Unlocking Innovation: Embracing Validation 4.0 for a Digital Pharma Future

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October 2025

In this episode, Michelle Vuolo, Head of Quality at Tulip Interfaces and ISPE Good Practice Guide: Validation 4.0 co-lead, along with Guide team member, Victor de Oliveira Silva Ferreira, Project Manager at the Instituto De Tecnologia Em Imunobiológico/Fundação Oswaldo Cruz, join the podcast share their insights on how Validation 4.0 aims to leverage digital tools to transition from traditional validation methods to more dynamic, real-time processes. Explore how to utilize the principles of Quality by Design and Quality Risk Management to create dynamic, continuous validation practices, powered by digital innovations. Vuolo will present on this topic during a session titled “Transforming Pharma 4.0™: ISPE’s New Pharma 4.0™ Guides” at the upcoming 2025 ISPE Pharma 4.0™ Conference.

Get the ISPE Good Practice Guide: Validation 4.0

Guests

Michelle Vuolo

Head of Quality

Tulip Interfaces

Victor De Oliveira Silva Ferreira

Validation Division Manager

Instituto De Tecnologia Em Imunobiológico/Fundação Oswaldo Cruz
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Welcome to the ISPE podcast, Shaping the Future of Pharma,
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where ISPE supports you on your journey,
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fueling innovation, sharing insights, thought leadership,
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and empowering a global community to reimagine what's possible.
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Hello and welcome to the ISPE podcast, Shaping the Future of Pharma.
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I'm Bob Chew, your host, and today we have another episode
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where we'll be sharing the latest insights and thought leadership
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on manufacturing, technology, supply chains,
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and regulatory trends impacting the pharmaceutical industry.
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You'll hear directly from the innovators, experts,
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and professionals driving progress and shaping the future.
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Thank you again for joining us, and now let's dive into this episode.
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Our topic today is Unlocking Innovation,
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Embracing Validation 4.0 for a Digital Pharma Future.
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To share more about this topic, I would like to welcome Michelle Vuolo,
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head of quality at Tulip Interfaces and co-lead of the Validation 4.0 guide team.
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And fellow guide team member representing South America
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is Victor de Oliveira Silva Ferreira,
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Project Manager for PEQMS, Implementation of Electronic Systems
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for the Quality Management System at the Instituto de Tecnologia
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Em Imunobiológico Fundação Oswaldo Cruz.
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Michelle and Victor, welcome to the podcast.
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We're so glad to have you both with us.
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Thanks. Thanks for having us.
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I hope that's a thank you for invitation.
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Well, first, before we jump into some of the questions about the guide,
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I'm curious, how did you guys get involved in this guide?
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What's your background? What's your passion? Why this one?
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Michelle?
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Sure. Yeah, I'll go ahead and start.
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Yeah, I work at Tulip Interfaces,
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which is a technology company providing software for manufacturing environments.
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I've been here about five years, but before that,
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I spent about 25 years in life sciences and doing all things quality
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from lab to manufacturing operations quality to all the way to IT quality,
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probably my natural progression and decided to get engaged
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with the Pharma 4.0 community of practice.
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And so I wanted to help modernize the way we look at quality and validation topics
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and thought that it would best fit in the Pharma 4.0 community of practice.
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So fast forward five years and lots of PE,
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pharmaceutical engineering articles and conference speaking
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and lots of really great active members in the ISPE community.
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Later, we published the good practice.
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And Victor?
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I have to work with qualification and validation for entire of my career,
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mainly with the development new strategies to release new products in my company.
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For the last five years, I was dedicated to understand
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how technology can enhance quality and validation strategies.
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So I joined in validation 14 and have been working with Michelle for these years in GPD.
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Well, great.
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Well, let's start out with kind of the big picture.
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What exactly is validation 4.0?
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Yeah, I can start because I do recall when we first got our working group
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now called subcommittee together.
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That was the big question.
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Like, what is it?
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Because validation is such a broad topic covering so many aspects.
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And it was very clear that it wasn't computerized system validation specifically,
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because there's Gantt for that very well established group.
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But that we wanted to look at how we could modernize validation
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and look at how to become more efficient and effective with validation
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in this digital world, right?
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Like, it doesn't have to be digital, but what's happening
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or what's driving the change to look at validation was the digital transition.
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And I think bigger picture even on that is really trying to help enable
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real-time validation, again, with the usage of digital technologies,
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real-time validation, continuous validation, looking at upstream and downstream
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sort of impacts on validation of what you're trying to validate.
