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2020DataScience-1988x680

2020 PDA Virtual Pharmaceutical Manufacturing Data Science Workshop

Jul 13 - Jul 16, 2020
Eastern Standard Time | Online
  • Virtual
  • Conference
  • Online
Program Highlights

Overview

This four-part virtual workshop will provide hands-on experience for managers in the pharmaceutical manufacturing field. Learn best practices for breaking down data silos using traditional and advanced analytics to realize the promise of “Pharma 4.0” so that you can evaluate project proposals, their results, and transfer to the business.

Get an interactive preview of the types of data science dashboards you'll develop during one of the many hands-on sessions during the Workshop.

Data Science Sample Report
Explore Principal Component Analysis (PCA)

During this virtual Workshop, you'll learn how to leverage PCA to explore large, complex data sets to interpret relationships between variables. Leverage new technologies like Industrial Internet of Things (IIoT), cloud, big data, and artificial intelligence (AI) to open the door to computational resources that were not available previously. Get a preview of PCA and what you'll achieve by attending this Workshop.

Agenda

  • Day 1
  • Day 2
  • Day 3
  • Day 4
  • 10:00 a.m. – 12:30 p.m. EDT | P1

    In this first of four interactive webinars, participants will review the foundations of pharmaceutical manufacturing data science, including the industry 4.0 paradigm and the structure of a data science project. Principles for the day, vocabulary, and use cases will also be outlined. Then, participants will load the first use case and begin to assess the data quality.

    10:00 a.m. | Welcome and Opening Remarks from Workshop Chair
    Arne Zilian, PhD, Manufacturing Science and Technology, Global Head Systems and Standards, Novartis

    10:30 a.m. | Foundations of Pharmaceutical Manufacturing Data Science
    Arne Zilian, PhD, Manufacturing Science and Technology, Global Head Systems and Standards, Novartis

    11:00 a.m. | Case 1: Data Transformation: Breaking Down Silos
    Richard Love, Founder, HarborView LLC

    12:00 p.m. | Wrap Up and Q&A
  • 10:00 a.m.  12:30 p.m. EDT | P2

    In the second interactive webinar, participants will continue using the first use case to build a quality metrics dashboard for a product portfolio. Following this exercise, the predictive release concept will be introduced in preparation for the second use case.

    10:00 a.m. | Recap of Day 1 and Opportunity for Questions
    Arne Zilian, PhD, Manufacturing Science and Technology, Global Head Systems and Standards, Novartis

    10:30 a.m. | Case 1: Quality Metrics Dashboard

    Richard Love, Founder, HarborView LLC

    11:30 a.m. | Predictive Release
    Toni Manzano, PhD, R&D Director and Founder, Bigfinite

    12:00 p.m. | Wrap Up and Q&A
  • 10:00 a.m.  12:30 p.m. EDT | P3

    In the third interactive webinar, participants will take the second use case to build a predictive release model with the goal to improve the manufacturing processes through artificial intelligence (AI), glean knowledge from historical data, and apply knowledge in real-time. After the use case, the implementation roadmap will be analyzed to show how to start small to deliver results early and then how to extend the steps to work on more complex opportunities.

    10:00 a.m. | Recap of Day 2 and Opportunity for Questions
    Arne Zilian, PhD, Manufacturing Science and Technology, Global Head Systems and Standards, Novartis

    10:30 a.m. | Case 2: Data Assessment

    Toni Manzano, PhD, R&D Director and Founder, Bigfinite

    11:30 a.m. | Build the Roadmap
    Vasu Rangadass, PhD, President and CEO, L7 Informatics

    12:00 p.m. | Wrap Up and Q&A
  • 10:00 a.m.  12:30 p.m. EDT | P4

    In the final interactive webinar, participants will review the agile ways of working and change management under GxP and then will finish their second use case checking the quality of the AI results. The workshop will end with feedback and shared learnings.

    10:00 a.m. | Recap of Day 3 and Opportunity for Questions
    Arne Zilian, PhD, Manufacturing Science and Technology, Global Head Systems and Standards, Novartis

    10:30 a.m. | Agile Methodology and Testing Tools

    Frank Gorski, Director, Quality Assurance – Technology Audits, Merck

    11:00 a.m. | Case 2: Required Quality around AI
    Toni Manzano, PhD, R&D Director and Founder, Bigfinite

    12:00 p.m. | Feedback and Closing Remarks
    Arne Zilian, PhD, Manufacturing Science and Technology, Global Head Systems and Standards, Novartis

Highlighted Speakers

Frank L. Gorski
Frank L. Gorski
Merck & Co., Inc.
Richard N. Love
Richard N. Love
HarborView LLC
Toni Manzano
Toni Manzano
Aizon
Vasu Rangadass
Vasu Rangadass
L7 Informatics, Inc.
Arne Zilian
Arne Zilian
Novartis

Learning Objectives

Upon completion of this Workshop, you will be able to:

  • Recognize and discuss foundational data science concepts, workflows, methods, and vocabulary
  • Justify the need for multivariate statistics
  • Develop simple data science models for pharmaceutical manufacturing problems, and evaluate their quality
  • Compare and contrast the commonalities and differences between PAT and Predictive Release/ Digital Twin models
  • Give examples of the main use-cases in digital transformation, their prerequisites, and their benefits
  • Design a roadmap supporting digital transformation
  • Describe the benefits of agile ways-of-working and how they still satisfy all regulatory/GMP expectations
  • Summarize the principles supporting change control and maintenance of data science models

Who Should Attend

Departments

QA | Quality | Quality Metrics | Regulatory | Manufacturing Science and Technology | Technical Services | Operations | IT

Level of Expertise

Manager | Project Leader

Registration Fees

Register Now
Registration Type  
Member $1,095
Non-member $1,095



































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  • Molly E. O’Neill, CMP
    Vice President
    Tel: +1 (301) 656-5900 ext. 132
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