Whole-Body Physiologically Based Pharmacokinetic Modeling Framework for Tissue Target Engagement of CD3 Bispecific Antibodies Monica E. Susilo, Stephan Schaller, Luis David Jiménez-Franco, Alexander Kulesza, Wilhelmus E. A. de Witte, Shang-Chiung Chen, C. Andrew Boswell, Danielle Mandikian, Chi-Chung Li Pharmaceutics, 2025 Background: T-cell-engaging bispecific (TCB) antibodies represent a promising therapy that utilizes T-cells to eliminate cancer cells independently of the major histocompatibility complex. Despite their success in hematologic cancers, challenges such as cytokine release syndrome (CRS), off-tumor toxicity, and resistance limit their efficacy in solid tumors. Optimizing biodistribution is key to overcoming these challenges. Methods: A physiologically based pharmacokinetic (PBPK) model was developed that incorporates T-cell transmigration, retention, receptor binding, receptor turnover, and cellular engagement. Preclinical biodistribution data were modeled using two TCB formats: one lacking tumor target binding and another with target arm binding, each with varying CD3 affinities in a transgenic tumor-bearing mouse model. Results: The PBPK model successfully described the distribution of activated T-cells and various TCB formats. It accurately predicted preclinical biodistribution patterns, demonstrating that higher CD3 affinity leads to faster clearance from the blood and increased accumulation in T-cell-rich organs, often reducing tumor exposure. Simulations of HER2-CD3 TCB doses (0.1 µg to 100 mg) revealed monotonic increases in synapse AUC within the tumor. A bell-shaped dose-Cmax relationship for synapse formation was observed, and Tmax was delayed at higher doses. Blood PK was a reasonable surrogate for tumor synapse at low doses but less predictive at higher doses. Conclusions: We developed a whole-body PBPK model to simulate the biodistribution of T-cells and TCB molecules. The insights from this model provide a comprehensive understanding of the factors affecting PK, synapse formation, and TCB activity, aiding in dose optimization and the design of effective therapeutic strategies.
Immune digital twins for complex human pathologies: applications, limitations, and challenges Anna Niarakis, Reinhard Laubenbacher, Gary An, Yaron Ilan, Jasmin Fisher, Åsmund Flobak, Kristin Reiche, María Rodríguez Martínez, Liesbet Geris, Luiz Ladeira, Lorenzo Veschini, Michael L. Blinov, Francesco Messina, Luis L. Fonseca, Sandra Ferreira, Arnau Montagud, Vincent Noël, Malvina Marku, Eirini Tsirvouli, Marcella M. Torres, Leonard A. Harris, T. J. Sego, Chase Cockrell, Amanda E. Shick, Hasan Balci, Albin Salazar, Kinza Rian, Ahmed Abdelmonem Hemedan, Marina Esteban-Medina, Bernard Staumont, Esteban Hernandez-Vargas, Shiny Martis B, Alejandro Madrid-Valiente, Panagiotis Karampelesis, Luis Sordo Vieira, Pradyumna Harlapur, Alexander Kulesza, Niloofar Nikaein, Winston Garira, Rahuman S. Malik Sheriff, Juilee Thakar, Van Du T. Tran, Jose Carbonell-Caballero, Soroush Safaei, Alfonso Valencia, Andrei Zinovyev, James A. Glazier Npj Systems Biology and Applications, 2024 Digital twins represent a key technology for precision health. Medical digital twins consist of computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis. Many health conditions involve the immune system, so it is crucial to include its key features when designing medical digital twins. The immune response is complex and varies across diseases and patients, and its modelling requires the collective expertise of the clinical, immunology, and computational modelling communities. This review outlines the initial progress on immune digital twins and the various initiatives to facilitate communication between interdisciplinary communities. We also outline the crucial aspects of an immune digital twin design and the prerequisites for its implementation in the clinic. We propose some initial use cases that could serve as “proof of concept” regarding the utility of immune digital technology, focusing on diseases with a very different immune response across spatial and temporal scales (minutes, days, months, years). Lastly, we discuss the use of digital twins in drug discovery and point out emerging challenges that the scientific community needs to collectively overcome to make immune digital twins a reality.
Model Development Alexander Kulesza, Axel Loewe, Andrea Stenti, Chiara Nicolò, Enrique Morales-Orcajo, Eulalie Courcelles, Fianne Sips, Francesco Pappalardo, Giulia Russo, Marc Horner, Marco Viceconti, Martha De Cunha Maluf-Burgman, Raphaëlle Lesage, Steve Kreuzer Synthesis Lectures on Biomedical Engineering, 2024 Good Simulation Practice implies that a computational model considered for a simulation task has also been developed according to good practice.
