PHARMA AI

  • 25 April, 2019
  • 26 April, 2019
  • London

Artificial intelligence promises vast opportunities for economic and societal benefits in the pharmaceutical industry. This conference provides an comprehensive view of the role that AI plays, the key challenges and opportunities, as well as the strategic perspective on industry change. In times of disruptive innovation, success is based on a company’s ability to adapt, innovate and collaborate. This event therefore serves as a platform that fosters industry relationships, providing the opportunity for thedevelopment of innovative business solutions.

Key Practical Learning Points of the Summit:

•     Understanding the role of artificial intelligence in the pharmaceutical industry
•     The current state of AI technologies
•     Challenges and issues for implementing AI systems
•     Establishing evaluation standards and benchmarks
•     Adjusting pharmaceutical business models to incorporate AI technologies
•     New industry entrants: possibilities for strategic collaborations, partnerships, and alliances
•     Opportunities for R&D: time and cost efficiency, process optimization
•     Refining the drug discovery and development process
•     Lead optimization
•     Data integrity, governance and control
•     What’s next for computer assisted interventions and medical imaging analysis?
•     Proactive frameworks for predictive analysis
•     Risk management models and risk minimization
•     Business-Academia partnerships
•     Utilizing Big-data to enable AI capabilities

Who Should Attend:

Medical doctors| Research scientists |Data-scientists | CEOs| CTOs| Managers| Directors |Department Heads |Biomedical |Research Engineers specializing in pharmaceutical:

•     Data-science
•     Artificial Intelligence
•     Machine-learning
•     Drug discovery and development
•     Deep-learning
•     Predictive analytics
•     Data-analytics
•     Pre-clinical trials
•     Clinical trials
•     Research & Development
•     Medical imaging
•     Bio-technology
•     Bio-informatics
•     Clinical innovation
•     Scientific computing
•     Drug design
•     Computational screening

Target Audience:

•     Pharmaceutical companies
•     Health-care companies
•     Biomedical companies
•     Biotech companies
•     AI and Machine-learning companies
•     Data-analytics companies
•     Academia and research institutions
•     Hospitals

UNDERSTANDING THE ROLE OF ARTIFICIAL INTELLIGENCE IN THE PHARMACEUTICAL INDUSTRY

•     What AI really is: understanding AI, machine-learning, deep-learning and neural networks
•     The current state of AI technologies for the pharmaceutical industry
•     The use of AI in pre-clinical and clinical development
•     What’s next for medical imaging analysis and computer-aided diagnostics?
•     Accelerating the adoption of AI
•     Risk management models and risk minimization
•     Utilizing AI for next-generation therapeutics
•     Utilizing big-data to enable AI capabilities
•     The use of AI in pre-clinical and clinical development
•     Evaluating the potential for drug-to-drug interaction
•     Patient support and personalization
•     New possibilities for predictive analytics
•     AI use drug toxicity analysis

DRUG DISCOVERY AND DEVELOPMENT

•     The role of AI in the drug discovery and development process
•     Lead optimization
•     Process, time and cost optimization for efficiency
•     Compound and target identification improvements
•     Compound screening and lead identification
•     Design and augmentation possibilities with AI
•     Real-time defect detection: insight into compound analysis
•     Decreasing research and development expenditures
•     Automating molecule design

CHALLENGES AND ISSUES

•     Data control, regulation and governance
•     Data integrity and quality
•     Establishing evaluation standards and benchmarks
•     Meeting stringent regulations in drug development: transparent algorithms
•     Innovation VS implementation VS realization
•     Introducing data science talent into the pharmaceutical industry
•     Creating effective data-silos and encouraging a data-centric view

STRATEGIC PERSPECTIVE OF AI IMPLEMENTATION

•     Developing and implementing new business models for AI
•     Economic analysis: is the pharmaceutical industry in a state of crisis?
•     The impact of new entrant high-tech businesses in the pharmaceutical industry: strategic partnerships, acquisitions, collaborations and alliances
•     Developing internal infrastructure and expertise for AI application
•     Business-Academia partnerships (MLPDS)
•     Strategic and investment implications

 

For any enquiry on regards to special offers & group discounts please contact us directly at:
info@globalbsg.com

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