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Wow! Hello everyone!

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And welcome to a new and fresh episode of Pharma Insights,

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the talk show created by Platforce to connect,

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to connect, share

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and develop new professional relations all over world.

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I'm so happy to be here and be your host today.

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My name is Juliana Kreisel and in this episode

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we will explore omnichannel.

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We are going to discover how we can leverage

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AI technologies for enhanced engagement,

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how to personalise customer experience

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and increase sales effectiveness.

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I'm not going to be alone here today

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so let me introduce

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my co host for this incredible webinar

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Mr Stefan Repin.

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He is the Head of Marketing here at Plaforce.

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Hello, Stef.

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Hey Juliana, how are you today?

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Hey I'm good.

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I'm good I'm good.

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It's actually, it's the last day before Easter

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so I'm really excited about the audience

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I guess they're all like

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waiting for this webinar and then heading home

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to their families so...

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Um yeah.

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So

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I'm gonna try to make it really exciting today so they

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they don't

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they don't sit in front of their screens for

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for nothing because I have like

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Today I have like

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guests are so amazing and they're so different that um

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I think is gonna be such an exciting chat.

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So today we're gonna,

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we're gonna talk about omnichannel and AI,

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the AI implementation and omnichannel

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that's why you have brought some

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some wonderful

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consultants here,

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and which some of them are really hands-on

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so I really hope that you guys

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I mean the audience can learn a lot from

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from them.

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Well,
you can go forward and present our wonderful speakers.

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Sure, so first I'm going to introduce Ben.

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Hi, Ben! How are you? Welcome!

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Hey, very good.

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Thank you.

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Excited to be here and excited for the Easter break too.

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haha thank you

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Well,

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you're the pharmaceutical consultant

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Do you want to talk a little bit about that?

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Yeah so yeah

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So hi everyone my name is Ben Keppie.

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I'm a consultant at 28B

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and I typically work with brand teams,

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commercial leads,

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and creative agencies to really enable and empower

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pharma field teams

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talk straight

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great customer experiences through three main areas.

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So the first being CRM, the second being CLM content,

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and then lastly

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the data that really marries the two together.

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And my background before joining 28B

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which is agency side uh

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my experience has all been in house in pharma

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so I started off in the labs

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moved through to clinical research

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and then over to oncology uh commercial

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so I held some oncology marketing roles across tactical

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execution and strategy

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and then also had some experience in sales

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as an oncology kickout manager up in Scotland.

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Thank you. Thank you.

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You

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You are quite an amazing guest.

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So second I'm going to introduce James

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Hey, James, how are you?

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I'm good. How you doing?

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I'm good. So, James,

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you are the founder of Camino.

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Can you talk us a little bit about that?

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Yes!

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We're calling Camino

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the omnichannel native medcoms agency

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that is we're a medcoms agency

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but we do it differently

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because taking our omnichannel approach

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that's twice I've said "omnichannel" now

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I'm gonna keep count more times.

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I come originally as a developer

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come from digital background

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I then ended up building digital teams within agencies

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for pharma

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then I guess kind of beginning of the pandemic

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realized the opportunity of digital

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becoming omnichannel and so go omnichannel teams

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and then I founded Camino at the start of 2023

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so we've been going about 15 months

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about nine people now and as I say

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we're focusing on that

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omnichannel approach to medcoms

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with a little bit of AI sprinkled as well

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because that's something I'm quite interested

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which I'm sure we'll also say a number of times.

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Nice!

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I like how we're

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keeping count of how many times we say "omnichannel".

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Okay so last but not least

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let me introduce our third speaker to this panel

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Mr Manuel Mitola. Hello, Manuel.

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How are you?

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Hello, Juliana.

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All good. Hello everyone

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And yeah so I quickly introduce myself

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so my name is Manuel Mitola and

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I come from Italy actually I live in uh

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in Milan and yeah at the moment

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I'm covering the role as a global

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digital innovation manager at Menarini

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but I have let's say

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years of experience also in another pharma company

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that I'm pretty sure you all know

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it's Eli Lily as a Global

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Associate Director for Neuroscience omni channel

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that was my last role and yeah

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so

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I spent many years working into the omni channel area

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especially for um for pharma.

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I am a marketeer by the ground

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I also have let's say

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a degree in communication science,

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and MBA in digital transformation

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so I mean these are the things that I

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let's say have worked a lot in the last

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8, 9 years and yeah

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I'm very glad to be here with you

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and to speak about omni channel

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and especially also about AI

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that's I mean AI is one of the topic that

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it is very close to my yard

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I mean if you go on my LinkedIn profile

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and perhaps

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you do the mistake of adding me to your contact

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basically you will see a lot of content about AI

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because what I do on my LinkedIn account

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also on my YouTube account actually is to test

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do a lot of tests on AI solution

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I mean Gemini AI, Chat GPT

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and so on I mean

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you know there are many and basically test it on

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let's say the practical usage of an omnichannel

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marketer for big corporate

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so I tested and then I shared the learning on my

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on my LinkedIn account so yeah

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glad to be here learn and from you guys

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and to interact with the audience with the

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with the questions. So thank you very much.

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Thank you. Well.

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Before we start let me thank you guys for being here.

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Thank you for being our amazing panel.

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And I also want to thank you

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attendees

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for taking the time to watching our talk show

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we are very excited to have you here

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and I want to remind everyone that

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if you have any questions

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or any comments

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or anything that you want to share with us

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you can always do it on the comment section

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below the video and we are going to bring it up here.

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So without any further delay

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let's start with this incredible panel.

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Stefan,

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do you want to lead?

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I'm leading. In fact,

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I'm very

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if you know me I'm quite hands on person

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so I'm super excited about AI and omnichannel

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you know?

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Maybe we can make it actually make a contest.

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How many times are we gonna say the word AI

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and omnichannel together? haha

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Oh we can haha

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Oh we can count at the end of this webinar

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but um

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I really like

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I'd like to start with

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what Manuel mentioned

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that he is a researcher.

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He's a researcher at his job and in life and marketers.

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So I would like to know how are you guys seeing?

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Like a practical use.

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Let's start with Manuel in fact.

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Can you please...? I like the LinkedIn,

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the amazing LinkedIn posts that you wrote about like

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what were your findings about AI in its usage and

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and omnichannel?

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Yeah I mean that's a very broad topic let's say.

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And I mean

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maybe one thing that I could

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that I could share very quickly uh

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is that uh I started

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I mean

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posting all this kind of very practical test on uh

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on LinkedIn because I saw that when there was

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let's say back to a couple of years ago

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the rise of the hype raised by ChatGPT

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and Stefan maybe

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we can also count how many time

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we are mentioning ChatGPT

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at the end of the all the webinar

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but basically I saw that there were a lot of hype

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and there was a lot of saying

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I mean "we can do everything" but from my side

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I mean, I come from the country side and to me

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let's say

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I like to be very practical and saying "it can be done..."

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"It can do everything". It doesn't mean anything to me.

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So basically I found that I mean

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everybody was saying "It can do everything"

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but then I needed to test it.

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So basically I started with um

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some practical application

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and what I was looking for was a

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for the things that AI basically is doing very well uh

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so for example dealing with the big amount of data

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dealing with um with um let's say um

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multisource multivariable sources,

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dealing with content generation,

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let's say thing that are difficult for our human brain

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so to make a practical example in marketing

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basically you are always working with the

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for example customer persona

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in pharma

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you are doing a lot of work around patient persona

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to understand let's say for example

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the needs the behavior of the

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of a patient in order to help him or her effectively

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so a practical application that I did

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if you go on my LinkedIn profile

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you will see also I spoke about Claude

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Claude is not let's say the model or AI service

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Claude is a custom GPT

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that it is a replicating the patient persona

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so statically speaking

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patient persona are static figures

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in this case what I did was

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to take the characteristics of a patient persona

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put it in the knowledge base of a custom GPT

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and make it dynamic so from one day to the next

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you were able to speak with your patient persona

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ask question

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interact with her in this case and it was a

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let's say a very good

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a very good use case that was also reported for

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I'm sure you know Isabella Bedoya

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so I mean she said I mean it was a very good GPT

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so that's something that I'm very proud of

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and basically very practical uh

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use cases then there are many others but uh

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I mean I leave the space also to James and Ben

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of course.

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I think that

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I just have to second the fact that

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if you're looking for practical uses of AIs

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Manuel's YouTube channel

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is a great host of

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a great library of that in term in practical terms

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which is fantastic

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I think we got a good good count going on there.

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So um you

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you you're talking about

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00:11:45,500 --> 00:11:50,660
about like how you like get on board with AI

279
00:11:50,660 --> 00:11:52,200
you said there was a lot of people going on

280
00:11:52,200 --> 00:11:56,200
"I can do anything". I had very similar experience

281
00:11:56,200 --> 00:11:57,500
I think like

282
00:11:57,500 --> 00:11:59,700
kind of peak excitement around

283
00:11:59,700 --> 00:12:02,930
ChatGPT was kind of February 2023

284
00:12:02,930 --> 00:12:05,800
February, March everybody was getting really excited

285
00:12:06,000 --> 00:12:08,460
literally do anything um

286
00:12:08,460 --> 00:12:10,660
and I was just starting you know at that time

287
00:12:10,660 --> 00:12:12,060
and so I was on LinkedIn

288
00:12:12,060 --> 00:12:14,900
arguing with people in the comment section of ismap

289
00:12:14,900 --> 00:12:16,800
posts and maps posts

290
00:12:17,360 --> 00:12:18,860
and just going yeah

291
00:12:18,860 --> 00:12:21,560
"No, no they can't do all of that" and

292
00:12:21,560 --> 00:12:23,930
you're getting a bit overexcited

293
00:12:23,930 --> 00:12:25,930
and there's people getting over excited one end

294
00:12:25,930 --> 00:12:28,900
and people being overly worried of the other end

295
00:12:28,900 --> 00:12:30,300
just like "Oh my God"

296
00:12:30,300 --> 00:12:31,930
"AI is gonna replace my job"

297
00:12:31,930 --> 00:12:33,260
steal all my data

298
00:12:33,460 --> 00:12:35,760
all before I've even woken up in the morning

299
00:12:35,760 --> 00:12:37,800
I was like "Watch, chill, calm down"

300
00:12:38,300 --> 00:12:40,460
so kind of arguing with both of those points

301
00:12:40,600 --> 00:12:43,960
and the way we approach kind of using AI and project

302
00:12:43,960 --> 00:12:45,460
which is work quite well for us

303
00:12:45,660 --> 00:12:48,360
is to look at it from three points of view

304
00:12:48,360 --> 00:12:51,600
which are: Are you adding efficiency?

305
00:12:51,660 --> 00:12:54,500
like an efficiency is great um

306
00:12:54,500 --> 00:12:58,530
I saw somebody posted a study today saying that 40%

307
00:12:58,530 --> 00:12:59,400
I can't release that number

308
00:12:59,400 --> 00:12:59,900
I think some like

309
00:12:59,900 --> 00:13:01,300
40% of pharma

310
00:13:01,300 --> 00:13:04,000
reckon that they're gonna save money in 2024

311
00:13:04,000 --> 00:13:05,100
from using AI.

312
00:13:05,760 --> 00:13:06,600
Okay, great.

313
00:13:06,600 --> 00:13:08,600
That's like the doom monger saying

314
00:13:08,600 --> 00:13:09,530
they might lose their job

315
00:13:09,530 --> 00:13:11,300
have a point if that's all we're looking at.

316
00:13:11,300 --> 00:13:13,200
So the efficiency is one thing.

317
00:13:13,200 --> 00:13:14,260
That's not the only thing.

318
00:13:15,000 --> 00:13:16,830
The other thing AI has to bring is value

319
00:13:17,060 --> 00:13:18,800
so can it do something better?

320
00:13:18,800 --> 00:13:21,300
so like one of the use cases we've had is looking at a

321
00:13:21,730 --> 00:13:22,530
um

322
00:13:22,930 --> 00:13:24,860
looking a bunch of clinical trials

323
00:13:24,860 --> 00:13:27,700
and having a much wider view than one medical

324
00:13:27,700 --> 00:13:30,400
you can normally look at so while looking 100 papers

325
00:13:30,400 --> 00:13:31,930
we're looking at 12000 papers

326
00:13:31,930 --> 00:13:34,300
so that's the added value of using AI.

327
00:13:34,300 --> 00:13:35,200
So you got efficiency,

328
00:13:35,200 --> 00:13:37,900
you got value, and the third thing is innovation, right?

329
00:13:37,900 --> 00:13:39,200
Some people wanna use AI

330
00:13:39,200 --> 00:13:41,100
cause it's exciting and different and

331
00:13:41,400 --> 00:13:44,530
and you're you're staying ahead of the competition

332
00:13:44,530 --> 00:13:47,930
that is valuable but if you do all those three things

333
00:13:47,930 --> 00:13:49,330
you're doing AI really well

334
00:13:49,330 --> 00:13:51,460
if you're just looking at efficiency

335
00:13:51,700 --> 00:13:53,260
or you're just looking innovation

336
00:13:53,260 --> 00:13:54,660
then not really.