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So it's sort of the bigger picture.
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It's rooted in the guideposts of the IEH guidelines,
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in particular quality risk management and quality by design
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to fundamental and foundational principles to enable validation.
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Really, when you look at validation as just like going back and saying,
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what is validation?
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It's really the demonstration of control.
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And so those are two fundamental principles and foundational aspects
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that need to be understood to really do validation on any focused way.
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Yeah.
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I don't like I did that.
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I see validation for is looking to data on the quality by design lens.
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So you need to ensure that the probability data
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is available for users during the entire life cycle.
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So there is an operational approach that approach itself.
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How do you need to do validation for?
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But there is an aspect, the business aspect regarding
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how you deal with validation quality as a business strategy,
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because it was discussed in years.
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Validation quality need to be work as business strategy
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to enhance control around the product process.
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So what triggered the creation of Validation 4.0?
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Was it the Pharma 4.0 good practice guide,
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or was it other factors in industry?
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Yeah.
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So, you know, we started working together as a group.
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There's, you know, there's an ebb and flow of folks
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that come and join on these groups,
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which is understood because people are volunteering their time to do this
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and have day jobs, so to speak.
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But, you know, I think our group was doing a lot.
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Like I said, we did a lot of
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pharmaceutical engineering magazine articles.
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We are trying to develop and define case studies.
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Then we moved on.
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We did a couple of presentations at most of the ISTE annual meetings,
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both in the EU and in the US.
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Also in the Eastern communities, too,
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because the co-lead of the Validation 4.0 working group is out of Bangkok.
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So we're able to do a lot of seminars and webinars out there in India as well.
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I'm forgetting.
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It's been five years.
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But then we got involved in one of the chapters,
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the quality chapter of the Pharma 4.0 baseline guide, right?
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So there's baseline guides, which are sort of higher level overarching,
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which is what GAMP is, for example.
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I think a lot of people with ISPE are very familiar with GAMP.
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And then under that umbrella,
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there's lots of good practice guides that are on specific topics.
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Like, for example, GAMP has an MES specific good practice guide.
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So, yeah, the Pharma 4.0 baseline guide was published in December of 23, I think it was.
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That's when we started saying,
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what are good opportunities for documenting more information
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on how to execute this Pharma 4.0 approach on particular topics?
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And so Validation 4.0 is prime for that.
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We've had our approach, our guideposts, our methodology defined.
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We've had a few case studies.
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So we started writing the good practice guide.
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And, you know, with the intentions of really trying to demonstrate to the industry
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how to do this more specifically than, you know, sort of this conceptual idea.
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If I go back many decades, there was an FDA aseptic process validation guide,
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if I recall correctly, talking about media fills or aseptic process simulation.
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And it specified a minimum of three lots.
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Now, in that case, one lot was at least 5,000 units.
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So you really were looking at the aseptic contamination possibility
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spread across 15,000 instances.
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But those three lots then kind of morphed into validation, process validation.
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And we need to do three lots.
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Now, we all would agree that three lots is not statistically significant
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and does not capture potential variability in raw materials and all this stuff.
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Now, up front, you're supposed to have development work
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that covers that base.
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And then you do these three lots.
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And then you do continuous process verification.
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Tell me how this validation 4.0 changes that.
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I can go first.
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And, Victor, jump in for sure if you want to help support or add anything different.
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But, yeah, so what we're trying to get away from in this validation paradigm
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towards a new paradigm is, you know, I think traditionally the three,
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you know, the tradition, the golden three-batch run,
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like that's always sort of like people immediately think of that
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when they think of, oh, how am I going to validate?
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What we're trying to do is shift the thinking away from,
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I have to do three runs of process validation
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towards how have I demonstrated the controls in my process?
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The only way to do that really is to understand your process requirements,
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which in my opinion are around quality by design, right?
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Quality by design, basically the fundamental of quality by design
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is the more you know about your product and process,
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the more you can control it, right?
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So the idea through CPP, CQAs, these critical aspects to your process
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are defined and identified as critical, right?
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Using your quality risk management principles
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and identifying the controls around each of those individually
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and developing controls around them.
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The validation of that is not just running through it three times.
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The validation of that is really building an evidence story
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around each of those controls and how you demonstrate them, really.
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So the idea is like the culmination of all these controls,
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the evidence of these controls really starts to become your validation package,
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not whether you ran it three times.
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You could have run it several times on, I don't know,
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different parameters and different things on a particular control area
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or a particular critical area of the process.
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But you're building this evidence file on an ongoing basis.