Model Credibility Eulalie Courcelles, Marc Horner, Payman Afshari, Alexander Kulesza, Cristina Curreli, Cristina Vaghi, Enrique Morales-Orcajo, Francesco Pappalardo, Ghislain Maquer, Giulia Russo, Liesbet Geris, Marco Viceconti, Michael Neidlin, Philippe Favre, Raphaëlle Lesage, Steve Kreuzer, Vincenzo Carbone Synthesis Lectures on Biomedical Engineering, 2024 The need for a framework to justify that a model has sufficient credibility to be used as a basis for internal or external (typically regulatory) decision-making is a primary concern when using modelling and simulation (M&S) in healthcare. This chapter reviews published standards on verification, validation, and uncertainty quantification (VVUQ) as well as regulatory guidance that can be used to establish model credibility in this context, providing a potential starting point for a globally harmonised model credibility framework.
In Silico Clinical Trials: Is It Possible? Simon Arsène, Yves Parès, Eliott Tixier, Solène Granjeon-Noriot, Bastien Martin, Lara Bruezière, Claire Couty, Eulalie Courcelles, Riad Kahoul, Julie Pitrat, Natacha Go, Claudio Monteiro, Julie Kleine-Schultjann, Sarah Jemai, Emmanuel Pham, Jean-Pierre Boissel, Alexander Kulesza Methods in Molecular Biology Clifton N J, 2024
Modeling the disruption of respiratory disease clinical trials by non-pharmaceutical COVID-19 interventions Simon Arsène, Claire Couty, Igor Faddeenkov, Natacha Go, Solène Granjeon-Noriot, Daniel Šmít, Riad Kahoul, Ben Illigens, Jean-Pierre Boissel, Aude Chevalier, Lorenz Lehr, Christian Pasquali, Alexander Kulesza Nature Communications, 2022 Respiratory disease trials are profoundly affected by non-pharmaceutical interventions (NPIs) against COVID-19 because they perturb existing regular patterns of all seasonal viral epidemics. To address trial design with such uncertainty, we developed an epidemiological model of respiratory tract infection (RTI) coupled to a mechanistic description of viral RTI episodes. We explored the impact of reduced viral transmission (mimicking NPIs) using a virtual population and in silico trials for the bacterial lysate OM-85 as prophylaxis for RTI. Ratio-based efficacy metrics are only impacted under strict lockdown whereas absolute benefit already is with intermediate NPIs (eg. mask-wearing). Consequently, despite NPI, trials may meet their relative efficacy endpoints (provided recruitment hurdles can be overcome) but are difficult to assess with respect to clinical relevance. These results advocate to report a variety of metrics for benefit assessment, to use adaptive trial design and adapted statistical analyses. They also question eligibility criteria misaligned with the actual disease burden.
Solving the Evidence Interpretability Crisis in Health Technology Assessment: A Role for Mechanistic Models? Eulalie Courcelles, Jean-Pierre Boissel, Jacques Massol, Ingrid Klingmann, Riad Kahoul, Marc Hommel, Emmanuel Pham, Alexander Kulesza Frontiers in Medical Technology, 2022 Health technology assessment (HTA) aims to be a systematic, transparent, unbiased synthesis of clinical efficacy, safety, and value of medical products (MPs) to help policymakers, payers, clinicians, and industry to make informed decisions. The evidence available for HTA has gaps—impeding timely prediction of the individual long-term effect in real clinical practice. Also, appraisal of an MP needs cross-stakeholder communication and engagement. Both aspects may benefit from extended use of modeling and simulation. Modeling is used in HTA for data-synthesis and health-economic projections. In parallel, regulatory consideration of model informed drug development (MIDD) has brought attention to mechanistic modeling techniques that could in fact be relevant for HTA. The ability to extrapolate and generate personalized predictions renders the mechanistic MIDD approaches suitable to support translation between clinical trial data into real-world evidence. In this perspective, we therefore discuss concrete examples of how mechanistic models could address HTA-related questions. We shed light on different stakeholder's contributions and needs in the appraisal phase and suggest how mechanistic modeling strategies and reporting can contribute to this effort. There are still barriers dissecting the HTA space and the clinical development space with regard to modeling: lack of an adapted model validation framework for decision-making process, inconsistent and unclear support by stakeholders, limited generalizable use cases, and absence of appropriate incentives. To address this challenge, we suggest to intensify the collaboration between competent authorities, drug developers and modelers with the aim to implement mechanistic models central in the evidence generation, synthesis, and appraisal of HTA so that the totality of mechanistic and clinical evidence can be leveraged by all relevant stakeholders.