337
00:13:55,200 --> 00:13:56,030
Do you agree?

338
00:13:58,300 --> 00:13:59,560
Yeah I mean

339
00:13:59,560 --> 00:14:00,660
from my side James

340
00:14:00,660 --> 00:14:02,760
I I fully agree with the

341
00:14:03,500 --> 00:14:06,100
with all the 3 pillars that you mentioned

342
00:14:06,100 --> 00:14:07,060
absolutely

343
00:14:08,360 --> 00:14:09,230
I also

344
00:14:11,100 --> 00:14:13,130
you're probably hoping for some bite back there James

345
00:14:13,130 --> 00:14:14,860
by the sounds of it very provocative

346
00:14:15,130 --> 00:14:17,060
no I think it was interesting

347
00:14:17,060 --> 00:14:18,760
what you picked up on there about the

348
00:14:18,760 --> 00:14:22,500
almost the fear of AI that we kind of see in the

349
00:14:22,500 --> 00:14:24,500
kind of the taking of people's jobs

350
00:14:24,500 --> 00:14:26,600
or replacing of people's jobs

351
00:14:26,600 --> 00:14:27,900
and you you hear that a lot

352
00:14:27,900 --> 00:14:30,400
but when you look at the kind of AI

353
00:14:30,400 --> 00:14:33,060
technologies that are being commercialised

354
00:14:33,060 --> 00:14:35,930
a lot of them are very much positioned as supporters

355
00:14:35,930 --> 00:14:38,500
to roles so like taking the field teams

356
00:14:38,500 --> 00:14:39,660
for example you know

357
00:14:39,660 --> 00:14:43,000
there's a kind of rise in potential

358
00:14:43,000 --> 00:14:46,160
virtual sales assistants that are coming to the market

359
00:14:46,160 --> 00:14:50,760
like Co Pilot from Actana or my idea from True Blue

360
00:14:50,860 --> 00:14:54,660
and that they're all solely positioned to really enable

361
00:14:54,660 --> 00:14:55,730
um you know

362
00:14:55,730 --> 00:15:00,500
and empower people just to be more effective ultimately

363
00:15:00,500 --> 00:15:01,660
um yeah

364
00:15:01,800 --> 00:15:05,060
do do their job better in a smarter way

365
00:15:05,060 --> 00:15:06,760
rather than having to

366
00:15:06,800 --> 00:15:09,330
having to go around the hard way and um

367
00:15:09,330 --> 00:15:12,400
do a lot of stuff that's not particularly of

368
00:15:12,400 --> 00:15:14,060
of value spending time doing

369
00:15:14,060 --> 00:15:15,800
so it's actually interesting

370
00:15:15,800 --> 00:15:19,900
how much the mindset is a really important piece

371
00:15:19,900 --> 00:15:22,860
when looking at the adoption of AI technologies

372
00:15:22,900 --> 00:15:25,860
and how it just relays how important it is

373
00:15:25,860 --> 00:15:28,400
that when you are adopting these new technologies

374
00:15:28,460 --> 00:15:31,060
how important that kind of mindset aspect is

375
00:15:31,060 --> 00:15:33,700
as well as the skill set terms of up

376
00:15:33,700 --> 00:15:35,300
ensuring you're giving the space to upskill

377
00:15:35,300 --> 00:15:38,660
on how to use the AI tools uh best as well.

378
00:15:39,960 --> 00:15:41,860
And if I may guys I mean

379
00:15:41,860 --> 00:15:45,300
James
you raised and Ben you raised also a very valid point

380
00:15:45,330 --> 00:15:47,700
let's say that it is related to the

381
00:15:48,400 --> 00:15:49,960
to the difference between

382
00:15:49,960 --> 00:15:51,360
in terms of perception

383
00:15:51,360 --> 00:15:55,760
between seeing the AI as a tool or seen it

384
00:15:56,600 --> 00:16:00,330
seeing it as an ally capable of everything and

385
00:16:00,330 --> 00:16:02,430
and basically I mean

386
00:16:02,600 --> 00:16:06,160
as you said James I started seeing

387
00:16:07,160 --> 00:16:09,660
the perception of seeing it capable of everything

388
00:16:09,660 --> 00:16:10,800
including I mean

389
00:16:10,800 --> 00:16:13,500
if you look at the newspaper killing the humanity

390
00:16:14,000 --> 00:16:15,860
but personally and I mean

391
00:16:15,860 --> 00:16:18,330
that's a question for you guys if you agree or not

392
00:16:18,330 --> 00:16:19,530
I mean personally

393
00:16:19,530 --> 00:16:24,500
I see the AI as a tool and I see it as something that

394
00:16:24,500 --> 00:16:27,800
it is as useful as the person

395
00:16:27,800 --> 00:16:30,400
that it is behind the tool or

396
00:16:30,400 --> 00:16:33,600
or I would say on top of the tool using it

397
00:16:34,100 --> 00:16:37,200
and without the person at this point of time

398
00:16:37,200 --> 00:16:41,200
where we are in terms of the AI evolution and so on

399
00:16:41,660 --> 00:16:44,700
I see it as a tool to be honest

400
00:16:44,700 --> 00:16:45,960
and I don't know if you

401
00:16:45,960 --> 00:16:48,930
if you agree with that or you see it as something that

402
00:16:48,930 --> 00:16:50,200
something different.

403
00:16:50,760 --> 00:16:53,000
I personally I do

404
00:16:53,000 --> 00:16:57,330
I do agree or rather did up until a few days ago uh

405
00:16:57,330 --> 00:16:59,330
when I saw the advancements that be

406
00:16:59,330 --> 00:17:02,800
made in video generation from uh

407
00:17:02,800 --> 00:17:04,600
AI terms and the fact that

408
00:17:04,600 --> 00:17:06,460
I think that there was a video release

409
00:17:06,460 --> 00:17:07,930
showing the latest sort of

410
00:17:07,930 --> 00:17:08,800
AI model

411
00:17:08,800 --> 00:17:12,500
where they essentially made a short film from a text

412
00:17:12,600 --> 00:17:14,700
to text a video piece

413
00:17:14,700 --> 00:17:17,860
and that then got me uh excited

414
00:17:17,860 --> 00:17:21,330
but also um start to move along

415
00:17:21,330 --> 00:17:24,760
that worried scale about how quick and how advanced AI

416
00:17:24,760 --> 00:17:27,630
technologies are moving forward um

417
00:17:27,800 --> 00:17:30,500
so I don't know I'm not as confident anymore

418
00:17:30,500 --> 00:17:32,360
that it's gonna stay that way forever

419
00:17:32,360 --> 00:17:35,160
just because of the scale and speed uh

420
00:17:35,160 --> 00:17:36,660
the AI is moving along

421
00:17:36,660 --> 00:17:38,130
but in

422
00:17:38,130 --> 00:17:41,200
in most part I do agree there is a supporting tool

423
00:17:41,200 --> 00:17:42,960
especially in our industry uh

424
00:17:42,960 --> 00:17:44,900
as well as I said a lot of the tools are

425
00:17:44,900 --> 00:17:45,960
they're being commercialised

426
00:17:45,960 --> 00:17:47,330
as supporting technologies

427
00:17:47,330 --> 00:17:50,230
which is uh I suppose reassuring for the industry.

428
00:17:53,500 --> 00:17:54,160
Guys, sorry.

429
00:17:54,160 --> 00:17:55,300
Sorry to interrupt you.

430
00:17:55,300 --> 00:17:58,130
I want to answer a few questions from our audience

431
00:17:58,130 --> 00:18:00,330
because there's a question about AI

432
00:18:00,330 --> 00:18:02,300
sure it's from Honey Hassan

433
00:18:02,300 --> 00:18:03,760
We're doing this for the audience

434
00:18:03,760 --> 00:18:04,630
so like

435
00:18:05,560 --> 00:18:08,060
so I'm going to quote I think that AI has facilities

436
00:18:08,060 --> 00:18:11,100
different aspects of the marketeer job scheme

437
00:18:11,100 --> 00:18:12,860
of saving time consumed in searching

438
00:18:12,860 --> 00:18:14,360
validation of research

439
00:18:14,660 --> 00:18:16,560
used in preparing the marketing plans

440
00:18:16,560 --> 00:18:18,900
and different areas of interest for any marketeer

441
00:18:18,900 --> 00:18:21,260
but how, here's the question,

442
00:18:21,360 --> 00:18:21,960
but how AI

443
00:18:21,960 --> 00:18:23,700
would reflect on the sales team currently

444
00:18:23,700 --> 00:18:25,560
and in the future?

445
00:18:25,560 --> 00:18:26,730
Let's take the question

446
00:18:26,730 --> 00:18:28,100
Who wants to take it first?

447
00:18:30,930 --> 00:18:32,760
I didn't get the question alright sorry

448
00:18:34,100 --> 00:18:36,900
How would AI reflect on the sales team currently and

449
00:18:36,900 --> 00:18:40,100
in the future? Would they cut the sales team?

450
00:18:40,130 --> 00:18:42,460
Would sales team use it together with AI?

451
00:18:42,530 --> 00:18:45,100
um maybe it wouldn't get

452
00:18:45,330 --> 00:18:46,860
it wouldn't get any adoption

453
00:18:46,930 --> 00:18:47,960
what do you think?

454
00:18:48,560 --> 00:18:51,600
I think to the point we're just talking about that

455
00:18:51,600 --> 00:18:54,160
it's a tool which assists people right

456
00:18:54,160 --> 00:18:58,530
so the sales team like any other team can or

457
00:18:58,530 --> 00:18:59,200
or or

458
00:18:59,200 --> 00:19:00,160
can or may

459
00:19:00,160 --> 00:19:03,660
or may not use AI in their job for various things

460
00:19:03,730 --> 00:19:06,660
and once it's integrated it's not very far away

461
00:19:06,660 --> 00:19:08,300
it's integrated into everybody's outlook

462
00:19:08,300 --> 00:19:10,060
for helping you rewrite emails

463
00:19:10,260 --> 00:19:10,760
you know that's the

464
00:19:10,760 --> 00:19:13,530
then it basically becomes as ubiquitous spell check

465
00:19:13,530 --> 00:19:16,530
and nobody thinks while I'm using AI no

466
00:19:16,530 --> 00:19:19,500
I'm just having the thing help me write my emails

467
00:19:19,500 --> 00:19:22,260
um and then you just extrapolate that out into

468
00:19:22,260 --> 00:19:25,260
all those other to Ben's point a minute ago about um

469
00:19:25,530 --> 00:19:28,260
kind of just assisting you in your day today

470
00:19:28,260 --> 00:19:30,530
just extract later and all the other jobs you do

471
00:19:30,530 --> 00:19:33,730
and the boring bit so the help me rewrite that

472
00:19:33,730 --> 00:19:36,800
just throw it together a slide deck all of that becomes

473
00:19:38,000 --> 00:19:40,500
part of a sales team's role, right?

474
00:19:40,500 --> 00:19:42,100
it becomes part of their day today

475
00:19:42,100 --> 00:19:44,500
so I'm I'm not actually answering the question

476
00:19:44,500 --> 00:19:47,460
um specifically for sales teams

477
00:19:47,760 --> 00:19:49,560
I don't know if there's any specific differences

478
00:19:49,560 --> 00:19:51,200
but maybe Ben disagrees

479
00:19:51,730 --> 00:19:53,200
um I think the

480
00:19:53,200 --> 00:19:54,660
the two main things will be like

481
00:19:54,660 --> 00:19:57,800
speed and simplification. I remember when I was in sales

482
00:19:57,800 --> 00:19:59,160
I'd have you know

483
00:19:59,200 --> 00:20:01,530
so many different dashboards to access

484
00:20:01,530 --> 00:20:03,500
all of the different forms of information

485
00:20:03,500 --> 00:20:04,360
that I'd need

486
00:20:04,360 --> 00:20:07,160
in order to truly understand my territory

487
00:20:07,330 --> 00:20:11,960
and then also truly be able to efficiently prequel plan

488
00:20:12,130 --> 00:20:14,100
um so I think that

489
00:20:14,100 --> 00:20:17,060
you know
with the likes of virtual sales assistants coming in

490
00:20:17,060 --> 00:20:18,760
being able to as Manuel said

491
00:20:19,000 --> 00:20:22,500
take loads of different source of information

492
00:20:23,160 --> 00:20:27,530
put some analysis over that and draw insights from it

493
00:20:27,530 --> 00:20:28,960
I think that there's yeah

494
00:20:28,960 --> 00:20:31,600
a lot of potential to save um

495
00:20:31,600 --> 00:20:33,460
field teams specifically

496
00:20:33,560 --> 00:20:36,060
time in some of those admin tasks

497
00:20:36,060 --> 00:20:38,000
to actually get those insights

498
00:20:38,000 --> 00:20:40,160
that then drive um

499
00:20:40,860 --> 00:20:43,100
drive change on on territory

500
00:20:43,860 --> 00:20:46,930
yeah and if I can add uh

501
00:20:46,930 --> 00:20:49,600
let's say when it comes to pharmaceutical science

502
00:20:49,600 --> 00:20:53,100
we are speaking about a very peculiar kind of

503
00:20:53,160 --> 00:20:55,700
kind of sales with very specific

504
00:20:57,300 --> 00:21:00,730
sales like cycle flows and so on

505
00:21:00,730 --> 00:21:04,100
so if I think about omnichannel in pharma

506
00:21:04,460 --> 00:21:07,230
let's say it has been always

507
00:21:08,300 --> 00:21:09,730
the biggest challenge

508
00:21:09,730 --> 00:21:13,800
was always to somehow integrate into all the digital

509
00:21:13,800 --> 00:21:15,900
marketing channels

510
00:21:15,960 --> 00:21:19,560
the customer facing teams and with AI

511
00:21:19,560 --> 00:21:21,760
I think I mean

512
00:21:21,760 --> 00:21:24,500
finally we could get close to that

513
00:21:24,500 --> 00:21:27,160
or at least achieve this thing.

