AI in Pharma Agenda

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Networking Available All Day


  • 9:00am – 5:00pm: Thursday, October 15th 

As the main agenda progresses throughout the day, you will have the choice of listening in to / participating in the live content or spend more of your time networking with your peers.

Here is how you will be able to achieve this, outside of the networking sessions on the agenda

  • See who’s in the room – you will be able to message all live attendees and connect with those who respond.
  • Schedule 1-2-1 video calls with your connections at any time that suits you.
  • Open Networking – think of this as the event lobby where you can replicate those all-important “water-cooler” moments.

You will be able to hop seamlessly between networking and on-going agenda sessions at any point.

With networking available all day, this will provide you with even more opportunities to meet your potential future partners and collaborators.


Main Agenda

  • Thursday, October 15th
Thursday, October 15th

Location: Stage

9:00 am

Chair’s Opening Remarks

  • How has the industry moved forward since AI in Pharma 2019?
  • What should we expect to have learned by the end of AI in Pharma 2020?

Brian Martin, Head of AI, AbbVie

9:10 am

Keynote Presentation: Accelerating Transformation with Machine Learning

  • Explore the uses of ML in R&D, clinical development, manufacturing & supply chain, commercialization, and patient support

Shez Partovi, MD, Worldwide Lead Healthcare, Life Sciences & Genomics, AWS

9:35 am

Panel Discussion – Is AI the Silver Bullet in Covid-19 Impacted Drug R&D?

Covid-19 has sent shockwaves through the world, and has greatly impacted drug research and development. As we navigate through our “New normal”, crucial questions must be answered to find out how AI can help. Hear exclusive insights from industry experts who are leading the charge with AI in their organizations. 

  • Has the impact of Covid-19 changed how we view the potential of AI? 
  • After the Coronavirus pandemic, will AI get a strong foothold in drug R&D? 
  • How can AI help accelerate drug R&D during Covid-19 through Virtual Trials?
  • What new challenges do we face given the changes over the past few months?
  • How are organizations now deploying AI approaches compared to previously?
  • Are we now on the cusp of an AI revolution in pharma?
  • What do we hope to achieve by the end of this Summit?

Ryan Copping, Global Head of Analytics, Genentech

José Duca, Global Head, Computer-Aided Drug Discovery, Novartis

Reza Olfati-Saber, Global Head of AI and Deep Analytics, Sanofi

Lihua Yu, President, Chief Data Science Officer, H3 Biomedicine

Location: The Choice is Yours!

10:05 am

Life Admin Break

Catch-up on emails, let the dog out, brew some more coffee… use this time to take care of regular day-to-day life.


Location: Sessions

10:05am

Open Q&A with Speakers

This is your chance to pose your burning questions to the expert speakers from the previous panel.

Ryan Copping, Global Head of Analytics, Genentech

José Duca, Global Head, Computer-Aided Drug Discovery, Novartis

Reza Olfati-Saber, Global Head of AI and Deep Analytics, Sanofi

Lihua Yu, President, Chief Data Science Officer, H3 Biomedicine

Actively or passively take part in this session.


10:25am

Speed Networking

In the purpose-built Networking area, get ready to expand your network through randomly assigned 1 on 1 quick-fire video meetings. You can choose who you want to “connect” with and then set-up 1-2-1 in-depth catch-up’s throughout the rest of the event. 

This function also ensures that you don’t meet the same person more than once, allowing you to meet as many fellow attendees as you desire.

Your future collaborators or partners could be just one click away!

AI in Pharma Virtual will now split into two tracks, whilst keeping open the opportunity for networking and 1-2-1 meetings.

Personalize your experience by hopping in and out of sessions and meetings seamlessly.

Location: Stage

AI Case Studies


10:55 am

Presentation: AI and Machine Learning at Arrakis Therapeutics

  • A look at how ML can be applied to unlock previously inaccessible biology in the pursuit of drugging RNA with small molecules
  • Discover how Arrakis Therapeutics is developing transformative medicines for patients.

Donovan Chin, Director of Computational Drug Discovery, Arrakis Therapeutics


11:20 am

Wellness Break

Get-up and have a stretch before the next session begins.


11:25 pm

Presentation: What are the Key Lessons Being Learned During the Deployment of AI at Scale?

  • How to overcome the key challenges of getting colleagues from other departments on board with AI approaches
  • How is AI making waves in developing, commercial, manufacturing and more.

Nimit Jain, Head of Data Science, ACOE, Novartis


11:50 am

Life Admin Break

Get-up and have a stretch before the next session begins.


Location: Sessions

Roundtable Discussions


10:55 am

Interactive Roundtable –  The 3 C’s: Communication, Consistency and Cross-Company adoption

  • Due to the complexity of Machine Learning, many senior decision makers don’t fully understand the science behind AI, and vice versa, tech experts in some cases don’t understand the needs of business users – How do we work together to improve this?
  • How can we help bridge the communication gap between Data Science-experts and the commercial decision makers?
  • How can we create a level of consistency across the board of companies, to demystify its complexity and further accelerate AI adoption?
  • How can we work together as an industry to improve the adoption of AI?

Lina Williamson, Founder & Chief Innovation Officer, Translational Medicine Accelerator


11:35 am

Wellness Break

Get-up and have a stretch before the next session begins.


