Optimisation, from Development to Scale-Up into Manufacturing

PAT enables access to powerful analytics and provides a detailed insight into your process, yielding improved monitoring, control and optimisation. But to realise the full potential of PAT, your journey shouldn’t end with the hardware. PharmaMV transforms PAT data into easy-to-digest information, allowing decisive actions to be taken quickly and with confidence. PharmaMV is an integrated

Continuous Process Verification In pharmaceutical process and product development, design and qualification stages are succeeded by Continuous Process Verification ( CPV ). This provides ongoing assurance that the product attributes remain within compliance for regulatory bodies. PharmaMV provides a comprehensive set of CPV tools which facilitate the integration and interfacing to your process

Multivariate Analysis and its application in Statistical Process Control Multivariate Analysis (MVA) includes a variety of mathematical techniques which can handle multiple inputs and outputs, and the interactions which occur between them. These MVA techniques, such as Principal Component Analysis (PCA) , Partial Least Squares (PLS) and Multiple Linear Regression (MLR) find application whenever

Build, Validate and Optimise Your Process Digitally Digital Design and Scale-Up Digital Design techniques can be used to rapidly develop and test Advanced Process Control (APC) and monitoring schemes in-silico, using parameterised mechanistic models as Digital Twins. The PharmaMV platfom is used to apply process response tests to a mechanistic process model, to generate a statistically rich

Predictive, Optimised Control of Batch and Continuous Processes Advanced Process Control for Pharmaceutical Manufacturing Advanced Process Control (APC) describes a set of tools used in process industries that are far more sophisticated than basic control strategies, such as PID control. Model Predictive Control (MPC) is a well-proven APC technique widely used in many process industries that

Machine Learning - The Future Of Pharma Faster process optimisation using ML enabled workflows Real processes have numerous objectives. Being able to locate the optimal trade-off point where all targets are met is no easy task. Machine Learning enabled workflows make this easier than ever before. Use previous experimental results to create models that can select the next most important

From Design to Development To Production - One Integrated Platform Pharma MV incorporates a dedicated suite of tools for real-time Design of Experiments execution. The time to steady state, time at steady state and rate-of-change tolerance at steady state are defined This then determines the minimum experiment time required Users can quickly create intuitive templates for data

Advanced Design of Experiment, process monitoring, predictive control

Optimised drug substance and drug product development and manufacturing