Pharmacokinetics And Human PK Prediction Strategy

Poster illustrating a pharmacokinetics strategy combining in vitro and in vivo data to enhance accuracy and confidence in human PK prediction.

Poster Authors:

Michael Bestwick, Elnaz Gozalpour, David Lugo, John Pollard, Simon Taylor, Simon Teague

Pharmaron, West Hill Innovation Park, Hertford Road, Hoddesdon, Hertfordshire, EN11 9FH, United Kingdom

Confidence Through Data-Driven PK Prediction Strategies

Estimating human pharmacokinetics (PK) parameters is vital in determining whether a drug candidate meets its target product profile and is viable for Phase 1 clinical trials. Pharmaron’s predictive framework combines calibrated in vitro assays, preclinical in vivo data, and advanced PK modeling to strengthen confidence in human exposure estimates.

This integrated approach leverages multi-species scaling, PBPK modeling, and sensitivity analysis to identify optimal clinical dosing strategies, minimizing risk and maximizing translation.

Core Elements of Pharmaron’s PK Prediction Workflow

1. Absorption Assessment

In vitro permeability via Caco-2 or MDCK-KO cells
In vivo Fa × Fg estimates from preclinical species
Limiting factors (solubility, permeability, or first-pass metabolism) identified early

Capabilities

Knowledge Center

Discovery in vivo PK

Regulatory in vivo PK Studies

Integrated in vitro and in vivo ADME

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2. Clearance Prediction

In vitro hepatocyte/microsomal data with scaling corrections
Allometric scaling across multiple species
Regression-offset corrections improve accuracy

3. Volume of Distribution (Vss)

Allometric scaling and Øie-Tozer methods
Mechanistic PBPK simulations reflect system-level tissue partitioning

Bridging Data to Human Relevance

Predictive PK Modeling Tools

Compartmental models
Physiologically based pharmacokinetic (PBPK) models
Advanced Compartmental Absorption and Transit (ACAT) model for solubility and GI transit

Integration with PD and Target Efficacy

Aligns corrected in vitro IC50/IC90 values with relevant PK drivers (e.g., Cmax, AUC)
Adjusted for plasma protein binding and species differences
Supports dose prediction aligned to the mechanism of action

Delivering Confident Clinical Dose Forecasts

Using multi-tiered strategies for PK prediction, Pharmaron supports:

Human clearance estimation
Dose range prediction for clinical trials
Mechanism-based exploration of absorption challenges

All results are validated through sensitivity analyses, ensuring that dose projections reflect real-world uncertainty and variability.

References:

Download the full poster to see how integrated PK prediction informs early development decisions.