Pharmacokinetic (PK) Prediction Service
Accurate prediction of pharmacokinetics (PK) of drugs will help better select compounds for in vivo studies, thereby reducing the number of experiments required and the associated costs. CD ComputaBio provides comprehensive PK prediction services, which are critical in the early stages of drug discovery and development. Leveraging our advanced computational modeling and simulation technologies helps maximize the value of your ADME and PK data.
Introduction to Pharmacokinetic (PK) Prediction
PK is the result of a complex interaction between compound properties and physiology, and detailed characterization of molecular PK parameters during preclinical studies is key to understanding the relationship between applied dose, exposure, and pharmacological action. In order to avoid the early advancement of compounds with undesirable properties and reduce animal testing, it is highly desirable to predict human PK based on the chemical structure of the compound. Existing PK characterization methods generally rely on in vivo studies in animal models such as mice, rats, and dogs. This is currently the gold standard for making these PK predictions, however, their overall correlation with in vivo clinical studies is low, and the failure rate of compounds entering the clinic is as high as 92%. Moreover, these studies are expensive and time-consuming. In silico prediction, as an alternative method, is becoming increasingly important. It uses existing compound data and advanced modeling techniques to predict the human pharmacokinetic properties of compounds at an early stage, thereby reducing reliance on animal experiments. These methods help to screen candidate compounds with good pharmacokinetic properties and reduce the risk of clinical trial failure.
Fig. 1 AI-PBPK model is used to predict the PK parameter of compounds. (Zhang M, et al.; 2025)
Our Services
At CD ComputaBio, our scientists use advanced computational tools and algorithms to give you a strong start in compound optimization. Thanks to state-of-the-art modeling techniques and extensive expertise, we provide clients with predictions of key PK parameters in humans and multiple species based solely on compound structure. Compound synthesis, ADME, or PK screening are prioritized based on the most favorable predicted PK.
Importantly, the drug pharmacokinetic PK prediction services we provide can target different types of drug molecules, including but not limited to small molecules, proteins, antibodies, peptides, oligonucleotide fragments, and even advanced drug delivery systems.
PK Parameter Prediction Service
We predict key PK parameters in humans and different species based on compound structures and ADME data. These parameters include absorption rate, bioavailability, distribution volume, clearance, half-life, area under the curve (AUC) and Cmax, etc. Based on the most favorable predicted PK, we determine the priority development direction of the compound for our customers.
PK Curve Prediction Service
We also provide PK profile prediction services. By simulating the concentration-time curve of the compound in vivo, we can maximize the value of your early ADME data in humans. Our team of experts uses advanced modeling techniques, combined with physiological parameters and drug properties, to accurately predict the PK profile of intravenous and/or oral dosing regimens (single or repeated dosing) to determine effective dosing regimens.
Comprehensive PK Modeling and Prediction
To meet more complex R&D needs, CD ComputaBio provides comprehensive PK modeling and prediction services. We are not limited to the prediction of a single parameter or curve but build comprehensive pharmacokinetic models. This includes population pharmacokinetic (PopPK) modeling, physiologically based pharmacokinetic (PBPK) modeling, etc. Through these models, we can simulate drug behavior under different species, pathological states and administration methods.
More
We also provide a range of additional services to support your compound optimization, including ADME/Tox prediction, tissue distribution prediction, and customized computational solutions. Our team of experts is committed to providing you with high-quality computational support to accelerate your research and development process and meet your unique project needs.
Advanced Modeling Technology
PBPK Modeling
In the drug discovery process, we focus on pioneering the use of generic PBPK models to predict the performance of lead compounds during the identification and optimization phases. In addition to customized PBPK modeling for specific needs, we also provide unique screening services that provide reliable PK predictions using early ADME data, enabling the selection of the best compounds based on predicted human PK parameters.
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Machine Learning and QSAR/QSPR Modeling
We have many years of expertise in using machine-learning techniques to predict ADME, pharmacokinetics, and toxicity in drug development. By building machine learning-based models and quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) models, we are able to predict compound properties based on their structure, or integrate structural properties and in vitro data to predict complex in vivo properties.
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PK/PD Modeling
Our PK/PD modeling predictions are dedicated to providing comprehensive pharmacokinetic and pharmacodynamic analysis of your compounds. Our expertise includes but is not limited to, compartmental modeling, non-compartmental modeling, vascular and extravascular PK/PD modeling, systems pharmacology models, and prodrug/active metabolites to support your in-depth understanding of the PK/PD properties of your compounds.
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Service Highlights
Accurate Insights
We use state-of-the-art computer modeling techniques to provide accurate and reliable PK predictions to accurately guide rational drug design decisions.
Time and Cost Efficiency
By leveraging computational methods, we accelerate the drug development process, saving time and resources compared to traditional experimental methods.
Fast Turnaround Time
We are committed to delivering results as quickly as possible without compromising service quality.
PK prediction is one of the key steps in driving new drug development using computational methods. CD ComputaBio provides cutting-edge PK prediction services to accelerate the client's R&D process. Our scientists have extensive experience and expertise and are committed to providing you with high-quality computational support. Please don't hesitate to contact us, if you are interested in our services.
References:
- Zhang M, et al. Prediction of pharmacokinetic/pharmacodynamic properties of aldosterone synthase inhibitors at drug discovery stage using an artificial intelligence-physiologically based pharmacokinetic model. Front Pharmacol. 2025; 15:1578117
- Wu K, et al. Predicting pharmacodynamic effects through early drug discovery with artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) modelling. Front Pharmacol. 2024;15:1330855.
- Zhu L, et al. Prediction of the pharmacokinetics and tissue distribution of levofloxacin in humans based on an extrapolated PBPK model. Eur J Drug Metab Pharmacokinet. 2016;41(4):395-402.
* For Research Use Only.
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