514
00:21:27,160 --> 00:21:28,160
So I think

515
00:21:28,160 --> 00:21:30,900
the biggest change will be the integration

516
00:21:31,400 --> 00:21:33,960
and it will be an integration

517
00:21:33,960 --> 00:21:37,630
where the sales rep will be able to know

518
00:21:37,730 --> 00:21:40,860
let's say what it is what the company is doing

519
00:21:40,960 --> 00:21:43,000
in terms of the other channel

520
00:21:43,000 --> 00:21:45,960
I'm thinking about Massimen for example

521
00:21:45,960 --> 00:21:49,260
or I'm thinking about activity on third parties

522
00:21:49,260 --> 00:21:51,660
of authority let's say Manscape

523
00:21:51,660 --> 00:21:55,860
Unibad is and and so on and in pharma

524
00:21:56,130 --> 00:21:58,900
when it comes to sales there is also I mean

525
00:21:58,900 --> 00:22:02,260
of course the production of email,

526
00:22:02,260 --> 00:22:04,900
the production of content that sales reps present

527
00:22:04,900 --> 00:22:06,260
into the physician

528
00:22:07,000 --> 00:22:08,360
but there was always

529
00:22:08,500 --> 00:22:11,330
always something around the so called

530
00:22:11,330 --> 00:22:13,060
let's say next best action

531
00:22:13,300 --> 00:22:16,800
that it was something that it was recommending

532
00:22:16,930 --> 00:22:19,060
the sales rep to do an action

533
00:22:19,060 --> 00:22:21,230
after a certain event

534
00:22:21,760 --> 00:22:26,900
I think AI having the possibility to take multiple uh

535
00:22:26,900 --> 00:22:29,400
and several different sources uh

536
00:22:29,400 --> 00:22:30,730
into account

537
00:22:30,730 --> 00:22:33,530
will be finally able to give the integration

538
00:22:33,530 --> 00:22:36,700
and the recommendation needed for the sales rep

539
00:22:36,700 --> 00:22:38,430
to take the right

540
00:22:39,500 --> 00:22:40,330
the right action

541
00:22:40,330 --> 00:22:44,100
so definitely I think it would be a game changer

542
00:22:44,860 --> 00:22:47,760
but I mean the key step to arrive there

543
00:22:47,760 --> 00:22:52,360
it would be also training and sales force on boarding

544
00:22:52,360 --> 00:22:54,060
because without I mean

545
00:22:54,060 --> 00:22:57,830
training people to effectively use this tool

546
00:22:57,900 --> 00:22:59,360
they will simply reject it

547
00:22:59,360 --> 00:23:00,800
and I can tell you by experience

548
00:23:00,800 --> 00:23:06,130
I mean usually sales raps I mean are very varied

549
00:23:06,130 --> 00:23:09,660
let's say a very diverse group of people

550
00:23:09,660 --> 00:23:12,500
so you have people that are embracing the change

551
00:23:12,500 --> 00:23:14,560
embracing the innovation

552
00:23:14,560 --> 00:23:18,160
but you have also a lot of people rejecting it at all

553
00:23:18,760 --> 00:23:22,860
scared I remember years ago with the digital

554
00:23:22,860 --> 00:23:25,560
I don't want a digital I don't want even an iPad

555
00:23:25,660 --> 00:23:30,360
so I mean that's something that truly interesting

556
00:23:30,360 --> 00:23:33,760
but it is crucial to give them all the instrument

557
00:23:33,760 --> 00:23:36,300
to understand the potential of AI

558
00:23:36,300 --> 00:23:38,560
and using it practically.

559
00:23:40,880 --> 00:23:43,200
hmm I think as well

560
00:23:44,300 --> 00:23:45,200
Go ahead, Ben.

561
00:23:45,200 --> 00:23:46,560
I want to make a short comment

562
00:23:46,560 --> 00:23:48,300
really short comment that um

563
00:23:48,400 --> 00:23:49,530
in marketing

564
00:23:49,530 --> 00:23:51,230
we have um

565
00:23:52,460 --> 00:23:52,860
basically

566
00:23:52,860 --> 00:23:54,800
when the customer goes through a certain funnel

567
00:23:54,800 --> 00:23:56,460
we give it a certain points

568
00:23:56,460 --> 00:23:59,200
certain points of like how ready is that customer

569
00:23:59,200 --> 00:24:01,800
what topics are going to um

570
00:24:01,800 --> 00:24:03,560
to be interesting for that customer

571
00:24:03,560 --> 00:24:04,400
and I think

572
00:24:04,500 --> 00:24:07,400
the better quality data we have on customers right

573
00:24:07,400 --> 00:24:11,100
so the AI is as good as the data that we gather, right?

574
00:24:11,100 --> 00:24:13,160
so I think it's quite important

575
00:24:13,160 --> 00:24:14,930
in the omnichannel strategy

576
00:24:14,930 --> 00:24:17,260
because when we have more data on our customers

577
00:24:17,400 --> 00:24:17,960
and AI

578
00:24:17,960 --> 00:24:20,860
can predict the better next action for the sales rep

579
00:24:20,860 --> 00:24:21,560
Yeah, right.

580
00:24:21,560 --> 00:24:23,130
And I know that you are in data

581
00:24:23,130 --> 00:24:25,130
so you're a scientist in one way

582
00:24:25,130 --> 00:24:27,930
so you and James know that even better than that though

583
00:24:27,930 --> 00:24:29,230
that the best

584
00:24:29,330 --> 00:24:31,360
the more information we have our customers

585
00:24:31,460 --> 00:24:34,200
the more exact the next step is gonna be

586
00:24:34,200 --> 00:24:37,500
so thank you for the grain of salt

587
00:24:37,760 --> 00:24:40,660
I think but AI isn't gonna solve the problem of

588
00:24:40,660 --> 00:24:43,630
we've already got loads of data, right?

589
00:24:43,900 --> 00:24:45,730
Already you generate

590
00:24:45,730 --> 00:24:48,160
your website generates bucket loads of data

591
00:24:48,160 --> 00:24:49,900
you send a bunch of emails to get a load of data

592
00:24:49,900 --> 00:24:52,000
your field reps have them ipads

593
00:24:52,000 --> 00:24:53,260
and they come back with loads of data

594
00:24:53,260 --> 00:24:54,860
and nobody does anything with it

595
00:24:54,860 --> 00:24:57,400
because nobody really knows why we collected that

596
00:24:57,400 --> 00:24:58,260
or what and then

597
00:24:58,260 --> 00:25:01,330
or an AI isn't gonna solve that answer and call

598
00:25:01,330 --> 00:25:02,160
that means that

599
00:25:02,160 --> 00:25:04,060
and then therefore there's something else

600
00:25:04,160 --> 00:25:05,660
and because you're not asking the question

601
00:25:05,660 --> 00:25:08,700
you don't know what question to ask I think the

602
00:25:08,700 --> 00:25:10,760
the challenge that needs to be solved first

603
00:25:10,760 --> 00:25:13,600
in terms of like omnichannel metrics is

604
00:25:14,100 --> 00:25:16,130
why are we doing this what we're trying to do

605
00:25:16,130 --> 00:25:16,960
what's the

606
00:25:17,060 --> 00:25:19,930
we've got a framework where we start with the outcome

607
00:25:19,930 --> 00:25:21,500
and we sit down with teams and go

608
00:25:21,560 --> 00:25:22,800
what are we trying to do okay

609
00:25:22,800 --> 00:25:25,200
that's the outcome was the KPIs

610
00:25:25,500 --> 00:25:28,900
what's the tactics and therefore what's the metrics

611
00:25:28,900 --> 00:25:31,000
and then rather than having a sea of data

612
00:25:31,000 --> 00:25:32,800
we have a few data points

613
00:25:32,800 --> 00:25:35,060
that point towards an outcome now yeah

614
00:25:35,060 --> 00:25:37,130
in terms of like uh getting those like

615
00:25:37,130 --> 00:25:41,000
like if those data points are in field notes

616
00:25:41,000 --> 00:25:43,860
then an LM is great for extracting them or

617
00:25:43,860 --> 00:25:45,660
you know sentiment analysis yeah

618
00:25:45,660 --> 00:25:46,460
it's great for that

619
00:25:46,460 --> 00:25:48,700
but I think it's not gonna solve the biggest challenge

620
00:25:48,700 --> 00:25:49,200
of like

621
00:25:49,200 --> 00:25:52,600
just choosing what it is you're doing and why hmm

622
00:25:52,930 --> 00:25:54,860
wholeheartedly agree with that James

623
00:25:54,900 --> 00:25:56,330
it like that what what

624
00:25:56,330 --> 00:25:58,460
what you just summed up there is exactly what we do

625
00:25:58,460 --> 00:25:59,500
when we um

626
00:25:59,500 --> 00:26:03,100
when I consult on ICVAs or or e details

627
00:26:03,100 --> 00:26:05,460
isels whatever name you want to choose um

628
00:26:05,460 --> 00:26:06,660
but really thinking about

629
00:26:06,660 --> 00:26:09,530
what is it that you're wanting from that field team

630
00:26:09,530 --> 00:26:09,860
engagement

631
00:26:09,860 --> 00:26:12,360
what are those rich questions that you're asking

632
00:26:12,360 --> 00:26:13,460
uh the HCP

633
00:26:13,760 --> 00:26:17,130
and how can you have content with you to support

634
00:26:17,130 --> 00:26:20,600
asking those questions and also extract that data

635
00:26:20,660 --> 00:26:21,760
uh as well

636
00:26:21,760 --> 00:26:24,300
because ultimately I think we may or

637
00:26:24,300 --> 00:26:25,700
or may not uh agree

638
00:26:25,700 --> 00:26:28,530
that the most rich customer insight comes from that

639
00:26:28,530 --> 00:26:29,560
one to one interaction

640
00:26:29,560 --> 00:26:31,060
or one to many interaction

641
00:26:31,060 --> 00:26:33,130
that field teams have with Hcps

642
00:26:33,130 --> 00:26:33,660
cause you know

643
00:26:33,660 --> 00:26:34,660
the Hcps that

644
00:26:34,660 --> 00:26:36,730
they're not gonna give up their clinical pathway

645
00:26:36,730 --> 00:26:40,760
to a bannerad or give up a barrier to prescribing to a

646
00:26:40,900 --> 00:26:43,460
uh automated email campaign

647
00:26:43,460 --> 00:26:46,160
regardless of how much AI you shove into it

648
00:26:46,160 --> 00:26:47,830
you're gonna get it from the field team

649
00:26:47,860 --> 00:26:51,730
uh and their conversations with HCP's um

650
00:26:51,730 --> 00:26:55,600
person to person so I think that there's

651
00:26:55,700 --> 00:26:57,000
and I'm quite passionate about this

652
00:26:57,000 --> 00:26:57,960
I think that in our industry

653
00:26:57,960 --> 00:26:58,560
there's still a lot

654
00:26:58,560 --> 00:27:02,200
of work to do on the foundations of HCP engagement

655
00:27:02,330 --> 00:27:04,130
uh across the whole mindset

656
00:27:04,130 --> 00:27:06,660
skillset and toolset spectrum

657
00:27:06,860 --> 00:27:08,030
but really

658
00:27:08,160 --> 00:27:12,130
in mastering what it is that we're using our CRMs for

659
00:27:12,130 --> 00:27:14,660
how can we use our uh CRMs

660
00:27:14,730 --> 00:27:17,630
uh how can we use our CRMs and how can we get that

661
00:27:17,800 --> 00:27:18,960
those nice data points

662
00:27:18,960 --> 00:27:23,630
that can then potentially be used later on by those um

663
00:27:23,660 --> 00:27:25,860
by and then start talking about AI later on

664
00:27:26,530 --> 00:27:27,800
and I'll be cheaper to implement

665
00:27:27,800 --> 00:27:29,530
and probably have a greater commercial impact

666
00:27:29,530 --> 00:27:30,430
quite frankly

667
00:27:31,860 --> 00:27:33,300
and maybe I mean

668
00:27:33,300 --> 00:27:35,300
I have a couple of comments for you guys

669
00:27:35,300 --> 00:27:38,900
for Ben and James so I start with Ben

670
00:27:38,900 --> 00:27:41,900
I mean I fully agree with you that I mean

671
00:27:41,900 --> 00:27:44,660
the face to face interaction is super important

