AUGMENTED INTELLIGENCE IN DRUG DISCOVERY XCHANGE
EAST COAST 2023
Boston
May 25, 2023

Welcome to hubXchange’s Augmented Intelligence (AI) in Drug Discovery Xchange East Coast 2023, bringing together executives from pharma and biotech to address and find solutions to the key issues faced in AI-led drug discovery.

Discussion topics will cover Data Quality, Target Identification, Lead Generation, Lead Optimization and Drug Response Prediction.

Take advantage of this unique highly interactive meeting format designed for maximum engagement, collaboration and networking with your peers.

Please note this is an In-Person meeting.

VENUE DETAILS: Hilton Boston Woburn Hotel, 2 Forbes Road, Woburn MA 01801

SNAPSHOTS OF DISCUSSION TOPICS

  • Overcoming current limitations in data generation and management
  • Guidance on standard practice in clinical genomic data generation and data analysis pipelines
  • Use of AI in integrating multi-dimensional datasets for target discovery
  • Emerging modeling approaches to identify the covalently druggable targets
  • Bridging the gap between biological nails and AI hammers
  • Molecular design cycle: computation-first approach
  • Challenges and approaches to building deep learning models for antibody lead optimization

  • Can machine learning methods provide insights and predictions for cancer drug response?

Full Xchange Agenda

Click on each track for detailed agenda

Data Quality

Time
Titles and Bullets
Facilitator
8:00 – 8:30
Registration
8:30 – 9:00

Opening Address & Keynote Presentation
Building predictive models on rock and not quicksand: solid data foundations

Most if not all cutting-edge predictive models we see appear in Data Science and Life Science R&D are built on data. The challenge which is often overlooked is how to make sure the data foundations for these models are of high quality, reliable, normalized, and re-usable. This talk will focus on the experiences and processes needed in making both Elsevier and customer internal data “machine-learning ready”. Surprisingly, this often not only involves changes in data capture and modelling, but also changes in  people and processes. 

Senior Director Professional Services and Consulting, Corporate R&D, Elsevier

In Elsevier’s Professional Services team, Frederik leads the global consultancy practice on data integration and analytics projects throughout the life science, chemistry and engineering domains using commercial, proprietary, and public data sources. He holds a doctorate in Chemical Physics from the University of Amsterdam / FOM Institute AMOLF and a master’s degree in Chemistry from Utrecht University. 

Frederik van den Broek
09:05 – 10:05

Guidance on standard practice in clinical genomic data generation and data analysis pipelines

  • Vendor Qualification and fit for purpose assay selection
  • Global regulatory guidance for CRO based data generation 
  • Integration of new technologies in clinical research

 

 

Senior Scientist, Takeda

After finishing his postdoctoral training in Harvard Med School, Genetics dept. Banerjee has been navigating through genomics research both at the biotech industry and Pharmaceutical organization setting and has gained significant knowledge of the various facets of drug development process. He spent a few years as a Program co-Lead and Tech R&D lead in several drug programs in Cellarity, Inc. There he lead a team of scientists to perform protocol optimization and data generation efforts using fit for purpose technology /tool-kits.

Currently, he’s the Genomics subject matter expert (SME) for preclinical and clinical drug development workflows at Takeda Pharmaceuticals as a member of the Biomarker Science and Technologies team in PTS. He is an advisor for the current programs for genomics assay development to ensure fit-for-purpose assay selection and development for clinical biomarker assessment in patients for Neuroscience, GI, Oncology and Rare disease programs.

Budhaditya Banerjee
10:10 – 10:40
1-2-1 Meetings / Networking Break
10:40 – 11:10
1-2-1 Meetings / Networking Break
11:10 – 11:20
Morning Refreshments
11:20 – 12:20

Data quality challenges: how enabling data dogfooding helps to use and re-use data in AI Drug Discovery.

  • Capturing data with model building / re-use in mind
  • Mapping, harmonizing and combining internal and external data sets for analytics and ML
    model training
  • The role of ontologies in data harmonization
  • Levels of trust in quality of internal and external/public data

Senior Director Professional Services and Consulting, Corporate R&D, Elsevier

In Elsevier’s Professional Services team, Frederik leads the global consultancy practice on data
integration and analytics projects throughout the life science, chemistry and engineering domains using commercial, proprietary, and public data sources. He holds a doctorate in Chemical Physics from the University of Amsterdam / FOM Institute AMOLF and a master’s degree in Chemistry from Utrecht University.

Frederik van den Broek
12:20 – 13:20

Networking Lunch

13:20 – 13:50

1-2-1 Meetings / Networking Break

13:50 – 14:20

1-2-1 Meetings / Networking Break

14:25 – 14:55

Poster Session
Unlocking Biomedical Data for AI / ML using Large Language Models (LLMs)

  • To effectively train predictive models in drug discovery, large volumes of clean and linked data are required, which can be a costly and time-consuming task to curate manually. As such, there is a growing need for automated curation processes that can accurately and efficiently label data at scale.
  • Elucidata has developed a biocuration process that leverages domain-trained BERT-like models for a variety of information extraction tasks: Identification of cell type, cell line, tissue, disease, and other characteristics from unstructured biomedical datasets. This approach has shown promising results in improving the quality and efficiency of data curation.
  • In this session, we will explore the specifics of Elucidata’s NLP-based biocuration and how it can help R&D teams make their data interoperable, enable data and metadata integration and generate model quality datasets for AI/ML use cases.
  • As a bonus, we will also demonstrate our experiments with Open AI’s Chat-GPT and its potential in solving edge cases in biocuration.

Solutions Architect, Elucidata

Mya (my-uh, not me-uh) Steadman is a Bioinformatics Scientist at Elucidata, working with data scientists at therapeutic and diagnostic companies to identify and resolve roadblocks in their research due to unclean biomedical data. Before Elucidata, Mya was a metabolomics scientist studying Cancer and Autoimmune diseases at several biotech start-ups in Cambridge, Massachusetts, including Agios Pharmaceuticals. While at Agios, she had the chance to work with Elucidata’s founder Abhishek Jha, who taught her that the value of your results is determined by the quality of your data.

Mya Steadman
16:00 – 16:15

Afternoon Refreshments

16:15 – 17:15

Data quality, variability and integrity: how do we achieve it?

  • What data are you using? What’s the most challenging problem for data quality in your job? How do you ensure high data quality?
  • Key issues: messy public data/metadata, raw data are not available, data are not processed in a consistent way

 

Director of Computational Biology, Immunitas Therapeutics

Ming “Tommy” Tang is the Director of Computational Biology at Immunitas. Prior to joining Immunitas Tommy was at Dana-Farber Cancer Institute and Harvard University, where he led a team to analyze immune-oncology related single-cell sequencing datasets and spearheaded an NIH-funded project called Cancer Immunological Data Commons. Tommy has a wealth of experience as a computational biologist with over ten years in analyzing large-scale (epi)genomic/transcriptomic data and automating the analysis by using workflow languages such as Snakemake.. Prior to joining Dana-Farber, Tommy received his Ph.D. in Genetics and Genomics from the University of Florida and completed a three-year postdoc at MD Anderson. He has a keen interest in teaching computational skills to wet biologists and is a certified instructor for Data Carpentry.

Tommy Tang
17:15 – 18:15
Evening Drinks Reception

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