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PRECLINICAL DEVELOPMENT

PK/PD Analysis & Pharmacometrics

Noncompartmental, compartmental, and population PK/PD analysis to characterize exposure, understand response, and support dose and study decisions across preclinical development.

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PK/PD and Pharmacometrics
OUR APPROACH

Quantitative PK/PD Insight for Better Development Decisions

PK/PD and Pharmacometrics translate concentration-time data into development decisions. We use noncompartmental analysis, compartmental modeling, and population PK/PD approaches to characterize exposure, understand response, and support dose selection across preclinical programs.

Our work connects bioanalytical data, toxicology findings, and pharmacology signals into one quantitative framework. This helps sponsors evaluate exposure-response relationships, compare species, project first-in-human starting doses, and strengthen model-informed decisions with traceable, scientifically grounded analysis.

Modeling Applications

In-silico Simulations
Projecting exposure and response using animal PK data
Dose Optimization
Supporting therapeutic window assessment and starting-dose decisions
Species Scaling
Translating PK behavior from preclinical species to human projections
Exposure-Response
Linking concentration profiles to efficacy and safety biomarkers
Core Capabilities

Six Modeling Disciplines. One Integrated Practice.

Covering the full pharmacometric spectrum from NCA through MIDD.

Population PK (PopPK) Modeling
Characterizing inter-individual variability and identifying significant covariates using non-linear mixed-effects modeling.
Noncompartmental Analysis (NCA)
Rapid and rigorous calculation of primary PK parameters (Cmax, Tmax, AUC, t1/2) for GLP toxicology studies.
Pharmacodynamic (PD) Modeling
Quantifying the relationship between exposure and pharmacological effect using Emax, sigmoidal Emax, or indirect response models.
In-vitro to In-vivo Correlation (IVIVC)
Establishing quantitative links between laboratory dissolution or metabolism data and in-vivo performance.
Allometric Scaling & FIH Projections
Using physiological and empirical scaling methods to support IND-enabling safety margin calculations.
Model-Informed Drug Development (MIDD)
Integrating modeling and simulation to support strategic Go/No-Go decisions throughout the program lifecycle.
Workflow

Six Steps from Data to Insight

A structured pharmacometric workflow from raw data through regulatory-ready deliverables.

1

Ingest

Aggregation of concentration and biomarker data from bioanalytical labs.

2

Explore

Exploratory data analysis (EDA) to identify trends and outliers.

3

Model

Structural model development and parameter estimation.

4

Validate

Goodness-of-fit assessments and visual predictive checks (VPC).

5

Simulate

Trial simulations to predict outcomes under different dosing scenarios.

6

Report

Final modeling report delivery for regulatory submission.

Tools and Standards

Software Platforms and Standards.

Platforms
Phoenix WinNonlin
NONMEM
R / mrgsolve
SAS
MATLAB
Standards
CDISC ADaM (ADPC / ADPP)
CDISC SDTM (PC / PP)
21 CFR Part 11 Compliant
Get Started

Optimize Your Development Strategy.

Ensure your dose selection is backed by rigorous pharmacometric modeling.

Request a Modeling Assessment