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If you can do this during product development, right?
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These iterations of like through risk management though, right?
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A controlled process of identify a risk and put a control in place,
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determining if it's effective or not,
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and iterating on that in this sort of continuous loop.
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That's where we also want to get into this continuous validation
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or the idea that we can, at any one point in time,
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understand our state of control.
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Yeah, we, using Go, said that we are going to move
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from the stage of validation to stage of validation.
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Because in the moment that we're starting,
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Go have control about the data since the development.
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You have confidence to scale up all validation activities
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through their all study, clinical studies,
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and to reach the commercial match understanding for the entire process.
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This is what you should know about holistic control strategy,
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is have all control for all strategies need to be implemented during the life cycle.
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Okay, you mentioned quality risk management.
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There's a lot of different views on that.
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There's a lot of different practices on that.
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I think those of us who have done it would agree that in most cases,
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certainly many cases, it's subjective.
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The probability, the effectiveness of the controls,
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and the probability given those controls, et cetera.
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How is validation 4.0 dealing with those,
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that subjective nature of quality risk management?
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And can technology turn subjectivity into objectivity?
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Yeah, I can go first or Victor,
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I want to give you the opportunity to go first if you want.
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Okay, I think that we are thinking validation 4
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in quality risk management.
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We are not speaking about using spreadsheets,
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but using digital tools to enhance the entire management.
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So, this allows to have capability to integrate systems with MERS,
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LIMS, and other kind of stuff to get data since the development,
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going through this system, provide the control.
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Obviously, there is some kind of complexity in doing this,
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but in the moment that you take quality validation group and IT group,
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look into the strategy of the whole process,
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you can provide control for all decision
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and activity that will occur in your manufacturing process.
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I believe this is the main point that quality risk management
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and validation can enhance.
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The possibility to, since the first time they start a process or product,
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you're working together to think,
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okay, what can affect my process, my product?
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How the sensor could be failed during my process
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and how this information put through quality risk management digital
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and send the trigger action that you can do in real time.
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So, these are, as I see, validation for enhancing quality risk management.
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Yeah, I think just to add to that too,
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is like one of the things that we have,
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like in all the presentations I've given on this,
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like one of the things we do say is like
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we are not prescribing a particular risk methodology at all.
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Like we're not saying FMEA is great or not or whatever.
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What we do, like what I do with myself
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and what I do like about ICHQNAN is risk identification,
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risk assessment, and risk control.
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Just logically that process works really well.
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And if you're doing a three-by-three matrix or a two-by-two matrix
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or you're using detectability or frequency or likelihood,
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we don't get into that level of detail.
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But what we're saying is we need to identify and understand
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the risk associated with certain data points, right,
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associated with your process.
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And so, and the idea is, again, as you are identifying the risk,
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you're like a sterility assurance,
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you identify the control, whichever it might be,
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and then you ultimately then verify the effectiveness of that control
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right away through several iterations or several runs.
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But the idea is that as soon as you get an effective or ineffective data point,
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that gets fed back into the risk,
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identified if the risk changes,
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which not often does the risk change itself,
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but the risk control is either effective or ineffective.
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And you determine if you need to adjust your risk control.
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So again, it's not a three-by-three matrix.
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It's not subjective or objective.
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It's, you know, the basis is product quality, patient safety always.
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So in those terms is where, again,
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that continuous loop allows you to feedback
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and adjust your controls as necessary.
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But again, I just think of many examples
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of having been in risk assessments in my previous life.
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And there is not that continuous loop.
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There's not that feedback loop.
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You know, we spend hours and hours and hours in a meeting room
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trying to determine the risk level of something
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and not really following up or understanding
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whatever control we put in place.
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Was it effective?
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Was it not?
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Did it impact other things?
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Like there's no assessment.
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And that is ultimately the most important piece.
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You know, coupling what Victor said is like in the digital world,
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digital is enabling us to do that more immediate feedback loop, right?
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And to look at things independently as well
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or look at individual controls as well,
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which I think is very important.
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This is, in my opinion, has not necessarily
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been done on a big scale until now.
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So risk assessments, as we just talked about,
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there's statistics behind them.
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They're probabilistically determined, right?
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It's a high probability.
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It's a low probability.
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There's a statistic to that.
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The concept of a design space assumes
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that you have some sort of statistical understanding
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of the interrelationships between different variables.
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Some of the relationships are strong,
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i.e. a high correlation coefficient.
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Some of them are weak, a low correlation coefficient,
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but it's statistics, right?
