Biotechnology and pharmaceutical space - Primary, contract lab, product or service provider
Startup companies (e.g. series A) who must identify the best talent and tools in which to invest to achieve PoC and beyond.
A large biopharma company seeking meaningful improvements - digital transformation, automated laboratories, team topologies, knowledge management
Pre-clinical stage research and development
Analytical testing and diagnostics
Any therapeutic modality (not med devices)
Drug Discovery requires a complex process subject to the same rules as any other process: the output is only as good as the weakest component in the process.
We can identify and correct this together to reduce cost, improve quality, and raise productivity even in the most dynamic or rigid environments.
⏩Prioritize your business objectives and focus
🧩Ensure you have the right teams and talent
🏆Define and communicate your business objectives to drive team autonomy and productivity
⚖️Balance your OpEx and CapEx with your timelines and budget
🌐Optimize your internal and external collaborations and outsource partners
🚀Define your digital transformation and make it happen!
Facility layout and infrastructure planning
Equipment and instrumentation selection, implementation oversight, operational planning
Supply chain planning
Accelerate your entire design-make-test-analyze cycle
Adopt agile methods for project progression from speculative idea to the clinic
Analyze your science to architect the best fit from commercially available automation
Ensure your teams have the right talent to maximize the impact of your automation and evolve your automation as your science evolves
Integrate existing technology in novel ways to fill gaps in commercial solutions
Identify the right partners and solution architecture where new tehcnology must be created
Find commercial solutions to accelerate your science by improving and reducing the number of tools you use to enhance the user experience for your researchers
Ensure modern and feasible data and information security policies exist and are met
Ensure the entire discovery cycle is supported by your information systems from hypothesis to conclusions
Ensure FAIR and contextualized data in order to support modern AI/ML innovations
Develop your talent to ensure you can autonomously maintain synergy with your evolving science
Training: Develop your own in-house expertise
Liquid handling
Chromatography techniques, hardware, software
LIMS/ELN administration