Alan Scientific provides a customized ADMET and blood-brain barrier (BBB) prediction service for small molecules and peptides, with a particular focus on brain penetration, CNS exposure, passive permeability, efflux transport, and the molecular factors that may limit or support BBB transport.
Our BBB assessment goes beyond a simple BBB-positive or BBB-negative classification. Depending on the project, we integrate multiple prediction layers including LogBB, Kp,brain, Kp,uu,brain, physicochemical properties, P-gp/BCRP efflux, plasma protein binding, brain tissue binding, and other CNS exposure-related factors.
Selected prediction models can achieve more than 85% predictive accuracy within validated applicability domains. Model performance depends on the endpoint, molecular class, available training data, and whether the submitted candidate falls within the model's applicable chemical or sequence space.
Each project is delivered as a customized scientific report, combining computational predictions with integrated interpretation to support candidate comparison, risk identification, and experimental planning.
BBB & CNS Exposure Assessment
| Assessment Layer | Key Metrics | What It Helps Answer |
| Physicochemical Profile | MW, LogP, LogD, pKa, TPSA, HBD, HBA, rotatable bonds, solubility, charge state | Does the candidate have physicochemical properties compatible with passive BBB penetration? |
| BBB Penetration | Brain Penetration: High / Medium / Low | What is the overall predicted potential to cross the blood-brain barrier? |
| Brain Distribution | LogBB, Kp,brain | How is total compound exposure predicted to distribute between plasma and brain? |
| Unbound Brain Exposure | Kp,uu,brain | How does predicted unbound brain exposure compare with unbound plasma exposure? |
| Efflux Transport | P-gp and BCRP substrate / inhibitor probability and efflux risk | Could active efflux limit CNS exposure despite favorable passive permeability? |
| Protein & Tissue Binding | Plasma protein binding, fu,p, brain tissue binding, fu,brain | How may plasma and brain binding influence pharmacologically available exposure? |
| Extended Brain Exposure | Brain Cmax, Brain AUC, Brain half-life | When sufficient PK information is available, what level and duration of brain exposure may be expected? |
Why BBB Prediction Requires More Than One Metric
BBB penetration is not determined by a single molecular property or prediction score. A candidate may show favorable passive permeability but still have limited brain exposure because of active efflux, strong plasma binding, brain tissue binding, ionization, or other pharmacokinetic factors.
Alan Scientific therefore evaluates BBB behavior using a multi-layer assessment rather than relying on one classification model.
Key BBB Prediction Metrics
| Metric | What It Represents |
| BBB Classification | Initial prediction of whether a candidate is likely to show low, moderate, or high BBB penetration potential |
| LogBB | Predicted relationship between total brain concentration and total plasma concentration |
| Kp,brain | Brain-to-plasma distribution ratio based on total compound exposure |
| Kp,uu,brain | Relationship between unbound drug exposure in brain and unbound exposure in plasma |
| LogPS / Permeability Metrics | Computational assessment of permeability-surface area behavior and CNS penetration potential |
| fu,p | Predicted fraction of unbound compound in plasma |
| fu,brain | Predicted fraction of unbound compound in brain tissue |
Why Kp,uu,brain Matters
Total brain concentration does not necessarily represent pharmacologically available drug in the brain.
Kp,brain describes total brain-to-plasma distribution, while Kp,uu,brain focuses on unbound brain exposure relative to unbound plasma exposure. This distinction can be particularly important when evaluating whether sufficient free compound may be available to interact with a CNS target.
For this reason, BBB assessment can integrate LogBB, Kp,brain, Kp,uu,brain, plasma protein binding, and brain tissue binding rather than interpreting total brain exposure alone.
P-gp & BCRP Efflux Assessment
Passive permeability alone does not determine CNS exposure. Some compounds may enter the BBB by passive diffusion but subsequently be transported out of the brain by active efflux systems.
Alan Scientific's BBB assessment can include:
P-gp substrate probability, P-gp inhibitor probability, P-gp efflux risk, BCRP substrate probability, BCRP inhibitor probability, BCRP efflux risk
Transporter predictions are interpreted together with passive permeability, physicochemical properties, binding, and predicted brain exposure.
Additional CNS Transporter Assessment
For selected projects, additional uptake or transport mechanisms can be evaluated when relevant to the candidate structure and proposed mechanism of CNS entry.
Project-specific assessment may include selected transporter systems such as:
LAT1
OATP-family transporters
OCT-family transporters
MCT-related transport mechanisms
Other CNS uptake or elimination pathways
The selection of additional transporter endpoints depends on molecular structure, charge, passive permeability, therapeutic target, administration route, and intended site of action.
BBB Prediction for Small Molecules and Peptides
Alan Scientific supports BBB prediction for both small molecules and peptides, while recognizing that the determinants of BBB transport differ between these molecular classes.
