Lab Of The Future Survey 2024

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* 1. Tell us, what role, of the R&D process you are involved in...

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* 2. Company Sector (Pharma, Biotech, Academia, Research Group, Not for Profit, Charitable, Other)

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* 3. What type of lab do you work in? Please specify eg Pharmacology; Analytical Chemistry, Toxicology

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* 4. Where are you based?

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* 5. Where is your company HQ?

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* 6. Which of the following technologies is your company currently using in the lab?

LIMS (Laboratory Information Management Systems)

ELNs (Electronic Lab Notebooks)

Cloud data platforms (public, private, or hybrid infrastructures)

AI/ML (Artificial Intelligence/Machine Learning)

Lab wearables, VR/AR (Virtual and Augmented Reality)

Robotics/Automation

IoT (Internet of Things) devices, smart/connected devices, sensors

Automated Labs

Digital Twins

Quantum Computing

Other (please specify)

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* 7. Which of the following technologies DO YOU EXPECT your company to be using in the lab in the next two years (Tick all that apply)

LIMS (Laboratory Information Management Systems)

ELNs (Electronic Lab Notebooks)

Cloud data platforms (public, private, or hybrid infrastructures)

AI/ML (Artificial Intelligence/Machine Learning)

Lab wearables, VR/AR (Virtual and Augmented Reality)

Robotics/Automation

IoT (Internet of Things) devices, smart/connected devices, sensors

Automated Labs

Digital twins

Quantum Computing

Other (please specify)

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* 8. In which area(s) is your organisation planning to make the most investments in the next two years? (Tick your top three)

LIMS (Laboratory Information Management Systems)

Digital Twins

ELNs (Electronic Lab Notebooks)

Cloud data platforms (both public and private, and hybrid infrastructures)

AI/ML (Artificial Intelligence/Machine Learning)

Fully Automated Labs

Lab wearables, VR/AR (Virtual and Augmented Reality)

Robotics/Automation

IoT (Internet of Things) devices, smart/connected devices, sensors

People

Quantum Computing

Other (please specify)

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* 9. What do think are the biggest benefits of digitalising and automating the lab? (Tick your top three)

Improving the efficiency and effectiveness of R&D

Reducing the long-term cost of research

Accelerating innovation and new breakthroughs

Lower barriers to interoperability, data sharing and collaboration between researchers

Greater accuracy and reproducibility of research

Accelerating precision medicine

Improved sustainability

Augmenting human work power

Other (please specify)

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* 10. What are the biggest barriers to making the best use of experimental data? (Tick your top three)

Unstructured data

Data silos / inability to access data

FAIRification of data

Inability to share/tranfer analytical methods

Ontology management

Lack of metadata standardisation

Lack of infrastructure and tooling

Cultural barriers and institutional resistance to data sharing/collaboration

Lack of knowledge and expertise

Absence of documented data governance within organisations

Other (please specify)

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* 11. What help is needed to make data FAIR ( Findable, Accessible, Interoperable, and Reusable) at scale within your organization? (Tick all that apply)

Opportunity to collaborate with other organisations

Educational courses on FAIR data

Ontology training

Maintenance and management of data standards and ontologies

FAIR Data Governance frameworks

Publicly available data catalogues/shared platforms (eg. expert curated lists of FAIR data, FAIR data repositories)

Use cases that demonstrate value of FAIR Implementation

Business case examples for leadership

Best practice guides and “how-to’s”

Templates for standardization and metadata

Organization FAIR maturity models, to benchmark and guide progress in FAIR implementation processes

Other (please specify)

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* 12. What are the biggest barriers to implementing AI/ML at scale within your company's laboratory environment? (Tick your top three)

Perception that it’s not trustworthy, reliable, or responsible.

Privacy and security concerns around sensitive data

Data that is not FAIR

Low quality and poorly curated datasets (data not labelled or annotated)

Financial barriers

Cultural or social barriers

Lack of proven use cases or business cases

Lack of infrastructure and tooling

Absence of governance and regulation

Internal skillsets

Other (please specify)

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* 13. What support would you like to help you integrate AI/ML within the laboratory environment? (Tick all that apply)

Opportunity to collaborate with other organisations and share knowledge and risks

AI/ML skills and algorithm building training

Publicly available training datasets

Educational courses on AI/ML in the laboratory

Best practice use cases, business cases, guides and ‘how-to’s

Ethical, regulatory and sustainability best practices

Freely available documented data governance principles/frameworks

Industry regulation on AI/ML in the lab

Other (please specify)

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* 14. What is the single biggest barrier within your organization preventing a culture of cross lab collaboration? (Tick one)

Lack of confirmed patient consent to reuse data

No company standards or guidelines for data reuse and sharing

Tools, systems and/or workflows do not support data sharing

Concerns around safeguarding the use of data

Insufficient incentives to share data

Insufficient management encouragement

Other (please specify)

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* 15. What do you perceive as the primary challenges in implementing change in R&D labs? (Tick Your Top Three)

Resistance to change from lab personnel

Limited resources and budget constraints

Lack of clear communication and leadership support

Complexity of scientific workflows and processes

Priorities / Workload

Training

Fit for purpose solutions

Other (please specify)

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* 16. What would motivate you to join a community of pre-competitive projects? (Tick all that are relevant)

Access to shared resources and expertise

Networking opportunities with industry peers

Contributing to advancing industry knowledge and innovation

Potential for cost-sharing and risk reduction

Other (please specify)

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* 17. If you would like to receive a copy of the final survey please provide your details

Name

Business Email Address

Job Title