About Us

Committed to improving research and development productivity for organizations around the world through better science and technology.

Made to Cure Webinars

Transferring technology from the laboratory to the manufacturing and commercialization stage of development can significantly impact the overall value generated by a new treatment. However, as biotherapeutics organizations expand operations around the world and the distance between lab and factory increases, the need for insight into process efficiency becomes greater and more difficult.

This challenge becomes greater if Process Development, Manufacturing, and Quality initiatives are disconnected. Poor sharing of data from previous experiences can drive up costs, delay key steps in process optimization, and even create significant compliance risk. Biotherapeutics organizations can no longer afford to operate in the dark.

The Made to Cure Industry Solution Experience connects the various data streams used in Process Development, Manufacturing, and Quality initiatives, providing unprecedented context and insight into process knowledge.

Upcoming Webinars

Date Title and Speaker
Dec. 5, 2017
8:00 AM PST

Data Collaboration through the Cloud – Introducing the BIOVIA Discoverant Cloud Exchange
Karri Unruh, PMP, CSPO, Sr. Product Manager, Discoverant Product Suite, Dassault Systèmes BIOVIA

The days of "one company does it all" are long gone. Outsourcing has become common for a number of organizational roles and responsibilities. But increasing regulatory scrutiny has introduced additional challenges for biopharma companies trying to manage costs and internal resources.

Whether you are a CMO, a sponsor, or a joint manufacturing partner, you won't want to miss this introduction to the ways that the BIOVIA Discoverant Cloud Exchange can help you share data automatically and securely between companies.

 Register Now

Past Webinars

Title and Speaker

Scalable Quality Data Best Practices in Medical Device Manufacturing
Kate Lusczakoski, PhD, Director, BIOVIA Value Engineering, Fellow, BIOVIA Science Council, Dassault Systèmes BIOVIA

With the increase in complexity of medical device manufacturing, data transparency and the case for quality initiatives become increasingly difficult to streamline and scale across the enterprise. This presentation will address quality best practices to maximize automated data science workflows to reduce root-cause analysis investigation cycle time, reduce reject rates, and increase process improvement to reduce complaints and adverse events.

In this webinar, we will cover:

  • Key challenges in the medical device industry
  • Overcoming quality barriers with an end-to-end informatics solution
  • Strategies to scale and optimize automated data science workflows
  • Implementing real-time assessment of quality to reduce reject rates
  • Decreasing root-cause investigation cycle time
  • And more...

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Biologics Manufacturing - Is Your Company Ready?
Unmesh Lal, Program Manager Life Sciences & Transformational Health Frost & Sullivan
Guillaume Kerboul, Business Consultant Director Life Sciences Dassault Systèmes (3DS)

Biologics sales are growing faster than small molecule. In fact, it’s predicted that protein-based science will account for more than 25% of the product portfolio in the very near future due to superior therapeutic efficacy, premium pricing, 12 year exclusivity (i.e., US), “biosimilar” replication difficulty, and satisfying the shift towards personalized medicine. However, current best practices in pharmaceutical manufacturing are not transferable and require innovative approaches to deliver effectively. This webcast will not only reveal the current trends and challenges in Biologics manufacturing, but also new business models and how technology can drive high quality and operational efficiency.

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Why Apply Non-Linear Regression for your Stability Data?
Ron Ortiz, Director, Manufacturing Science & Technology at Pacira Pharmaceuticals
Larry R. Fiegland, Ph.D., Lead Field Application Scientist at Dassault Systèmes BIOVIA


Stability Data Evaluation Methods, and their application with BIOVIA Discoverant

When evaluating the active pharmaceutical ingredient (API) or drug product stability under various environmental conditions, classical stability studies typically show linear degradation over time.

Many biological molecules or molecules with complex structures do not follow linear trends. According to the ICH Q1E Section 2.6 (Evaluation for Stability Data), “Regression analysis is considered an appropriate approach to evaluating the stability data for a quantitative attribute and establishing a retest period or shelf life.

The nature of the relationship between an attribute and time will determine whether data should be transformed for linear regression analysis. The relationship can be represented by a linear or non-linear function on an arithmetic or logarithmic scale. In some cases, a non-linear regression can better reflect the true relationship.”

Since the guidelines allow for non-linear modelling in stability studies, when is it appropriate to use these methods? What techniques are available for these types of analysis? This talk will focus on answering these questions and will include a demonstration of non-linear analysis using BIOVIA’s Discoverant Stability Module within InVision.

Session Highlights

  • When to consider non-linear modeling with Stability Data
  • New features within BIOVIA Discoverant InVision for non-linear modeling of Stability Data
  • How to automate your stability analysis

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Impact of Recent Regulatory Trends on the Pharmaceutical and Biologics Manufacturing Process and Quality Enterprise
Justin Neway Ph.D. - Vice President, Process Production Operations, Senior Fellow, Science Council, Dassault Systèmes BIOVIA

On-going industry consolidation and the growth of contract manufacturing, coupled with an increasing focus on quality and risk by regulatory agencies, has highlighted the need to promote data-driven collaboration across the manufacturing process and quality enterprise, including outsourced operations (CMO’s). A recent industry survey highlighted the problems of multiple disparate quality systems and data sources, and lack of an effective quality culture and the lack of quality metrics, as the top challenges for shortening time to market. These represent needless barriers to improved process understanding and control of variability, because they impede the implementation of role-based process monitoring with automated alerts for review-by-exception to improve process performance and compliance with Continued Process Verification (CPV), and Manufacturing Quality Metrics (MQM) initiatives. This presentation will describe how leading companies have overcome these barriers.

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Pharmaceutical Product & Process Understanding – Critical Opportunity for Product Quality, Profitability and Risk Management
Pharmaceutical Manufacturing

What is helping and/or preventing today's companies from putting their process and quality data to work?

BIOVIA and Pharmaceutical Manufacturing partnered to conduct a survey to learn more about current product and process understanding approaches among life sciences manufacturers, and to identify opportunity for industry-wide improvement.

This presentation includes highlights of that research as well as a discussion of the successes, challenges and opportunities for product quality, profitability and risk management.

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