A strategic guide to AI implementation in drug discovery, clinical operations, and regulatory compliance.
Sub Category
- Business Analytics & Intelligence
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Objectives
- Apply generative models (GANs/VAEs) and AlphaFold for de novo molecular design and optimization.
- Evaluate the impact of AI on target identification using multi-omics data and knowledge graphs.
- Design intelligent clinical protocols and optimize site selection using historical data simulation.
- Implement strategies for Decentralized Clinical Trials (DCTs) utilizing digital biomarkers.
- Analyze Real-World Evidence (RWE) for post-market surveillance and regulatory label expansion.
- Understand the regulatory landscape for AI as a Medical Device (SaMD) including FDA/EMA guidance.
- Assess predictive toxicology and ADME properties to reduce preclinical attrition rates.
- Integrate multi-modal data for precision medicine and companion diagnostic development.
Pre Requisites
- General understanding of the pharmaceutical drug development lifecycle (Discovery to Commercialization).
- Familiarity with basic biological and chemical concepts is helpful but not strictly required.
- No programming experience is necessary; the course focuses on strategy, application, and concepts.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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