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The challenges of the analytical space are clear. Organizational barriers often make it difficult for scientists to collaborate and leverage their most important asset – data. The Thermo Fisher Connect Platform breaks down these barriers to connect people, instruments, and systems. This begins with integration to the data created through analytical techniques. The Thermo Scientific Ardia Platform connects IC, GC, LC and MS data, to provide a holistic view and enable deeper analysis, providing scientists a clearer path to the next significant breakthrough. Since scientists don’t operate alone, it’s crucial to connect scientific data with production, operational and other enterprise data. Thermo Fisher Connect is the conduit between the lab and the enterprise.
As an organisation committed to helping customers deliver life-changing medicines, we have always been focused on commercial excellence, and the importance of driving the most value from what is available to us. From a data and information perspective we recognise there is significant opportunity to build data mobility, make connections and automate processes to deliver greater impact to our customers. In this talk, I will discuss the challenges PPD recognise as being central to customer success, the digital solutions we considered as part of our path forward, and our story so far.
Mark Fischer-Colbrie, Chief Executive Officer, Strateos
Many new lab informatics projects are destined to be cloud-based, which is great for flexibility, ease of access, and deployment speed. However, a common roadblock is how to connect on premise lab equipment to cloud-based informatics solutions, because the method must be both scalable and secure while navigating different layers of firewalls and private networks. Indeed, such connections can be challenging even for on premise software networking to on-premise instruments.
In this session, we will present some best practices for equipment connections that BIOVIA has determined from working closely with customers in the life sciences industry. Additionally, we will discuss the importance of data governance for standardizing instrument readings across your organization.
Labs are full of hidden costs and expenses related to asset management. LabOps teams are held accountable to tight budgets and demanding technology requirements. A powerful strategy to manage these conditions is leveraging equipment usage data to guide purchasing decisions, service contracts, retirements, and beyond to maximize ROI. In this session, Elemental Machines and Zentalis Pharmaceuticals will present use cases for these benefits:
● Harnessing data-driven purchasing decisions with advanced analytics and usage data during times of supply chain crisis
● Data management strategies and resources supporting consistent quality & compliance requirements
● Practical cost-saving applications through service contracts, underused equipment, and maximizing lab spaces
● Best practices and tools to empower lab teams for greater technology adoption, improved processes and proven ROI outcomes
Fabio Rancati Lead Optimization Unit Head , Chiesi Farmaceutici
The digital world has immense potential to transform the value we get from experiments. Digitalization efforts often focus on how we can gather and structure experiment data and metadata so that companies can make best use of the information that they’re continually producing. However, this invariably leads to a misalignment: the company needs highly structured and standardized data with as much contextual metadata as possible, while -due to time pressures- the scientist wants to just gather the data and context required to draw immediate conclusions and move on. This misalignment means that (meta)data will rarely be recorded in sufficient detail to get anything but the most immediate value.
Marc Siladi, Executive Director Operations, Strateos
Real-time contextualization to enable data-driven decisions
Decision based on historical data are only as good as the data itself
Downstream data repositories intervene poorly on the data collection process in real-time
Efforts must be made to ensure data quality at the point of capture
The digital transformation journey from a traditional to an intelligent lab
The key elements and prerequisites for this transformation
The infrastructure for collaboration and exchange of scientific data
The role does data organization and standardization
The Sustainable Lab is the Lab of the Future
Generating FAIR Lab Data at AbbVie
Rainer Winnenburg, Team Lead Literature-based Scientific Discovery – FAIR Data, AbbVie
Richard Snell, Director, Global Scientific Services, GSK
The session will cover some examples of industry-wide projects, programs and communities of interest facilitated by the not for profit organization Pistoia Alliance.
1. IDMP Common Core Ontology Project – the goal of the project is to enable deep, semantic interoperability based on FAIR principles to augment the existing ISO IDMP standards of the European Medical Agency
2. User Experience for Life Sciences (UXLS) Community – which develops and delivers numerous best practice guides, blogs, and toolkits to increase the adoption of user experience (UX) practices in life sciences.
3. D&I IN STEM Leadership Program – which promote diversity in top executive roles and aims at improving leaders’ understanding of the importance of D&I industry-wide. The program alumni include participants from 17 large size pharma organizations.
• Virtual Reality (VR) is a mature technology, used for 3D insights and connecting teams across the globe
• UCB developed a re-usable in-house VR platform for drug design with an academic partner
• We present key learnings on setting up an industry-academic collaboration and on the introduction of this type of new technology
Does the digital lab solve scientists’ problems? Is automation the key to advancement? The real route to progress is in making small changes that have a significant impact. In this talk we’ll discuss our three rules to make lab life easier using digital solutions that are accessible today:
Protect IP while making data more accessible
Reserve instrument time, monitor experiments and analyze data
Empower scientists to manage resources
– Data exists, but how do we utilize it to the fullest potential?
– Standardization is the stepping stone to data FAIRification
– What the data journey looks like for life science companies
– How to get tangible impact and continue to build on this
– Shooting for the stars if you get this right
