Junior Biologics Formulation
Brochures and specifications | 2017 | Unchained LabsInstrumentation
Biologics formulation is a critical step in the development of protein-based therapeutics, impacting stability, efficacy and manufacturability. High-throughput, automated workflows accelerate preformulation studies, reduce manual errors and expand the range of conditions tested, thereby de-risking downstream development.
This whitepaper introduces "Junior," an integrated automation platform by Unchained Labs, designed to streamline key formulation tasks—pH measurement, viscosity determination and visual inspection—via configurable high-throughput protocols. The goal is to demonstrate how automation elevates developability assessment and formulation robustness studies.
The Junior platform combines robotic handling modules with dedicated analytical stations. Core components include:
Automated pH measurements of a full 96-well plate, including calibration and washes, were completed in less than 30 minutes, eliminating manual bench time. Viscosity assays ran five times faster than conventional methods, reducing hands-on time by approximately 40-fold. The 3-in-1 visual inspection improved objectivity by capturing standardized images and matching them against quality thresholds. The seamless linkage of experimental parameters and analytical outputs within the LEA environment enabled rapid decision-making and minimized data handling errors.
The Junior platform offers multiple advantages:
This approach is particularly valuable for biopharmaceutical R&D, QA/QC laboratories and contract testing facilities aiming to accelerate candidate selection and optimize formulation stability.
Emerging directions include integration of machine learning for predictive formulation design, expansion of on-line analytical modules (e.g., DSC, DLS), tighter connectivity with laboratory information management systems and enhanced miniaturization for ultra-high-throughput screening. These developments promise to further reduce timelines and sample requirements while providing deeper insight into formulation behavior.
The Junior automated platform transforms traditional formulation workflows by combining high-throughput pH, viscosity and visual analysis within a unified, software-driven environment. By removing manual bottlenecks and linking experimental design to analytics, it accelerates biologics developability assessments and supports informed decision-making throughout drug development.
No external references were provided in the source document.
Sample Preparation, RAMAN Spectroscopy, XRD
IndustriesManufacturerUnchained Labs
Summary
Significance of the Topic
Biologics formulation is a critical step in the development of protein-based therapeutics, impacting stability, efficacy and manufacturability. High-throughput, automated workflows accelerate preformulation studies, reduce manual errors and expand the range of conditions tested, thereby de-risking downstream development.
Aims and Study Overview
This whitepaper introduces "Junior," an integrated automation platform by Unchained Labs, designed to streamline key formulation tasks—pH measurement, viscosity determination and visual inspection—via configurable high-throughput protocols. The goal is to demonstrate how automation elevates developability assessment and formulation robustness studies.
Methodology and Instrumentation
The Junior platform combines robotic handling modules with dedicated analytical stations. Core components include:
- Multi-channel pH arm with four probes for automated 96-well measurements including calibration, sampling and wash steps
- Viscosity station for Newtonian and non-Newtonian fluids requiring as little as 100 µL and delivering results in under 6 minutes
- Visual inspection station performing simultaneous color, turbidity and visible particle counts with image capture and archival
- Robotic vial/plate gripper, plate racks, waste management and sample hotel for continuous unattended operation
- LEA software suite: Library Studio for experiment design, Automation Studio for execution and PolyView for integrated data review and reporting
Main Results and Discussion
Automated pH measurements of a full 96-well plate, including calibration and washes, were completed in less than 30 minutes, eliminating manual bench time. Viscosity assays ran five times faster than conventional methods, reducing hands-on time by approximately 40-fold. The 3-in-1 visual inspection improved objectivity by capturing standardized images and matching them against quality thresholds. The seamless linkage of experimental parameters and analytical outputs within the LEA environment enabled rapid decision-making and minimized data handling errors.
Benefits and Practical Applications
The Junior platform offers multiple advantages:
- Substantial reduction in manual labor and bench time
- Consistent, reproducible measurements across large sample sets
- Broader exploration of formulation space with minimal sample consumption
- Integrated data management supporting regulatory-grade reporting
This approach is particularly valuable for biopharmaceutical R&D, QA/QC laboratories and contract testing facilities aiming to accelerate candidate selection and optimize formulation stability.
Future Trends and Opportunities
Emerging directions include integration of machine learning for predictive formulation design, expansion of on-line analytical modules (e.g., DSC, DLS), tighter connectivity with laboratory information management systems and enhanced miniaturization for ultra-high-throughput screening. These developments promise to further reduce timelines and sample requirements while providing deeper insight into formulation behavior.
Conclusion
The Junior automated platform transforms traditional formulation workflows by combining high-throughput pH, viscosity and visual analysis within a unified, software-driven environment. By removing manual bottlenecks and linking experimental design to analytics, it accelerates biologics developability assessments and supports informed decision-making throughout drug development.
References
No external references were provided in the source document.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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