AI aims to move medical treatment away from general, one-size-fits-all options to more personalized solutions. Learn more about the incredible amounts of information generated through precision medicine, and the critical capabilities needed to analyze,
store, normalize and trace that data. This seminar is tailored towards those working in the healthcare and pharmaceutical industries.
Wednesday, October 23
7:30 am Registration Open
8:00 Continental Breakfast
8:55 – 12:05 pm AI World Executive Summit
12:05 Enjoy Lunch on Your Own
1:15 Opening Remarks
Jonathan Dry, PhD, Director, Bioinformatics and Data Science, Research and Early Development, Oncology R&D, AstraZeneca
1:20 Graphical Models for Precision Therapeutics
Jonathan Dry, PhD,
Director, Bioinformatics and Data Science, Research and Early Development, Oncology R&D, AstraZeneca
Networks can provide a powerful representation of biological systems that capture their underlying complexity by integrating information of biological entities and their interactions. The current work focuses on a network approach based on graph representation
learning, to integrate prior knowledge with data corresponding to drugs and patients. This approach enables us to simultaneously combine multi-omics and clinical features with the goal of predicting biomarkers associated with patient outcomes and
1:45 AI-Guided Read & Write Brain Tech Platform: Revolutionizing Brain Therapy
Ana Maiques, CEO, Neuroelectrics
What would you do if you could read and write on the brain? Let’s imagine Neuroelectrics can non-invasively read (EEG) and write (transcranial current stimulation) your brain and with AI, build a personalized model of your brain. This personalized
model would allow us to design a protocol to help treat your brain disease using non-invasive neuromodulation. The company is now implementing its AI-guided read/write platform to epilepsy, where we are conducting a clinical trial at Boston Children’s
Hospital for kids that do not respond to medication.
2:10 CO-PRESENTATION: Making Artificial Intelligence Actionable for Patients with Chronic Diseases
Len Usvyat, PhD, Vice
President, Applied Advanced Analytics, Fresenius Medical Care North America
Caitlin Monaghan, PhD, Data Scientist II, Applied Advanced Analytics, Fresenius Medical Care North America
Fresenius Medical Care (the world’s largest kidney dialysis provider) leverages artificial intelligence to gain insights that guide the delivery of truly personalized care. We will detail several examples of machine learning-based predictive
model algorithms designed for pre-emptive identification of patients at a greater risk of: 7-day all-cause and fluid overload-related hospital admissions, non-adherence with routine dialysis, and progression from chronic kidney disease to end-stage
2:35 Refreshment Break
2:55 Deep Learning Network to Generate Synthetic Dataset to Protect Personally Identifiable Information in Clinical Trials
Shanrong Zhao, PhD, Director of Computational Biology, Pfizer, Inc.
The challenge in data privacy is to share data while protecting personally identifiable information. However, de-identified EHR (Electronic Health Record) data risk should be re-identified. Generative Adversarial Networks (GANs) can generate synthetic
datasets to protect personally identifiable information.
3:15 Personalized Healthcare: Leveraging IoT & Quantum Computing
Uzair Rashid, Senior Manager, Healthcare Strategy & Innovation, CVS Health
The healthcare system is fragmented, costly, slow to react, and contains gaps in access to care. By leveraging key tech enablers, Quantum Computing, and IoT devices, we can create an integrated, proactive solution for individualized healthcare management.
3:35 PANEL: AI in Personalized Medicine and Digital Health
Moderator: Len Usvyat, PhD, Vice President, Applied Advanced Analytics, Fresenius Medical Care North America
Maiques, CEO, Neuroelectrics
Senior Manager, Healthcare Strategy& Innovation, CVS Health
Albine Martin, Executive in Residence, Johns Hopkins University
- Opportunities for AI in personalized and precision medicine
- Who are the stakeholders of AI and personalized medicine? How can we promote and ensure efficient collaboration between these stakeholders?
- Implementation and acceptance in existing health care systems: What are the challenges/roadblocks?
- Education of future generations: What messages would you like to pass to the future generation of practitioners?
4:10 Session Break
4:20 Plenary Keynote Panel
5:00 Grand Opening Reception in the Expo
6:30 Attendee Roundtable Discussions & Meetup Groups - Click here for details
7:30 Close of Day