Data Analytics and Artificial Intelligence Drug Development

• Understand the principles of data analytics and AI in the context of drug development.
• Gain proficiency in using data analytics tools and machine learning algorithms for pharmaceutical research.
• Explore the applications of AI in various stages of the drug development pipeline.
• Develop skills to analyze and interpret complex biological data.
• Learn to apply data-driven approaches to optimize drug discovery and development processes.

Module 1

• Collecting data from primary sources
• Types & Methods of Primary researches
• Legal, Ethical and Regulatory consideration while collecting information
• The role of AI, technology and innovation in pharmaceutical primary research
• Applications, Case Studies and Trends

Module 2

• Information Analysis: Art of collecting information from Secondary domain
• Importance of Clinical Trials in Information analysis
• The role of virtual clinical trials and remote monitoring in new drug development
• Drug delivery systems innovation: advances in formulation and delivery technologies
• Applications, Case Studies and Trends

Module 3

• The impact of data analytics and artificial intelligence in pharmaceutical R&D
• Connecting the dots (Insight generation from the data collected)
• Storytelling and Story building
• Case Studies and Trends

• Undergraduate degree in Life Sciences, Computer Science, Biotechnology, or related fields.
• Professionals in the pharmaceutical, biotechnology, or healthcare industries.
• Researchers and scientists with a keen interest in data-driven drug development and AI applications.