672
00:27:44,960 --> 00:27:47,730
and the insights that you get from there

673
00:27:47,730 --> 00:27:48,530
I mean

674
00:27:49,300 --> 00:27:52,600
priceless the problem with that is that

675
00:27:53,200 --> 00:27:54,330
I mean first of all

676
00:27:54,330 --> 00:27:56,260
you need to have um

677
00:27:56,330 --> 00:28:00,530
big enough salesports to reach out to all your customer

678
00:28:00,530 --> 00:28:02,330
or at least on your target list

679
00:28:02,330 --> 00:28:05,130
and if you have have a very small uh

680
00:28:05,130 --> 00:28:08,960
salesports compared to the universe of the physician

681
00:28:08,960 --> 00:28:10,600
then it will become very

682
00:28:10,600 --> 00:28:15,060
very difficult to get this kind of um information

683
00:28:15,060 --> 00:28:16,800
and it is here where

684
00:28:16,800 --> 00:28:19,230
let's say the only channel can make the difference

685
00:28:19,360 --> 00:28:21,900
especially because the access to physician

686
00:28:22,100 --> 00:28:27,300
especially in UK also is a producing ear after ear

687
00:28:27,300 --> 00:28:27,730
I mean

688
00:28:27,730 --> 00:28:30,900
I see data where the access to physician is decreasing

689
00:28:30,900 --> 00:28:31,800
a lot

690
00:28:31,900 --> 00:28:36,060
and so only channel can somehow help fill in this gap

691
00:28:36,800 --> 00:28:38,960
and that's one thing the other thing James

692
00:28:39,560 --> 00:28:40,730
I I again

693
00:28:40,730 --> 00:28:42,000
I agree with you

694
00:28:42,000 --> 00:28:46,100
AI is not a kind of financial solve in all the issues

695
00:28:46,100 --> 00:28:47,830
especially when it comes to data

696
00:28:48,760 --> 00:28:50,700
but I think historically speaking

697
00:28:50,700 --> 00:28:54,430
I mean pharma companies as always have a lot of data

698
00:28:54,900 --> 00:28:58,160
especially vertical data about also um

699
00:28:58,300 --> 00:28:59,660
the physician I mean

700
00:28:59,660 --> 00:29:03,360
there is a lot of database is about the

701
00:29:03,360 --> 00:29:04,760
customer that say

702
00:29:05,700 --> 00:29:10,860
I think the issue was to get inside out of this data

703
00:29:10,860 --> 00:29:14,700
because people were simply overwhelmed by all this data

704
00:29:14,800 --> 00:29:17,530
and maybe with AI asking for example

705
00:29:17,530 --> 00:29:20,860
to a chatport neutral language question

706
00:29:20,860 --> 00:29:22,600
asking about inside

707
00:29:22,700 --> 00:29:27,400
maybe it could be a tool again to help mitigate in this

708
00:29:27,600 --> 00:29:29,100
uh this

709
00:29:29,100 --> 00:29:31,660
let's say abundance of data

710
00:29:31,660 --> 00:29:34,600
with a missed opportunity of the data

711
00:29:34,600 --> 00:29:36,700
so I think data is the oil

712
00:29:36,700 --> 00:29:41,760
I think we are refining it and AI can help there

713
00:29:41,760 --> 00:29:44,900
but it's not a 100% solution fully with you

714
00:29:46,000 --> 00:29:48,400
um I'm going to add a commercial pass

715
00:29:48,400 --> 00:29:49,100
nah I'm kidding

716
00:29:49,100 --> 00:29:52,760
I'm going to add a pass here to ask a question

717
00:29:53,330 --> 00:29:57,660
um regarded that one of our beautiful attendees ask

718
00:29:57,660 --> 00:29:59,960
is my question to the panel

719
00:30:00,000 --> 00:30:03,530
Pharma and GMP follows strict regulations

720
00:30:03,530 --> 00:30:06,730
when you consider implementating AI in pharma

721
00:30:06,730 --> 00:30:09,400
are you aware of the regulations and guidelines

722
00:30:09,400 --> 00:30:10,800
guidelines needed?

723
00:30:11,530 --> 00:30:15,060
How would you validate an AI system?

724
00:30:15,200 --> 00:30:17,100
So who wants to talk a lot?

725
00:30:17,360 --> 00:30:22,200
I see James glowing. Please, James.

726
00:30:22,200 --> 00:30:24,760
You validate all your team using Microsoft Words

727
00:30:24,760 --> 00:30:27,260
or your agency using Adobe Photoshop

728
00:30:27,260 --> 00:30:27,660
like

729
00:30:27,660 --> 00:30:30,630
it's just a tool and you're not worried about that

730
00:30:30,660 --> 00:30:32,160
X software is AI powered

731
00:30:32,160 --> 00:30:33,860
and Adobe Photoshop is AI powered

732
00:30:33,860 --> 00:30:35,760
so unless yeah okay

733
00:30:35,760 --> 00:30:38,730
we're building you a custom AI platform

734
00:30:38,730 --> 00:30:40,160
that's gonna be a big deal

735
00:30:40,160 --> 00:30:41,060
if you wanna roll out

736
00:30:41,060 --> 00:30:42,600
as a lot of pharma companies are doing

737
00:30:42,600 --> 00:30:43,860
if you wanna roll out your own

738
00:30:43,860 --> 00:30:45,500
version GPT your

739
00:30:45,500 --> 00:30:47,330
it team will do some checks

740
00:30:47,330 --> 00:30:49,100
and run it through Microsoft as well

741
00:30:49,330 --> 00:30:50,930
and we'll say beyond

742
00:30:50,930 --> 00:30:52,600
here's some training and it'll be fine

743
00:30:53,060 --> 00:30:54,630
not big deal in my opinion

744
00:30:55,530 --> 00:30:56,560
but I could be wrong.

745
00:30:59,700 --> 00:31:02,100
Maybe I can add something to this James

746
00:31:03,460 --> 00:31:05,530
yeah very quickly I think yes

747
00:31:05,530 --> 00:31:06,500
of course I mean

748
00:31:06,500 --> 00:31:09,560
we are fully aware of the of the regulation and

749
00:31:10,000 --> 00:31:12,930
and basically this is something that pharma

750
00:31:12,930 --> 00:31:16,460
companies are taking into serious consideration

751
00:31:16,860 --> 00:31:18,260
because of course I mean

752
00:31:19,130 --> 00:31:22,300
they are used before rolling out any

753
00:31:22,660 --> 00:31:25,660
any solution to take into account in Europe

754
00:31:25,660 --> 00:31:30,160
I think we are somehow luckier than other country

755
00:31:30,160 --> 00:31:33,860
because Europe is ahead of the curve in terms of AI

756
00:31:33,860 --> 00:31:37,960
regulation so on top of the usual pharma regulation

757
00:31:37,960 --> 00:31:42,860
we do also have somehow from the European Union AI Act,

758
00:31:43,400 --> 00:31:46,630
AI recommendation, IMA is

759
00:31:46,960 --> 00:31:49,660
is say saying something about AI

760
00:31:49,660 --> 00:31:52,360
I think that the key part is to

761
00:31:52,360 --> 00:31:55,160
let's say when you are working on the

762
00:31:55,160 --> 00:31:59,060
on the AI solution to take privacy uh

763
00:31:59,060 --> 00:32:02,860
in privacy compliance regulation officers

764
00:32:02,860 --> 00:32:03,700
let's say

765
00:32:03,700 --> 00:32:07,130
together with you from the very first step of the

766
00:32:07,130 --> 00:32:09,160
of the deployment of the solution

767
00:32:09,460 --> 00:32:12,100
because otherwise this is not gonna fly

768
00:32:12,100 --> 00:32:13,860
but definitely is something crucial

769
00:32:13,860 --> 00:32:14,700
you know pharma

770
00:32:14,700 --> 00:32:17,630
when is releasing a product is starting from safety

771
00:32:17,860 --> 00:32:19,900
and then looking to a frequency

772
00:32:20,100 --> 00:32:22,000
so in this case is the same.

773
00:32:22,000 --> 00:32:24,330
I think okay.

774
00:32:24,330 --> 00:32:25,800
We have another question.

775
00:32:25,800 --> 00:32:28,160
I like this audience. It's very active.

776
00:32:28,160 --> 00:32:31,700
From George, he says an observation

777
00:32:31,800 --> 00:32:34,660
Is the life science industry ready and mature

778
00:32:34,660 --> 00:32:37,960
to such extent that we are already talking about

779
00:32:37,960 --> 00:32:41,200
omnichannel excellence? My question to the panel

780
00:32:41,200 --> 00:32:42,130
what do you think

781
00:32:42,130 --> 00:32:44,560
the future of omni channel experience will be

782
00:32:44,560 --> 00:32:48,500
in terms of patient and HCP engagement?

783
00:32:51,960 --> 00:32:55,060
I can start and you can start then no

784
00:32:55,060 --> 00:32:55,860
I I

785
00:32:56,900 --> 00:32:57,900
yeah Manuel

786
00:32:58,700 --> 00:33:01,100
but I'll put your turn yeah

787
00:33:01,660 --> 00:33:02,800
because I was reading this

788
00:33:02,800 --> 00:33:05,260
this question and thank you George for sharing

789
00:33:05,260 --> 00:33:07,530
it's very interesting personally

790
00:33:07,530 --> 00:33:08,160
uh um

791
00:33:08,160 --> 00:33:09,430
I I think is

792
00:33:10,000 --> 00:33:10,760
um the

793
00:33:10,760 --> 00:33:12,000
the industry

794
00:33:12,000 --> 00:33:16,060
has a very different and very diverse level of maturity

795
00:33:16,060 --> 00:33:18,500
company against company

796
00:33:18,500 --> 00:33:22,200
let's say I see companies that are very

797
00:33:23,130 --> 00:33:24,360
let's say very advanced

798
00:33:24,360 --> 00:33:27,200
some other that are lagging behind

799
00:33:27,200 --> 00:33:30,660
in terms of adoptionality of the AI

800
00:33:30,730 --> 00:33:34,160
I'm speaking about the adoption of the say

801
00:33:34,160 --> 00:33:37,100
already classical omnichannel

802
00:33:37,400 --> 00:33:39,960
so I think it depends company by company

803
00:33:39,960 --> 00:33:40,560
and when I

804
00:33:40,560 --> 00:33:44,030
when I think about the future of omni channel

805
00:33:44,330 --> 00:33:50,160
experience I think it will be the keyword

806
00:33:50,200 --> 00:33:50,930
let's say

807
00:33:50,930 --> 00:33:55,000
it will be either personalization on both sides um

808
00:33:55,000 --> 00:33:57,360
I'm gonna say both sides I mean

809
00:33:57,360 --> 00:34:01,600
internal to have let's say AI used to

810
00:34:01,600 --> 00:34:03,700
let's say training for example

811
00:34:03,700 --> 00:34:07,660
your states course on a specific subgroup of HCP

812
00:34:08,730 --> 00:34:11,800
in order to say focal I mean

813
00:34:11,930 --> 00:34:14,660
shape your plan shape your strategy

814
00:34:14,700 --> 00:34:18,600
for a specific subgroup of physician internally

815
00:34:18,600 --> 00:34:22,730
and then externally in terms of content uh production

816
00:34:22,730 --> 00:34:25,400
so these are hyper personalization

817
00:34:25,400 --> 00:34:26,100
I think it

818
00:34:26,100 --> 00:34:29,460
would be the the the keyword and we will hear uh

819
00:34:29,460 --> 00:34:31,600
a lot about it because it includes uh

820
00:34:31,700 --> 00:34:33,660
next step next best action

821
00:34:33,660 --> 00:34:37,930
it includes uh hyper personalized content and so on

822
00:34:37,930 --> 00:34:40,700
so that this is I think it will be the key

823
00:34:40,860 --> 00:34:44,260
and another quick thing is that in the past

824
00:34:44,260 --> 00:34:48,700
we were going toward the creation of many

825
00:34:48,700 --> 00:34:52,260
many content we deployed Content Factory

826
00:34:52,330 --> 00:34:54,900
pushing for more and more content

827
00:34:54,960 --> 00:34:59,560
the result: physicians are overwhelmed by all the content

828
00:34:59,560 --> 00:35:02,330
so I think we will have also less content

829
00:35:02,330 --> 00:35:03,900
but higher personalization,

830
00:35:03,900 --> 00:35:07,400
higher quality of the of the content in the future.

831
00:35:08,730 --> 00:35:09,860
I just I was on

832
00:35:11,160 --> 00:35:12,300
Who wants to go?

833
00:35:12,300 --> 00:35:15,300
I don't think the future is hyper personalization

834
00:35:15,300 --> 00:35:17,760
and maybe I'm being unfair in terms of like what

835
00:35:17,900 --> 00:35:19,700
what I think that means

836
00:35:19,960 --> 00:35:23,600
but like it's not about going hey

837
00:35:23,800 --> 00:35:25,700
you know Doctor Keppie

838
00:35:25,960 --> 00:35:30,000
we noticed that you were using your phone at 12:42 pm

839
00:35:30,000 --> 00:35:32,400
and you looked up this and therefore we did that

840
00:35:32,400 --> 00:35:33,760
like getting that.

