About
This advanced program delves into the use of artificial intelligence to enhance the effectiveness of drug delivery systems specifically for cancer treatment. Participants will learn about AI algorithms that predict drug behavior, personalize treatments, and optimize delivery mechanisms to improve patient outcomes. The course covers interdisciplinary fields combining pharmacology, oncology, computer science, and bioinformatics.
Aim
The aim of “Artificial Intelligence for Cancer Drug Delivery” is to equip participants with cutting-edge skills in AI to revolutionize cancer treatment, focusing on precision and personalized drug delivery systems. The program strives to advance the integration of AI in oncology to improve treatment efficacy and patient outcomes significantly.
Workshop Objectives
- Understand the role of AI in cancer research and drug delivery.
- Explore machine learning models that enhance drug targeting and delivery.
- Develop skills to integrate AI with existing pharmaceutical and biomedical practices.
Workshop Structure
Day 1:
1. Introduction to Artificial Intelligence (AI) and its applications in healthcare
- Definition and overview of AI
- How AI is revolutionizing cancer drug delivery
- Importance of AI in precision medicine
2. Understanding Cancer Drug Delivery
- Overview of traditional cancer drug delivery methods and their limitations
- Challenges in drug delivery for cancer treatment
- Introduction to targeted drug delivery and its benefits
3. Nanoparticles and convergence of artificial intelligence for targeted drug delivery for
cancer therapy: Current progress and challenges
- Role of AI in optimizing drug formulations
4. Case Studies on AI in Cancer Drug Delivery
- Highlighting successful applications of AI in drug delivery
- Exploring AI-driven technologies like nanotechnology and robotics in drug delivery
- Ethical considerations and regulatory challenges in AI-enabled drug delivery
Day 2:
1. Role of Data in AI for Cancer Drug Delivery
- Importance of data in AI-driven drug delivery solutions
- The significance of artificial intelligence in drug delivery system design
2. Data-driven Approaches for Cancer Drug Delivery
- Utilizing electronic health records (EHRs) for treatment optimization
- Drug design for cancer using AI
- Integration of imaging data for drug delivery planning
3. AI Applications in Drug Discovery
- Using AI for virtual screening of potential drug candidates
- Accelerating lead optimization using AI-driven algorithms
- AI-enabled target identification and validation
4. Artificial intelligence in cancer target identification and drug discovery
- explore and discuss potential AI solutions for specific drug delivery challenges
- Brainstorming AI-driven strategies and techniques for improved cancer treatment
outcomes
Day 3:
1. AI for Predictive and Precision Medicine
- Understanding predictive modeling for patient stratification
- Precision medicine and its integration with AI
- Case studies on precision medicine and AI in cancer drug delivery
2. AI for Drug Delivery Optimization and Personalization
- Real-time monitoring and feedback mechanisms for personalized drug delivery
- Challenges and future directions in AI-driven personalized medicine
3. Ethical and Legal Considerations in AI for Cancer Drug Delivery
- Privacy and security concerns in handling patient data
- Ethical implications of AI-enabled decision-making in drug delivery
- Regulatory landscape and guidelines for AI in healthcare
4. Artificial intelligence in cancer therapy
- Final thoughts on the future of AI in cancer drug delivery
Participant’s Eligibility
- Students, PhD scholars, academicians, and industry professionals in fields like oncology, pharmacology, computer science, and bioinformatics.
- Medical researchers and pharmaceutical scientists interested in AI applications in drug delivery.
- Data scientists and AI specialists looking to apply their skills in healthcare.
Important Dates
Registration Ends: 2024-09-24 (Indian Standard Timing 4:00 pm)
Workshop Dates: 2024-09-24 to 2024-09-26 (Indian Standard Timing 4:30 pm)
Workshop Outcomes
- AI and Machine Learning Proficiency: Advanced understanding and application of AI and machine learning in biomedical contexts.
- Pharmacokinetic Modeling: Skills in modeling drug behavior and interactions using AI algorithms.
- Personalized Medicine Development: Ability to develop personalized treatment plans based on patient-specific data analysis.
- Data Analysis and Interpretation: Proficiency in handling and interpreting large sets of clinical and pharmacological data.
- Interdisciplinary Collaboration: Skills in working effectively across diverse fields to integrate AI with cancer treatment strategies.
- Ethical and Regulatory Compliance: Understanding of the ethical considerations and regulatory requirements in using AI for medical applications.
- Innovative Problem Solving: Ability to apply AI tools to solve complex problems in cancer drug delivery.
Mentor Profile
Name: Dr. Bandoo Chhagan Chatale
Designation: Founder and Mentor of Pharmacy Success HubEdit
Affiliation: Pharmacy Success Hub
Dr. Bandoo Chhagan Chatale is a distinguished figure in the pharmacy sector, celebrated for his visionary and mission-oriented approach. As the founder and mentor of Pharmacy Success Hub since July 2014, he has been a guiding force in empowering pharmacy professionals. He completed his Ph.D. in Pharmaceutical Chemistry from the Institute of Chemical TechDeactivatedlogy, Mumbai, in September 2020, after obtaining his master’s degree from NIPER, Mohali in June 2014. With a decade of experience in teaching and research, Dr. Chatale specializes in Computer-Aided Drug Design, taste masking, synthesis of small chemical entities, cocrystal formation, and Hot Melt Extrusion (HMT) TechDeactivatedlogy. His work extends into the inDeactivatedvative realms of Artificial Intelligence in Pharmacy and Healthcare. Dr. Chatale has authored six international research articles and holds a design patent granted by the UK government, marking significant contributions to his field.
