Meet IntiQuan Team

All IntiQuan team members
are recognized experts
in modeling & simulation

OUR TEAM MEMBERS HAVE EXCELLENT
EXPERTISE IN MODELING & SIMULATION, ADVANCED ANALYTICS, AND DRUG DEVELOPMENT

We combine several decades of experience in the model-based and strategy-based support of drug development programs and general application of advanced analytics to inform decision making

Stefan Wetzel, PhD

Managing Director

Bio

Stefan Wetzel is a trained chemist with a background in biology, pharmacology and computational modelling. After his award-winning Ph.D. obtained at the Max-Planck Institute in Dortmund, Germany, he worked as presidential postdoctoral fellow in quantitative biology at Novartis in Basel. Moving from science to business, Stefan joined Bain & Company, one of the top tier strategy consultancies, where he worked in and led projects. Combining his passion for health care and consulting, Stefan joined IQVIA as local lead for commercial effectiveness consulting for healthcare marketing and sales. In this role, Stefan built a team supporting Swiss and international clients with state-of-the-art analyses of commercial data and recommendations for commercial topics including go-to-market strategy, pricing and reimbursement and marketing. In addition, Stefan acted as IQVIA’s Swiss market expert regularly making public appearances and providing insights into the Swiss pharma market to an interested audience.

Stefan has been part of the IntiQuan team since March 2021, where he leads the commercial and operational part as well as the strategic development of IntiQuan.

Publications

PHD THESIS

1. Wetzel, S. (2009) Similarity in chemical and protein space : finding novel starting points for library design, Ph.D. Thesis, Technical University of Dortmund, Dortmund, Germany

SOFTWARE

2. Scaffold Hunter: a Java-based open source tool for the visual analysis of data sets with a focus on data from the life sciences, in collaboration with the department of informatics of the Technical University Dortmund, http://scaffoldhunter.sourceforge.net/

BOOK CHAPTERS

3. Lachance H., Wetzel S., Waldmann H. (2009) Role of Natural Products in Drug Discovery in Morphy, R. and Rankovic, Z. (Eds.), Modern Approaches to Lead Discovery.

4. Wetzel S., Lachance H., Waldmann H. (2009) Natural Products as lead source for drug development, in Mander, L. and Liu, H. W. (Eds.), Comprehensive Natural Products Chemistry II, Elsevier.

5. Kumar K., Wetzel S., Waldmann H. (2008) Biology Oriented Synthesis and Diversity Oriented Synthesis in Compound Collection Development in Camille G. Wermuth (Ed.), The Practice of Medicinal Chemistry, 3rd Edition, Academic Press, London.

6. Dekker F.J., Wetzel S., Waldmann H. (2006) Natural product scaffolds and protein structure similarity clustering (PSSC) as inspiration sources for compound library design in chemogenomics and drug development in Edgar Jacoby (Ed.) CHEMOGENOMICS – Knowledge-based Approaches to Drug Discovery, Imperial College Press, London.

JOURNAL PUBLICATIONS

7. Hoepfner D, Helliwell SB, Sadlish H, Schuierer S, Filipuzzi I, Brachat S, Bhullar B, Plikat U, Abraham Y, Altorfer M, Aust T, Baeriswyl L, Cerino R, Chang L, Estoppey D, Eichenberger J, Frederiksen M, Hartmann N, Hohendahl A, Knapp B, Krastel P, Melin N, Nigsch F, Oakeley EJ, Petitjean V, Petersen F, Riedl R, Schmitt EK, Staedtler F, Studer C, Tallarico JA, Wetzel S, Fishman MC, Porter JA, Movva NR. (2014) High-resolution chemical dissection of a model eukaryote reveals targets, pathways and gene functions. Microbiol Res., doi: 10.1016/j.micres.2013.11.004.

8. Over B, Wetzel S, Grütter C, Nakai Y, Renner S, Rauh D, Waldmann (2013) H. Natural-product-derived fragments for fragment-based ligand discovery. Nat Chem., doi: 10.1038/nchem.1506.

9. Lachance H, Wetzel S, Kumar K, Waldmann H. (2012) Charting, navigating, and populating natural product chemical space for drug discovery. J Med Chem., doi: 10.1021/jm300288g.

10. Deraeve C, Guo Z, Bon RS, Blankenfeldt W, DiLucrezia R, Wolf A, Menninger S, Stigter EA, Wetzel S, Choidas A, Alexandrov K, Waldmann H, Goody RS, Wu YW. (2012) Psoromic acid is a selective and covalent Rab-prenylation inhibitor targeting autoinhibited RabGGTase. J Am Chem Soc., doi: 10.1021/ja211305j.

11. Willmann D, Lim S, Wetzel S, Metzger E, Jandausch A, Wilk W, Jung M, Forne I, Imhof A, Janzer A, Kirfel J, Waldmann H, Schüle R, Buettner R. (2012) Impairment of prostate cancer cell growth by a selective and reversible lysine-specific demethylase 1 inhibitor. Int J Cancer. , doi: 10.1002/ijc.27555.

12. Wetzel S, Bon RS, Kumar K, Waldmann H. (2011) Biology-oriented synthesis. Angew Chem Int Ed Engl., doi: 10.1002/anie.201007004.

13. Hedberg C, Dekker FJ, Rusch M, Renner S, Wetzel S, Vartak N, Gerding-Reimers C, Bon RS, Bastiaens PI, Waldmann H. (2011) Development of highly potent inhibitors of the Ras-targeting human acyl protein thioesterases based on substrate similarity design. Angew Chem Int Ed Engl., doi: 10.1002/anie.201102965.

14. Bon RS, Guo Z, Stigter EA, Wetzel S, Menninger S, Wolf A, Choidas A, Alexandrov K, Blankenfeldt W, Goody RS, Waldmann H. (2011) Structure-guided development of selective RabGGTase inhibitors. Angew Chem Int Ed Engl., doi: 10.1002/anie.201101210.

15. Dekker FJ, Rocks O, Vartak N, Menninger S, Hedberg C, Balamurugan R, Wetzel S, Renner S, Gerauer M, Schölermann B, Rusch M, Kramer JW, Rauh D, Coates GW, Brunsveld L, Bastiaens PI, Waldmann H. (2010) Small-molecule inhibition of APT1 affects Ras localization and signaling. Nat Chem Biol., doi: 10.1038/nchembio.362.

16. Wetzel S, Wilk W, Chammaa S, Sperl B, Roth AG, Yektaoglu A, Renner S, Berg T, Arenz C, Giannis A, Oprea TI, Rauh D, Kaiser M, Waldmann H. (2010) A scaffold-tree-merging strategy for prospective bioactivity annotation of gamma-pyrones. Angew Chem Int Ed Engl., doi: 10.1002/anie.200906555.

17. Tan KT, Guiu-Rozas E, Bon RS, Guo Z, Delon C, Wetzel S, Arndt S, Alexandrov K, Waldmann H, Goody RS, Wu YW, Blankenfeldt W. (2009) Design, synthesis, and characterization of peptide-based rab geranylgeranyl transferase inhibitors. J Med Chem., doi: 10.1021/jm901117d.