Small Molecules
For small molecules, the assessment may emphasize:
Molecular weight
LogP and LogD
pKa and ionization
TPSA
Hydrogen-bond donors and acceptors
Passive permeability
Plasma and brain binding
P-gp and BCRP efflux
Peptides
For peptides, additional factors such as sequence composition, peptide length, molecular size, net charge, hydrophobicity, structural conformation, stability, and potential transport mechanisms may significantly influence BBB behavior.
Peptide BBB projects are therefore evaluated according to peptide-specific characteristics rather than simply applying small-molecule rules to peptide sequences.
Broader ADMET Assessment
BBB prediction can be combined with broader ADMET analysis when additional pharmacokinetic or safety information is important to the project.
| ADMET Area | Examples of Available Assessments |
| Absorption | Solubility, permeability, Caco-2, PAMPA, intestinal absorption, oral bioavailability |
| Distribution | BBB, plasma protein binding, free fraction, tissue distribution, volume of distribution |
| Metabolism | Microsomal stability, hepatocyte stability, CYP substrate / inhibition / induction, UGT and selected metabolite predictions |
| Excretion | Renal clearance, biliary clearance, transporter-related elimination, predicted half-life |
| Toxicity | Selected endpoints including hERG, DILI, Ames, genotoxicity and other project-relevant safety predictions |
What Is Included in a Customized BBB Report?
The final deliverable is a structured scientific report, not simply a prediction score.
Executive Summary
Overall BBB Penetration: High / Medium / Low
Overall CNS Accessibility: High / Medium / Low
Primary factors supporting BBB penetration
Primary factors limiting brain exposure
P-gp / BCRP efflux risk
Overall scientific interpretation
Physicochemical Profile
Molecular weight
LogP / LogD
pKa
TPSA
HBD / HBA
Solubility
Charge state
Passive BBB Permeability
Predicted BBB penetration
LogBB
Kp,brain
Selected permeability metrics
Model applicability assessment
Efflux Transport
P-gp assessment
BCRP assessment
Additional transporter considerations when relevant
Brain Exposure & Binding
Kp,brain
Kp,uu,brain
Plasma protein binding
fu,p
Brain tissue binding
fu,brain
Extended brain PK metrics when supported by the available information
Integrated Interpretation
Major strengths of the candidate BBB profile
Potential CNS exposure liabilities
Candidate comparison when multiple structures are submitted
Suggested priorities for further computational or experimental evaluation
Optional CNS Target Accessibility Analysis
For projects involving a defined CNS target, BBB analysis can be extended beyond brain penetration to consider whether predicted exposure is relevant to the intended biological target.
Depending on project requirements and available information, this analysis may include:
Target prediction
Target expression
Brain-region distribution
Cell-type expression
Target localization
Relevant biological pathways
Brain exposure relative to target potency
A candidate reaching the brain does not necessarily mean that it reaches the correct target at a sufficient unbound concentration.
Predictive Performance & Applicability
Selected Alan Scientific prediction models can achieve >85% predictive accuracy within validated applicability domains.
Prediction performance is endpoint-dependent and may vary according to molecular class, chemical space, peptide sequence space, dataset quality, and the availability of relevant experimental training data.
For this reason, each customized report considers not only the predicted value, but also the applicability and confidence of the prediction when interpreting the result.
How the Service Works
| Step 1 | Submit Your Candidate Provide a small-molecule structure or peptide sequence together with the research objective. |
| Step 2 | Define the Prediction Scope We determine which BBB, CNS exposure, transporter, and ADMET endpoints are relevant to the project. |
| Step 3 | Computational Prediction Relevant models are applied according to molecular class and project requirements. |
| Step 4 | Integrated Scientific Interpretation BBB penetration, exposure, efflux, binding, and other relevant predictions are interpreted together. |
| Step 5 | Customized Prediction Report Results, interpretation, model considerations, major risks, and conclusions are delivered in a structured scientific report. |
Sample ADMET Prediction Report
View our sample report to see the format and level of analysis available through Alan Scientific's customized ADMET and BBB prediction service.
View Sample ADMET Prediction Report
Understanding Computational Predictions
ADMET and BBB predictions are computational estimates. An accuracy value above 85% for a validated model does not mean that every individual prediction has an 85% probability of being correct, nor does it replace experimental measurement.
Predicted BBB penetration, Kp,brain, Kp,uu,brain, transporter behavior, brain exposure, and other ADMET endpoints should therefore be interpreted within the model's applicability domain and the biological context of the candidate.
Experimental studies remain necessary to confirm BBB penetration, pharmacokinetics, safety, target engagement, and biological performance.
Request a Customized ADMET & BBB Prediction Report
Send us your small-molecule structure or peptide sequence, together with the intended application, CNS target if available, and the questions you would like the analysis to address.
Alan Scientific can define a customized BBB and ADMET prediction package and provide a structured scientific report for candidate evaluation and experimental planning.
Request an ADMET & BBB Prediction Report, Please Contact sales@alanscientific.com