virtual screening combined with in vitro validation
  • CXCR4 dataset curation → standardised dataset → AI model training → AI-driven hit prediction
Watch Project Milestone
Contact Us

Get in touch with CE-NPACD

Location and contact channels for the Center

Location

Faculty of Pharmaceutical Sciences
Chulalongkorn University, Pathumwan, Bangkok