18. Wetzel S, Klein K, Renner S, Rauh D, Oprea TI, Mutzel P, Waldmann H. (2009) Interactive exploration of chemical space with Scaffold Hunter. Nat Chem Biol., doi: 10.1038/nchembio.187.

19. Renner S, van Otterlo WA, Dominguez Seoane M, Möcklinghoff S, Hofmann B, Wetzel S, Schuffenhauer A, Ertl P, Oprea TI, Steinhilber D, Brunsveld L, Rauh D, Waldmann H. (2009) Bioactivity-guided mapping and navigation of chemical space. Nat Chem Biol., doi: 10.1038/nchembio.188.

20. Triola G, Wetzel S, Ellinger B, Koch MA, Hübel K, Rauh D, Waldmann H. (2008) ATP competitive inhibitors of D-alanine-D-alanine ligase based on protein kinase inhibitor scaffolds. Bioorg Med Chem., doi: 10.1016/j.bmc.2008.02.046.

21. Guo Z, Wu YW, Tan KT, Bon RS, Guiu-Rozas E, Delon C, Nguyen TU, Wetzel S, Arndt S, Goody RS, Blankenfeldt W, Alexandrov K, Waldmann H. (2008) Development of selective RabGGTase inhibitors and crystal structure of a RabGGTase-inhibitor complex. Angew Chem Int Ed Engl. , doi: 10.1002/anie.200705795.

22. Bisek N, Wetzel S, Arndt HD, Waldmann H. (2008) Synthesis and conformational analysis of stevastelin C3 analogues and their activity against the dual-specific vaccina H1-related phosphatase. Chemistry. doi: 10.1002/chem.200800692.

23. Kaiser M, Wetzel S, Kumar K, Waldmann H. Biology-inspired synthesis of compound libraries. (2008) Cell Mol Life Sci., doi: 10.1007/s00018-007-7492-1.

24. Köhn M, Gutierrez-Rodriguez M, Jonkheijm P, Wetzel S, Wacker R, Schroeder H, Prinz H, Niemeyer CM, Breinbauer R, Szedlacsek SE, Waldmann H. (2007) A microarray strategy for mapping the substrate specificity of protein tyrosine phosphatase. Angew Chem Int Ed Engl., doi: 10.1002/anie.200701601.

25. Wetzel S, Schuffenhauer A, Roggo S, Ertl P, Waldmann H (2007) Cheminformatic Analysis of Natural Products and their Chemical Space, CHIMIA, 10.2533/chimia.2007.355.

26. Schuffenhauer A, Ertl P, Roggo S, Wetzel S, Koch MA, Waldmann (2007) H. The scaffold tree–visualization of the scaffold universe by hierarchical scaffold classification. J Chem Inf Model., doi: 10.1021/ci600338x.

27. Charette BD, Macdonald RG, Wetzel S, Berkowitz DB, Waldmann H. (2006) Protein structure similarity clustering: dynamic treatment of PDB structures facilitates clustering. Angew Chem Int Ed Engl. 2006, doi: 10.1002/anie.200602125.

28. Koch MA, Schuffenhauer A, Scheck M, Wetzel S, Casaulta M, Odermatt A, Ertl P, Waldmann H. (2005) Charting biologically relevant chemical space: a structural classification of natural products (SCONP). Proc Natl Acad Sci U S A, doi: 10.1073/pnas.0503647102.

CONFERENCE ARTICLES / TALKS

1. Session Chair for the session “Exploring the Chemical Space” at the XXth International Symposium on Medicinal Chemistry, Vienna, Austria, 2008

2. Invited lecture on “Scaffold Hunter: Charting and Exploring Chemical Space” at the XXth International Symposium on Medicinal Chemistry, Vienna, Austria, 2008

3. Invited lecture on “Mapping Protein Space by Comparing Ligand-Sensing Cores” at the workshop “New approaches in drug design and discovery – merging chemical and biological space”, Rauischholzhausen, Germany, 2007

POSTERS

4. Poster“BIOS: Similarity-based Design of Natural Product derived Compound Collections“ at the 115th International Summer Course, BASF SE, Ludwigshafen, Germany, 2008.

5. Poster “Scaffold Huntger: Exploiting Holes in Chemical Space” at the 8th International Conference on Chemical Structures, Noordwijkerhout, Netherlands, 2008

6. Poster “BIOS: Similarity-based Design of Natural Product derived Compound Collections” at the 3rd Conference in Chemoinformatics, Goslar, Germany, 2007.

7. Poster “Chemical Space: Structural Classification of Bioactive Compounds” at Crossing Borders in Chemical Biology, Rolduc, Netherlands, 2007.

8. Poster “BioChemIsTree: Software-assisted Scaffold Tree Analysis of Large Compound Collections” at the 4th Joint Sheffield Conference on Cheminformatics, Sheffield, UK, 2007.

9. Poster “Charting Chemical Space: Structural Classification of Bioactive Compounds“ at the 2nd Conference in Chemoinformatics, Goslar, Germany, 2006.

10. Poster award for the poster “Protein Structural Similarity Clustering“ at the Summer School on Medicinal Chemistry, Regensburg, Germany, 2006.

11. Poster award for the poster “Charting Chemical Space: Structural Classification of Bioactive Compounds“ at the European Conference on QSAR and Modelling, on board the MSC Opera on the Mediterranean Sea, 2006.

12. Poster “Structural Classification of Natural Products“ at the Openeye Usergroup Meeting CUP VII, Santa Fe, New Mexico, USA, 2006.

13. Poster “Structural Classification of Natural Products“ at the 1st German Conference on Chemoinformatics, Goslar, Germany, 2005.

14. Poster “Protein Structure Similarity Clustering“ at the CBC Symposium of the Imperial College London and GlaxoSmithKline, Stevenage, UK, 2005.

Henning Schmidt, PhD

Chief Scientific Officer

Bio

Expert in Model-Informed Drug Development with cross-functional domain expertise supporting various therapeutic areas with over fifteen years of experience in the field. Professional experience includes assessing all available data and information within drug development projects (nonclinical, translational, early and late clinical, registration) in the context of the current drug development questions. Perform gap analyses, devise model based strategies to address key questions, select adequate methodological approaches, hands-on execution of analyses, supervision and mentoring of more junior modelers, and communication of results. Therapeutic area experience includes oncology, dermatology, immunology, infectious diseases, respiratory, gastrointestinal, bone and muscle wasting diseases. Pharmacometric experience includes (population) PK/PD, exposure-response, survival analysis, clinical trial simulations to assess certain metrics of interest (e.g., probability of success), complex mechanistic quantitative systems pharmacology models. Software and computational experience includes more than 18 years in the development of state-of-the-art software in support of efficient modeling and simulation across areas of Systems Biology, Quantitative Systems Pharmacology, and Pharmacometrics. These tools are key to allow focusing on the drug development question to address.

