Disruptive Innovation in Bio-Pharma Ecosystem through Artificial Intelligence and Machine Learning
Location:
Bristol-Myers Squibb
1 Squibb Drive
New Brunswick, NJ 08902
(entrance from Rt. 1 South)
This session will cover the foundational aspects of AI and ML is and why now is the right timing to consider AI. Real life examples of how AI & ML is being leveraged and the value it is driving in the Biopharma industry, across the entire value chain including – Drug Discovery, Clinical, Commercial, Supply Chain & Operations, Quality & Regulatory.
In the last 3-4 years, the dramatic improvements in computing capacity, both in terms of raw computational power as well as architectural advancements have profoundly altered the data analytics landscape, including advancements in artificial intelligence. Although it may not be directly evident, the effects of this shift manifest themselves in various aspects of our day-to-day lives.
As the Health care industry struggles to control drug prices, demonstrate tangible improvements in a value-based care environment, reduce the drug development timeline and cost and develop personalized medicine, the industry has a unique opportunity to leverage the emerging analytics-based ecosystem and to assume a leadership role in the landscape of Data Analytics & AI to save and improve the lives of patients with terminal diseases. The intellectual assets of Life Science companies related to (R&D and Operations data ) makes it better suited than most other industries to mobilize AI.
During the session the speakers will discuss real-life use cases such as follows:
- Longitudinal Patient Analysis using advanced data mining tools can reveal complex patterns that cause adverse outcomes.
- Machine Learning methods such as Unsupervised Learning can detect biologically similar patients across large volumes of genomic profiles.
- Commercial Market Research can utilize neural network models to improve forecasting models.
Speakers:
Over 18 years experience in Big data, ML and advanced Data Science. Commercial Research, Health Outcomes, Data Management, Enterprise Architecture, Ultra-low latency platforms, Big Data platforms, Machine Learning/Data Science, Low Latency Analytics, ECN/Trading Networks, High-Frequency Trading (IT Infra). A regular speaker at AI conferences. Author of the book ‘Practical Big Data Analytics'.
Education:
- Bachelor of Science, Computer Science and Mathematics, University of Bridgeport, 2002
Advised global fortune-500 life science companies with focus on Biopharma and MedTech sector. Over 25 years of consulting experience that combines strategy, business and technology consulting, to solve complex challenges. Key Functional and Technology expertise include - Clinical, Supply Chain, Operations, Quality & Regulatory; Technology Enabled Business Transformation leveraging Advanced Analytics.
Education:
- Masters of Management in Clinical Informatics, Duke University School of Medicine, Durham, NC USA
- Engineering, Instrumentation,, R.V. College of Engineering, Bangalore, India
Agenda
- 5:00 pm - 6:00 pm Registration & Networking Reception
- 6:15 pm - 7:30 pm Program
Cost
- Members - $40
- Non-Members - $50
- Young Professionals/Students - $20
Sponsorships
- Gold Sponsorship - $500
2 free registrations, recognition on all announcements, recognition at event and in newsletter - Silver Sponsorship - $250
1 free registration, recognition on all announcements, recognition at event and in newsletter