841
00:35:33,760 --> 00:35:35,130
That's stalking haha

842
00:35:35,130 --> 00:35:38,160
Creepy stalking, right? It's not about being

843
00:35:39,200 --> 00:35:40,000
you

844
00:35:43,260 --> 00:35:44,500
like, you like ice cream

845
00:35:44,500 --> 00:35:45,700
therefore we're gonna

846
00:35:45,700 --> 00:35:47,900
tell you about the efficacy of our diabetes portal

847
00:35:47,900 --> 00:35:48,760
like I don't know

848
00:35:49,500 --> 00:35:50,800
I don't think it's about being like

849
00:35:50,800 --> 00:35:53,200
hyper personalized in terms of push

850
00:35:53,330 --> 00:35:54,900
and maybe this isn't what you meant

851
00:35:54,960 --> 00:35:58,360
but I think like when we talk about personalization

852
00:35:58,360 --> 00:36:00,800
is not a personalized content.

853
00:36:00,800 --> 00:36:02,100
It's a personalized journey.

854
00:36:02,760 --> 00:36:06,530
So like how you use Netflix you know

855
00:36:06,530 --> 00:36:08,460
everyone gets the same content on Netflix

856
00:36:08,460 --> 00:36:10,530
but your journey through that content is different

857
00:36:10,530 --> 00:36:12,400
when it when you finish watching something

858
00:36:12,400 --> 00:36:14,260
it says "you may also like"

859
00:36:14,300 --> 00:36:17,160
those are personalized messages that they get you

860
00:36:17,160 --> 00:36:18,400
and the things that tells you

861
00:36:18,400 --> 00:36:20,600
what you might wanna watch is all personalized

862
00:36:20,600 --> 00:36:22,200
and that's the personalized journey

863
00:36:22,600 --> 00:36:25,400
and but crucially they're giving you a choice

864
00:36:25,400 --> 00:36:28,500
Netflix doesn't say you have to watch this next says

865
00:36:28,500 --> 00:36:30,330
we think you'll watch this next

866
00:36:30,330 --> 00:36:32,130
and that's self personalization

867
00:36:32,130 --> 00:36:33,100
so I think

868
00:36:33,200 --> 00:36:35,530
and maybe we're talking the same thing as I say

869
00:36:35,530 --> 00:36:39,360
but I think the future is so I think so is allowing you

870
00:36:39,360 --> 00:36:40,530
it's just like saying

871
00:36:40,530 --> 00:36:42,960
we think you're gonna want this or maybe this

872
00:36:42,960 --> 00:36:44,930
maybe this is something this more bread

873
00:36:44,930 --> 00:36:46,430
this is more depth

874
00:36:46,530 --> 00:36:48,860
giving that choice and giving multiple choices

875
00:36:49,330 --> 00:36:51,500
such that your physician goes

876
00:36:51,500 --> 00:36:53,530
oh yeah I do want to know about that

877
00:36:53,530 --> 00:36:54,330
that doesn't look interesting

878
00:36:54,330 --> 00:36:57,360
thanks very much and that's continuing the conversation

879
00:36:57,360 --> 00:36:59,500
okay you've organized that content stories

880
00:36:59,500 --> 00:37:00,960
continuing the conversation

881
00:37:01,400 --> 00:37:05,360
but it's not about being really creepy

882
00:37:06,160 --> 00:37:06,960
yeah think

883
00:37:06,960 --> 00:37:08,860
it's all about the strategic thought

884
00:37:08,860 --> 00:37:10,860
about relevant content

885
00:37:10,860 --> 00:37:14,200
rather than starting with trying to personalize

886
00:37:14,200 --> 00:37:15,900
for personalization's sake

887
00:37:15,960 --> 00:37:17,660
it's really starting to think about

888
00:37:17,660 --> 00:37:19,360
what is the relevant content

889
00:37:19,360 --> 00:37:21,360
and in terms of like a you know

890
00:37:21,530 --> 00:37:22,800
practical tip for that

891
00:37:22,800 --> 00:37:25,460
you can most brand teams today have uh

892
00:37:25,460 --> 00:37:28,230
you know
an adoption ladder and a behavioral segmentation

893
00:37:28,300 --> 00:37:29,560
if you can do a real

894
00:37:29,560 --> 00:37:32,130
simple activity of drawing up a nice grid

895
00:37:32,130 --> 00:37:34,960
and then mapping out where your current content uh

896
00:37:34,960 --> 00:37:37,560
fits for each of those uh

897
00:37:37,560 --> 00:37:39,100
each of those areas and then

898
00:37:39,100 --> 00:37:42,160
you'll start to be able to see where those gaps are um

899
00:37:42,160 --> 00:37:43,130
or whether

900
00:37:43,130 --> 00:37:45,330
potentially you're focusing too heavy for content

901
00:37:45,330 --> 00:37:47,700
on one particular area and

902
00:37:47,700 --> 00:37:48,860
if you haven't got content

903
00:37:48,860 --> 00:37:50,300
that covers all of those areas

904
00:37:50,300 --> 00:37:52,400
how are you gonna personalize if you have

905
00:37:52,400 --> 00:37:55,160
not even starting from a relevant content base

906
00:37:55,260 --> 00:37:56,900
on that front no

907
00:37:57,600 --> 00:38:00,600
And just to answer James

908
00:38:00,600 --> 00:38:02,260
very quickly I think we were speaking

909
00:38:02,260 --> 00:38:05,360
actually we were speaking about the same thing because

910
00:38:05,360 --> 00:38:07,260
um when when um

911
00:38:07,260 --> 00:38:10,560
you made the example of hyper personalization

912
00:38:10,560 --> 00:38:11,560
of course I mean

913
00:38:12,360 --> 00:38:16,600
you put it to the extreme and it looks like a stalking

914
00:38:16,600 --> 00:38:18,500
not the hyperpersonalization

915
00:38:18,500 --> 00:38:21,100
but the example that you made about Netflix

916
00:38:21,100 --> 00:38:22,700
I think this is exactly

917
00:38:22,700 --> 00:38:25,730
a perfect example of hyperpersonalization

918
00:38:25,730 --> 00:38:27,560
because if you open Netflix

919
00:38:27,560 --> 00:38:32,000
of course we have access to the same list of movies

920
00:38:32,000 --> 00:38:33,960
but my own page of the website

921
00:38:33,960 --> 00:38:36,030
will be completely different from yours

922
00:38:36,160 --> 00:38:36,900
and if I

923
00:38:36,900 --> 00:38:40,860
I mean if I go to a website of pharmaceutical company

924
00:38:40,860 --> 00:38:42,300
this could be the case

925
00:38:42,400 --> 00:38:44,200
but it is not the case at the moment

926
00:38:44,200 --> 00:38:46,460
and that's the level of hyper personalization

927
00:38:46,460 --> 00:38:49,230
so if I'm a physician that usually is more

928
00:38:49,400 --> 00:38:53,060
let's say firm to look at clinical studies

929
00:38:53,100 --> 00:38:54,160
maybe in the home page

930
00:38:54,160 --> 00:38:57,060
I have a lot of clinical studies and I

931
00:38:57,060 --> 00:38:59,360
I don't think we are um

932
00:38:59,360 --> 00:39:00,900
already there but then

933
00:39:00,900 --> 00:39:04,900
it must be absolutely a mix of push and pull channels

934
00:39:05,360 --> 00:39:07,700
but I think from my side date

935
00:39:07,700 --> 00:39:08,760
this is the

936
00:39:09,400 --> 00:39:09,900
the the

937
00:39:09,900 --> 00:39:12,260
the future of personalization yeah

938
00:39:12,260 --> 00:39:13,260
if I might, if I might

939
00:39:13,260 --> 00:39:15,560
I'm gonna put my five cents here um

940
00:39:15,560 --> 00:39:17,700
Did you know so that Netflix they're

941
00:39:18,000 --> 00:39:19,500
they're potentially looking into

942
00:39:19,500 --> 00:39:21,900
creating different scenarios for the movie?

943
00:39:21,900 --> 00:39:24,660
So my ending of the movie could be different

944
00:39:24,660 --> 00:39:25,760
from your own movie.

945
00:39:25,960 --> 00:39:28,060
So based on that yeah

946
00:39:28,060 --> 00:39:30,260
so let's say I like more drama right

947
00:39:30,260 --> 00:39:32,130
and then let's say I want

948
00:39:32,130 --> 00:39:34,060
I like when the ending is dramatic

949
00:39:34,060 --> 00:39:34,930
so they all think

950
00:39:34,930 --> 00:39:37,160
the movie that I will see is gonna be the different

951
00:39:37,160 --> 00:39:37,900
movie so

952
00:39:37,900 --> 00:39:38,760
I have a different scenario

953
00:39:38,760 --> 00:39:40,730
from the movie that you will see basically

954
00:39:40,730 --> 00:39:42,360
this is gonna have two endings

955
00:39:42,500 --> 00:39:44,560
a happy ending and a dramatic ending

956
00:39:44,560 --> 00:39:45,660
for example well

957
00:39:45,660 --> 00:39:46,760
But in my case

958
00:39:46,760 --> 00:39:49,800
I'm going to bring the Netflix case with my husband

959
00:39:49,800 --> 00:39:52,660
we would with either user

960
00:39:52,660 --> 00:39:55,860
so I'm going to have an actual action ending

961
00:39:55,860 --> 00:39:57,600
when I want a romantic ending I

962
00:39:57,600 --> 00:40:00,260
I'm not happy about this.

963
00:40:00,260 --> 00:40:01,400
Why no one asked me? No haha

964
00:40:01,400 --> 00:40:02,900
I'm kidding haha

965
00:40:02,900 --> 00:40:05,460
um yeah please

966
00:40:05,800 --> 00:40:08,000
I find it quite funny how we uh

967
00:40:08,200 --> 00:40:11,200
we do love the Netflix analogy in our industry

968
00:40:11,200 --> 00:40:13,860
and I don't I don't know whether it's just me

969
00:40:13,860 --> 00:40:14,660
but

970
00:40:14,660 --> 00:40:17,560
I haven't had the best experiences of recommendations

971
00:40:17,560 --> 00:40:19,860
of of content personally

972
00:40:19,860 --> 00:40:23,060
so is that, should we take a step back and think like

973
00:40:23,060 --> 00:40:25,360
is that something that we really want to strive towards

974
00:40:25,360 --> 00:40:28,560
as an industry for recommendations?

975
00:40:28,560 --> 00:40:29,330
Yeah okay.

976
00:40:29,330 --> 00:40:31,800
Ok, do you mind just care for someone else?

977
00:40:31,800 --> 00:40:32,730
Do you know? I've got

978
00:40:32,730 --> 00:40:34,160
I've got my own own little setup

979
00:40:34,160 --> 00:40:36,660
my own little nice profile picture in there

980
00:40:36,660 --> 00:40:38,960
but maybe that's pretty much enough.

981
00:40:39,260 --> 00:40:42,300
In my case that the recommendations are pretty bad.

982
00:40:42,300 --> 00:40:45,560
I have to agree with Ben and that like um

983
00:40:45,560 --> 00:40:46,730
they offer like

984
00:40:46,730 --> 00:40:49,860
they give me a suggestion of a movie or a

985
00:40:50,100 --> 00:40:53,400
or a show and I get really bored with those

986
00:40:53,400 --> 00:40:56,200
so I need to do my own research

987
00:40:56,500 --> 00:40:58,060
so my question will be

988
00:40:58,060 --> 00:41:01,460
if we do the person that like hyper personalization

989
00:41:01,460 --> 00:41:03,300
are we going to face the same issue?

990
00:41:03,300 --> 00:41:06,400
because if Netflix has it why we are

991
00:41:07,660 --> 00:41:09,060
and then the other

992
00:41:09,760 --> 00:41:12,900
and then if that happens you lose customer correct

993
00:41:12,900 --> 00:41:15,960
because you are not giving them what they want

994
00:41:15,960 --> 00:41:17,030
at the end of the day

995
00:41:17,130 --> 00:41:19,700
the crucial thing is to give choice is to like

996
00:41:19,930 --> 00:41:21,100
you know Netflix doesn't tell you

997
00:41:21,100 --> 00:41:22,100
"you should only watch this"

998
00:41:22,100 --> 00:41:24,560
it says "here five things you might like"

999
00:41:24,560 --> 00:41:26,930
and okay maybe those are all completely wrong

1000
00:41:26,930 --> 00:41:28,260
um but it's

1001
00:41:28,330 --> 00:41:30,900
I think one of the you know

1002
00:41:30,900 --> 00:41:33,460
one of the tenants of on the channel is connectivity

1003
00:41:33,460 --> 00:41:36,130
right? And we find a lot of things

1004
00:41:36,130 --> 00:41:37,560
Take the the website example

1005
00:41:37,560 --> 00:41:41,130
We were just discussing a lot of content that we

1006
00:41:41,130 --> 00:41:43,630
put on websites has no next step

1007
00:41:43,700 --> 00:41:46,160
it just goes this thing you direct traffic

1008
00:41:46,260 --> 00:41:47,530
here's the thing like I

1009
00:41:47,530 --> 00:41:50,460
I get that maybe the recommendations might not be great

1010
00:41:50,460 --> 00:41:53,100
but even giving recommendations is better than nothing

1011
00:41:53,100 --> 00:41:53,560
truly like

1012
00:41:53,560 --> 00:41:56,160
if you launch Netflix and it was just a blank screen

1013
00:41:56,160 --> 00:41:58,100
but what do you wanna watch, Juliana?