Publications

Journal Articles

Martin Johnson, Yu-Wei Lin, Henning Schmidt, Mikael Sunnaker, Eline Van Maanen, Xiangning Huang, Yuri Rukazenkov, Helen Tomkinson, Karthick Vishwanathan (2025) Population Pharmacokinetics of Osimertinib in Patients With Non-Small Cell Lung Cancer. Pharmacology Research & Perspectives, https://doi.org/10.1002/psp4.12426

Martin Johnson, Yu-Wei Lin, Henning Schmidt, Mikael Sunnaker, Eline Van Maanen, Xiangning Huang, Yuri Rukazenkov, Helen Tomkinson, Karthick Vishwanathan (2024) Exposure–response modelling of osimertinib in patients with non-small cell lung cancer. British Journal of Clinical Pharmacology, https://doi.org/10.1111/bcp.16199

Johnson, M., Kaschek, K., Ghiorghiu, D., Lanke, S., Miah, K., Schmidt, S., Mugundu, G. (2023) Population pharmacokinetic modelling of adavosertib (AZD1775) in patients with solid tumours, submitted to Clinical Pharmacokinetics.

Lill D., Kümmel A., Mitov V., Kaschek D., Gobeau N., Schmidt H., Timmer J. (2022) Efficient simulation of clinical target response surfaces. CPT Pharmacometrics and Systems Pharmacology 11 (4):512-523

Helmlinger, G. et al (2019) Quantitative Systems Pharmacology: An Exemplar Model Building Workflow with Applications in Metabolic, Cardiovascular, and Oncology Drug Development, CPT Pharmacometrics Syst Pharmacol., doi: 10.1002/psp4.12426.

Schmidt, H., Radivojevic, A. (2014) Enhancing population pharmacokinetic (popPK) modeling efficiency using an integrated workflow, Journal of Pharmacokinetics and Pharmacodynamics, invited paper, 41(4)

Hallow, K.M., et al. (2014) A model-based approach to investigating the pathophysiological mechanisms of hypertension and response to antihypertensive therapies: Extending the Guyton model, American Journal of Physiology, DOI: 10.1152/ajpregu.00039.2013

Sunnaker, M., Schmidt, H., Jirstrand, M., Cedersund, G. (2010) Zooming of states and parameters using a lumping approach including back-translation, BMC Systems Biology, 4(28)

Dell’Orco, D., Schmidt, H., Mariani, S, Fanelli, F. (2009) Network-level analysis of light adaptation in rod cells under normal and altered conditions, Molecular BioSystems, DOI: 10.1039/b908123b

Schmidt, H., Madsen, M., Danø, S., Cedersund, G. (2008) Complexity Reduction of Biochemical Rate Expressions, Bioinformatics, doi: 10.1093/bioinformatics/btn035

Dell’Orco, D., Schmidt, H. (2008) Mesoscopic Monte Carlo simulations of stochastic encounters between photoactivated rhodopsin and transducin in the ROS-disc membrane, Journal of Physical Chemistry, doi: 10.1021/jp709963f

Nedbal, L., Červený, J., Rascher, U., Schmidt, H. (2007) A modeling approach to understand chlorophyll fluorescence transients and complex dynamic features of photosynthesis in fluctuating light, Photosynthesis Research, 93, 223-234

Schmidt, H., Drews, G., Vera, J., Wolkenhauer, O. (2007) SBML Export Interface for the Systems Biology Toolbox for MATLAB, Bioinformatics, 23, 1297-1298

Schmidt, H. (2007) SBaddon: High Performance Simulation for the Systems Biology Toolbox for MATLAB, Bioinformatics, 23, 646-647

Danø, S., Madsen, M., Schmidt, H., Cedersund, G. (2006) Reduction of a biochemical model with preservation of its basic dynamic properties, FEBS Journal, 273, 4862-4877

Schmidt, H., Jirstrand, M., Wolkenhauer, O. (2006) Information Technology in Systems Biology, invited article for it–Information Technology, 48(3), 133-139

Schmidt, H., Jirstrand, M. (2006) Systems Biology Toolbox for MATLAB: A computational platform for research in Systems Biology, Bioinformatics, 22(4), 514-515

Ullah, M., Schmidt, H., Cho, K.-H., Wolkenhauer, O. (2006) Deterministic Modelling and Stochastic Simulation of Pathways using MATLAB, IEE Proceedings – Systems Biology, 153(2), 53-60

Schmidt, H., Jacobsen, E.W., Cho, K.-H. (2005) Identification of Small Scale Biochemical Networks Based on General Type System Perturbations, FEBS Journal, 272(9), 2141-2151

Schmidt, H., Jacobsen, E.W. (2004) Linear systems approach to analysis of complex dynamic behaviours in biochemical networks, IEE Systems Biology, 1, 149-158

Schmidt, H., Jacobsen, E.W. (2004) Identifying feedback mechanisms behind complex cell behaviour, IEEE Control Systems Magazine, 24(4), 91-102

Book Chapters

Nedbal, N., Červený, J., Schmidt, H. (2009) Scaling and Integration of Kinetic Models of C3 Photosynthesis: Towards Comprehensive E-Photosynthesis, book chapter, Photosynthesis in silico, Springer

Ericsson, A., Mojzita, D., Schmidt, H., Hohmann, S. (2008) Case study in systematic modelling: Thiamine uptake in Yeast S. cerevisiae, book chapter, Essays in Biochemistry – Systems Biology, Portland Press

Conference posters

Clegg, L.E., Schmidt, H., Gibbs, M., Sedani, S., Tullio, N., Sadow, S., Stepanov, O., Pilla Reddy, V., Tang, W., Någård, M., Martinez-Alier, N., Cohen, T., Faust, S., Esser M.T. (2023) Consistency of AZD7442 Pharmacokinetics Across Prophylaxis and Treatment and Adult and Pediatric Participants: Application of Population Pharmacokinetics to Enable Rapid Decision-Making During the COVID-19 Pandemic, submitted to IDWeek 2023, Boston, MA, USA

Lill D., Kümmel A., Gobeau N., Schmidt H., Timmer J. (2020) Efficient simulation of clinical target isoboles applied to drug combinations for malaria, Eleventh American Conference on Pharmacometrics (ACoP). Recipient of the MCS SIG award

Johnson, M., et al. (2019) Model based analysis of the effect of adavosertib, a WEE1 kinase inhibitor on olaparib exposure, ASCPT 2019 Annual Meeting, USA

Johnson, M., et al. (2019) Population pharmacokinetics and exposure response relationship following osimertinib treatment, ASCPT 2019 Annual Meeting, USA

Moorthy, G., et al. (2018) Population Pharmacokinetic Model of AZD8186, a Potent and Selective Inhibitor of PI3Kβδ, in Patients with Advanced Solid Tumors, ASCPT 2018 Annual Meeting, Orlando, USA

Kümmel, A., Sunnåker, M., Kaschek, D., Schmidt, H. (2017) Manage your data comfortably: Data programming and analysis using R, Eight American Conference on Pharmacometrics (ACoP), Fort Lauderdale, USA

Sokolov, V, et al. (2017) Drug-Disease modeling: a practical workflow from model development to simulations, Eight American Conference on Pharmacometrics (ACoP), Fort Lauderdale, USA