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Now, today we have AI,
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we have digital twins, process and equipment,
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and they're statistical tools, right?
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That's all they are.
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They're very sophisticated, but they're statistical tools.
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So we have a need over here from a design space
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and a risk assessment to have statistical analysis.
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And now we've got all these really cool tools
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that are statistical tools.
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How do we bring them together?
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Yeah, yeah.
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Well, so it was easy.
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Like one of my first things was like,
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oh, we just need digital risk assessment tools.
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And yes, that can help enable.
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Like I ultimately would like to see
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that some of these digital tools for risk management
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become validation tools, right?
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But even more importantly,
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and we have a few cases,
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I think we have two case studies in the guidance
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on utilizing a digital quality by design tool.
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What was really exciting about those case studies
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is that it was demonstrating the ability
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to use a digital quality by design tool to do that, right?
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And it was providing you the correlations
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between different control groups and different things.
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And it gave you the visibility or in a visual way
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about how like when you identify
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through quality by design,
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what's critical, what's not,
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what controls you put in place,
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and you can also link in what controls
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are impacting other critical aspects as well.
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But it provides you the ability
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to do statistical analysis
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on your control effectiveness as well,
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as you can plug in the evidence data
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after you execute this thing,
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you can determine whether those controls
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are effective or not,
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they might impact other things.
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So this is where we didn't wanna start
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with digital tools, right?
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Because we wanna get the fundamental aspects down,
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but we have a whole section on the main part
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of the document that's about enablers,
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digital tools and key enablers,
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which we feel like, yeah,
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if you wanna get to the state where we're,
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I don't wanna say promising,
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but the nirvana of this would be to get to the state
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of like just running continuously
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and being able to do a snapshot validation
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at any one point in time,
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you need to do that through digital tools, right?
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And I think the most effective ones
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that I have seen to date are,
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like I said, in the examples and the case studies
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on the quality by design tool that we used
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so that you could do that.
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So you could do the statistics
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so that you could see your effectiveness
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of controls in real time.
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So currently we've got three stages
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of validation, right?
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We've got what happens in development,
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then we've got the demonstration lots,
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and then we've got the ongoing.
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How does validation 4.0 change any of that?
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Or are they still those three phases?
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And will they ever change?
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My hope is yes.
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Do you wanna go, Victor?
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Yeah, I like to think that in validation 4,
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we are discussing about this stage of validation,
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thinking all in scalability.
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When you're looking for a new product,
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quality by phase appropriate is a tool
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to determine the level of effort
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that you need to put.
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But there is some difficulty to do
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in the paper-based way.
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So in the moment that you have control
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about all points of data,
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all aspects, all risk in your process,
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you can escalate this control organically
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because you have digital tools to do that.
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So I like to say that validation 4.0
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is about validation stage.
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I always consider that my process is validated,
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considering the level of the rigor of my phase.
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If my product goes to the phase one,
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to the phase two, I have control.
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And I know exactly what level of control
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I need to put because I have digital system,
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a digital ecosystem provide me visibility.
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How my strategy is going on
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and how this strategy can evolve
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uses the point to me.
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Yeah.
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Just on that, I heard an interesting quote
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and it's not direct word for word,
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but I'm reading the words a little bit.
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But the point was somebody asked
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at a conference I was at that said,
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can we get from R&D to manufacturing,
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shift to research and design and manufacturing?
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I don't know if you appreciate
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the subtlety difference there,
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but the idea is that can we get from this state
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that's like, again, R&D is this whole thing
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and then there's this tech transfer
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and then there's this manufacturing space.
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Can we get rid of this zone in the middle
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where we're getting from research,
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really just beginning stages of quality by design
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to development and manufacturing as a stage, right?
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And this is, in my opinion,
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this is like, again, now you're speaking to Nirvana,
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but hey, we need a North Star here.
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Get to the state of just getting
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to these iterative cycles really early
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in the QBD process, right?
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So if you are starting,
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you've got the infrastructure in place
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to identify risks, identify risk controls
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and have a repository for,
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or a place to capture evidence of control effectiveness
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and loop that back,
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very early in the process,
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it can be a design or a process development tool,
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in my opinion,
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which means that you're just building evidence
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of your control file from the very beginning.
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I mean, in reality, you've got two control strategies.
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You've got process control strategy
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and contamination control strategy, right?
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For contamination control,
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that's somewhat molecule agnostic.
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It's strictly, are you filling vials
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or are you pressing pills, right?
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On the process side,
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yeah, they're different molecules.