1014
00:41:58,200 --> 00:41:59,800
You be like "I don't know"

1015
00:42:00,330 --> 00:42:03,600
I have my list and I rewatch things

1016
00:42:03,600 --> 00:42:04,530
so that's the thing

1017
00:42:04,530 --> 00:42:06,460
I like to rewatch things that I liked

1018
00:42:07,760 --> 00:42:08,560
that's weird.

1019
00:42:09,360 --> 00:42:11,130
There's also the thing of um

1020
00:42:11,130 --> 00:42:13,660
like chances are users of Netflix you

1021
00:42:13,660 --> 00:42:15,700
you spend a fair bit of time on it

1022
00:42:15,700 --> 00:42:17,200
um but

1023
00:42:17,200 --> 00:42:18,860
Are we expecting HCPs

1024
00:42:18,860 --> 00:42:20,160
to spend a similar amount of time

1025
00:42:20,160 --> 00:42:23,360
to be able to actually harness meaningful

1026
00:42:23,360 --> 00:42:24,160
recommendations?

1027
00:42:24,160 --> 00:42:27,660
Or is it more commercially sensible to them

1028
00:42:27,660 --> 00:42:29,160
focus on that you know

1029
00:42:29,160 --> 00:42:32,160
strategically focusing on what is relevant

1030
00:42:32,160 --> 00:42:33,900
and providing it through a

1031
00:42:33,900 --> 00:42:38,030
a different means that might not be AI recommendations?

1032
00:42:38,060 --> 00:42:39,200
um but more so

1033
00:42:39,200 --> 00:42:42,230
just being pragmatic and strategic around it

1034
00:42:42,600 --> 00:42:44,360
hmm yeah

1035
00:42:44,360 --> 00:42:45,960
food for thought no

1036
00:42:46,160 --> 00:42:47,100
no no

1037
00:42:48,960 --> 00:42:54,200
um I think we have... There were comments

1038
00:42:54,200 --> 00:42:57,160
but stuff if you want to take um

1039
00:42:57,300 --> 00:42:58,460
want to read something oh

1040
00:42:58,460 --> 00:43:00,360
We have a mention here

1041
00:43:00,360 --> 00:43:02,400
which is I find quite interesting

1042
00:43:02,660 --> 00:43:06,360
so Tanya who asked us a question says that um

1043
00:43:06,360 --> 00:43:07,830
she appreciates the answer

1044
00:43:08,130 --> 00:43:08,900
and she's saying that

1045
00:43:08,900 --> 00:43:11,560
my colleagues and I are following the Use AI Act

1046
00:43:11,560 --> 00:43:13,130
and fee FBI is processed too

1047
00:43:13,130 --> 00:43:14,000
but I agree with the panel

1048
00:43:14,000 --> 00:43:16,800
that the current guidelines still applies

1049
00:43:16,800 --> 00:43:18,760
such as G a and P 5

1050
00:43:19,530 --> 00:43:21,560
uh but it will be interesting to see how the new

1051
00:43:21,560 --> 00:43:23,560
developed regulations uh

1052
00:43:23,560 --> 00:43:28,360
for Emma and if they produce will turn out um

1053
00:43:29,130 --> 00:43:33,100
the then she's recommending here that ISO standard 42 0

1054
00:43:33,100 --> 00:43:38,000
0 1 AA management system so my I

1055
00:43:38,000 --> 00:43:40,860
I would rather have like a more of a comment here

1056
00:43:41,060 --> 00:43:43,700
and how do you think the new AI acts

1057
00:43:43,700 --> 00:43:46,060
and the FDX will regulate AI

1058
00:43:46,060 --> 00:43:47,200
in the terms that

1059
00:43:47,530 --> 00:43:51,360
do you think it will hurt the AI features

1060
00:43:51,360 --> 00:43:53,360
we're gonna use it on the channel or not?

1061
00:43:53,460 --> 00:43:55,460
And if he hasn't then how

1062
00:43:56,060 --> 00:43:59,960
and do we have a solution to use to solve this?

1063
00:44:02,730 --> 00:44:04,600
It's a big question. Go on, Manuel.

1064
00:44:05,160 --> 00:44:08,430
yeah maybe it start. Thank you, James.

1065
00:44:09,330 --> 00:44:10,760
Stay under the bus on that one

1066
00:44:10,760 --> 00:44:12,600
I'm not gonna start you start

1067
00:44:15,060 --> 00:44:18,330
No, I start with the with the AI Act for example

1068
00:44:18,330 --> 00:44:20,960
and the one thing that the AI

1069
00:44:20,960 --> 00:44:23,300
Act is introducing into the game

1070
00:44:23,300 --> 00:44:24,860
is the risk based approach

1071
00:44:24,860 --> 00:44:26,200
that it is something that

1072
00:44:26,200 --> 00:44:32,760
it is something quite common in the pharma and

1073
00:44:33,260 --> 00:44:34,500
and basically I mean

1074
00:44:34,500 --> 00:44:38,200
having this approach of the AI actor saying

1075
00:44:38,200 --> 00:44:43,000
if an AI solution is somehow riskier than another

1076
00:44:43,000 --> 00:44:46,460
then you have to follow this rule if not

1077
00:44:46,660 --> 00:44:49,860
you have to follow let's say other rules or you are

1078
00:44:49,860 --> 00:44:52,600
I mean obliged not to go there

1079
00:44:52,600 --> 00:44:53,660
for example I mean

1080
00:44:53,930 --> 00:44:56,900
social scoring this kind of things

1081
00:44:56,930 --> 00:44:58,360
I think I mean

1082
00:44:58,360 --> 00:45:03,530
this is something that can help pharma companies,

1083
00:45:03,530 --> 00:45:06,100
service provider take the

1084
00:45:06,100 --> 00:45:09,200
the right decision to the regulation to apply

1085
00:45:09,260 --> 00:45:10,660
while on the other countries

1086
00:45:10,660 --> 00:45:12,760
I see broad and when it is broad

1087
00:45:12,760 --> 00:45:17,560
it becomes also matter of interpretation of the law

1088
00:45:17,700 --> 00:45:21,160
so still low and non

1089
00:45:21,160 --> 00:45:23,800
the legal aspect that not an exact science

1090
00:45:23,960 --> 00:45:27,960
but I think Europe is doing very well with days

1091
00:45:27,960 --> 00:45:30,260
because you have somehow um

1092
00:45:30,260 --> 00:45:31,900
risk balance and approach

1093
00:45:32,130 --> 00:45:35,460
you can do something you cannot do uh

1094
00:45:35,460 --> 00:45:37,760
something else still you have

1095
00:45:37,760 --> 00:45:42,060
let's say a balance between taking the risk and say

1096
00:45:42,130 --> 00:45:43,860
not missing an opportunity

1097
00:45:44,160 --> 00:45:48,000
and I think it can be um over out there

1098
00:45:48,100 --> 00:45:51,060
I'm not let's say a legal expert uh

1099
00:45:51,060 --> 00:45:53,600
but for example in self promotion

1100
00:45:53,600 --> 00:45:59,400
let's say mode in the upcoming weeks I'm releasing a um

1101
00:45:59,400 --> 00:46:03,560
a YouTube video where I involve the legal person um

1102
00:46:03,560 --> 00:46:05,430
expert in pharma

1103
00:46:05,800 --> 00:46:09,560
speaking about all the implication of the AI Act for

1104
00:46:10,260 --> 00:46:11,930
for pharma and this person

1105
00:46:11,930 --> 00:46:14,330
let's say from I mean

1106
00:46:14,330 --> 00:46:16,200
his legal background and son

1107
00:46:16,200 --> 00:46:20,530
he has to study a lot and deep diving to the subject

1108
00:46:20,530 --> 00:46:22,300
math so and he's an expert

1109
00:46:22,300 --> 00:46:26,100
so I can only leave my 2 cents on the on this topic

1110
00:46:27,560 --> 00:46:28,330
yeah I did

1111
00:46:28,330 --> 00:46:30,560
I did pick up on what someone said in the comments

1112
00:46:30,560 --> 00:46:32,100
earlier that um

1113
00:46:32,100 --> 00:46:35,060
we're talking about AI in terms of the gender to be AI

1114
00:46:35,060 --> 00:46:36,000
and large language morals

1115
00:46:36,000 --> 00:46:37,660
all that trendy AI

1116
00:46:37,660 --> 00:46:40,100
that's come around in the last year and a half or so

1117
00:46:40,100 --> 00:46:42,060
but pharma especially

1118
00:46:42,060 --> 00:46:44,500
has been using AI in drug discovery for years

1119
00:46:44,500 --> 00:46:45,500
and years and years

1120
00:46:45,500 --> 00:46:47,700
and have natural life processing teams

1121
00:46:47,700 --> 00:46:49,560
and big data teams um

1122
00:46:49,560 --> 00:46:51,600
I was working with the pharma company again

1123
00:46:51,600 --> 00:46:52,900
kinda early last year

1124
00:46:52,900 --> 00:46:56,430
talking about this new chat GPT and um

1125
00:46:56,930 --> 00:46:57,360
and they still

1126
00:46:57,360 --> 00:46:59,800
will you come and give a presentation to our teams

1127
00:46:59,800 --> 00:47:00,460
yeah absolutely

1128
00:47:00,460 --> 00:47:01,160
I'll come talk about

1129
00:47:01,160 --> 00:47:03,400
and explain how you could use it in the mid affairs

1130
00:47:03,500 --> 00:47:05,360
and then kind of two weeks later they went

1131
00:47:05,360 --> 00:47:07,930
oh it turns out we've got a whole data science team

1132
00:47:07,930 --> 00:47:10,060
and they do AI we didn't even know

1133
00:47:10,200 --> 00:47:12,400
so we're gonna get one of them to come along and join

1134
00:47:12,400 --> 00:47:13,960
the presentations that okay

1135
00:47:13,960 --> 00:47:14,660
I was like yeah

1136
00:47:14,660 --> 00:47:16,260
cool so I spoke to her and said

1137
00:47:16,260 --> 00:47:17,600
do you feel that like you know

1138
00:47:17,600 --> 00:47:20,000
you've been ignored and now suddenly she said yeah

1139
00:47:20,000 --> 00:47:22,460
I've been doing AI for years

1140
00:47:22,660 --> 00:47:25,600
you know
in this big pharma company now chat GPT come through

1141
00:47:25,600 --> 00:47:27,030
only people are interested

1142
00:47:28,260 --> 00:47:29,600
so I think there is three of like

1143
00:47:29,600 --> 00:47:30,530
when we're talking about yeah

1144
00:47:30,530 --> 00:47:32,900
we're in that there is a whole law

1145
00:47:32,900 --> 00:47:34,900
and to the point of the AI Act

1146
00:47:34,900 --> 00:47:36,800
I think pharma and this is a guest

1147
00:47:36,900 --> 00:47:40,500
are probably quite far along in how they use AI

1148
00:47:40,500 --> 00:47:41,700
because they have been using it

1149
00:47:41,700 --> 00:47:43,500
where some other industries have

1150
00:47:44,100 --> 00:47:45,100
hmm yeah

1151
00:47:46,330 --> 00:47:49,860
I like to hear Ben about this because he he's not

1152
00:47:49,860 --> 00:47:51,160
but he is not

1153
00:47:51,160 --> 00:47:54,560
I'm nodding because this is all new information for me

1154
00:47:54,560 --> 00:47:57,160
and I clearly haven't done my AI

1155
00:47:57,160 --> 00:47:59,760
research on rules and regulations

1156
00:48:00,460 --> 00:48:02,060
to be able to weigh in the conversation

1157
00:48:02,060 --> 00:48:03,960
that anything uh

1158
00:48:03,960 --> 00:48:05,760
of more value than what James

1159
00:48:05,760 --> 00:48:07,100
Manuel have already covered

1160
00:48:07,330 --> 00:48:09,700
I don't know any of that to begin with anyway

1161
00:48:09,700 --> 00:48:12,800
so it's been enlightening for me uh

1162
00:48:12,800 --> 00:48:14,130
I will bring a

1163
00:48:14,130 --> 00:48:16,600
hope that it's related to an upcoming web

1164
00:48:16,600 --> 00:48:20,960
whenever we had a discussion with a speaker and she

1165
00:48:20,960 --> 00:48:21,700
the

1166
00:48:21,700 --> 00:48:26,130
said that it's very important that all the strategies

1167
00:48:26,130 --> 00:48:27,360
uh of AI

1168
00:48:27,360 --> 00:48:30,700
or everything that we use needs to be regionalized

1169
00:48:30,800 --> 00:48:33,530
because sometimes and it happens for example

1170
00:48:33,530 --> 00:48:37,100
she she talks about the difference in use industry

