Drug Release Rate Modeling Service
Drug release rate is a key factor affecting drug efficacy and safety. It determines the release rate and absorption degree of the drug in the body, which directly affects the bioavailability and therapeutic effect of the drug. Accurate drug release rate modeling helps to deeply understand and predict the release behavior of drugs under different conditions. CD ComputaBio has rich experience and expertise in the field of drug release rate modeling. Whether you want to optimize candidate compounds in the drug discovery phase through drug release rate modeling or conduct formulation development in the drug development phase, our experienced experts can provide you with the most professional solutions.
Introduction to Drug Release Rate Modeling
Drug release rate represents the rate at which the active drug ingredient is released from its dosage form into the dissolution medium or the body, which significantly affects its therapeutic effect and overall impact on the treatment outcome. It is a complex phenomenon that, depending on the delivery system, may include one or more of the following processes: drug diffusion, drug dissolution and/or drug distribution, as well as penetration, swelling, erosion, disintegration and/or degradation of the delivery system. Therefore, establishing an accurate drug release model is essential for designing effective drug delivery systems and predicting drug performance in vivo. Drug release behavior is a dynamic process that can be accurately described and predicted by mathematical models and computer modeling. Traditional drug release models include zero-order, first-order, Higuchi model, Korsmeyer-Peppas model, etc. With the development of modern computing technologies, such as machine learning and computational fluid dynamics, new tools and methods are provided for drug release rate modeling. These technologies can handle complex systems, and improve the accuracy and predictive ability of the model, thus designing efficient drug delivery systems and optimizing drug performance in vivo.
Fig.1 The major framework of ML in drug release modeling. (Aghajanpour S, et al.; 2025)
Our Services
As an AI-driven drug development service provider, CD ComputaBio provides professional drug release rate modeling services that can deeply analyze the release kinetics of traditional small molecule oral drugs and accurately predict their release behavior in vivo and in vitro. What attracts our customers is that our team of experts is not only good at dealing with simple small molecule drugs, but also has rich expertise and experience in dealing with biological macromolecule preparations, such as complex compounds such as nucleic acids, proteins, antibodies, etc. These macromolecular preparations are usually administered by injection, transdermal, or topical administration.
Furthermore, for sustained/controlled-release preparations and new nano-delivery systems, we can also use advanced machine learning technology to help you accurately predict their release and accelerate your drug development process. Our services include but are not limited to:
Drug Release Kinetics Modeling and Simulation
We provide mathematical modeling of drug release processes from the molecular level to the macroscopic level, and apply different mathematical models, such as zero-order, first-order, Higuchi model, Korsmeyer-Peppas model, etc., to simulate release kinetics and gain a deep understanding of the mechanism of drug release from preparations.
In Vitro and In Vivo Release Behavior Prediction
Based on the in vitro experimental data and physiological parameters provided by customers, our expert team simulates the effects of different physiological conditions such as pH value and enzyme environment on drug release and accurately predicts the release and absorption behavior of drugs in vivo.
Biomacromolecule Release Analysis
For biomacromolecules such as nucleic acids, proteins, antibodies, etc., we have established a special release model that can analyze the stability and release characteristics of these macromolecules in different delivery systems.
Multi-Route Drug Delivery Simulation
Based on the effects of physiological barriers and environmental factors including gastrointestinal pH, skin barrier, lung mucosa, etc., unique to the drug delivery route on drug release, we have established a special release model to simulate the release and absorption behavior under different drug delivery routes.
Sustained/Controlled Release & Nano delivery System Simulation
For sustained and controlled release preparations and new nano delivery systems such as nanoparticles, liposomes, polymer microspheres, etc., we use advanced computational simulation technology to predict the drug release curve by simulating the drug encapsulation, release and delivery process.
More
CD ComputaBio provides customized drug release rate model development and data analysis services based on the specific needs of our customers. No matter which stage of drug development you are in - candidate compound optimization in the drug discovery phase, or formulation development in the drug development phase - we can provide you with professional solutions.
Methods for Drug Release Rate Modeling
Machine Learning
Utilizing machine learning algorithms, such as artificial neural networks (ANN), support vector machines (SVM), deep learning, etc. to capture complex nonlinear relationships that are difficult to describe with traditional models from a large amount of experimental data, and achieve accurate prediction of complex drug release systems.
Release Kinetics Model
We apply a variety of classical and advanced mathematical models to describe drug release kinetics, including zero-order model, first-order model, Higuchi model, Korsmeyer-Peppas model, etc., and select the most suitable model according to the characteristics of the drug formulation.
Molecular Dynamics (MD) Simulation
For complex drug release systems, we also use MD simulation technology to explore the drug release process at the molecular and atomic levels. By simulating the interaction between drug molecules and carrier materials, such as polymer matrices, nanoparticles, and liposomes, we predict the release characteristics of drugs under different conditions.
Combining traditional mathematical models with advanced computational simulation techniques, CD ComputaBio can select the most appropriate modeling approach and accurately predict the release behavior based on your specific formulation type and drug release characteristics. Please don't hesitate to contact us, if you are interested in our services.
References:
- Aghajanpour S, et al. Utilizing machine learning for predicting drug release from polymeric drug delivery systems. Comput Biol Med. 2025;188:109756.
- Alshahrani SM, et al. Modeling and validation of drug release kinetics using hybrid method for prediction of drug efficiency and novel formulations. Front Chem. 2024;12:1395359.
* For Research Use Only.
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