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And once in a while, it's really different,
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but still the basic key parameters
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around pills or filling vials,
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I'm not saying they're the same,
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but there's certainly a whole science
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behind it that we understand.
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How could we not start
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from a blank sheet of paper every time?
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Yeah.
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And how does validation 4.0
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bring in the lessons from other places?
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Yeah, I'm just giving you the term
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is maybe loosely adopted from pharma 4.0,
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but like plug and produce in a way,
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but in a very different sort of scope,
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but can you plug and play
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with different controls?
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Yes, it would seem like that, right?
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You're going to have to provide evidence
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for that on all of your products anyway.
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You're just going to have to, right?
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But can you plug in a control strategy
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for like pills or like vials
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or can you do that?
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It seems like, yes, with the digital world,
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you potentially could.
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Given the same parameters of X, Y, and Z,
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can you take your control
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and control evidence and plug it
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into a different product and process?
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It seems like you could.
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Obviously, there's nuances to that, of course,
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but like, again, just the infrastructure
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would be there.
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Yeah, I like I did that,
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but edition four, as I said,
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we said about data control of data,
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the next one is too much about data.
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There's several aspects
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in the requirements on X, Y, and Z
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saying that you need to evaluate
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all data for several control strategies
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in a holistic way
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because obviously,
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all pharmaceutical companies
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has on a certain level
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a contamination control strategy.
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But what an X, Y, and Z brings is
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we need to evaluate all these data.
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So validation for under this vision
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provide the tools and the approach
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to ensure that all controls,
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to ensure a serenity,
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ensure that there is no contamination
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in your facility is under control
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and evaluate together
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several source of data.
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OK, are there any other new philosophies,
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new approaches, differences
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that you would find
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in validation 4.0 guide
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versus the past practices?
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00:27:30,000 --> 00:27:32,000
It's time for you to really show off
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the newness.
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What's cool?
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Do you want to go, Victor?
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OK, yeah.
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So I think what I started with is
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we didn't create quality by design
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nor did we create quality risk management,
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00:27:49,000 --> 00:27:52,000
which are the fundamental key purposes.
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What we've tried to do is
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take an existing frameworks.
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00:27:56,000 --> 00:27:57,000
Of course, we're not going to change
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the regulatory landscape.
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That's not our point.
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Or our objective.
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So we took the existing regulatory landscape
512
00:28:03,000 --> 00:28:05,000
and tried to articulate it
513
00:28:05,000 --> 00:28:08,000
in terms of where we are today,
514
00:28:08,000 --> 00:28:10,000
the capabilities that we have today.
515
00:28:11,000 --> 00:28:12,000
Also, I think the big piece
516
00:28:12,000 --> 00:28:13,000
is shifting the mindset away
517
00:28:13,000 --> 00:28:15,000
from methodology.
518
00:28:18,000 --> 00:28:20,000
I do, I say that because it's funny
519
00:28:20,000 --> 00:28:21,000
that one of the first questions
520
00:28:21,000 --> 00:28:22,000
that was asked was,
521
00:28:22,000 --> 00:28:23,000
what about the three runs
522
00:28:23,000 --> 00:28:25,000
of process validation, right?
523
00:28:25,000 --> 00:28:26,000
Always, because when you're talking
524
00:28:26,000 --> 00:28:27,000
to a validation person,
525
00:28:27,000 --> 00:28:29,000
that's immediately what comes to mind
526
00:28:29,000 --> 00:28:31,000
is three runs of process validation.
527
00:28:31,000 --> 00:28:32,000
And it's really starting to shift
528
00:28:32,000 --> 00:28:34,000
that mindset away from
529
00:28:34,000 --> 00:28:36,000
this sort of finite
530
00:28:39,000 --> 00:28:41,000
validation document package,
531
00:28:41,000 --> 00:28:43,000
which is, let's face it,
532
00:28:43,000 --> 00:28:44,000
it's a snapshot in time.
533
00:28:44,000 --> 00:28:46,000
It's a static thing, typically, right?
534
00:28:46,000 --> 00:28:47,000
That, oh, we might do it,
535
00:28:47,000 --> 00:28:48,000
redo it each year
536
00:28:48,000 --> 00:28:51,000
or some rendition of that.
537
00:28:51,000 --> 00:28:53,000
But what we need to start getting towards
538
00:28:53,000 --> 00:28:55,000
is a way, a methodology
539
00:28:55,000 --> 00:28:57,000
to start looking at these things
540
00:28:57,000 --> 00:29:01,000
sort of in uniquely
541
00:29:01,000 --> 00:29:02,000
and in real time.