1171
00:48:37,100 --> 00:48:38,960
or the different strategies used

1172
00:48:38,960 --> 00:48:41,000
for example in uh

1173
00:48:41,000 --> 00:48:45,200
the in Europe uh in different countries uh

1174
00:48:45,200 --> 00:48:49,400
but sometimes they bring the same idea to LATAM

1175
00:48:49,400 --> 00:48:51,760
where it's completely different

1176
00:48:51,760 --> 00:48:53,060
like she said that

1177
00:48:53,060 --> 00:48:54,000
the person in person

1178
00:48:54,000 --> 00:48:56,930
contact is one of the most important things

1179
00:48:56,930 --> 00:48:58,960
and I'm here given an

1180
00:48:59,260 --> 00:49:02,030
a little bit of a trailer about that

1181
00:49:02,330 --> 00:49:04,900
about our coming topic but women are

1182
00:49:04,900 --> 00:49:07,160
but how do you guys feel about that

1183
00:49:07,160 --> 00:49:10,300
do you agree with that sentence

1184
00:49:10,300 --> 00:49:12,600
in terms of regionalization

1185
00:49:12,600 --> 00:49:15,960
and adopting techniques need to be used

1186
00:49:15,960 --> 00:49:18,600
in terms of a need to be strategiced

1187
00:49:18,600 --> 00:49:21,560
in terms of who are your customers and who

1188
00:49:21,560 --> 00:49:22,900
what is the costume

1189
00:49:22,900 --> 00:49:25,030
or culture that you're talking with

1190
00:49:26,460 --> 00:49:29,100
I think so I think it's extremely important and not

1191
00:49:29,100 --> 00:49:34,000
not even just for AI or large omni channel projects

1192
00:49:34,000 --> 00:49:35,930
but even you know simple

1193
00:49:35,930 --> 00:49:37,130
global to local

1194
00:49:37,130 --> 00:49:41,060
content creation is a absolutely crucial part because

1195
00:49:41,330 --> 00:49:43,200
um if you're not you know

1196
00:49:43,200 --> 00:49:45,130
adapting to what the local needs are

1197
00:49:45,130 --> 00:49:48,300
it's not gonna resonate with the um

1198
00:49:48,360 --> 00:49:50,660
healthcare professionals that's being used with

1199
00:49:50,700 --> 00:49:54,330
but also chances are the people that um

1200
00:49:54,330 --> 00:49:56,900
use the localized content

1201
00:49:56,900 --> 00:49:58,500
so um

1202
00:49:58,530 --> 00:50:01,560
whether it's a marketeer or a field team user chances are

1203
00:50:01,560 --> 00:50:03,060
they're not going to want to adopt it

1204
00:50:03,060 --> 00:50:05,700
if it's not relevant for their local market either

1205
00:50:05,700 --> 00:50:07,830
so yeah it's absolutely crucial that

1206
00:50:09,560 --> 00:50:14,030
things are localised when when it's important to do so

1207
00:50:16,100 --> 00:50:18,030
could you just use AI to do that

1208
00:50:18,060 --> 00:50:19,960
you just go here's the global content

1209
00:50:19,960 --> 00:50:23,060
we're adapting this for Argentina

1210
00:50:23,460 --> 00:50:27,460
make it a good be a good starting point right

1211
00:50:27,860 --> 00:50:29,130
it can be a starting point

1212
00:50:29,130 --> 00:50:30,330
but at the same time

1213
00:50:30,330 --> 00:50:34,100
and I am going to use a movie reference

1214
00:50:34,100 --> 00:50:36,530
I don't know if you guys saw Hidden Figures

1215
00:50:36,530 --> 00:50:39,460
the movie about the NASA woman

1216
00:50:40,760 --> 00:50:43,430
I don't sorry

1217
00:50:44,130 --> 00:50:47,360
I'm sorry Netflix but it wasn't there now

1218
00:50:47,360 --> 00:50:49,100
it was it was movie about this woman

1219
00:50:49,100 --> 00:50:51,930
and they were implemented the new machine

1220
00:50:51,930 --> 00:50:53,930
I don't remember the recall the name

1221
00:50:53,930 --> 00:50:59,060
but the thing was that they were given some wrong data

1222
00:50:59,060 --> 00:51:03,660
so how we can ensure when using this tools

1223
00:51:03,660 --> 00:51:06,930
that we are having the correct answer

1224
00:51:06,930 --> 00:51:09,260
let's say to what we were asking like

1225
00:51:09,260 --> 00:51:11,160
how can I ensure that uh

1226
00:51:11,160 --> 00:51:13,060
my originalization with AI

1227
00:51:13,060 --> 00:51:13,760
it's going to be

1228
00:51:13,760 --> 00:51:16,930
give me the information that I want from Argentina

1229
00:51:16,930 --> 00:51:18,560
currently and not from Argentina

1230
00:51:18,560 --> 00:51:19,160
I don't know

1231
00:51:19,160 --> 00:51:22,600
two years ago or one year ago that we have an uh

1232
00:51:22,600 --> 00:51:23,800
a change of

1233
00:51:23,800 --> 00:51:26,300
let's say presidency and a change of government

1234
00:51:26,300 --> 00:51:28,300
so that will be my question

1235
00:51:28,860 --> 00:51:31,830
how can we rely that much or not

1236
00:51:32,960 --> 00:51:33,860
I think

1237
00:51:33,930 --> 00:51:36,060
I think Ben kind of already answered that when he said

1238
00:51:36,060 --> 00:51:38,000
it would be a start right

1239
00:51:38,060 --> 00:51:38,800
I think that

1240
00:51:38,800 --> 00:51:41,660
so we all say when you're using AI to do anything

1241
00:51:41,660 --> 00:51:43,000
you're never gonna get 100%

1242
00:51:43,000 --> 00:51:46,060
if you got 80% there you've done really well

1243
00:51:46,200 --> 00:51:48,860
and even if you like generate an image with Darling

1244
00:51:48,860 --> 00:51:51,130
or getting someone to rewrite your email

1245
00:51:51,130 --> 00:51:52,700
like it'll get you 80% there

1246
00:51:52,700 --> 00:51:55,130
but you keep there's no point keep hammering at the eye

1247
00:51:55,130 --> 00:51:57,660
not do this nor do that it's like some point

1248
00:51:57,730 --> 00:51:59,800
probably the 80% point you get there

1249
00:51:59,800 --> 00:52:02,760
you stop and you finish it yourself um

1250
00:52:03,330 --> 00:52:04,530
and I think something like

1251
00:52:04,530 --> 00:52:07,660
your regional adaptation for Argentinian content

1252
00:52:07,660 --> 00:52:09,800
it might help you get 20% of the way

1253
00:52:09,800 --> 00:52:11,900
but thanks still 20% of the way

1254
00:52:11,930 --> 00:52:13,160
you still got to do the rest of the work

1255
00:52:13,160 --> 00:52:15,500
so yeah hit the nail on the head though

1256
00:52:15,500 --> 00:52:17,560
I think it's that um

1257
00:52:17,560 --> 00:52:19,800
the main knowledge and having someone to just sense

1258
00:52:19,800 --> 00:52:21,730
check it and forget it

1259
00:52:21,730 --> 00:52:24,360
get it finalized is still at least at the

1260
00:52:24,360 --> 00:52:27,530
moment still required for most aspects of

1261
00:52:27,530 --> 00:52:30,560
you know generation of content

1262
00:52:31,330 --> 00:52:32,200
um Steph

1263
00:52:32,200 --> 00:52:34,360
you have a question that you want

1264
00:52:34,360 --> 00:52:36,000
that you wanted to ask

1265
00:52:38,500 --> 00:52:40,030
or um what

1266
00:52:41,300 --> 00:52:42,530
if I got I got a question

1267
00:52:42,530 --> 00:52:43,860
I got a question that's been like

1268
00:52:43,860 --> 00:52:45,360
that's that's a bit more practical

1269
00:52:45,360 --> 00:52:47,730
so I know you guys will hate me about that so

1270
00:52:47,730 --> 00:52:48,530
um

1271
00:52:49,130 --> 00:52:50,700
um so my question is this so

1272
00:52:50,700 --> 00:52:52,260
um we were

1273
00:52:52,260 --> 00:52:54,300
thought we were talking about objective

1274
00:52:54,300 --> 00:52:55,900
objectives and keep your eyes right

1275
00:52:55,900 --> 00:52:58,530
and somebody mentioned that okay

1276
00:52:58,530 --> 00:52:59,300
you got a yeah

1277
00:52:59,300 --> 00:53:01,160
it's very very large topic

1278
00:53:01,160 --> 00:53:03,760
whatever and some was well

1279
00:53:03,760 --> 00:53:04,960
some people don't even know that

1280
00:53:04,960 --> 00:53:07,660
they have an AI team working there for 20 years

1281
00:53:07,900 --> 00:53:10,860
and they just discovered chatGPT right so

1282
00:53:10,860 --> 00:53:11,730
um what metric

1283
00:53:11,730 --> 00:53:12,800
metrics or keep your eyes

1284
00:53:12,800 --> 00:53:14,860
should be used to measure the success of

1285
00:53:14,860 --> 00:53:15,300
let's say

1286
00:53:15,300 --> 00:53:18,330
some AI driven personalization we're gonna use in

1287
00:53:18,330 --> 00:53:19,230
on the channel

1288
00:53:19,260 --> 00:53:24,160
be it like in person online or like hybrid

1289
00:53:24,160 --> 00:53:26,560
yeah so let's let's

1290
00:53:26,560 --> 00:53:28,300
let's let's see that Manuel

1291
00:53:28,300 --> 00:53:29,260
do you want to start

1292
00:53:30,060 --> 00:53:33,730
yeah so maybe I can start with with um

1293
00:53:33,730 --> 00:53:34,830
I mean you

1294
00:53:34,930 --> 00:53:37,760
you say that we are gonna hate this question

1295
00:53:37,760 --> 00:53:41,800
I think you're gonna hate the answer because I think

1296
00:53:41,800 --> 00:53:44,560
I mean it really depends uh

1297
00:53:44,560 --> 00:53:46,500
it really depends uh

1298
00:53:46,500 --> 00:53:47,200
because uh

1299
00:53:47,200 --> 00:53:48,800
I mean AI is very broad

1300
00:53:48,800 --> 00:53:51,960
so it really depends on the objective of the AI

1301
00:53:51,960 --> 00:53:53,500
solution that you are uh

1302
00:53:53,730 --> 00:53:56,400
trying to adopt that you are using

1303
00:53:56,400 --> 00:53:59,400
and then you can have a very different code from

1304
00:53:59,400 --> 00:54:01,100
from my standpoint that say

1305
00:54:01,100 --> 00:54:04,230
I have a very business oriented mindset

1306
00:54:04,260 --> 00:54:07,760
so any solution must let's say

1307
00:54:08,160 --> 00:54:11,460
be done to achieve a certain business goal

1308
00:54:11,460 --> 00:54:14,460
either engagement either say

1309
00:54:14,460 --> 00:54:16,330
so that should be I mean

1310
00:54:16,330 --> 00:54:19,460
the key goal of the solution should be the KPI

1311
00:54:20,130 --> 00:54:21,060
number one

1312
00:54:21,400 --> 00:54:24,960
then I think it depends on the nature of the solution

1313
00:54:24,960 --> 00:54:27,660
I mean if it is a chocolate is one thing

1314
00:54:27,660 --> 00:54:29,500
if it is a um

1315
00:54:29,500 --> 00:54:30,530
let's say uh

1316
00:54:30,530 --> 00:54:33,530
forecast tool for sales that's another thing

1317
00:54:33,530 --> 00:54:35,460
so if it is a chocolate for example

1318
00:54:35,460 --> 00:54:38,660
you may want to measure as a KPI

1319
00:54:38,660 --> 00:54:40,460
the successful conversation

1320
00:54:40,460 --> 00:54:43,300
that this chocolate is able to um

1321
00:54:43,300 --> 00:54:44,100
to

1322
00:54:44,400 --> 00:54:46,860
to use or if you have a forecasting tool

1323
00:54:46,860 --> 00:54:49,160
maybe you wanna measure the

1324
00:54:49,160 --> 00:54:53,700
its capacity its ability of predicting actual states

1325
00:54:53,700 --> 00:54:56,160
so it really depends there

1326
00:54:56,700 --> 00:54:58,800
and I mean

1327
00:54:58,800 --> 00:55:02,630
these are the two key things when it comes to KPI

1328
00:55:03,130 --> 00:55:04,000
let's say

1329
00:55:04,700 --> 00:55:06,800
I mean you can have thousands of

1330
00:55:06,800 --> 00:55:07,660
of KPI

1331
00:55:08,330 --> 00:55:11,130
personally speaking I try to

1332
00:55:11,130 --> 00:55:16,330
let's say prioritize as much as possible to have 1

1333
00:55:16,330 --> 00:55:18,800
2 3 maximum KPIs

1334
00:55:18,860 --> 00:55:22,100
because KPIs are something that also drive behaviours

