Welcome to Elucidata's
USER GROUP MEETING 2021
October 27, 2021 | 9 AM – 1:30 PM (Pacific Time)
We’re excited to host Elucidata’s 2nd User 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.
Gary Churchill, Ph.D.
the jackson laboratory
Integration of Multi-Omics Data across Human & Mouse
Marina sirota, Ph.D.
Bakar Computational Health Sciences Institute, UCSF
Computational Drug Discovery in the era of Precision Medicine
Aaron Mackey, Ph.D.
VP Computational Multiomics
Abhishek Jha, Ph.D.
CEO & Co-Founder
Dr. Emma Huang
Johnson & Johnson
Brandon AllGood, Ph.D.
Chief AI officer
dewakar sangaraju, Ph.D.
Sr. scientist & metabolomics group head - genentech
Rama Balakrishnan, Ph.D.
Biomedical Ontology Specialist genentech
Dr. Richard Kibbey
Co-founder, Scientific Advisory Board - Elucidata
director, data products
shefali lathwal, Ph.D.
director, customer success
cto & co-founder
Todd Harris, Ph.D.
Founder & CEO
09 - 9.10 am
Watch the session here Speaker: Abhishek Jha, Co-Founder & CEO at Elucidata; Prof. Richard Kibbey, Scientific Co-Founder at Elucidata
9.10 - 9.40 am
Keynote Presentation 1: Integration of multi-omics data across human and mouse
Watch the session here 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.
9.40 - 10.10 am
A Data-Centric Approach to AI initiatives - The Changing Paradigm
Watch the session here 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.
10.10 - 10.40 am
Keynote Presentation 2: Computational Drug Discovery in the era of Precision Medicine
Watch the session here 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.
10.40 - 11.10 am
ML Applications of the Future: The Building Blocks
Watch the session here 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.
Data & Technology
Polly Enabled Solutions
11.15 - 11.45 am
Thinking about Data Quality
Watch the session here Speaker: Shefali Lathwal, Lead Scientist While the value of FAIR biomolecular data to the research community is uncontested, data quality control methods show high variability across data types and use cases. This necessitates a standard framework that addresses the overall quality of biomedical data. In this session, we will discuss our approach towards measuring, improving, and maintaining high-quality data.
11.15 - 11.45 am
High throughput Metabolomics Analysis using Polly
Watch the session here Speaker: Dewakar Sangaraju, Sr. Scientist at Genentech Faster downstream analysis & visualization of data is a bottleneck in the use of Metabolomics techniques for identifying metabolite signatures. This session will demonstrate how our partner, Genentech, leverages production-ready GUI applications developed by Elucidata experts to accelerate insight generation & uncover complex relationships in data.
11.45 - 12.15 pm
Maximizing data value for Biopharma through FAIR & Quality Implementation
Watch the session here Speaker: Dr Rama Balakrishnan, Biomedical Ontology Specialist at Genentech Dr. Rama Balakrishnan and her team aims to FAIRify legacy datasets in different Therapeutic Areas (TA) and design processes for prospective FAIRification of future studies. This session details the need for FAIR data metrics, Data Quality Assessment (DQA) for clinical trials as well as EHR data, and how to accelerate the generation of new medical treatments through FAIR data.
11.45 - 12.15 pm
Target Identification using public data
Watch the session here Speaker: Todd Harris, Founder & CEO at Tyra Biosciences; Abhishek Jha, Co-Founder & CEO at Elucidata The power of multi-omics data is evident in the recent surge of molecular biology-based therapeutic breakthroughs, but the complexity of managing multi-dimensional data from disparate sources continues to be a challenge. This session details a real-world use case on how Polly powers curated ML-ready omics data, enabling an integrative multi-omics approach that helps identify safe & efficacious drug targets.
12.15 - 12.45 pm
Curating Biomedical Molecular Data at Scale, our IP
Watch the session here Speaker: Shashank Jatav - Director, Data Products Elucidata’s proprietary curation platform, built on top of NLP-based AI models, generates harmonized metadata annotations with scientific context at an accuracy matching that of human experts. In this session, we will look at how the platform enables data curation at scale and equips users with ML-Ready biomolecular data for their drug discovery workflows.
12.15 - 12.45 pm
Engagement Models & Polly Enabled Solutions
Watch the session here Speaker: Soumya Luthra - Director, Customer Success Through a combination of our data platform Polly and in-house bioinformatics experts, we empower multi-disciplinary R&D teams with production-ready pipelines & applications, scale their data curation efforts and help them get to quicker actionable insights. Take a quick tour of Polly Enabled Solutions & see how they add value to your bioinformatics enterprise.
12.50 - 1.20 pm
Panel Discussion: Challenges & Opportunities of setting up a Data Infrastructure
Watch the session here Panelists:: 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.
1.20 - 1.30 pm
Speaker: Abhishek Jha, Co-Founder & CEO at Elucidata