542
00:29:02,000 --> 00:29:04,000
And the way to do that
543
00:29:04,000 --> 00:29:06,000
is through really rooting ourselves
544
00:29:06,000 --> 00:29:06,000
in the principles
545
00:29:06,000 --> 00:29:08,000
that are important to demonstrate.
546
00:29:08,000 --> 00:29:09,000
Again, I go back to
547
00:29:10,000 --> 00:29:13,000
demonstrating control, right?
548
00:29:13,000 --> 00:29:14,000
And if you ask any different
549
00:29:14,000 --> 00:29:16,000
validation experts,
550
00:29:17,000 --> 00:29:18,000
demonstrating control
551
00:29:18,000 --> 00:29:19,000
is probably not the first thing
552
00:29:19,000 --> 00:29:20,000
that they're going to say.
553
00:29:20,000 --> 00:29:22,000
Like, I've been around
554
00:29:22,000 --> 00:29:24,000
many validation people in my life
555
00:29:24,000 --> 00:29:27,000
and that word never really
556
00:29:27,000 --> 00:29:28,000
came up that often,
557
00:29:28,000 --> 00:29:29,000
which blew my mind
558
00:29:29,000 --> 00:29:30,000
when we started saying,
559
00:29:30,000 --> 00:29:31,000
what is validation?
560
00:29:31,000 --> 00:29:32,000
It really is about demonstrating control
561
00:29:33,000 --> 00:29:35,000
in the context of
562
00:29:35,000 --> 00:29:36,000
patient safety product quality
563
00:29:36,000 --> 00:29:37,000
at the end of the day.
564
00:29:38,000 --> 00:29:39,000
And so it's like really rooting ourselves
565
00:29:39,000 --> 00:29:40,000
in these principles,
566
00:29:40,000 --> 00:29:42,000
utilizing the requirements
567
00:29:42,000 --> 00:29:42,000
that are already out there.
568
00:29:42,000 --> 00:29:44,000
Again, I see HQ8, Q9,
569
00:29:45,000 --> 00:29:46,000
utilizing digital technologies
570
00:29:46,000 --> 00:29:48,000
because those are new capabilities
571
00:29:48,000 --> 00:29:48,000
we have now,
572
00:29:49,000 --> 00:29:52,000
new-ish, but new relative to,
573
00:29:52,000 --> 00:29:53,000
you know, previous approaches.
574
00:29:54,000 --> 00:29:55,000
And really getting ourselves
575
00:29:55,000 --> 00:29:58,000
into a state where we can determine
576
00:29:58,000 --> 00:30:00,000
and demonstrate validation in real time.
577
00:30:01,000 --> 00:30:02,000
This, in my opinion,
578
00:30:02,000 --> 00:30:03,000
will help us get to
579
00:30:03,000 --> 00:30:05,000
potentially quicker time to value
580
00:30:05,000 --> 00:30:06,000
on new products,
581
00:30:06,000 --> 00:30:07,000
but really also the evolutions
582
00:30:07,000 --> 00:30:08,000
of existing products,
583
00:30:09,000 --> 00:30:12,000
but also potentially taking account
584
00:30:12,000 --> 00:30:15,000
for upstream and downstream data, right?
585
00:30:15,000 --> 00:30:16,000
There's a lot of data out there
586
00:30:16,000 --> 00:30:16,000
we're not using,
587
00:30:16,000 --> 00:30:18,000
whether it's our raw material suppliers
588
00:30:18,000 --> 00:30:20,000
or it's real world evidence
589
00:30:20,000 --> 00:30:21,000
or whatever.
590
00:30:21,000 --> 00:30:22,000
Why does that not feed
591
00:30:22,000 --> 00:30:25,000
into our validation loop,
592
00:30:25,000 --> 00:30:26,000
our life cycle, right?
593
00:30:26,000 --> 00:30:28,000
Like now maybe in like
594
00:30:28,000 --> 00:30:29,000
annual product reviews,
595
00:30:29,000 --> 00:30:30,000
we might look at that stuff,
596
00:30:30,000 --> 00:30:31,000
but really as part of
597
00:30:31,000 --> 00:30:32,000
product and process
598
00:30:32,000 --> 00:30:34,000
and how that can help.
599
00:30:34,000 --> 00:30:36,000
Again, this is our North Stars
600
00:30:36,000 --> 00:30:37,000
trying to get to these places,
601
00:30:37,000 --> 00:30:38,000
but you got to get
602
00:30:38,000 --> 00:30:39,000
the infrastructure in place
603
00:30:39,000 --> 00:30:40,000
and the thinking
604
00:30:40,000 --> 00:30:41,000
and the cultural shifts.
