Certificate Course In Computer Aided Drug Development

English

What you'll learn

To make learner aware about computer applications in Pharmaceutical Industry

To make learner aware about computer applications in Formulation Development

To make learner aware about Computer Aided Pharmaceutics

To make learner about global scenario of Computer assisted technology in Formulation Development and Pharmaceutics

Requirements

Basics of Science and Pharmacy

Description

Computers play a crucial role in pharmaceutical research and development (R&D) across various stages of drug discovery, development, and delivery. Here are some specific uses of computers in pharmaceutical R&D:Drug Design and Discovery:- Molecular Modeling: Computational methods such as molecular docking, molecular dynamics simulations, and QSAR analysis are used to model the interactions between drug molecules and biological targets, aiding in the rational design of new drugs.- Virtual Screening: High-throughput virtual screening techniques help identify potential drug candidates by screening large databases of chemical compounds against specific drug targets or biological pathways.- De Novo Drug Design: Computer algorithms are used to generate novel drug-like molecules with desired properties based on predefined criteria, accelerating the discovery of lead compounds.Bioinformatics:- Genomics and Proteomics: Computers are used to analyze genomic and proteomic data to identify potential drug targets, understand disease mechanisms, and personalize treatment strategies.- Sequence Analysis: Bioinformatics tools facilitate the analysis of DNA and protein sequences to identify conserved regions, predict protein structures, and assess the functional impact of genetic variations.- Systems Biology: Computational modeling techniques are employed to simulate complex biological systems and study the interactions between genes, proteins, and metabolites, providing insights into disease pathways and drug responses.Chemoinformatics:- Chemical Database Management: Computers are used to store, organize, and retrieve chemical information from large databases of chemical compounds, enabling efficient data mining and analysis.- Structure-Activity Relationship (SAR) Analysis: Computational methods help analyze the structure-activity relationships of compounds to optimize their pharmacological properties and predict their biological activities.- Quantitative Structure-Property Relationship (QSPR) Modeling: QSPR models predict the physicochemical properties of compounds based on their molecular structures, facilitating the selection of lead compounds with desired properties.Clinical Trials and Drug Development:- Clinical Trial Design: Computers aid in the design and optimization of clinical trials by generating randomization schedules, calculating sample sizes, and simulating trial outcomes to assess statistical power.- Data Management: Electronic data capture (EDC) systems and clinical trial management systems (CTMS) streamline the collection, storage, and analysis of clinical trial data, improving data quality and compliance.Overall, computers play a pivotal role in accelerating the pace of pharmaceutical R&D, facilitating the discovery of novel drugs, optimizing drug development processes, and improving the efficacy and safety of pharmaceutical products.This course discusses Computer Application in Drug Development area. For simplicity the course is divided into 13 chapters.

Overview

Section 1: Introduction Computers in Pharmaceutical Research

Lecture 1 Introduction: Computers in Pharmaceutical Research

Lecture 2 Regulations and Protection using computers

Lecture 3 Pharmaceutical Quality by design

Lecture 4 Optimization and Pharmaceutical Product development

Section 2: Computer Aided Formulation Development

Lecture 5 Computer aided formulation development

Lecture 6 Computers in Preclinical drug development

Lecture 7 Computer-Aided Biopharmaceutical Characterization: Gastrointestinal Absorption

Lecture 8 Computer Simulation in Pharmacokinetics and Pharmacodynamics

Section 3: Computers in Clinical Development

Lecture 9 Computers in Clinical Development

Lecture 10 Computational Fluid Dynamics in Pharmaceutical Technology

Section 4: Computer applications and Artificial Intelligence

Lecture 11 Artificial Intelligence and Its Applications in the Pharmaceutical Sector

Section 5: Automation and Statistical Modelling

Lecture 12 Pharmaceutical Automation: Merits, Demerits, Current Challenges & Future

Lecture 13 Statistical Modeling in Pharmaceutical Research and Development

Science and Pharmacy Graduates,Beginners, All levels