#lab innovation

Automated platforms and robotic systems are fundamentally reshaping laboratory workflows in the life science and process industries, spanning sample preparation, liquid handling, and high-throughput analytical processes. As walk-away automation and collaborative robots become more widely deployed, questions of system integration, method transfer, and the interface between automated laboratory environments and production or quality systems gain relevance. Contributions addressing both technological advances and practical implementation experience are invited.

• Laboratory automation
• High-throughput processes
• Collaborative robots (cobots)

AI and deep learning methods are increasingly embedded in laboratory workflows, enabling pattern recognition in complex analytical datasets, predictive modelling of experimental outcomes, and accelerated method development. Applications range from spectroscopic data interpretation and image-based quality assessment to autonomous experimental design. Questions of model validation and data quality present concrete challenges that researchers and practitioners are invited to address.

• Machine & deep learning in the laboratory
• Analytical data interpretation
• Predictive modelling
• Autonomous experimental design
• Image-based quality assessment
• Model validation

Self-driving laboratories, which integrate closed-loop experimentation with automated platforms and data-driven decision-making, are gaining traction across chemistry, biotechnology, and analytical science. By combining robotic execution with algorithmic experiment planning, these systems can accelerate method development and materials discovery with minimal human intervention. Contributions are sought on architectures, workflows, and practical experience from implementations in research and laboratory environments.

• Walk-away automation
• Workflow orchestration
• Closed-loop experimentation
• Algorithmic decision-making (ADM)

In the life science industries, the laboratory has evolved from a purely analytical environment into an integrated platform that bridges early-stage research, bioprocess development, and quality assurance. Across biotechnology, pharmaceutical, and diagnostics applications, laboratory infrastructure increasingly determines the pace and reliability of translation from discovery to production. Contributions are invited that address platform concepts, instrumentation strategies, and the integration of laboratory workflows with downstream development and manufacturing stages.

• Life science laboratory platform
• Lab-to-production translation
• Integrated laboratory workflows
• Quality assurance

Advances in optical, spectroscopic, and sensor-based techniques are expanding the scope and precision of measurements in life science and process industry. From hyperspectral imaging and inline spectroscopy to miniaturised sensor arrays, new methods and tools enable faster characterisation, improved process understanding, and more reliable quality assessment. Contributions are sought on novel imaging and sensing approaches, as well as analytical methods and their integration into laboratory and industrial workflows.

• Analytical methods
• Spectrometry and spectroscopy
• Optical imaging techniques
• Sensor systems and technology

Effective transfer of laboratory results into production requires more than technical accuracy: it demands structured data flows, standardised interfaces, and close collaboration between laboratory personnel and production teams. An improved connectivity between the lab and production can ultimately lead to better products, improved efficiency, and increased customer satisfaction. Share your experiences at the ACHEMA 2027 Congress!

• Data simulation, modelling and transfer
• LIMS, ELN
• Manufacturing execution systems (MES)
• Quality control
• Cross-functional collaboration

Laboratories in the chemical, pharmaceutical, and life science industries are among the most resource-intensive facilities in the process sector, consuming significant amounts of energy, water, solvents, and single-use consumables. Measures like energy-efficient equipment, solvent recovery, waste minimisation, and sustainable procurement play a key role in achieving the UN Sustainable Development Goals. Contributions are invited on guidelines, best practices, and assessments methods.

• Energy efficiency and smart energy management in laboratories
• Solvent recovery and waste minimisation
• Sustainable procurement
• Environmental assessment of labs

Planning, building and maintaining laboratories that meet today’s scientific and operational requirements demands a holistic approach, from initial concept and user-needs analysis through technical design to commissioning and operation. In life science and process industries, new working models and hybrid research environments are reshaping how laboratory spaces are conceived. Contributions are sought on integrated project methodologies, stakeholder engagement, digital planning tools, operational readiness, and lessons learned from completed laboratory projects.

• Laboratory planning and design
• Digital planning tools
• Operational readiness
• Stakeholder engagement