605
00:30:43,000 --> 00:30:43,000
Victor?
606
00:30:44,000 --> 00:30:45,000
Michelle, it was perfect.
607
00:30:47,000 --> 00:30:50,000
Yeah, it was perfectly all sentence.
608
00:30:50,000 --> 00:30:52,000
So I believe this is the point
609
00:30:52,000 --> 00:30:54,000
that we shall stage,
610
00:30:55,000 --> 00:30:56,000
have control.
611
00:30:56,000 --> 00:30:58,000
There is a chapter in our guide
612
00:30:58,000 --> 00:31:00,000
that say that
613
00:31:00,000 --> 00:31:01,000
holistic control strategy,
614
00:31:01,000 --> 00:31:03,000
how you need to define
615
00:31:03,000 --> 00:31:04,000
this holistic control strategy,
616
00:31:04,000 --> 00:31:06,000
mapping the process,
617
00:31:06,000 --> 00:31:07,000
mapping the strategies,
618
00:31:07,000 --> 00:31:11,000
and how you can have this visibility.
619
00:31:11,000 --> 00:31:12,000
So this I think,
620
00:31:12,000 --> 00:31:13,000
this I believe is
621
00:31:14,000 --> 00:31:16,000
the core of the approach.
622
00:31:16,000 --> 00:31:18,000
Have control, have visibility.
623
00:31:18,000 --> 00:31:20,000
How this control is
624
00:31:20,000 --> 00:31:22,000
going through your process.
625
00:31:22,000 --> 00:31:23,000
Understanding in,
626
00:31:24,000 --> 00:31:25,000
how do you need to define
627
00:31:25,000 --> 00:31:28,000
a level of effort of activities
628
00:31:28,000 --> 00:31:31,000
to not to waste too much time.
629
00:31:31,000 --> 00:31:34,000
Because sometimes I have seen that
630
00:31:34,000 --> 00:31:37,000
there are a lot of work to do again,
631
00:31:37,000 --> 00:31:39,000
but if you have control of the data,
632
00:31:39,000 --> 00:31:41,000
mainly you can use to leverage
633
00:31:41,000 --> 00:31:42,000
previous knowledge,
634
00:31:42,000 --> 00:31:44,000
previous activities.
635
00:31:44,000 --> 00:31:46,000
So control is the fundamental
636
00:31:46,000 --> 00:31:47,000
of this approach.
637
00:31:47,000 --> 00:31:49,000
Have control of the data.
638
00:31:49,000 --> 00:31:52,000
Well, there's so many more dimensions
639
00:31:52,000 --> 00:31:53,000
that we could talk about
640
00:31:53,000 --> 00:31:55,000
for the next four hours.
641
00:31:56,000 --> 00:31:58,000
But to bring this
642
00:31:58,000 --> 00:31:59,000
to kind of a wrap up,
643
00:32:00,000 --> 00:32:03,000
I'm really excited about
644
00:32:03,000 --> 00:32:03,000
what's in this
645
00:32:04,000 --> 00:32:07,000
validation 4.0 good practice guide.
646
00:32:08,000 --> 00:32:11,000
What I see when you talk about
647
00:32:11,000 --> 00:32:12,000
quality by design
648
00:32:12,000 --> 00:32:14,000
and quality risk management
649
00:32:14,000 --> 00:32:16,000
as being the fundamentals,
650
00:32:16,000 --> 00:32:18,000
and then demonstrating
651
00:32:19,000 --> 00:32:23,000
that your controls are effective,
652
00:32:23,000 --> 00:32:23,000
that they work.
653
00:32:26,000 --> 00:32:28,000
To me, that's what
654
00:32:28,000 --> 00:32:30,000
the regulators have been
655
00:32:30,000 --> 00:32:32,000
wanting us to do all along.
656
00:32:33,000 --> 00:32:35,000
But we've kind of been
657
00:32:35,000 --> 00:32:37,000
shackled by past practices.
658
00:32:39,000 --> 00:32:42,000
And I'm hopeful that this document
659
00:32:42,000 --> 00:32:44,000
helps us move towards
660
00:32:44,000 --> 00:32:46,000
where the regulators
661
00:32:46,000 --> 00:32:47,000
really want us to be.
