As every researcher in early development knows, there is constant pressure to identify high-quality drug candidates—while also increasing the speed and efficiency of the discovery process. Yet, increasing the quality of a candidate traditionally implies adding more steps—more models, more analysis, more complexity. What if you could boost candidate quality without disrupting your current workflow?
That’s exactly what ADMET Predictor® enables through its powerful, easy-to-integrate REST API. With just a few lines of code, you can bring industry-leading predictive models directly into your existing platforms, tools, and pipelines—no manual steps, just smarter, more informed decisions at every stage.
Seamless Integration in Real-World Platforms
Many of our partners are already reaping the benefits of this flexibility. Roche, for instance, has successfully embedded the HTPK (High-Throughput Pharmacokinetics) module from ADMET Predictor into their in-house drug design platform1. By doing so, their scientists can assess species-specific PK parameters—such as clearance, fraction unbound, and bioavailability—on-demand, without leaving their core design environment.
The most requested model for integration is our industry-leading pKa model. It provides unmatched accuracy in predicting acid/base ionization states—an essential factor for solubility, permeability, and bioavailability predictions—and includes pK₅₀ values for individual functional groups.
Customers frequently integrate this and other models into various in-house and commercial platforms, including LiveDesign (Schrödinger Life Science), allowing for real-time property prediction and optimization directly within their compound design workflows. This seamless incorporation means that chemists and modelers can access predictive insights in the same space where ideas are generated—keeping the momentum of innovation intact.
Power Tools for Drug Design and Optimization
ADMET Predictor goes far beyond traditional property prediction. Its suite of drug design and optimization tools is engineered to support the full span of your decision-making process:
- HTPK Module: Quickly assess absorption, distribution, metabolism, and excretion characteristics across human, rat, mouse, dog, and monkey, with time-profile visualizations and parameter sensitivity analysis.
- DILIsym® Inputs Module: Leverage quantitative systems toxicology (QST) modeling to assess the risk of drug-induced liver injury, enhancing safety profiles earlier in the pipeline.
- Metabolism Module: Predict metabolic pathways and identify potential sites of metabolism (SOMs), helping to avoid metabolic liabilities.
- Multi-Criteria Decision Analysis (MCDA): Make confident optimization decisions using multiparameter scoring functions that align candidate profiles with your project’s success criteria.
These modules aren’t just powerful—they’re modular. Whether you’re building a proprietary platform or using commercial design tools, ADMET Predictor’s REST API makes it easy to plug in just the functionality you need, right where you need it.
Smarter Decisions, Same Workflow
Improving your drug candidate quality doesn’t have to mean reengineering your process. With ADMET Predictor, you get the predictive power of cutting-edge ADMET, PK, and optimization models—right at your fingertips, wherever you’re already working. Better insights, better candidates, no extra steps.
Ready to see how easy it is to elevate your workflow? Contact us to schedule a demo or learn more about our REST API and other integration capabilities.
- Umehara K, Klammers F, Walter I, et al. Prediction of hepatic metabolic clearance in rats and dogs using long-term cocultured hepatocytes. Drug Metabolism and Disposition. 2025;53(4). doi:10.1016/j.dmd.2025.100055