Absorption & Permeability Prediction

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Overview

A compound that cannot reach its target is not a drug, whatever its affinity. We predict the absorption and permeability profile — passive permeability, efflux liability, intestinal absorption, oral bioavailability and blood–brain barrier penetration — and, where a compound fails, identify whether the cause is size, polarity, ionisation, hydrogen-bonding or transporter recognition. For CNS programmes we add the multiparameter optimisation scoring that governs brain-penetrant design.

Schematic: properties are predicted across the series and each liability is attributed to the substructure responsible, so the result points to a modification.

Key Advantages

Cause Diagnosed, Not Only Predicted

A low permeability prediction is accompanied by the property driving it, because a compound failing on polar surface area requires a different fix from one failing on efflux.

Efflux Treated Separately

P-glycoprotein and related transporter liability is predicted independently of passive permeability, which is essential for CNS and oncology programmes where efflux is the usual failure mode.

CNS MPO Scoring

Brain-penetrant programmes receive full multiparameter optimisation scoring with per-property contributions, showing precisely which parameter is holding the score down.

Series Trends Made Visible

Permeability is reported across the series against structural change, so the chemistry team can see which modifications cost absorption and which do not.

Where This Service Is Used

Deciding which hits from a screen are worth progressing to cell-based assays

Diagnosing a disconnect between biochemical potency and cellular activity

Designing CNS-penetrant compounds and predicting brain exposure risk

Assessing oral bioavailability risk before in vivo pharmacokinetic studies

Guiding prodrug or formulation strategy for compounds with intrinsically poor absorption

Methods and Techniques Applied

Passive permeability prediction benchmarked against Caco-2 and PAMPA style endpoints

P-glycoprotein substrate and inhibitor prediction, with other efflux transporters where models permit

Human intestinal absorption and oral bioavailability prediction with applicability-domain checking

Blood–brain barrier penetration prediction and CNS multiparameter optimisation scoring

Property-based diagnosis linking each failure to polarity, ionisation, size or hydrogen-bond count

Comparison against reference compounds with known behaviour to place predictions in context

What We Need From You

Compounds as SMILES or SDF with stereochemistry specified

Intended route of administration and target tissue, including whether CNS exposure is required

Any measured permeability, efflux ratio or pharmacokinetic data for calibration

Known cellular activity data, which often explains whether permeability is the limiting factor

What You Receive

Absorption and permeability table with predicted values and confidence indicators

Efflux liability assessment per compound

CNS MPO scores with per-property breakdown for neuroscience programmes

Diagnostic commentary attributing each failure to a specific property

Recommendation of which compounds to progress and which assay would settle the remaining uncertainty

What We Compute and Report

Predicted passive permeability benchmarked against standard cell-monolayer and artificial-membrane endpoints

Efflux transporter substrate and inhibitor likelihood, reported independently of passive permeability

Human intestinal absorption and oral bioavailability estimates with applicability-domain flags

Blood–brain barrier penetration estimate and CNS multiparameter score with per-property contributions

Attribution of each predicted failure to the property driving it

Interpretation and Limitations

Computational predictions prioritise hypotheses; they do not independently establish binding, biological activity, therapeutic efficacy, safety or clinical validity. Performance depends on input quality, target class, the structural evidence available and the applicability domain of the selected methods. Scores used for ranking are comparative devices and should not be read as measured quantities. All deliverables are for research use only and are not intended for diagnostic or therapeutic use.

Specifications

Item	Specification	Notes
Compounds per run	1–50,000	Batch processing available
Typical turnaround	3–7 working days	Including diagnostic interpretation
Endpoints	Caco-2, PAMPA, P-gp, HIA, BBB, F%	Endpoint set agreed during scoping
Output	Tables + report	With per-compound diagnosis of failure causes

Service Workflow

Step 01

Scientific Consultation

We discuss the objective, the decision it supports and the data you hold. Nothing is quoted before we understand what the result has to answer.

Step 02

Feasibility Review

We check that the data, target class and available structural evidence can support the proposed approach, and say plainly where they cannot.

Step 03

Technical Proposal

Scope, methods, deliverables, timeline and price are confirmed in writing, together with the limitations we expect to report.

Step 04

Computation and QC

The analysis runs on pinned tool versions in a containerised environment, with quality checkpoints and method comparison where that is informative.

Step 05

Report and Follow-Up

You receive the ranked results, the documented methods, the limitations and a proposed validation plan, plus support in interpreting them.

Is This the Right Service for You?

Choose this service when

Biochemical potency is not translating into cellular activity

A CNS programme needs brain exposure risk assessed before in vivo work

Oral bioavailability risk must be understood before pharmacokinetic studies are commissioned

Consider another service when

Clearance rather than absorption is the suspected problem

Metabolic Stability & CYP Prediction

The molecule sits far outside conventional property space

Macrocycle Design

What Goes Wrong, and How We Handle It

The failure modes that produce confident-looking results which do not survive the next experiment. Each one is designed against rather than discovered afterwards.

Transporter liability is predicted independently of passive permeability, because the two require different fixes.

Case Studies

The situation

Enzyme IC50 values were in the low nanomolar range while the cell assay showed nothing at ten micromolar.

What the work involved

Passive permeability, efflux liability and ionisation were predicted across the series, and the results were correlated against the structural changes the chemists had made.

What came back

A basic amine introduced three rounds earlier was driving efflux across the whole series. Two neutral replacements were proposed, and the property-versus-potency trade-off was quantified for each.

Illustrative of the shape this work takes. Details are generalised, no client or target is identified, and scope and outcome vary with the system in question.

Questions We Are Asked Before Scoping

Note: ICDMO delivers computational (in silico) services. Results prioritise hypotheses for testing; they do not by themselves establish binding, biological activity, efficacy or safety. All deliverables are for research use only and are not intended for diagnostic or therapeutic use. Downstream experimental work is scoped separately and executed through qualified partners.

Get in Touch
about Absorption & Permeability Prediction

Tell us about the target, the data you hold and the decision the result needs to support. A scientist reviews every enquiry and replies within one business day.

Feasibility reviewed before any scope or price is fixed

Methods, parameters, confidence and limitations in every report

Confidentiality agreement available before data is shared