662
00:32:49,000 --> 00:32:50,000
And hopefully shed
663
00:32:51,000 --> 00:32:54,000
some non-value-added practices
664
00:32:54,000 --> 00:32:57,000
that we thought we had to do
665
00:32:58,000 --> 00:32:59,000
along the way.
666
00:33:00,000 --> 00:33:01,000
And really get us to where
667
00:33:01,000 --> 00:33:04,000
we're always evaluating the data
668
00:33:04,000 --> 00:33:06,000
as it comes in, in real time.
669
00:33:08,000 --> 00:33:09,000
Maybe even making adjustments
670
00:33:09,000 --> 00:33:11,000
without regulatory approval
671
00:33:12,000 --> 00:33:13,000
based on data.
672
00:33:13,000 --> 00:33:15,000
Yeah, I agree.
673
00:33:15,000 --> 00:33:16,000
I can't agree with you more.
674
00:33:16,000 --> 00:33:18,000
And you've summarized it really well.
675
00:33:19,000 --> 00:33:21,000
And just one little anecdote is,
676
00:33:21,000 --> 00:33:22,000
we did work with
677
00:33:22,000 --> 00:33:24,000
a quality innovation group
678
00:33:24,000 --> 00:33:24,000
out of the EMA.
679
00:33:24,000 --> 00:33:26,000
And that was really an exciting process
680
00:33:26,000 --> 00:33:28,000
that they were so willing
681
00:33:28,000 --> 00:33:29,000
to spend the time with us
682
00:33:29,000 --> 00:33:31,000
to review our concepts.
683
00:33:31,000 --> 00:33:33,000
And they had some great input
684
00:33:33,000 --> 00:33:34,000
and that did ultimately
685
00:33:34,000 --> 00:33:35,000
get into the guide.
686
00:33:36,000 --> 00:33:38,000
But I think they were excited.
687
00:33:38,000 --> 00:33:40,000
They were excited because
688
00:33:40,000 --> 00:33:40,000
they're like, this is what
689
00:33:40,000 --> 00:33:41,000
they've been trying to push
690
00:33:41,000 --> 00:33:43,000
for Annex 15 for so long.
691
00:33:44,000 --> 00:33:47,000
And there's wording in there,
692
00:33:47,000 --> 00:33:48,000
in the Annex 15 already,
693
00:33:48,000 --> 00:33:50,000
it states continuous validation
694
00:33:50,000 --> 00:33:51,000
and all these kinds of things.
695
00:33:51,000 --> 00:33:53,000
And it pushes the principles.
696
00:33:53,000 --> 00:33:54,000
And I think they thought
697
00:33:54,000 --> 00:33:56,000
that maybe this will help
698
00:33:56,000 --> 00:33:58,000
also push the industry
699
00:33:58,000 --> 00:34:00,000
to adopt something that, again,
700
00:34:00,000 --> 00:34:02,000
has been out there for a while now.
701
00:34:02,000 --> 00:34:04,000
Well, that brings us to the end
702
00:34:04,000 --> 00:34:07,000
of another episode of the ISPE podcast,
703
00:34:07,000 --> 00:34:09,000
Shaping the Future of Pharma.
704
00:34:09,000 --> 00:34:12,000
A very big thank you to our guests,
705
00:34:12,000 --> 00:34:13,000
Michelle and Victor,
706
00:34:13,000 --> 00:34:16,000
for sharing how Validation 4.0
707
00:34:16,000 --> 00:34:19,000
will help industry apply technology
708
00:34:19,000 --> 00:34:20,000
to improve quality,
709
00:34:21,000 --> 00:34:22,000
reduce cost of goods,
710
00:34:22,000 --> 00:34:25,000
and perhaps even speed time to licensure.
711
00:34:26,000 --> 00:34:27,000
Please be sure to subscribe
712
00:34:27,000 --> 00:34:30,000
so you don't miss future conversations
713
00:34:30,000 --> 00:34:32,000
with the innovators, experts,
714
00:34:32,000 --> 00:34:34,000
and change makers
715
00:34:34,000 --> 00:34:35,000
driving our industry forward.
716
00:34:36,000 --> 00:34:38,000
On behalf of all of us at ISPE,
717
00:34:38,000 --> 00:34:40,000
thank you for listening.
718
00:34:40,000 --> 00:34:41,000
And we'll see you next time
719
00:34:41,000 --> 00:34:44,000
as we continue to explore the ideas,
720
00:34:44,000 --> 00:34:46,000
trends, and people
721
00:34:46,000 --> 00:34:51,000
shaping the future of pharma.

Unlocking Innovation: Embracing Validation 4.0 for a Digital Pharma Future

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