Model Integration in Computational Biology: The Role of Reproducibility, Credibility and Utility Jonathan Karr, Rahuman S. Malik-Sheriff, James Osborne, Gilberto Gonzalez-Parra, Eric Forgoston, Ruth Bowness, Yaling Liu, Robin Thompson, Winston Garira, Jacob Barhak, John Rice, Marcella Torres, Hana M. Dobrovolny, Tingting Tang, William Waites, James A. Glazier, James R. Faeder, Alexander Kulesza Frontiers in Systems Biology, 2022
Possible Contexts of Use for in Silico Trials Methodologies: A Consensus-Based Review Marco Viceconti, Luca Emili, Payman Afshari, Eulalie Courcelles, Cristina Curreli, Nele Famaey, Liesbet Geris, Marc Horner, Maria Cristina Jori, Alexander Kulesza, Axel Loewe, Michael Neidlin, Markus Reiterer, Cecile F. Rousseau, Giulia Russo, Simon J. Sonntag, Emmanuelle M. Voisin, Francesco Pappalardo IEEE Journal of Biomedical and Health Informatics, 2021
Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility Flora T. Musuamba, Ine Skottheim Rusten, Raphaëlle Lesage, Giulia Russo, Roberta Bursi, Luca Emili, Gaby Wangorsch, Efthymios Manolis, Kristin E. Karlsson, Alexander Kulesza, Eulalie Courcelles, Jean‐Pierre Boissel, Cécile F. Rousseau, Emmanuelle M. Voisin, Rossana Alessandrello, Nuno Curado, Enrico Dall’ara, Blanca Rodriguez, Francesco Pappalardo, Liesbet Geris Cpt Pharmacometrics and Systems Pharmacology, 2021
Action-FRET of a Gaseous Protein Steven Daly, Geoffrey Knight, Mohamed Abdul Halim, Alexander Kulesza, Chang Min Choi, Fabien Chirot, Luke MacAleese, Rodolphe Antoine, Philippe Dugourd Journal of the American Society for Mass Spectrometry, 2017
Silver cluster-biomolecule hybrids: From basics towards sensors Vlasta Bonačić-Koutecký, Alexander Kulesza, Lars Gell, Roland Mitrić, Rodolphe Antoine, Franck Bertorelle, Ramzi Hamouda, Driss Rayane, Michel Broyer, Thibault Tabarin, Philippe Dugourd Physical Chemistry Chemical Physics, 2012
Best Practices on QSP Model Reporting for Regulatory Use: perspectives from ISoP QSP SIG Working Group S Zaph, B Shtylla, S Chang, Y Cheng, JQX Gong, A Gulati, E Hansson, ... arXiv preprint arXiv:2604.07811 , 2026 2026
OPEN-SOURCE MODULAR FRAMEWORK FOR PHARMACOKINETIC, PHARMACODYNAMIC, AND SAFETY SIMULATIONS OF ANTI-TUBERCULOSIS DRUGS M Siccardi, N Nauwelaerts, V Baier, V Karamitsou, R Lesage, ... CLINICAL PHARMACOLOGY & THERAPEUTICS 119 , 2026 2026
OPEN-SOURCE MODULAR PBPK-QSP PLATFORM FOR TRANSLATIONAL MODELING AND SAFETY ASSESSMENT OF BISPECIFIC T-CELL ENGAGERS S Schaller, A Kulesza CLINICAL PHARMACOLOGY & THERAPEUTICS 119 , 2026 2026
Continuous infusion simulations in PBPK and QSP models reveal steady-state properties and rate-limiting steps. W Witte, A Kulesza, S Schaller American Conference of Pharmacometrics, T-004 , 2026 2026
Towards uncertainty assessment-based acceptability thresholds for model validation? A Kulesza, C Massaux, FM Tshinanu American Conference of Pharmacometrics, M-023 , 2026 2026
A multi-model strategy in R to address cytopenia A Kulesza, V Karamitsou, V Baier, P Balazki, M Albrecht, L Villain, T Jukier, ... American Conference of Pharmacometrics, M-022 , 2026 2026
A pipeline for generating large virtual dog populations to predict preclinical drug-induced liver injury V Karamitsou, R Lesage, R Engelke, M Siccardi, SJ Schaller, A Kulesza American Conference of Pharmacometrics, T-015 , 2026 2026
P18-107 Reducing Animal Use in Toxicological Research through Open-Source Individualized (PB) PK/QST Modeling: A Case Study with Phenobarbital in Dogs V Karamitsou, R Lesage, R Engelke, M Siccardi, S Schaller, T Jukier, ... Toxicology Letters 411, S233 , 2025 2025
P18-41 Integrating Lines of In Silico Toxicological Evidence to Create a Weight-of-Evidence for Adverse Outcomes M Cronin, S Chavan, G Chrysochoou, G Ecker, S Enoch, J Firman, ... Toxicology Letters 411, S205 , 2025 2025