Sunnåker, M., Kümmel, A., Kaschek, D., Schmidt, H. (2017) Towards a user-friendly and powerful Modeling & Simulation environment in R – Enabling efficient work across QSP and Pharmacometrics with access to robust estimation algorithms, Eight American Conference on Pharmacometrics (ACoP), Fort Lauderdale, USA

Schmidt, H., Kaschek, D., Kümmel, A., Sunnåker, M. (2017) Systems Pharmacology Modeling in R, powered by Shiny, Eight American Conference on Pharmacometrics (ACoP), Fort Lauderdale, USA

Johnson, M., Schmidt, H., Sunnaker, M., Hamren, B., AlHuniti, N., Nayak, S., Tomkinson, H., Vishwanathan, K. (2017) Exposure response relationship of interstitial lung disease (ILD) events following Osimertinib treatment, Population Approach Group (PAGE) meeting 2017, Budapest, Hungary

Johnson, M., Schmidt, H., Sunnaker, M., Nash, T., Nayak, S., Tomkinson, H., Vishwanathan, K. (2017) Population pharmacokinetic and pharmacodynamic analysis of osimertinib, American Society of Clinical Oncology – 53rd Annual Meeting (ASCO2017), Chicago, USA

Sunnåker, M., Schmidt, H. (2016) IQM Tools: Efficient State of the Art Modeling across Pharmacometrics and Systems Pharmacology (ACoP7), Seattle, USA

Radivojevic, A., Schmidt, H. (2015) Datasets for pharmacometric analyses: internal review and standardization efforts, Sixth American Conference on Pharmacometrics (ACoP6), Arlington, VA, USA

Schmidt, H. (2015) SBPOP/mPD: Informing dose-concentration-response relationships – Application to study design and information generation based on competitor data, Population Approach Group (PAGE) meeting 2015, Hersonissos, Greece

Weber, F. Schmidt, H., Pfister, M., J v.d. Anker (2015) Pharmacometric approach to characterize key metabolites of acetaminophen in preterm and term neonates, Population Approach Group (PAGE) meeting 2015, Hersonissos, Greece

Goldhahn, J., Radivojevic, A., Tanko, L., 3, Papanicolaou, DA., Schmidt, H. (2013) Modeling rehabilitation after hip fracture, 2nd Fragility Fracture Network Congress, Berlin, Germany

Schmidt, H. (2013) The “SBPOP Package”: Efficient Support for Model Based Drug Development – From Mechanistic Models to Complex Trial Simulation, Population Approach Group (PAGE) meeting 2013, Glasgow, Scotland

Radivojevic, A., Fink, M., Steimer, J.-L., Schmidt, H. (2013) Enhancing Population PK modeling efficiency using an integrated workflow, Population Approach Group (PAGE) meeting 2013, Glasgow, Scotland

Zhudenkov, K., Helmlinger, G., Schmidt, H. (2012) Application of the SBTOOLBOX2 in drug discovery and development, Population Approach Group (PAGE) meeting 2012, Venice, Italy

Frey, S., Schmidt, H., Rateitschak, K., Beltran, G., Garcia-Salcedo, R., Elbing, K., Bosch, D., Ye, T., Hohmann, S., Wolkenhauer, O. (2009) Modelling Snf1 regulation in Saccharomyces cerevisiae, 9th International Conference on Systems Biology, Gothenburg, Sweden

Egea, J.A., Schmidt, H., Banga, J.R. (2008) A new tool for parameter estimation in nonlinear dynamic biological systems using global optimization, 9th International Conference on Systems Biology, Gothenburg, Sweden

Liebal, U.W., Schmidt, H. (2008) Sensitivity Analysis based Adaptive Search-Space Reduction for Parameter Estimation Applications, 9th International Conference on Systems Biology, Gothenburg, Sweden

Bittig, A.T., Schmidt,H. (2008) Format Overflow? Handling of Modeling Projects in Systems Biology, 9th International Conference on Systems Biology, Gothenburg, Sweden

Dell’Orco, D., Fanelli, F., Schmidt, H. (2008) Dynamic modeling of phototransduction biochemistry in vertebrate rods: from dark/light adaptation to disease, 9th International Conference on Systems Biology, Gothenburg, Sweden

Almquist, J., Schmidt, H., Lang, P., Prätzel-Wolters, D., Deitmer, J.W., Jirstrand, M., Becker, H.M. (2008) A model reduction approach to the kinetics of the monocarboxylate transporter MCT1 and carbonic anhydrase II, 9th International Conference on Systems Biology, Gothenburg, Sweden

Schmidt, H. (2008) Hierarchical Modelling of Metabolism: From Methodology to Application, ISGSB 2008, Elsinor, Denmark

Schmidt, H., Jirstrand, M., Cedersund, G. (2006) A Systematic Modelling Framework for Biochemical and Biological Systems, 7th International Conference on Systems Biology, Yokohama, Japan

Cedersund, G., Jirstrand, M., Schmidt, H. (2006) Model reduction for various levels of model development, 7th International Conference on Systems Biology, Yokohama, Japan

Jirstrand, M., Schmidt, H., Cedersund, G. (2006) Parameter Estimation Using Alternative Cost Functions, 7th International Conference on Systems Biology, Yokohama, Japan

Mojzita, D., Nahmany, A., Schmidt, H., Homann, S. (2006) Dynamic modelling of thiamine regulation in Saccharomyces cerevisiae based on High Performance Liquid Chromatography (HPLC) measurements, International Specialised Symposium on Yeasts, Helsinki, Finland

Schmidt, H., Jirstrand, M. (2005) Systems Biology Toolbox for MATLAB: A computational platform for research in Systems Biology, 6th International Conference on Systems Biology, Boston, USA

Schmidt, H., Jacobsen, E.W. (2004) On the Decomposition of Biochemical Networks, H. Schmidt and E. Jacobsen, 5th International Conference on Systems Biology, Heidelberg, Germany

Schmidt, H., Jacobsen, E.W. (2004) Identification of the dynamic structure of biochemical networks based on least squares estimation of the Jacobian, 5th International Conference on Systems Biology, Heidelberg, Germany

Schmidt, H., Jacobsen, E.W. (2003) A linear systems approach to the analysis of complex behaviours within biochemical reaction networks – application to the cell cycle, 4th International Conference on Systems Biology, Saint Louis, USA

Petra Jauslin, PhD

Senior Director Modeling & Simulation

Bio

Dr. Petra Jauslin, is an experienced pharmacometrician with more than fifteen years in model-informed drug development, holding a PhD in pharmacometrics and an MSc in pharmacy from Uppsala University. Professional background in the pharmaceutical industry and consultancy includes roles at Roche, Exprimo, Quantitative Solutions, Certara, and IntiQuan. Expertise includes population PK, PK-PD, exposure-response, mechanistic and disease-model development, and clinical trial simulation to support study design, dose selection, and bridging to new pop-ulations and indications. Skilled in defining modeling strategies across all development stages, delivering reg-ulatory-compliant analyses and documentation, and contributing to scientific publications. Has led multidis-ciplinary project teams, managing scope, timelines, and budgets, and has contributed to multiple NDA and BLA submissions across metabolic, dermatologic, neurologic, and oncologic indications. Frequently engaged in quality initiatives, additional responsibilities in mentoring and line management. Proficient in NONMEM, PsN, and R, and fluent in German, English, and Swedish.

