C9485 - MACHINE LEARNING, IN VITRO AND IN VIVO MODELS FOR DRUG DISCOVERY

Learning outcomes

The course aims to provide students with theoretical and practical knowledge on the use of machine learning and experimental in vitro and in vivo methodologies in the preclinical development and validation of the pharmacological effects of both new drugs (drug discovery) and new therapeutic indications for already authorized drugs (drug repurposing). Practical sessions in computer laboratories will allow students to apply theoretical knowledge of machine learning and in vitro methods to assess the pharmacological efficacy of both new and existing drugs.

Course contents

Drug discovery pipeline: from target identification to preclinical studies. Drug repurposing strategies. Machine learning and bioinformatics applied to pharmacology. Pharmacological and chemoinformatic databases. In silico prediction of ADME-Tox properties.

In vitro models for preclinical studies. Organization of a cell culture laboratory. Basic Methods and Tools. Types of Cultures. iPS Cells (Induced Pluripotent Stem Cells). 2D vs 3D cell cultures (spheroids, organoids). Functional assays: viability, proliferation, apoptosis, migration.

In vivo models for preclinical studies. Principles of the 3Rs in animal experimentation. Organization of an animal facility and animal management for research purposes. Classical and alternative animal models (rodents, zebrafish, C. elegans, Drosophila). In vivo pharmacokinetics and pharmacodynamics. Animal models of disease. Preclinical endpoints, biomarkers and outcome measures.

Good Laboratory Practice (GLP): OECD principles, organization of GLP-compliant studies, quality assurance and data integrity. Translational research: from bench to bedside. Integrated in silico-in vitro-in vivo workflow.

Computer laboratory sessions, group work, and presentation of a drug repurposing project are included.

Readings/Bibliography

Slides regarding the course material used by teacher during the lessons. Students can find the slides on Virtuale.

Teaching methods

Lectures

Assessment methods

Oral exam

 

Teaching tools

PC

Slides

Overhead projector

Office hours

See the website of Andrea Tarozzi