Translational PBPK
and First Time in
Human Dose Predictions

Accurately predicting pharmacokinetics (PK) and target site exposure is essential for any drug development strategy, as it informs decisions about how a drug will be delivered and its potential impact on patient outcomes. By integrating pharmacokinetics with pharmacodynamics (PD), we can predict therapeutic responses and develop dosing strategies that are both safe and effective. This integration allows for a deeper understanding of the dose-response relationship, critical for determining optimal dosing regimens.

Physiologically based pharmacokinetic (PBPK) and quantitative systems pharmacology (QSP) models provide detailed insights into how a drug is absorbed, distributed, metabolized, and excreted (ADME), as well as how it interacts with biological targets to produce desired therapeutic effects.

Translational PBPK refers to the use of physiologically based pharmacokinetic modeling to bridge this gap, leveraging in vitro and in vivo data to predict human PK and inform early clinical decisions, such as First Time in Human (FTIH) dosing.

These models account for complex biological interactions and individual variability, enabling predictions that reflect real-world conditions. This comprehensive modeling approach not only optimizes dose levels to balance efficacy and safety but also supports personalized treatment adjustments across different patient populations, ensuring that dosing strategies are tailored for maximum therapeutic benefit with minimal risk.

Physiologically based biopharmaceutics modeling (PBBM) is a specific field of PBPK model applications that aims to establish the link between the formulation’s properties and in vivo performance.

This field of application of PBPK modeling is evolving at a fast-pace and offers the link between in vivo and in vitro to support pharmaceutical development in the selection of the best drug substance and product, as well as later in development in the establishment of manufacturing quality and controls.
Dissolution testing is often a key input in PBBM. Results from in vitro experiments characterizing drug substances and the formulation behavior (e.g., solubility, particle size, dissolution) can be linked to key ADME parameters and integrated into full PBPK models to predict PK exposure in plasma and/or specific tissues or organs.

These models can also be linked to Pharmacodynamic (PD) relationships to derive the impact of physicochemical, drug and formulation properties on safety and efficacy. The role of Physiologically Based Biopharmaceutics Modeling (PBBM) in drug development spans multiple stages, including supporting patient-centric design, guiding life cycle management, informing regulatory submissions, streamlining development processes, optimizing dosing strategies, enhancing study design, and aiding in formulation development and developability assessment.

What we can offer

At ESQlabs, we specialize in developing tailored PBPK and PD models for a variety of drug modalities, including small molecules, biologics, and novel drug formats. Using the Open Systems Pharmacology Suite, we combine ADME properties and receptor interactions to simulate dose-effect relationships across different dosing regimens. Our models support critical phases of drug development, from discovery to clinical trials, providing predictive insights to refine dosing strategies and maximize therapeutic benefits while minimizing risks.

We can integrate date from:

  • Quantitative structure-activity relationships
  • In vitro and organ-on-a-chip experiments
  • Preclinical in vivo studies
  • Clinical studies

We can investigate the impact of:

  • Drug parameters (physiochemistry, route, formulation, dosing regimen)
  • In vivo system parameters (species, individual physiological parameters)
  • Drug-system parameters (binding partners, transporters, metabolism and biotransformation)

For application in:

  • Drug Discovery (DMPK design)
  • Translational research (FIH study design)
  • Clinical development (dose escalation, expansion,
R2PD, dose optimization and selection)

Related Platforms

IVIVE Toolset

Workflows, leveraging in-vitro computational models for IVIVE-PBPK.
Find out more 

Large Molecules, Biologics and Novel Modalities

Advancing PBPK-based solutions for (Bi-specific) antibodies, conjugated drugs, gene therapy, and other novel modalities.
Find out more 

Small Molecules and Chemicals

Advancing PBPK-based solutions for small molecules and chemicals across all services.
Find out more 

QSP Disease and QST Models

Diabetes, Oncology, Hematology, Liver Diseases, DILI, Cardiovascular, Ocular, Endocrine/Thyroid, Contraception, and more.
Find out more 