Publications

Selected publications:

Fauchet F, Largajolli A, Jauslin PM, Schindler E, Hamimed M, Kantasiripitak W, Gonçalves A, Van Maanen E, Benkali K, Saito T, Silverberg JI, Wollenberg A, Graeber M, Ulianov L, Piketty C, Loprete L, Duval V, Wagner N. Model-informed drug development to support nemolizumab clinical develop-ment in adults and adolescents with moderate to severe atopic dermatitis. Br J Clin Pharmacol. 2026 Jan. Epub ahead of print.

Marathe DD, Jauslin PM, Jan Kleijn H, De Miranda Silva C, Chain A, Abraham AK, Kauh EA, Liu Y, Perini RF, Alwis DP, Jain L. 2024. Exposure-Response Analyses for Belzutifan to Inform Dosing Considera-tions and Labeling. J Clin Pharmacol. Vol 64(10):1246-1258

Wagner N, Loprete L, Duval V, Jauslin P, Benkali K, Silverberg JI, Wollenberg A, Saito T, Ahmad F, Graeber M, Winkelman W, Piketty C. 2023. Selection of Nemolizumab Clinical Dosage for Atopic Der-matitis. J Drugs Dermatol. Vol 22(10):1017-1020

He JZ, Duval V, Jauslin P, Gonçalves A, Abegesah A, Fan C, Lim K, Song X, Chen C, Shi X, Mann H, Krug L, Ren S, Phipps A, Gibbs M, Zhou D. 2023. Population Pharmacokinetics and Exposure-Response Analysis for the CTLA-4 Inhibitor Tremelimumab in Metastatic NSCLC Patients in the Phase III POSEI-DON Study. Clin Pharmacol Ther. Vol 114(6):1375-1386

Marathe DD, Jauslin PM, Kleijn HJ, de Miranda Silva C, Chain A, Bateman T, Shaw PM, Abraham AK, Kauh EA, Liu Y, Perini RF, de Alwis DP, Jain L. 2023. Population pharmacokinetic analyses for belzuti-fan to inform dosing considerations and labeling. CPT Pharmacometrics Syst Pharmacol. Vol 12(10):1499-1510.

Tortorici MA, Yuraszeck T, Cornblath D, Bril V, Hartung HP, Sobue G, Lewis RA, Merkies ISJ, Lawo JP, Praus M, Durn BL, Mielke O, Ma X, Jauslin P, Pfister M, van Schaik IN; PATH study group. 2021. Phar-macometric analysis linking immunoglobulin exposure to clinical efficacy outcomes in chronic inflam-matory demyelinating polyneuropathy. CPT Pharmacometrics Syst Pharmacol. Vol 10(8):839-850

Kerbusch T, Li H, Wada R, Jauslin PM, Wenning L. 2020. Exposure-response characterisation of til-drakizumab in chronic plaque psoriasis: Pooled analysis of 3 randomised controlled trials. Br J Clin Pharmacol. Vol 86(9):1795-1806

Jauslin P, Kulkarni P, Li H, Vatakuti S, Hussain A, Wenning L, Kerbusch T. 2019. Population-Pharmaco-kinetic Modeling of Tildrakizumab (MK-3222), an Anti-Interleukin-23-p19 Monoclonal Antibody, in Healthy Volunteers and Subjects with Psoriasis. Clin Pharmacokinet. Vol 58(8):1059-1068.

Jauslin PM, Karlsson MO, Frey N. 2012. Identification of the Mechanism of Action of a Glucokinase Activator from OGTT Data in Type 2 Diabetic Patients using an Integrated Glucose-Insulin Model. J Clin Pharmacol. Vol 52(12):1861-71

Jauslin PM, Frey N, Karlsson MO. 2011. Modeling of 24-hour glucose and insulin profiles of patients with type 2 diabetes. J Clin Pharmacol. Vol 51(2):153-64

Silber HE, Jauslin PM, Frey N, Karlsson MO. 2009. An integrated model for the glucose-insulin system. Basic Clin Pharmacol Toxicol. Vol 106(3):189-94. Review.

Jauslin PM, Silber HE, Frey N, Gieschke R, Simonsson US, Jorga K, Karlsson MO. 2007. An integrated glucose-insulin model to describe oral glucose tolerance test data in type 2 diabetics. J Clin Pharma-col. Vol 47(10):1244-55.

Silber HE, Jauslin PM, Frey N, Gieschke R, Simonsson US, Karlsson MO. 2007. An integrated model for glucose and insulin regulation in healthy volunteers and type 2 diabetic patients following intrave-nous glucose provocations. J Clin Pharmacol. Vol 47(9):1159-71.

Stetina PM, Madai B, Kulemann V, Kirch W, Joukhadar C. 2005. Pharmacokinetics of scopolamine in serum and subcutaneous adipose tissue in healthy volunteers. Int J Clin Pharmacol Ther. Vol 43(3):134-9.

Conference Talks and Posters

Chain A, Hennig S, van der Vleuten G, Hui K, Kleijn HJ, Jauslin P. 2024. Population Pharmacokinetic and Exposure Response Analysis of Belzutifan in Advanced Renal Cell Carcinoma. PAGE, Rome, Italy.

Fauchet F, Kantasiripitak W, Jauslin P, Duval V, Goncalves A, Largajolli A, Jabbar Lopez Z, Graeber M, Piketty C, Fleuranceau Morel P, Loprete L, Wagner N. 2024. Pharmacokinetic/Pharmacodynamic framework to support the subcutaneous dosing regimen of nemolizumab in subjects with Prurigo Nodularis. PAGE, Rome, Italy.

Jauslin PM, Largajolli A, Schindler E, Loprete L, Wagner N, Duval V. 2019. Modeling bounded scales for evaluation of treatment response to subcutaneous nemolizumab in moderate to severe atopic dermatitis. PAGE, Stockholm, Sweden.

Schindler E, Largajolli A, Jauslin PM, Loprete L, Wagner N, Duval V. 2019. A continuous-time Markov model (CTMM) for investigator’s global assessment (IGA) score in moderate to severe atopic derma-titis treated with subcutaneous nemolizumab. PAGE, Stockholm, Sweden.

Jauslin PM, Kulkarni P, Wada R, Vatakuti S, Hussain A, Wenning L, Kerbusch T. 2018. Population Phar-macokinetic Analysis of Tildrakizumab, an Anti-IL-23 Antibody, in Healthy Volunteers and Subjects with Psoriasis. PAGE, Montreux, Switzerland.

Jauslin PM, Kulkarni P, Wada R, Vatakuti S, Hussain A, Wenning L, Kerbusch T. 2017. Population Phar-macokinetic Modeling of Tildrakizumab (MK-3222), an Anti-interleukin-23-p19 Monoclonal Anti-body, in Healthy Volunteers and Subjects with Psoriasis. PSORIASIS from Gene to Clinic, London, UK.

