User Group Meeting, 2021

We’re excited to host Elucidata’s 2ndUser Group Meeting, bringing the latest on omics data ingestion, the role of Machine Learning in the future of drug discovery, and the value of early access to curated omics data. This virtual event features thought-provoking seminars from data science leaders in drug discovery, panel discussions on the challenges and opportunities of setting up a robust data infrastructure in laboratories, and user-led presentations on drug asset discovery using public omics data.

Event Details

Keynote Speakers

GARY CHURCHILL
PROFESSOR
THE JACKSON LABORATORY
Integration of Multi-Omics Data across Human & Mouse
MARINA SIROTA
ASSOCIATE PROFESSOR
BAKAR COMPUTATIONAL HEALTH SCIENCES INSTITUTE, UCSF
Computational Drug Discovery in the era of Precision Medicine

All Speakers

AARON MACKEY
VP COMPUTATIONAL MULTIOMICS
ROIVANT SCIENCES
ABHISHEK JHA
CEO & CO-FOUNDER
ELUCIDATA
BEVAN EMMA HUANG
SR. DIRECTOR
JOHNSON & JOHNSON
BRANDON ALLGOOD
CHIEF AI OFFICER
VALO HEALTH
DEWAKAR SANGARAJU
SR. SCIENTIST & METABOLOMICS GROUP HEAD - GENENTECH
DR. RAMA BALAKRISHNAN
BIOMEDICAL ONTOLOGY SPECIALIST GENENTECH
RICHARD KIBBEY
CO-FOUNDER, SCIENTIFIC ADVISORY BOARD - ELUCIDATA
SHASHANK JATAV
DIRECTOR, DATA PRODUCTS
ELUCIDATA
SHEFALI LATHWAL
LEAD SCIENTIST
ELUCIDATA
SOUMYA LUTHRA
DIRECTOR, CUSTOMER SUCCESS
ELUCIDATA
SWETABH PATHAK
CTO & CO-FOUNDER
ELUCIDATA
TODD HARRIS
FOUNDER & CEO
TYRA BIOSCIENCES

Agenda

Welcome Note

Speaker: Abhishek Jha, Co-Founder & CEO at Elucidata; Prof. Richard Kibbey, Scientific Co-Founder at Elucidata

Keynote Presentation 1: Integration of multi-omics data across human and mouse

Speaker: Gary Churchill, Professor at the Jackson Laboratory

The Churchill lab applies a systems approach to study the genetics of health and diseases, incorporating new methods & software that help investigate complex disease-related traits in the mouse. In his keynote address, Professor Gary Churchill will discuss how integration of human and mouse Multi-Omics Data helps characterize the genetic architecture of diseases.

A Data-Centric Approach to AI initiatives - The Changing Paradigm

Speaker: Abhishek Jha, Co-Founder & CEO at Elucidata

The recent surge in biomedical data has resulted in corresponding advances in ML algorithms for insight discovery. However, AI-driven drug design carries several challenges - the need for appropriate datasets, FAIR quality data & the ability to generate and test evolving biological hypotheses, to name a few. In this session, we discuss how a data-centric approach recognizes the value of ML-Ready data & significantly improves the efficiency of ML-Driven drug discovery initiatives.

Keynote Presentation 2: Computational Drug Discovery in the era of Precision Medicine

Speaker: Marina Sirota, Associate Professor at the Bakar Computational Health Sciences Institute, UCSF

Marina and her team at UCSF apply integrative computational methods in the context of disease diagnostics and therapeutics. Their primary focus is on leveraging and integrating different types of omics and clinical data to better understand the role of the immune system in diseases. Join this session as she discusses the role of computational drug discovery in precision medicine.

ML Applications of the Future: The Building Blocks

Speaker: Swetabh Pathak, Co-Founder & CTO at Elucidata

ML applications in drug research have matured from automating routine, low-level analyses to predicting the most complex structures we know of. However, quality data remains crucial to validate these approaches and generate accurate predictions and insights. Through this segment, we discuss the opportunities of applying ML across the drug research process & the steps discovery teams must take to accommodate this paradigm shift.

Panel Discussion: Challenges & Opportunities of setting up a Data Infrastructure

Speaker: Aaron Mackey, VP at Roivant Sciences; Brandon Allgood, Chief AI Officer at Valo Health; Bevan Emma Huang, Sr. Director at Johnson & Johnson; Swetabh Pathak, CTO & Co-Founder at Elucidata

The complexities of managing and delivering value from high throughput multi-omics data far outpace traditional approaches to IT infrastructure. Thus, building a robust, centralized ecosystem that ingests, stores & pre-processes these data for downstream ML applications becomes critical. Join our panel of industry experts as they make a case for strategic investments in biomedical data management and shed light on the challenges of building a data infrastructure from the ground up.

Ending Note

Speaker: Abhishek Jha, Co-Founder & CEO at Elucidata

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