Our technological capabilities, coupled with our deep understanding of Biopharma processes, form the foundation to every feature and tool developed for our products.
We are continuously researching and developing new approaches to solve real world problems, so our solutions remain at the very forefront of what is possible of bioprocess development
Below are a few of our core disciplines.
What is a Hybrid model?
Hybrid models combine two sources of knowledge, process data and engineering process knowledge, to better and more accurately understand processes. Hybrid models integrate process knowledge and data by combining mechanistic and machine learning models. Learn more.
Benefits of Hybrid Models
By considering process knowledge, hybrid models require less process data to reach an outcome thereby reducing experimentation. These models also offer the best of both worlds, retaining most of the predictability of mechanistic models, while also maintaining the flexibility of machine learning models and their ability to adapt to different process configurations.
DataHow's smart Hybrid models
DataHow’s hybrid models not only offer the predictive strengths of mechanistic models and flexibility of deterministic models, but are also enriched with DataHow’s unique technology and methodologies:
DataHow’s transfer learning capabilities are a key component behind our ability to significantly accelerate process development. The core principle behind this approach is that historical process knowledge can be transferred and used to inform the understanding and development of new processes. Our process models serve as vehicles for this knowledge transfer, taking past knowledge and transferring them between scales and products, leaving no room for misinterpretation.
How it works
DataHow's unique transfer learning technology, inspired by language processing methods, allows users to model and analyze data generated under different settings by automatically transferring them into a joint modeling space. Through this technology, knowledge can be transferred between processes, products or analytic methods, deriving insights from all your sources of data.
Why run new experiments when you can actively use data from past experiments? Importantly, the impact of knowledge transfer in DataHowLab is cumulative – as the knowledge bank within the software grows, its ability to apply past knowledge to new experiments multiplies. Already, we have realized experiment reductions of up to 80% with our customers. Imagine your process possibilities.
Active model-based learning is a unique capability which supports users through the more complex aspects of process model development.
The models are embedded with experimental design intelligence which consider the process goals, model selection, and data conditions to make suggestions for the next run of experiments.
This technology makes process model development simpler and faster. You no longer need to be a data scientist to understand the dark arts of process model development as DataHowLab provides assistance during this critical step. For specialists more at ease with this discipline, DataHowLab will make this step more efficient as active learning currently out-performs current methods and available solutions (trial-and-error or pure design of experiments) on time and cost.
A Digital Twin is a purpose centered, virtual representation of a real-world system with a bi-directional interface and connection.
When a physical system is connected to a digital twin with a robust process model, all data and system knowledge can be assessed and interrogated in a holistic, comprehensive, and interactive manner, with enriched predictive capabilities.
Why use a Digital Twin?
Digital Twins form a vital part of industry 4.0. Manual investigation, trial and error, and siloed understanding will be eliminated and replaced by digital, automated, purpose-driven, and interconnected operations. There are a range of powerful applications for this technology:
DataHowLab: A bioprocess digital twin with powerful hybrid model engines
Bioprocesses are uniquely complex requiring specific knowledge and understanding. Why use a generic digital twin within your operation when you can deploy a true bioprocess specialist? The software’s other core strength is its hybrid process models – enriching a smart system with a powerful and robust engine.
DataHow has also partnered with Securecell to help move biopharma towards industry 4.0 with digital twin technology.
Speak to one of our experts
to begin your bioprocess transformation with DataHowLab.