Jauslin PM, Dubar M, Sebastien B, Laveille C, Olsson Gisleskog P. 2014. Comparison of post-prandial glucose control by two GLP-1 receptor agonists (lixisenatide and liraglutide) in type 2 diabetes. PAGE, Alicante, Spain.

Jauslin PM, Fukushima Y, Mazer NA, Silber HE, Lledó R, Frey N, Karlsson MO. 2010. An integrated model for the glucose-insulin system: from construction to application in clinical drug development. 6th International Symposium on Measurement and Kinetics of In Vivo Drug Effects, Noordwijkerhout, Netherlands.

Jauslin PM, Karlsson MO, Frey N. 2008. Identification of the mechanism of action of a glucokinase activator using an integrated glucose-insulin model. PAGE, Marseille, France.

Bauer R, Guzy S, Silber HE, Jauslin PM, Frey N, Karlsson MO. 2007. Comparison between NONMEM and the Monte-Carlo Expectation Maximization (MC-PEM) method using a physiologically-based glu-cose-insulin model. PAGE, Copenhagen, Denmark.

Jauslin PM, Frey N, Karlsson MO. 2006. Simultaneous modelling of 14-hour glucose and insulin pro-files in type 2 diabetics. PKUK, Sheffield, UK.

Karlsson MO, Silber HE, Jauslin PM, Frey N, Gieschke R, Jorga K, Simonsson USH. 2006. Modeling of glucose-insulin homeostasis in provocation studies; bridging between healthy volunteers and pa-tients. 5th International Symposium on Measurement and Kinetics of In Vivo Drug Effects, Noord-wijkerhout, Netherlands.

Jauslin PM, Silber HE, Frey N, Gieschke R, Simonsson USH, Jorga K, Karlsson MO. 2005. A disease model describing the regulation of the glucose-insulin system in diabetic patients after IVGTT and OGTT. PAGE, Pamplona, Spain.

Silber H, Stetina P, McHugh B, Gieschke R, Frey N, Vicini P, Simonsson USH, Karlsson MO. 2004. A disease model for the regulation of the glucose-insulin system. PAGE, Uppsala, Sweden.

Daniel Kaschek, PhD

Director Modeling & Simulation

Bio

Dr. Daniel Kaschek is an experienced modeler working in the field of Systems Biology and Computational Biology since 2008. Over the past years, he has actively worked on the developed of novel mathematical and statistical approaches to data analysis and parameter estimation in ordinary differential equations with applications in Systems Biology and Systems Pharmacology. He is an enthusiast R package developer, authoring several packages on Data Preprocessing and Dynamic Modeling.

Daniel has a background in Physics and specialized on Mathematical Physics at the University of Freiburg, Germany. For his PhD he changed field and started his research in Systems Biology and Data Analysis at the Physics department. During his PhD he covered a broad range of biological applications, e.g., in Immunology, Cancer Research or Drug-Induced Liver Injury, developing and applying diverse mathematical methods related to statistical inference, optimal control and identifiability analysis.

After his PhD, he became leader of the subgroup “Physical Methods in Systems Biology” where he worked with his team on the translation of concepts from theoretical physics to applications in Systems Biology. He joined the IntiQuan team in 2017

Publications

Selected publications:

Kaschek, D.; Sharanek, A.; Guillouzo, A.; Timmer, J. & Weaver, R. J., A dynamic mathematical model of bile acid clearance in HepaRG cells, Toxicological Sciences, Oxford University Press, 2017

Rosenblatt, M.; Timmer, J. & Kaschek, D, Customized steady-state constraints for parameter estimation in non-linear ordinary differential equation models, Frontiers in Cell and Developmental Biology, Frontiers Media SA, 2016

Maiwald, T.; Hass, H.; Steiert, B.; Vanlier, J.; Engesser, R.; Raue, A.; Kipkeew, F.; Bock, H. H.; Kaschek, D.; Kreutz, C. & Timmer, J., Driving the model to its limit: profile likelihood based model reduction PloS ONE, Public Library of Science, 2016

Kaschek, D.; Mader, W.; Fehling-Kaschek, M.; Rosenblatt, M. & Timmer, J., Dynamic Modeling, Parameter Estimation and Uncertainty Analysis in R, bioRxiv, Cold Spring Harbor Labs Journals, 2016

Hass, H.; Kreutz, C.; Timmer, J. & Kaschek, D., Fast integration-based prediction bands for ordinary differential equation models, Bioinformatics, Oxford Univ Press, 2016

Kaschek, D.; Henjes, F.; Hasmann, M.; Korf, U. & Timmer, J., Testing the pattern of AKT activation by variational parameter estimation, IEEE Life Science Letters, 2016

Kaschek, D. & Timmer, J., A unified approach to integration and optimization of parametric ordinary differential equations, Springer, 2015

Merkt, B.; Timmer, J. & Kaschek, D., Higher-order Lie symmetries in identifiability and predictability analysis of dynamic models, Physical Review E, APS, 2015

Raue, A.; Schilling, M.; Bachmann, J.; Matteson, A.; Schelke, M.; Kaschek, D.; Hug, S.; Kreutz, C.; Harms, B. D.; Theis, F. J. & others, Lessons learned from quantitative dynamical modeling in systems biology, PloS One, Public Library of Science, 2013

Fiala, G. J.; Kaschek, D.; Blumenthal, B.; Reth, M.; Timmer, J. & Schamel, W. W., Pre-clustering of the B cell antigen receptor demonstrated by mathematically extended electron microscopy, Frontiers in Immunology, Frontiers Media SA, 2013

Kreutz, C.; Raue, A.; Kaschek, D. & Timmer, J., Profile likelihood in systems biology, FEBS Journal, Wiley Online Library, 2013

Kaschek, D. & Timmer, J., A variational approach to parameter estimation in ordinary differential equations, BMC Systems Biology, BioMed Central Ltd, 2012

Pfeifer, A. C.; Kaschek, D.; Bachmann, J.; Klingmüller, U. & Timmer, J., Model-based extension of high-throughput to high-content data, BMC Systems Biology, BioMed Central Ltd, 2010

Anne Kümmel, PhD

Director Modeling & Simulation

Publications

Selected peer-reviewed Articles

Kümmel A., Selzer P., Siebert D., Schmidt I., Reinhard J., Götte M, Ibig-Rehm Y., Parker C. N., Gabriel D. Differentiation and visualization of diverse cellular phenotypic responses in primary high-content screening Journal of Biomolecular Screening 16(3): 338-347 2012

Kümmel A., Ewald J. C., Fendt S.-M., Jol S., Picotti P., Aebersold R., Sauer U., Zamboni N., Heinemann M. Differential glucose repression in common yeast strains in response to a HXK2 deletion. FEMS Yeast Research 10(3): 322-32, 2010

Kümmel A., Beibel M., Gehin P., Gubler H., Gabriel D., Parker C. N. Integration of multiple readouts into the Z’ factor for assay quality control Journal of Biomolecular Screening 15(1): 95-101, 2010.