Whole-Body Physiologically Based Pharmacokinetic Modeling Framework for Tissue Target Engagement of CD3 Bispecific Antibodies ME Susilo, S Schaller, LD Jiménez-Franco, A Kulesza, WEA de Witte, ... Pharmaceutics 17 (4), 500 , 2025 2025
Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice A Kulesza, C Couty, P Lemarre, CJ Thalhauser, Y Cao Journal of pharmacokinetics and pharmacodynamics 51 (6), 581-604 , 2024 2024 Citations: 14
Immune digital twins for complex human pathologies: applications, limitations, and challenges A Niarakis, R Laubenbacher, G An, Y Ilan, J Fisher, Å Flobak, K Reiche, ... NPJ systems biology and applications 10 (1), 141 , 2024 2024 Citations: 83
Towards A QSP Platform To Support Drug Development In Hematological Cancers C Couty, P Lemarre, AI Toledo, A Schneider, M Hanke, A Kulesza, ... American Conference of Pharmacometrics , 2024 2024
Bispecific T-cell engagers and cytokine release syndrome: Modeling molecule, indication and patient-specific aspects A Kulesza, LDJ Franco, V Karamitsou, WEA de Witte, C Troisi, SJ Schaller American Conference of Pharmacometrics , 2024 2024
In-depth numerical model analysis tools to gain insight into model behavior of large-scale pharmacometric models WEA De Witte, A Kulesza, SJ Schaller American Conference of Pharmacometrics , 2024 2024
Mathematical modeling can help to successfully translate preclinical findings in mice models of asthma into first-in-human trials C Leon, T Galland, C Sansone, AV Chessex, C Pasquali, L Lehr, ... American Conference of Pharmacometrics , 2024 2024
Coupling A Quantitative Systems Pharmacology Model With A Simple Statistical Layer To Predict Asthma Exacerbation Rate Reduction From Allergen Challenge Results S Arsène, T Galland, C Leon, C Sansone, AV Chessex, C Pasquali, ... American Conference of Pharmacometrics , 2024 2024
A quantitative systems pharmacology workflow toward optimal design and biomarker stratification of atopic dermatitis clinical trials N Go, S Arsène, I Faddeenkov, T Galland, S Martis, D Lefaudeux, Y Wang, ... Journal of Allergy and Clinical Immunology 153 (5), 1330-1343 , 2024 2024 Citations: 8
Model Development A Kulesza, A Loewe, A Stenti, C Nicolò, E Morales-Orcajo, E Courcelles, ... Toward Good Simulation Practice: Best Practices for the Use of Computational … , 2024 2024 Citations: 1
Model credibility E Courcelles, M Horner, P Afshari, A Kulesza, C Curreli, C Vaghi, ... Toward Good Simulation Practice: Best Practices for the Use of Computational … , 2024 2024 Citations: 9
MOST CITED SCHOLAR PUBLICATIONS
Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility FT Musuamba, I Skottheim Rusten, R Lesage, G Russo, R Bursi, L Emili, ... CPT: pharmacometrics & systems pharmacology 10 (8), 804-825 , 2021 2021 Citations: 176
3D imaging of nanoparticle distribution in biological tissue by laser-induced breakdown spectroscopy Y Gimenez, B Busser, F Trichard, A Kulesza, JM Laurent, V Zaun, F Lux, ... Scientific reports 6 (1), 29936 , 2016 2016 Citations: 147
Synthesis, characterization and optical properties of low nuclearity liganded silver clusters: Ag 31 (SG) 19 and Ag 15 (SG) 11 F Bertorelle, R Hamouda, D Rayane, M Broyer, R Antoine, P Dugourd, ... Nanoscale 5 (12), 5637-5643 , 2013 2013 Citations: 103
Immune digital twins for complex human pathologies: applications, limitations, and challenges A Niarakis, R Laubenbacher, G An, Y Ilan, J Fisher, Å Flobak, K Reiche, ... NPJ systems biology and applications 10 (1), 141 , 2024 2024 Citations: 83
Possible Contexts of Use for In Silico Trials Methodologies: A Consensus-Based Review M Viceconti, L Emili, P Afshari, E Courcelles, C Curreli, N Famaey, L Geris, ... IEEE Journal of Biomedical and Health Informatics 25 (10), 3977-3982 , 2021 2021 Citations: 71
