When we discuss digital transformation, we don’t often mention the adaptation that must occur. Our systems and people, both analogue and digital, both new and old, must get to grips with new systems and more advanced data analytics. Older and bespoke systems may remain useful despite a growing focus on the digital, and needless forcing of them into the digital realm can do more harm than good. However, digitalisation must be built on digital interconnectivity and adapting older equipment to new digitalised systems is vital. Rather than focusing on the next tech solution, businesses can take a step back and ask what innovation can come from the environment around them, because as you transform systems, you must adapt yourselves.

Discovering which systems can undergo adaptation and which must be transformed helps to keep costs low and provide a focus on our digital priorities. Furthermore, each industry can remain insular in its practices, by engaging with different perspectives challenge yourself to find true digital harmony. Join this panel of experts as we discuss:

·       Adapting legacy systems that cannot be removed to fit new digital ecosystems

·       Ensuring new tools are implemented innovatively to maximise their cost-efficiency

·       Building interconnectivity into older systems and introducing adaption layers of digital communication

·       Upgrading skillsets and generating buy-in to ensure your workforce is digitally capable

·       Creating realistic and believable transformation plans that prioritise the efficiency of the upgrade

Sponsored by: Scimcon

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Michael Lang

Global Head of Business Excellence & Transformation
Boehringer Ingelheim

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Scientific data has the scope to deliver maximum value, both directly to your team as well as the wider organisation. Adopting a centralised, accessible platform with a forward-thinking approach will support your operations and potential of current and future projects. Join this discussion to better understand how you can maximise your data, use it to its full potential, and leverage organisation-wide operations.

•       Building automation workflows for analytical data

•       Retaining full control over workflows through simpler, faster automation

•       Considering automation capabilities best suited to your individual analytical datasets

Sponsored by: SciY

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As the wheel of lab transformation turns, there is an ever-increasing pressure to digitalize faster, to reach the point of automation sooner. But rushing down your roadmap leaves you vulnerable to the pitfalls of change management: Underprepared technicians and scientists can sabotage change from within, whether it is by poor data entry or a lack of adoption, digital transformation cannot happen without buy-in from the hands that hold the equipment.

 Join us for this comprehensive guide on how to direct digitalisation strategies effectively and cooperate with those your digitalisation effects the most.

·       Effectively managing your scientists and technicians’ engagement with digitalisation

·       Learn how to draw on past experiences of digital transformation to defeat change fatigue.

·       Examine how to get differing labs digitalisation at the same pace, and how to solve differences when one falls behind

·       Building consensus for Lab changes from the ground-up, and converting scientist enthusiasm into c-suite buy-in

·    Ensuring smooth transitions between the stages of digitalisation via stakeholder buy-in from across the business

Nils Hoffmann

Director Future Testing and Methods Development
Beiersdorf

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Shirin Keyhanian

Global Director, Medical Management
Beiersdorf

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As labs find their systems increasingly digital, managing and analysing the data you collect is more important than ever. With repeat testing and data retrieval work being a blunt inefficiency, having the right data, delivered straight to your hands, is becoming a necessity. To ensure this data can be translated into usable knowledge and accessed by those who need it, your data must be as digitised as your systems.

·       Utilising newly standardised ‘Legacy Data’ to perform historical analysis of system performance and drive digital transformation

·       Eliminating unnecessary work by using data modelling to predict test results

·       Ensuring access across the data portfolio, to make sure that those who need the data have it.

Sponsored by: LabVantage

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In the dynamic world of modern laboratories, achieving harmony through efficient workflows is vital for operational excellence. Finding your way to a fully automated set of process can only start with orchestrating harmony between existing systems. Dig deep into the innovative strategies and technologies that ensure operational efficiency and allow your systems and scientists to work together at the peak of their powers.

Join this session to explore the critical role of advanced laboratory software in streamlining operations, reducing errors, and achieving operational harmony:

• Implementing cutting-edge software and tools for workflow optimization
• Utilising AI and automation to enhance operational efficiency and data accuracy
• Integrating laboratory systems to create a cohesive, efficient environment
• Maintaining consistent quality and minimising errors in laboratory processes

Sponsored by: Thermo Fisher Scientific

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Within the digital world of A.I. and ML, it is easy to get lost in the science of data modelling, rather than using an engineer’s eye to connect and automate systems. When automating with A.I. the magic can only happen when you have integrated the interface of these systems with one another. However every lab is different, and each will present a new set of challenges to automation. The only approach to automation is to balance the digital modelling with engineering direction.

Join this session to understand:

• Creating simple ML and A.I. foundations for troubleshooting clarity
• Piloting new A.I. and ML methods on currently automated labs.
•  Standardizing data collection from differing systems to provide clean and clear data and metadata
• Closing the gap between a labs automative potential and how its systems are capable of fitting together

Bruno Betoni Parodi

Scientific Director
BASF

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Developing end-to-end automation is often seen as an end goal of digital automation, but it requires both a deep technical understanding, and collaboration across all stakeholders of the business. Join this session to explore the end-to-end automation journey with key examples, and the construction of a digital platform to drive continuous process improvement. Beyond the technical aspects, the session will highlight the importance of cross-functional leadership in navigating the complexities of such a multidisciplinary project, as well as how to lead adoption of these technologies among scientists and technicians.

·       Explore the design and implementation of an automated DNA assembly pipeline, including request management, liquid handling, Nanopore sequencing, and global IT integration.

·       Learn strategies for leading multidisciplinary teams, mentoring junior scientists, and fostering collaboration.

·       Discover how best to lead project development between both internal and external stakeholders.

David Öling

Director - Molecular Biology and Recombinant Protein Production
AstraZeneca

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