Kümmel A., Panke S., Heinemann M. Systematic assignment of thermodynamic constraints in metabolic network models BMC Bioinformatics 7:512, 2006

Kümmel A., Panke S., Heinemann M. Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data Molecular Systems Biology 2, 2006, doi:10.1038/msb4100074

Book chapters

Lowe P. J., Kümmel A., Vasalou C., Matsushima S., Skerjanec A. Integrated quantitation of drug-target binding, biomarkers and clinical response to support rational dose regimen selection. in ADME and translational pharmacokinetics/pharmacodynamics of therapeutic proteins: Applications in drug discovery and development. Zhou, H., Theil F.-P. Eds., John Wiley & Sons Inc.: Hoboken, New Jersey, 2015

Kümmel A., Parker C. N. The interweaving of cheminformatics and high-throughput screening in Cheminformatics and Computational Chemical Biology, Bajorath J. Ed., Humana Press/Springer: Totowa, N. J., 2010

Selected Poster and Oral Presentations at Conferences

Kümmel A., Abuhelwa A., Krause A. Try yourself! Making clinical teams explore dose response relationships in R Shiny Oral presentation @ 12th Basel M&S seminar, Basel, Switzerland, 19-20/09/2016

Kümmel A., Abuhelwa A., Krause A. PECAN, a Shiny application for calculating confidence intervals and prediction intervals for pharmacokinetic and pharmacodynamic models Poster presentation @ 25th PAGE meeting, Lisboa, Portugal, 07-10/06/2016

Kümmel A., Lowe P. Mechanism-based population PK modeling describing pharmacological effects from dose to clinical response enables mechanistics insights and projections beyond the studied treatment Poster presentation @ 7th Noordwijkerhout Symposium on Pharmacokinetics, Pharmacodynamics and Systems Pharmacology, Noordwijk, Netherlands, 23-25/04/2014

Amit Taneja, PhD

Director Modeling & Simulation

Bio

Dr. Amit Taneja is an experienced drug development professional specialising in Model-Informed Drug Discovery and Development (MID3), with a strong focus on applying quantitative approaches to support decision-making across the development lifecycle. His background spans the pharmaceutical industry, biotechnology, academia, and consulting, providing a broad and well-integrated perspective.

He has extensive experience across non-clinical, translational, and early- to late-phase clinical development for both new chemical entities and generics. Amit’s expertise includes designing and executing model-informed strategies, selecting appropriate quantitative methodologies, leading projects, performing in-depth analyses, and communicating insights effectively to cross-functional stakeholders. He also has experience in team leadership and line management.

His therapeutic area experience includes (haemato-)oncology, idiopathic pulmonary fibrosis, inflammation, neuropsychiatry, chronic and neuropathic pain, and dyslipidaemia. He has applied a wide range of methodologies, including population PK/PD modelling, longitudinal disease progression modelling, joint biomarker–survival analysis, clinical trial simulation, model-based meta-analysis, and physiologically based pharmacokinetic (PBPK) modelling.

Amit is an advanced user of both proprietary and open-source tools for nonlinear mixed-effects and PBPK modelling. He began his career in clinical research and clinical development and is trained as both a physician and pharmacologist.

Publications

JOURNAL PUBLICATIONS

Taneja A, Di Iorio VL, Danhof M, Della Pasqua O, Translation of Drug Effects from Experimental Models of Neuropathic Pain and analgesia to humans. Drug Discovery Today. 2012 (15-16):837-49.

Taneja A, Nyberg J, de Lange E, Danhof M, Della Pasqua O. Application of ED optimality to screening Experiments for Analgesic Compounds. Journal of Pharmacokinetics and Pharmacodynamics. 2012;39(6:673-81).

Taneja A, Nyberg J, de Lange E, Danhof M, Della Pasqua O. Optimised Protocol Design for the screening of Analgesic Compounds. Journal of Pharmacokinetics and Pharmacodynamics. 2012;39(661-71).

Taneja A, Troconiz IF, Danhof M, Della Pasqua O. Semi-Mechanistic Modelling of the Analgesic Effect of Gabapentin in the Formalin-Induced Rat Model of Experimental Pain. Pharm Res 2014:31(3):593-606.

Taneja A, Oosterholt SP, Danhof M, Della Pasqua O. Biomarker exposure response

relationships as the basis for rational dose selection: Lessons from a simulation exercise using a selective COX-2 inhibitor. J Clin Pharmacol. 2016 May; 56(5):609-21

Taneja A, Vermeulen A, Huntjens DR, Danhof M, De Lange EC, Proost JH. A comparison of two semi-mechanistic models for prolactin release and prediction of receptor occupancy following administration of dopamine D2 receptor antagonists in rats. Eur J Pharmacol. 2016 Oct 15; 789:202-14.

Taneja A, Vermeulen A, Huntjens DR, Danhof M, De Lange EC, Proost JH. Summary data of potency and parameter information from semi-mechanistic PKPD modelling of prolactin release following administration of the dopamine D2 receptor antagonists’ risperidone, paliperidone and remoxipride in rats. Data Brief. 2016 Aug 6; 8:1433-7.

Amit Taneja, An Vermeulen, Dymphy R. H. Huntjens, Meindert Danhof, Elizabeth C. M. De Lange, Johannes H. Proost. Modeling of prolactin response following dopamine D 2 receptor antagonists in rats: can it be translated to clinical dosing? December 2017.Pharmacology Research & Perspectives 5(6).

A Taneja, OE Della Pasqua, M Danhof, Challenges in translational drug research in neuropathic and inflammatory pain: the prerequisites for a new paradigm. The European Journal of Clinical Pharmacology. 2017 Oct;73(10):1219-1236.

Amit Taneja, Julie Desrivot, Paul Matthias Diderichsen, Roland Blanqué, Lisa Allamasey, Liesbeth Fagard, Ann Fieuw, Ellen Van der Aar, Florence Namour. Population Pharmacokinetic and Pharmacodynamic Analysis of GLPG1690, an Autotaxin Inhibitor, in Healthy Volunteers and Patients with Idiopathic Pulmonary Fibrosis. April 2019.Clinical Pharmacokinetics 58(6):1-17.

Maher TM, Ford P, Brown KK, Costabel U, Cottin V, Danoff SK, Groenveld I, Helmer E, Jenkins RG, Milner J, Molenberghs G, Penninckx B, Randall MJ, Van Den Blink B, Fieuw A, Vandenrijn C, Rocak S, Seghers I, Shao L, Taneja A, Jentsch G, Watkins TR, Wuyts WA, Kreuter M, Verbruggen N, Prasad N,Wijsenbeek MS; ISABELA 1 and 2 Investigators. Ziritaxestat, a Novel Autotaxin Inhibitor, and Lung Function in Idiopathic Pulmonary Fibrosis: The ISABELA 1 and 2 Randomized Clinical Trials. JAMA. 2023 May 9;329(18):1567-1578.

Jeremy Perrier 1, Virginie Gualano 1, Eric Helmer 2 3, Florence Namour 3, Viera Lukacova 4, Amit Taneja. Drug-drug interaction prediction of ziritaxestat using a physiologically based enzyme and transporter pharmacokinetic network interaction model Clin Transl Sci. 2023 Nov;16(11):2222-2235.

