Quality by Learning
Data analysis and modeling services for:
- Accelerated predictive stability studies
- Design of experiments (DoE) studies
- Pharmacokinetic/Pharmacodynamic (PK/PD) modelingstudies
- Digital twin development studies
Accelerated Predictive Stability Studies (APSS)
Accelerated Predictive Stability Studies (APSS) are a scientific and statistical approach designed to evaluate the durability and degradation of pharmaceutical, biotechnological, or chemical products under exaggerated environmental conditions (temperature, humidity, light, etc.).
Unlike traditional stability studies, which span months or years, APSS allows for predicting the long-term behavior of a product in a reduced timeframe using accelerated protocols and advanced predictive models.
Pharmacokinetic/Pharmacodynamic (PK/PD) Modeling Studies
PK/PD (Pharmacokinetic/Pharmacodynamic) modeling studies are a quantitative approach essential in drug development.
They aim to characterize the fate of a drug in the body (pharmacokinetics, PK) and to link drug concentrations to their therapeutic or toxic effects (pharmacodynamics, PD).
These studies enable the optimization of dosing regimens, improve treatment efficacy, and minimize adverse effects, while accelerating the clinical development process.
Construction of a Digital Twin for a Bioprocess
A digital twin of a bioprocess is a dynamic virtual replica of a biological or industrial system, integrating mathematical models, real-time data, and artificial intelligence algorithms.
It enables the simulation, analysis, prediction, and optimization of the physical process behavior in real time while facilitating proactive decision-making.
In the context of bioprocesses (e.g. fermentation, cell culture, biomolecule production), the digital twin is particularly valuable for improving efficiency, reproducibility, and product quality.
The system typically consists of three components: the physical layer, digital layer, and interface layer.
Statistical Design of Experiments (DoE) and Data Analysis
The statistical design of experiments (DoE) is a structured and efficient methodology used to explore, understand, and optimize complex processes, such as bioprocesses (fermentation, cell culture, biomolecule production, protein purification, etc.).
It enables the maximization of information obtained from a limited number of experiments while minimizing costs, time, and resources.
DoE is particularly useful for screening critical factors, analyzing interactions between factors, building response surfaces to identify optimal conditions and improve process robustness.
Dynamic Model Identification Studies for Process Control
Dynamic model identification studies are a critical step inautomation and process engineering, aimed atdetermining a mathematical model capable of describingthe dynamic behavior of a physical system (e.g. bioreactors, distillation columns, chemical processes).
This model is then used to design advanced controlstrategies (e.g., PID control, model predictive control,robust control) to optimize process performance, ensurestability, and guarantee robustness against disturbances.
Our clients love us
Thanks to depth attentiveness and comprehension of client’s needs, CYBERNANO is a reliable partner that delivers on time and complete outcomes. Highly competent in biological data modeling and analyses, the team shares their knowledge with pedagogy.
Céline BARRAUD
SANOFI PASTEUR
CYBERNANO has done a great job in assisting us to accelerate the optimization of our mRNA and lipid based nanoparticle platform. The CYBERNANO team combines excellent technical knowledge on data modelling with a customer oriented mindset and can do attitude. Highly recommended!
Stefaan De Koker
eTheRNA
Thanks to CYBERNANO expertise in bioproduction process optimisation Steminov has accelerated its drug candidate development. The QbD approach and platform of CYBERNANO is unique and a must have in any company working in bioproduction.
Julie Hutin
StemInov
CYBERNANO team has shown great professionalism, flexibility, and availability in the execution of their mission. CYBERNANO is attentive to the customer’s needs and has been able to suggest solutions compatible with industrial constraints through their meticulous data analysis
Joannah N’GOMPAZA-DIARRA
SEQENS
You want to save 20% of development time !?
Quality by Design allows to identify the critical quality attribute of your products and critical process parameters, but also to determine the relationship between them.
This knowledge makes it possible to predict the optimal product formulation and manufacturing recipe, as well as robust analytical procedures.