Digital Twins for Micro-physiological Systems: MPSlabs

MPSlabs- Our business unit to enable in-vivo relevance for Organ-on-Chip Systems as Non-Animal Methods.
Find out more 

Related publications and initatives

Studying metabolism with multiorgan chips: new tools for diseasemodelling, pharmacokinetics and pharmacodynamics
Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans
Local depletion of large molecule drugs due to target binding in tissue interstitial space
See all publications 

Meet the Team

Alexander Kulesza

Principal Scientist
Lead Systems Pharmacology
Google Scholar

Alexander is a Chemist by training with a PhD focusing on theoretical and computational methods for structural and optical property predictions.

After spending several years in academia (U. of Lyon) working on molecular dynamics simulation and free energy methods, Alex has most recently been working with CROs in applying large-scale disease and quantitative systems pharmacology models integrated into clinical trial simulations, across a number of disease areas.

Alex leads QSP/T and qAOP / Systems Pharmacology with the aim to promote widespread application of physiologically based and mechanistic modeling and to create robust and qualified, yet versatile models and applications for high impact decision making.

Christian Maass

Principal Scientist
Platform Lead Digital Organ-on-Chip
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Christian Maass is a physicist and computational biologist with over eight years of academic and industrial experience, where he established a strong national and international network. He is passionate about the integration of computational modeling and biological experiments for translational pharmacology applications.

Before joining ESQlabs, Christian Maass worked in various therapeutic areas, e.g. neurodegenerative, inflammatory, and metabolic diseases (Alzheimer, rheumatoid arthritis, NASH/NAFLD). Among others, he developed individualized PBPK models for molecular radiotherapy (leukemia), automated workflows for big data (*omics), network-based analysis of inflammation diseases, and mechanistic modeling of organ-on-chip data.

He received his Master in Medical Physics from the University College London in 2012 and PhD from the University of Heidelberg in 2015. As a postdoctoral researcher at the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, he focused on application-driven method development for microphysiological systems in safety pharmacology. In 2018, Christian Maass joined Certara’s Quantitative Systems Pharmacology (QSP) team, working on liver disease models and leading projects to integrate organ-on-chip (OoC) and computational modeling for translational pharmacology applications.

Diane Lefaudeux

Scientist
Consultant
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Diane Lefaudeux is an interdisciplinary scientist with a strong drive to understand complex mechanisms and in particular those arising from biological systems.

Before joining ESQlabs, she worked at Novadiscovery where she developed PBPK-QSP models on various therapeutic areas to predict outcomes using virtual populations.

Diane obtained her Master’s degree in General Engineering from École Centrale Paris, France, as well as in Control Systems Engineering and Systems Biology from University of Stuttgart, Germany.

 

Laura Villain

Scientist
Consultant
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Laura Villain is a biomodeler with interests in various mechanistic modeling approaches and statistical methods. She has experience with popPK, QSP, and PBPK models, complemented by her biostatistics skills.

Before joining ESQlabs, she worked at Novadiscovery, where she developed and improved several PBPK and PBPK-QSP models to reproduce in silico trials. She gained in-depth knowledge of all the steps required to develop a model that can reproduce clinical outputs in compliance with regulatory guidelines. She is also interested in R programming and has provided internal training on R within the company. Before that, she worked as a postdoctoral researcher in biostatistics in the oncology field at INRIA (Bordeaux University). There, she explored high-dimensional methods to link omics data with time-to-event outcomes.

Laura received her Master’s degree in biomodeling sciences from INSA Lyon (France). For her Ph.D. thesis, she studied the impact of interleukin 7 injections on HIV-infected patients. She used a mechanistic model and proposed an adaptive protocol of injections. Her PhD research was supervised by Dr. Daniel Commenges and Prof. Rodolphe Thiébaut at the Department of Public Health at Bordeaux University.

No publications assigned.

