Artificial intelligence and machine learning
have become widely discussed topics in the area of life sciences and healthcare over the last several years and the excitement keeps growing. While a lot of pharmaceutical companies and healthcare organizations express considerable interest in possible new opportunities, associated with the use of artificial intelligence for early drug discovery, clinical trial optimization, and business intelligence, a considerable gap still exists when it comes to understanding new technologies and identifying the impacts of AI in the progress level of drug delivery and development by pharmaceutical professionals and leaders.
As clinical failure rates remain unsustainable and the vast amounts of patient data increases further, AI, data and clinical development and drug discovery experts from across large pharmaceutical and biotechnology industries are concerned to discover the growing practical applications of AI and ML for drug discovery and development.Artificial Intelligence and Machine Learning for Advanced Drug Discovery & Development Forum
will bring together global pharmaceutical industry leaders to exchange experience and share the latest discoveries using artificial intelligence (AI) and machine learning (ML) to enhance service delivery level in health-related industries and pharmaceutical industries. During this two day session, senior executives, experts, and business professionals will join in-depth panel discussions, view practical case studies, attend interactive sessions, and participate in development workshops.
At the Artificial Intelligence and Machine Learning for Advanced Drug Discovery & Development Forum
, you will discover how to technically integrate and apply AI algorithms to enhance trial design, improve patient selection and retention and achieve more precise AI-powered drug. The topics related to the identification of effective means of intelligent tools in drug discovery and development, unlocking the prospects of machine learning and AI for drug discovery and development, and application of machine learning as a decision support tool will all be addressed at the event.
The Artificial Intelligence and Machine Learning for Advanced Drug Discovery & Development conference
will offer you opportunity to connect with AI experts, data scientists, clinical development and E-health experts from big pharmas and biotech to overcome the data quality, data security, cultural and technical challenges associated with employing AI to design and execute the right clinical trial for your drug design and drug development.
Discussions and Topics
- Artificial Intelligence (AI) for Early Drug Discovery
- Harnessing the Power of AI to Accelerate Each Step in the Drug Discovery Process
- The Potential of Machine Learning in Drug Discovery
- Driving Strategic Decisions Making through Effective Data Analytics Tools
- Deploying AI to Accelerate Drug Discovery from Patient Data to Drug
- Key benefits of AI associated with Service Delivery level in health-related industries or pharmaceutical industries
- Challenges in the application of AI and machine learning in Drug Discovery
- Unlocking the prospects of machine learning and AI for drug discovery and development
Key Learning Points
- The application of the emerging digital technology shall enable participants have an increased understanding of disease mechanisms in larger pool of patients and potential for developing personalized therapies
- Participants will be convinced about the positives built around the world of AI intelligence other than the usage of human intervention in drug development and discovery
- Participants will get to learn more about the operations, processes, systems and procedures of AI platforms and how it can be used effectively to facilitate drug discovery and development from case studies
- Participants will gain more insight on the application of AI in facilitating clinical success
- There will be discussion on cost-reduction strategies in relation with drug discovery and development
Areas of responsibility:
- Clinical Development
- Drug Discovery
- Artificial Intelligence
- Machine learning
- Internet of things
- Drug Development
- Real-World Evidence
- Predictive analytics
- Computational Biology and Chemistry
- Open Innovation
- Drug Design
- Vice Presidents
- Pharmaceutical companies
- AI and Machine Learning
- Medical sciences
- Life Science
- Arpita Ray, Principal Scientist - BenevolentAI
- Asif Jan, Group Director in Personalized Healthcare Data Science - Roche
- Dimitrios Vitsios, Senior Research Scientist - AstraZeneca Centre for Genomics Research
- Heli Salminen-Mankonen, Head, Data Driven Business and Research, PhD, Dos., eMBA - Oriola
- Marcus Schmitt, CEO - Data Revenue GmbH
- Ulf Hannelius, President & CEO - Diamyd Medical
- Will Spooner, Co-Founder and CEO - Zetta Genomics
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