1335
00:55:22,100 --> 00:55:24,760
so if you're focusing on the right thing

1336
00:55:24,760 --> 00:55:26,200
if you're measuring the right thing

1337
00:55:26,200 --> 00:55:29,400
then you can also have a somehow driving

1338
00:55:29,400 --> 00:55:32,500
the possibility to drive the successful adoption of

1339
00:55:32,500 --> 00:55:34,460
of the AI solution

1340
00:55:34,500 --> 00:55:37,260
and adoption by itself is also another KPI

1341
00:55:37,760 --> 00:55:39,660
that is important to be

1342
00:55:40,360 --> 00:55:44,860
to be adopted on top of another KPI that it is

1343
00:55:44,860 --> 00:55:48,460
of course the safety of the AI solution

1344
00:55:48,460 --> 00:55:50,900
that something that without safety

1345
00:55:50,900 --> 00:55:56,360
that's a no go regardless of any of any effectiveness

1346
00:55:56,360 --> 00:55:57,630
let's say of the solution

1347
00:55:59,200 --> 00:56:04,000
I think in general terms if it isn't AI kind of model

1348
00:56:04,000 --> 00:56:06,800
the general overarching um

1349
00:56:06,800 --> 00:56:07,260
a one

1350
00:56:07,260 --> 00:56:10,130
general overarching thing that you can kind of

1351
00:56:10,130 --> 00:56:11,900
measure for success will be like

1352
00:56:11,900 --> 00:56:14,060
it improving over time

1353
00:56:14,360 --> 00:56:16,460
so if we take like next best actions

1354
00:56:16,460 --> 00:56:18,800
uh or AI driven next best actions

1355
00:56:18,800 --> 00:56:20,860
just as an example you can have

1356
00:56:20,860 --> 00:56:23,860
you know quantitative measures of how

1357
00:56:23,960 --> 00:56:28,300
how often the suggestions are actually actioned uh

1358
00:56:28,300 --> 00:56:31,200
or the suggestions actually acted upon

1359
00:56:31,500 --> 00:56:33,700
and then you can also have the qualitative feedback

1360
00:56:33,700 --> 00:56:35,160
from the you know

1361
00:56:35,160 --> 00:56:37,260
simple feedback was this suggestion useful

1362
00:56:37,260 --> 00:56:39,060
and you can implement those kind of uh

1363
00:56:39,060 --> 00:56:41,730
feedback loops to get that ultimately that

1364
00:56:41,730 --> 00:56:42,900
that kind of overarching piece

1365
00:56:42,900 --> 00:56:44,700
if it is AI um

1366
00:56:44,700 --> 00:56:46,660
driven you should be looking for that kind of

1367
00:56:46,660 --> 00:56:48,530
overall improvement um

1368
00:56:48,530 --> 00:56:49,800
in in quality of a time

1369
00:56:49,800 --> 00:56:52,330
so for the next best actions example will be that

1370
00:56:52,330 --> 00:56:53,930
that quality of those suggestions

1371
00:56:53,930 --> 00:56:56,060
increase conversion of suggestions

1372
00:56:56,060 --> 00:56:59,660
launched versus actioned or acted upon

1373
00:57:02,060 --> 00:57:02,860
no

1374
00:57:03,530 --> 00:57:05,200
okay um

1375
00:57:05,200 --> 00:57:07,800
Steph do you have any um

1376
00:57:08,200 --> 00:57:11,730
any more questions we are almost on time

1377
00:57:11,730 --> 00:57:14,760
so I don't want to keep you guys here

1378
00:57:14,760 --> 00:57:17,530
for longer than it needs um

1379
00:57:17,530 --> 00:57:20,900
what I promised so I would really like

1380
00:57:20,900 --> 00:57:23,260
if each one of you could leave like a close

1381
00:57:23,260 --> 00:57:27,060
in comment or something like that to our audience

1382
00:57:27,330 --> 00:57:28,600
to lead up with

1383
00:57:32,330 --> 00:57:34,200
who wants to start you wanna start

1384
00:57:34,200 --> 00:57:37,000
just to mention guys audience while still here

1385
00:57:37,000 --> 00:57:41,160
please connect and follow our dear um

1386
00:57:41,400 --> 00:57:44,800
AI leaders and omnichannel James, Ben, and Emmanuel here

1387
00:57:44,800 --> 00:57:48,160
okay they will leave their LinkedIn accounts in the

1388
00:57:48,160 --> 00:57:49,100
in the chat here

1389
00:57:49,100 --> 00:57:53,260
so feel free to send them up hundreds of connections

1390
00:57:53,260 --> 00:57:56,200
okay they'll be headed to chat with you about the

1391
00:57:56,200 --> 00:58:00,200
a only channel content salesforce effectiveness

1392
00:58:00,200 --> 00:58:01,000
all right

1393
00:58:02,360 --> 00:58:03,200
thank you sir

1394
00:58:03,200 --> 00:58:05,360
sounds great looking forward to the influx there

1395
00:58:05,360 --> 00:58:06,230
um

1396
00:58:07,400 --> 00:58:10,060
so I think my uh

1397
00:58:10,100 --> 00:58:13,260
kind of I suppose closing statement would kind of be

1398
00:58:13,260 --> 00:58:17,860
it's really exciting time to technologically enable

1399
00:58:17,900 --> 00:58:20,660
HCP engagement we've never had access to

1400
00:58:20,730 --> 00:58:23,860
you know such advanced and exciting technology

1401
00:58:24,130 --> 00:58:26,930
but there is still uh in my opinion

1402
00:58:26,930 --> 00:58:29,100
from what I've seen a lot of work to do on that

1403
00:58:29,100 --> 00:58:31,760
foundational HCP engagement

1404
00:58:31,760 --> 00:58:35,260
um technology stack that we've already got in play

1405
00:58:35,260 --> 00:58:36,460
from CRM

1406
00:58:36,900 --> 00:58:40,760
CLM content and the just general data around that

1407
00:58:40,930 --> 00:58:42,160
uh and yeah

1408
00:58:42,160 --> 00:58:43,330
I believe that that

1409
00:58:43,330 --> 00:58:44,130
focusing on that

1410
00:58:44,130 --> 00:58:45,960
probably has a greater commercial return

1411
00:58:45,960 --> 00:58:47,930
investment than uh

1412
00:58:47,930 --> 00:58:50,060
and would be cheaper than

1413
00:58:50,130 --> 00:58:53,200
you know the likes of jumping straight to AI solutions

1414
00:58:53,200 --> 00:58:54,160
for the sake of it

1415
00:58:56,100 --> 00:58:57,360
um yeah

1416
00:58:57,360 --> 00:58:59,600
I I think mine would be um

1417
00:58:59,600 --> 00:59:01,700
on the channels not hard AI is not hard

1418
00:59:01,700 --> 00:59:03,430
just get started get on with it

1419
00:59:03,460 --> 00:59:04,900
sooner you get started the better

1420
00:59:07,260 --> 00:59:10,130
yeah and from my side that I mean

1421
00:59:10,130 --> 00:59:10,860
I think

1422
00:59:10,860 --> 00:59:15,330
it is important to keep the human at the center

1423
00:59:15,330 --> 00:59:18,830
I think AI is a is a tool and

1424
00:59:18,900 --> 00:59:21,560
and basically I think you have to I mean

1425
00:59:21,560 --> 00:59:23,900
if I can recommend something is to take it

1426
00:59:23,900 --> 00:59:25,860
practically test

1427
00:59:25,930 --> 00:59:31,000
touch it with hands and see what AI can do for you

1428
00:59:31,300 --> 00:59:33,700
that's something that I think is crucial

1429
00:59:34,460 --> 00:59:36,100
I like it um

1430
00:59:36,100 --> 00:59:38,500
before we leave uh James

1431
00:59:38,500 --> 00:59:41,130
I know you have something that you want to share

1432
00:59:41,130 --> 00:59:44,260
with us so please the Florida stores

1433
00:59:44,560 --> 00:59:46,100
we've got webinar coming up

1434
00:59:46,100 --> 00:59:49,730
and Christina Busmalis is from Benevolent AI

1435
00:59:49,730 --> 00:59:52,360
which is the premier AI and drug discovery company

1436
00:59:52,360 --> 00:59:55,260
previously from IBM Watson and Google Cloud

1437
00:59:55,300 --> 00:59:57,230
should be expert in healthcare AI

1438
00:59:57,460 --> 00:59:59,260
we've got her we've got Tim Bachelor

1439
00:59:59,260 --> 01:00:01,700
who's head of global commercial L&D Epsens

1440
01:00:01,700 --> 01:00:03,100
he's the farmer expert

1441
01:00:03,100 --> 01:00:04,400
and we're putting them in the room

1442
01:00:04,400 --> 01:00:06,700
we're making talk about AI um

1443
01:00:06,700 --> 01:00:07,660
they're the experts

1444
01:00:07,660 --> 01:00:09,600
I'm just gonna be there in the background

1445
01:00:09,900 --> 01:00:11,600
just to make sure it all happens

1446
01:00:11,600 --> 01:00:12,560
we're gonna let them talk

1447
01:00:12,560 --> 01:00:13,530
and it's gonna be really exciting

1448
01:00:13,530 --> 01:00:16,900
it is on the April the somethingth

1449
01:00:17,300 --> 01:00:19,130
well done there April the 11th

1450
01:00:19,130 --> 01:00:21,100
and you can register it in Collins.com

1451
01:00:22,300 --> 01:00:23,900
thank you for that uh

1452
01:00:23,900 --> 01:00:25,900
for anyone that wants more information

1453
01:00:25,900 --> 01:00:28,230
please do not hesitate to reach James

1454
01:00:28,500 --> 01:00:30,560
and for our thank you

1455
01:00:30,560 --> 01:00:32,900
I want to thank our panel thank you James

1456
01:00:32,900 --> 01:00:34,760
Ben and Manuel for being here

1457
01:00:34,760 --> 01:00:36,730
this has been incredible I

1458
01:00:36,730 --> 01:00:40,000
hope our attendees had as much fun

1459
01:00:40,000 --> 01:00:44,830
and I got some knowledge from what we shared here

1460
01:00:45,000 --> 01:00:48,200
uh Stefan thank you for being here with me

1461
01:00:48,200 --> 01:00:50,560
um and to everyone

1462
01:00:50,560 --> 01:00:52,160
I just want to let you know that

1463
01:00:52,160 --> 01:00:54,630
we also have an upcoming webinar

1464
01:00:55,530 --> 01:00:57,300
on April the 10th

1465
01:00:57,300 --> 01:00:59,660
related to the lifetime industry

1466
01:00:59,900 --> 01:01:02,500
so we're going to be posting more information

1467
01:01:02,500 --> 01:01:04,960
so if you want to do a whole schedule

1468
01:01:04,960 --> 01:01:06,960
you can come to ours on the 10th

1469
01:01:06,960 --> 01:01:09,060
and then go to James on the eleventh

1470
01:01:09,300 --> 01:01:11,200
I promise you are going to get then

1471
01:01:11,200 --> 01:01:14,500
also just to just to add a little bit of um

1472
01:01:14,800 --> 01:01:17,600
webinar fun to this we've also um

1473
01:01:17,600 --> 01:01:19,600
got a community called Digital Pharma Unlocked

1474
01:01:19,600 --> 01:01:21,700
that's got a hybrid event uh

1475
01:01:21,700 --> 01:01:22,900
on which is titled

1476
01:01:22,900 --> 01:01:25,960
to sell or not to sell on the April 25th

1477
01:01:25,960 --> 01:01:27,630
so face to face in London

1478
01:01:27,860 --> 01:01:30,200
uh or available virtually too

1479
01:01:30,200 --> 01:01:32,560
that's available on Meet Up and you'll see on my

1480
01:01:32,560 --> 01:01:34,460
my LinkedIn profile some links uh

1481
01:01:34,460 --> 01:01:36,760
links to that too but just to keep April

1482
01:01:36,900 --> 01:01:39,630
you know webinar full and lots of fun to come

1483
01:01:39,760 --> 01:01:43,460
so there you go guys schedule in your uh

1484
01:01:43,460 --> 01:01:44,460
in your agendas

1485
01:01:44,460 --> 01:01:47,660
you have the 10th occupy with platforms

1486
01:01:47,660 --> 01:01:50,800
11th with Camino and then on the 20

1487
01:01:50,800 --> 01:01:53,260
you said 25th 25th 25th

1488
01:01:53,260 --> 01:01:59,030
I had to go and see Ben it's it's mandatory so again

1489
01:01:59,060 --> 01:02:02,900
thank you everyone and we hope you thank you

1490
01:02:02,900 --> 01:02:04,500
thank you it's been great combo

1491
01:02:04,900 --> 01:02:06,330
thank you thank you

1492
01:02:06,330 --> 01:02:07,560
bye bye sir and uh

1493
01:02:07,560 --> 01:02:08,800
Happy Easter Ramadan actually

1494
01:02:08,800 --> 01:02:10,960
so happy Easter Happy Ramadan for everyone

1495
01:02:10,960 --> 01:02:13,360
yeah Ramadan came from all over the world

1496
01:02:13,360 --> 01:02:14,600
thank you bye

1497
01:02:14,600 --> 01:02:15,730
thank you bye