Absorption enhancement and conformational control of peptides by small silver clusters T Tabarin, A Kulesza, R Antoine, R Mitrić, M Broyer, P Dugourd, ... Physical review letters 101 (21), 213001 , 2008 2008 Citations: 63
Silver cluster–biomolecule hybrids: From basics towards sensors V Bonačić-Koutecký, A Kulesza, L Gell, R Mitrić, R Antoine, F Bertorelle, ... Physical Chemistry Chemical Physics 14 (26), 9282-9290 , 2012 2012 Citations: 62
2 core-level binding energies of size-selected free silicon clusters: Chemical shifts and cluster structure M Vogel, C Kasigkeit, K Hirsch, A Langenberg, J Rittmann, ... Physical Review B—Condensed Matter and Materials Physics 85 (19), 195454 , 2012 2012 Citations: 57
Conformational changes in amyloid-beta (12–28) alloforms studied using action-FRET, IMS and molecular dynamics simulations S Daly, A Kulesza, F Poussigue, AL Simon, CM Choi, G Knight, F Chirot, ... Chemical Science 6 (8), 5040-5047 , 2015 2015 Citations: 51
Doubly Charged Silver Clusters Stabilized by Tryptophan: Ag 4 2+ as an Optical Marker for Monitoring Particle Growth A Kulesza, R Mitrić, V Bonačić‐Koutecký, B Bellina, I Compagnon, ... Angewandte Chemie International Edition 50 (4), 878-881 , 2011 2011 Citations: 51
Tuning structural and optical properties of thiolate-protected silver clusters by formation of a silver core with confined electrons L Gell, A Kulesza, J Petersen, MIS Röhr, R Mitrić, V Bonacic-Koutecky The Journal of Physical Chemistry C 117 (28), 14824-14831 , 2013 2013 Citations: 49
Chiral supramolecular gold-cysteine nanoparticles: Chiroptical and nonlinear optical properties I Russier-Antoine, F Bertorelle, A Kulesza, A Soleilhac, ... Progress in Natural Science: Materials International 26 (5), 455-460 , 2016 2016 Citations: 44
Structural and optical properties of isolated noble metal–glutathione complexes: insight into the chemistry of liganded nanoclusters B Bellina, I Compagnon, F Bertorelle, M Broyer, R Antoine, P Dugourd, ... The Journal of Physical Chemistry C 115 (50), 24549-24554 , 2011 2011 Citations: 44
Experimental and theoretical study of the absorption properties of thiolated diamondoids L Landt, C Bostedt, D Wolter, T Möller, JEP Dahl, RMK Carlson, ... The Journal of chemical physics 132 (14) , 2010 2010 Citations: 44
Binding motifs of silver in prion octarepeat model peptides: a joint ion mobility, IR and UV spectroscopies, and theoretical approach B Bellina, I Compagnon, L MacAleese, F Chirot, J Lemoine, P Maître, ... Physical Chemistry Chemical Physics 14 (32), 11433-11440 , 2012 2012 Citations: 37
Photoabsorption and photofragmentation of isolated cationic silver cluster–tryptophan hybrid systems R Mitrić, J Petersen, A Kulesza, V Bonačić-Koutecký, T Tabarin, ... The Journal of chemical physics 127 (13) , 2007 2007 Citations: 36
A mixed quantum–classical description of excitation energy transfer in supramolecular complexes: Förster theory and beyond J Megow, B Röder, A Kulesza, V Bonačić‐Koutecký, V May ChemPhysChem 12 (3), 645-656 , 2011 2011 Citations: 34
Verifying and validating quantitative systems pharmacology and in silico models in drug development: current needs, gaps, and challenges FT Musuamba, R Bursi, E Manolis, K Karlsson, A Kulesza, E Courcelles, ... CPT: Pharmacometrics & Systems Pharmacology 9 (4), 195 , 2020 2020 Citations: 30
Structural and Photochemical Properties of Organosilver Reactive Intermediates MeAg 2 + and PhAg 2 + C Brunet, R Antoine, M Broyer, P Dugourd, A Kulesza, J Petersen, ... The Journal of Physical Chemistry A 115 (33), 9120-9127 , 2011 2011 Citations: 27
Bringing molecular dynamics and ion-mobility spectrometry closer together: Shape correlations, structure-based predictors, and dissociation A Kulesza, EG Marklund, L MacAleese, F Chirot, P Dugourd The Journal of Physical Chemistry B 122 (35), 8317-8329 , 2018 2018 Citations: 25
