Artificial Intelligence in Drug Discovery and Development Nptel Week 2 Answers
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AI in Drug Discovery and Development Week 2 Answers (July-Dec 2025)
Course link: Click here to visit course on Nptel Website
Question 1. What is the average cost of bringing a single drug to market through traditional discovery methods?
a) $500 million
b) $1.2 billion
c) $2.6 billion
d) $10 billion
Question 2. What does SAR stand for in hit-to-lead optimization?
a) Standardized Affinity Ratio
b) Structure-Activity Relationship
c) Signal Activity Response
d) Synthesis and Reactivity
Question 3. Which platform is known for integrating CRISPR knockout data with AI for target validation?
a) CanSAR
b) DepMap
c) OpenTargets
d) Cell Painting
Question 4. What kind of toxicity is predicted using hERG channel models in AI safety pharmacology?
a) Nephrotoxicity
b) Cardiotoxicity
c) Hepatotoxicity
d) Neurotoxicity
Question 5. Which tool supports automated regulatory documentation for IND submission?
a) SmartSolve
b) RegDocs365
c) GastroPlus
d) Trial Pathfinder
These are AI in Drug Discovery and Development Week 2 Answers
Question 6. Which AI platform helped optimize a cancer lead series EXS21546?
a) Exscientia
b) GNS Healthcare
c) Healx
d) IQVIA
Question 7. What does ADMET stand for?
a) Advanced Dose Modeling and Experimental Toxicology
b) Absorption, Distribution, Metabolism, Excretion, and Toxicity
c) Artificial Design Metrics Evaluation Tool
d) Analytical Drug Manufacturing Evaluation Technique
Question 8. Which AI tool was used to simulate human PK/PD profiles for dose decisions?
a) REINVENT
b) Formulation.ai
c) GastroPlus
d) Cell Painting
Question 9. Which platform created virtual patient cohorts to simulate responses across demographics?
a) Phesi
b) Deep6 AI
c) Trial Pathfinder
d) GNS Healthcare
Question 10. Which AI-powered pharmacovigilance system analyzes EHRs and social media?
a) Aetion
b) Flatiron Health
c) Saama
d) Medidata AI
These are AI in Drug Discovery and Development Week 2 Answers
Question 11. Which step in drug discovery directly benefits from protein structure prediction by AI?
a) ADMET
b) Target Identification
c) Hit-to-Lead
d) Patient Recruitment
Question 12. Why does AI improve success rates in drug development?
a) It reduces the number of animal studies.
b) It ensures lower manufacturing costs.
c) It enables earlier and more accurate identification of failures.
d) It increases patient compliance.
Question 13. How does AI help in reducing clinical trial failures?
a) By improving packaging and distribution
b) By predicting success rates based on previous trials and stratifying patients
c) By automating marketing approvals
d) By outsourcing recruitment
Question 14. What is the biggest advantage of virtual screening powered by AI in hit identification?
a) Cost of reagents is eliminated
b) Clinical trials can be skipped
c) It enables rapid screening of millions of compounds
d) It guarantees FDA approval
Question 15. Ethical concerns in AI-driven drug discovery primarily relate to:
a) Lack of medicinal chemistry expertise
b) Data privacy and model transparency
c) Shortage of patients
d) Clinical trial dropout rates
These are AI in Drug Discovery and Development Week 2 Answers