Marco Siccardi

Principal Scientist
Lead Toxicology & PBPK
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Marco is a Clinical Biologist by training with a PhD in molecular pharmacology and PK/PD modelling. He spent over 15 years at the University of Liverpool working on the topic of pharmacogenetics and in developing PBPK approaches for the optimisation of drug delivery, including HIV therapy optimisation.

Marco has most recently been working with CROs in taking this approaches for modelling and simulation approaches and PKTK (Systems Toxicology) models across a number of disease areas.

Marco leads the Systems Toxicology team with the aim to promote collaborative innovation and to develop novel modeling approaches to streamline the toxicological assessment.

Pavel Balazki

Senior Scientist
Lead Software ToolChain
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Pavel Balazki is a bioinformatitian by training with over 10 years of experience in PB(P)K and QSP/T modeling and software development.

Pavel’s modeling expertices is focused on developing complex PB-QSP/T disease models, such as the Diabetes Platform or the Thyroid Hormones Toxicology Platform.

Pavel leads the Software ToolChain team at ESQlabs, developing new technologies to enable an integrated ecosystem of software, models, and solutions.

Raphaëlle Lesage

Scientist
Consultant
Google Scholar

Raphaëlle, is a Systems Pharmacologist and Bioengineer by training. At ESQlabs, she focuses on applying PBPK and QSP modelling to support drug development, she coordinates the Special Population core service and is particularly interested in modelling special populations to optimize therapeutic strategies, design trials, and prevent unsafe exposure..

Previously, she served as Chief Scientific Officer at the Virtual Physiological Human Institute, where she coordinated scientific working groups in multiple European projects and led stakeholder engagement and regulatory initiatives for advancing in silico medicine.

She studied Bioengineering and Computational modelling for Biology and Pharmacology at Polytech Nice Sophia. She obtained a degree in reseach valorization from UMPC (Paris) and she holds an interdisciplinary PhD in Engineering and Biomedical Sciences from KU Leuven (Belgium), where she conducted research on computational modelling of therapeutic strategies to limit cartilage degeneration or promote bone regeneration.

Vanessa Baier

Senior Scientist
Consultant & Operations Manager
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Vanessa Baier is bioinformatician by training, with a focus on computational modeling in the field of systems biology/systems pharmacology. She has experience with lab data management tools, Bayesian population PBPK techniques, and the contextualization of in vitro data and mechanistic PBPK models. Her main area at ESQlabs lies in vitro/in vivo extrapolation and toxicity modeling within PBPK QSP

Vanessa Baier studied computer science at TU Braunschweig and Bioinformatics at Goethe University Frankfurt. After an internship at Sanofi, she completed her master thesis at Bayer in the group of Complex Systems Modeling / Applied Mathematics. She then joined the group of Lars Kuepfer at RWTH Aachen University to complete her PhD on PBPK modeling of drug-induced liver injury (DILI) .

Wilbert de Witte

Principal Scientist
Platform Lead Large Molecule PBPK
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Wilbert de Witte is a Pharmacologist with a strong drive to understand complex mechanisms and the models that represent them. At ESQlabs, he leads the large molecule PBPK and novel modalities platform and he leads the large molecule focus group of the OSP community.

Before joining ESQlabs, he worked at Ablynx NV, later Sanofi Ghent, on the preclinical and clinical development of NANOBODY® therapeutics. He developed several PBPK and PBPK-QSP models as well as traditional TMDD and PKPD models for mechanistic analysis of in vitro, in vivo, and clinical data. He accumulated in-depth knowledge on the behavior of large molecules in different modalities and with various target binding characteristics.

Wilbert de Witte obtained his Master’s degree in Bio-Pharmaceutical Sciences from Leiden University (the Netherlands). For his PhD thesis, he studied the impact of drug-target binding kinetics on in vivo drug action. His PhD research was supervised by Prof. Liesbeth de Lange, Prof. Piet-Hein van der Graaf and Prof. Meindert Danhof at the department of Pharmacology at Leiden University.