11:40 am

Interactive Roundtable – Capturing the Promise of Machine Learning: Overcoming Key Challenges to Accelerate Drug Discovery

There is no question that AI is already having a positive impact in many phases of the drug discovery and development pipeline, but there are also still many challenges to fully realizing the anticipated potential of AI.

This roundtable will deep-dive into the most urgent functional gaps hindering drug discovery teams from fully capturing the promise of machine learning to accelerating early-stage drug discovery for critical diseases. We will look at recent case studies and explore how key aspects such as data, algorithms, and molecular descriptors can be optimized to improve success.

Areas of discussion include:

  • What are the highest priority opportunities, blockers and risks?
  • How can we improve data access, preparation, management and diversity to support algorithm training and model validation to better predictions?
  • Is there overlooked potential in optimizing molecular fingerprints?
  • What is the next big emerging frontier in algorithmic approaches?
  • Are there different challenges in development of novel molecules versus drug repurposing efforts?
  • What impact are partnerships and collaborative projects having on advancing progress? What challenges are they facing?

Actively or passively participate in this discussion

Yugal Sharma, Senior Director, CAS Services

12:25 pm

Lunch

Finally, lunch at a conference that is completely your choice!

Use this extended break to have your regular lunch, spend time with your family, and give your brain a break. Recharge for the afternoon session.

The AI in Pharma includes an extended break in the middle to give you ample time for lunch and another chance to catch-up on the day job. Or if you have time, you can use this break for 1-2-1 meetings or open networking.

 

Location: Expo Area

2:00 pm

Tour of Expo

Take a tour of the virtual Expo and interact with partners of AI in Pharma to understand more about their services.

Location: Stage

AI Case Studies


2:20pm

Presentation: Shaping the Future of Pharma and Healthcare with Bayesian AI

  • As we understand the limits of Machine Learning, Bayesian AI brings new possibilities of how data can be analyzed
  • How can Pharma and Healthcare benefit from a technology that generates new knowledge from data?
  • We will discuss use cases in which Bayesian AI was successfully applied to Clinical Development and Health IT

Leonardo Rodrigues, Vice President, AI & Machine Learning, BERG Health


2:45pm

Wellness Break

Get-up and have a stretch before the next session begins.


2:50pm

Presentation: Expedite Rare Disease Diagnosis and Improve Patient Outcome in NICU/PICU

  • I will cover what is possible today in digital diagnostic and treatment options for one of the most vulnerable patient population
  • I will describe the playbook and its key elements (2 engines, a blueprint and supporting eco-system)

Sebastien Lefebvre, Senior Director, Data Sciences, Alexion Pharmaceuticals


Location: Sessions

Roundtable Discussions


2:20 pm

Interactive Roundtable – Applying AI Models in the Way that Suits You

This interactive, discussion-led session will enable you to deepen your understanding of how best to apply AI models. Share your insights, pose your questions to the group or simply listen in to the conversation, the choice is yours. Kickstarter discussions include:

  • Should you always apply a model in its entirety?
  • How do you take insights from a certain model and apply them elsewhere?
  • How can you use part of a model to generate the answers you are looking for?
  • Sociologically, are people more comfortable with applying the whole model in the way it was intended to be used for a particular project?
  • How can we work together as an industry to educate our colleagues on how to use models with flexibility?

Actively or passively participate in this discussion

Roundtable Leaders to be Announced


3:25pm

Life Admin Break

Catch-up on emails, let the dog out, brew some more coffee… use this time to take care of regular day-to-day life.

Location: Stage

3:45 pm

Panel Discussion – The Elephant in the Room: Dealing with the Data

Arguably the biggest hurdle facing this industry, the question of data is one that has given most folks in the industry a headache at one point or another! This panel will dig into the key questions facing our use and analysis of data, discuss the burning data questions in our minds, and how to best move forward to find the solutions. 

  • What key data hurdles need overcoming before AI’s potential can be fully realized?
  • How can we build trust in our AI approaches so users apply the predictions with confidence?
  • What structured parameters do we need to set ourselves to define what “Good” and “Bad” data is?
  • How can pre-competitive data sharing help with our data issues?
  • How do we effectively dissect the massive amounts of data produced by AI?
  • What do we hope the situation with regards to data looks like by the AI in Pharma Summit 2021?

John Reynders, Vice President, Data Sciences, Genomics, & Bioinformatics, Alexion Pharmaceuticals

Gayle Wittenberg, Senior Director, Neuroscience Data Science, Janssen

Camilo Zapata, Senior Director,  Advanced/Predictive Analytics, Alkermes

Kausheek Nandy, Director, Head of Central Data Science, Americas, Boehringer Ingelheim

Location: Networking & Sessions

4:15pm – 5:00pm

Virtual Drinks

Share a virtual drink with old friends or new connections. At small virtual tables, this is your chance to casually interact with the rest of the AI in Pharma industry.


Location: Sessions

4:15pm – 4:35pm

Open Q&A with Speakers

This is your chance to pose your burning questions to the expert speakers from the previous panel.

Actively or passively take part in this session.

John Reynders, Vice President, Data Sciences, Genomics, & Bioinformatics, Alexion Pharmaceuticals

Gayle Wittenberg, Senior Director, Neuroscience Data Science, Janssen

Camilo Zapata, Senior Director,  Advanced/Predictive Analytics, Alkermes

Kausheek Nandy, Director, Head of Central Data Science, Americas, Boehringer Ingelheim


5:00pm

Close of The AI in Pharma Summit

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