Peptide Drug ADMET Prediction Service
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PK/PD (Pharmacokinetic/Pharmacodynamic) correlation models, linking drug concentration to biological response to predict dose-effect relationships.
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Structural and physicochemical descriptor analysis, assessing parameters such as hydrophobicity, charge, and stability to predict permeability and clearance.
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Quantitative structure-activity relationship (QSAR) and structure-based models to predict bioavailability, enzymatic degradation, and potential toxicity.
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UPLC-HRMS and LC-Orbitrap HRMS analytical integration for validating peptide degradation and metabolite formation.
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Early-stage candidate prioritization before synthesis or biological testing
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Optimizing peptide design in therapeutic areas such as oncology, neurology, infectious disease, and metabolic disorders
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Supporting decision-making for formulation and delivery strategy (e.g., oral versus injectable)
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Guiding risk mitigation by identifying peptides with high toxicity or poor pharmacokinetics early
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Assisting in regulatory or preclinical documentation by providing prediction reports on peptide behavior in vivo
MtoZ Biolabs offers a specialized Peptide Drug ADMET Prediction Service that combines advanced computational modeling, machine learning algorithms, and pharmacokinetic simulation to forecast absorption, distribution, metabolism, excretion, and toxicity properties of therapeutic peptides. This service provides researchers with critical insights into peptide drug-like behavior, enabling smarter candidate selection and accelerated development.
Background
Peptide therapeutics occupy an increasingly prominent place in modern drug development. They lie between small molecules and biologics, offering benefits such as high specificity, relatively low toxicity, and the ability to engage challenging targets like protein–protein interactions. However, peptide drugs also bring unique hurdles: their susceptibility to enzymatic degradation, poor oral bioavailability, rapid clearance, and sometimes unexpected toxicity.
ADMET prediction refers to assessing how a molecule will be absorbed into the body, where it will be distributed, how it will be metabolized, how it will be excreted, and whether it may pose toxicity risks. For peptide drugs especially, early and reliable ADMET forecasting is essential to avoid costly failures downstream in preclinical or clinical studies. By predicting ADMET parameters before synthesis or extensive laboratory testing, researchers can prioritize candidates with favorable pharmacokinetics, low toxicity, and higher likelihood of therapeutic success.
Du, B. X. et al. iScience. 2023.
Figure 1. Comprehensive ADMET Profile
Principle of Peptide Drug ADMET Prediction
MtoZ Biolabs' Peptide Drug ADMET Prediction Service is based on integrated computational pharmacology and experimental pharmacokinetics. Using physiologically based pharmacokinetic (PBPK) modeling and machine learning algorithms, we simulate the absorption, distribution, metabolism, excretion, and toxicity (ADMET) behavior of peptides before experimental validation.
Our service framework combines:
Peptide Drug ADMET Prediction Service at MtoZ Biolabs
💠Pharmacokinetic and Pharmacodynamic Modeling
We apply PBPK models and compartmental simulations to forecast peptide absorption routes, distribution kinetics, and systemic exposure, supporting dose design and administration strategy optimization.
💠Stability and Metabolic Evaluation
Peptide degradation and stability are evaluated using simulated gastric and intestinal fluids, plasma, and blood samples. These tests identify cleavage hotspots and guide sequence modification to enhance resistance to enzymatic hydrolysis.
💠Plasma Protein Binding and Distribution Assessment
Rapid equilibrium dialysis and ultrafiltration methods are used to measure protein-binding efficiency, informing bioavailability and half-life predictions.
💠Metabolic Stability and Bioanalysis
Using UPLC/HRMS, peptide metabolism is characterized through incubation with S9 fractions or hepatocytes to identify metabolites and estimate in vivo half-life.
💠Comprehensive ADMET Prediction
Our computational models predict peptide lipophilicity (logP), ionization potential (pKa), oral absorption, brain penetration, bioavailability, clearance rate, and potential toxicity profiles.
💠In Vivo Pharmacokinetic Validation
Optional studies using rodent models allow direct confirmation of predicted pharmacokinetic behavior, including bioavailability, stability, and clearance, complemented by quantitative LC–MS bioanalysis.
Why Choose MtoZ Biolabs
☑️Predictive Accuracy and Speed: Our validated models allow you to identify high-potential candidates with reduced cost and time compared to experimental screening.
☑️Customizable and Scalable Solutions: We tailor our analyses to your peptide classes, target indications, and project objectives.
☑️Expert Team in Peptide Pharmacology: Our staff includes experts in peptide chemistry, pharmacokinetics, toxicology, and computational biology who deliver interpretable and actionable insights.
☑️Seamless Integration with Experimental Workflows: Predictions are formatted to support downstream in vitro or in vivo validation, aiding translational pipeline efficiency.
Applications of Peptide Drug ADMET Prediction Service
Our Peptide Drug ADMET Prediction Service is applicable in a wide range of discovery and development settings:
FAQ
Q1: What is the service general workflow?
Start Your Project with MtoZ Biolabs
Contact us today to discuss your project and request a customized proposal! MtoZ Biolabs' Peptide Drug ADMET Prediction Service equips you with a powerful computational platform to evaluate and refine therapeutic peptides before costly experimental steps.
How to order?