Amit Taneja, Garrit Jentsch, Stéphane Delage, Matthew J Randall, Bernt van den Blink, Yasmina Bauer, Florence Namour. ISABELA Studies: Plasma Exposure and Target Engagement Do Not Explain the Lack of Efficacy of Ziritaxestat in Patients with Idiopathic Pulmonary Fibrosis. Clin Pharmacol Ther 2024 Mar;115(3):606-615.

Schaller, Ingrid Michon, Vanessa Baier, Frederico Severino Martins, Patrick Nolain, Amit Taneja. Evaluation of BCRP-Related DDIs Between Methotrexate and Cyclosporin a Using Physiologically Based Pharmacokinetic Modelling, Drugs in R& D, Mar;25(1):1-17.

Kar P, Chandrashekhar N, Devi S, Shobna J Bhatia, Alvares JFF, A Taneja, Towar A. Safety and efficacy of rabeprazole in gastroesophageal reflux disease: report of a multicentre study. Ind J Gastroenterol, 2003, 153

S Prasad, A Taneja, K Sireesha, A study of the efficacy and safety of a new second generation Antihistamine-Mizolastine, compared to Cetrizine in patients of Allergic Rhinoconjunctivitis. Indian J Allergy Asthma Immunol 2003; 17(1) 1-4

CONFERENCE ARTICLES / TALKS

Amit Taneja (2018) Population Pharmacokinetic and Pharmacodynamic Analysis of GLPG1690, an Autotaxin Inhibitor, in Healthy Volunteers and Patients with Idiopathic Pulmonary Fibrosis PKUK, Manchester, UK.

Amit Taneja (2022) Leveraging in vitro dissolution profiles for prediction of in vivo human PK of oral IR formulations, Pharmacometrics Network Benelux, Utrecht, the Netherlands

Darius Schweinoch, PhD

Associate Director Modeling & Simulation

Bio

Dr. Darius Schweinoch is an experienced pharmacometrician and systems biology modeler with a broad track record across biological and pharmaceutical research.

At IntiQuan, he has primarily focused on population pharmacokinetics (popPK) modeling, population pharmacokinetic/pharmacodynamic (PK/PD) modeling, exposure-response (ER) analyses for both safety and efficacy endpoints, and quantitative systems pharmacology (QSP) modeling. Darius has prepared regulatory-relevant modeling reports for Phase 1, Phase 2, and Phase 3 clinical trials, as well as reports for nonclinical analyses. He has worked on a broad portfolio spanning biologics, small molecule drugs, cellular and gene therapy. His work includes both hands-on support as well as leading roles in project work.

Prior to joining IntiQuan in 2020, Darius worked in immunology and infectious diseases, developing mathematical models of viral replication and immune response signaling. His earlier research also includes PBPK modeling to improve in vitro/in vivo scaling and applied statistical and machine learning methods to biological and medical data. Darius was awarded the Add-On Fellowship for Interdisciplinary Life Sciences from the Joachim Herz Stiftung and has collaborated extensively with scientists from diverse background, including biology, informatics, and statistics.

Publications

Schweinoch, Darius, et al. “Mechanistic modeling explains the dsRNA length-dependent activation of the RIG-I mediated immune response.” Journal of Theoretical Biology 500 (2020): 110336.

Burkart, Sandy S. & Schweinoch, Darius, et al. „High-resolution kinetic characterization of the RIG-I-signaling pathway and the antiviral response.” Life Science Alliance 6.10 (2023).

Uenishi, Gene I., et al. “GNTI-122: an autologous antigen-specific engineered Treg cell therapy for type 1 diabetes.” JCI insight 9.6 (2024): e171844.

Wu, Guandi, et al. “High-throughput screening of E3 ubiquitin ligases identifies TRIM48 as a novel negative regulator of RIG-I signaling.” Cellular Signalling (2025): 111973.

Riccardo Colombo, PHD

VP, Expert Partner at PLG supporting IntiQuan

Bio

Dr. Riccardo Colombo is a trained biotechnologist and computational biologist with a background spanning genetics, systems biology and data science. After his Ph.D. in Computer Science (Bioinformatics) obtained at the University of Milan – Bicocca, where he developed mathematical models and optimization algorithms for metabolic network analysis, he pursued postdoctoral research contributing to projects in systems biology and diabetes research.

Moving from science to industry, Riccardo joined the biotech and diagnostics sector, where he progressively grew from bioinformatics to business development manager, building expertise in genetics, biobanking and services for CRO and pharma clients. In parallel, he co-led the scientific and commercial development of a genetic business line within an innovative startup, combining strategic marketing with hands-on technical development.

Combining his scientific depth with commercial mindset, Riccardo then moved into pharma consulting, where he established and developed strategic relationships with regional and global pharma and biotech companies, focusing on data strategy and quantitative sciences.

Riccardo has been part of the PLG and IntiQuan team as VP and Executive Partner since 2026, where he leverages his blend of scientific expertise and business development experience to support commercial growth, bringing deep technical credibility to client-facing engagements and strategic initiatives.

Publications

Journal Papers

Ferri A, Agrati S, Cabitza F, Colombo R, Filetti S, Galeone C, Lettieri E, et al. The HIBAD experience: using digital health technologies in the GDPR era. Health Policy and Technology 12(4):100788, 2023.

Damiani C, Maspero D, Di Filippo M, Colombo R, Pescini D, Graudenzi A, et al. Integration of single-cell RNA-seq data into population models to characterize cancer metabolism. PLoS Computational Biology 15(2):e1006733, 2019.

Maspero D, Damiani C, Antoniotti M, Graudenzi A, Di Filippo M, Vanoni M, Colombo R, et al. The influence of nutrients diffusion on a metabolism-driven model of a multi-cellular system. Fundamenta Informaticae 171(1-4):279-295, 2019.

Colombo R, Damiani C, Gilbert D, Heiner M, Mauri G, Pescini D. Emerging ensembles of kinetic parameters to characterize observed metabolic phenotypes. BMC Bioinformatics 19(7):251, 2018.

Damiani C, Colombo R, Gaglio F, Mastroianni F, Pescini D, et al. A metabolic core model elucidates how enhanced utilization of glucose and glutamine, with enhanced glutamine-dependent lactate production, promotes cancer cell growth. PLOS Computational Biology 13(9):e1005758, 2017.

Nobile MS, Cazzaniga P, Besozzi D, Colombo R, Mauri G, Pasi G. Fuzzy Self-Tuning PSO: A Settings-Free Algorithm for Global Optimization. Swarm and Evolutionary Computation, 2017.

Damiani C, Di Filippo M, Pescini D, Maspero D, Colombo R, Mauri G. popFBA: tackling intratumour heterogeneity with Flux Balance Analysis. Bioinformatics 33(14):i311-i318, 2017.

Di Filippo M, Colombo R, Damiani C, Pescini D, Gaglio D, Vanoni M, et al. Zooming-in on cancer metabolic rewiring with tissue specific constraint-based models. Computational Biology and Chemistry 62:60-69, 2016.

Damiani C, Pescini D, Colombo R, Molinari S, Alberghina L, Vanoni M, et al. An ensemble evolutionary constraint-based approach to understand the emergence of metabolic phenotypes. Natural Computing 13(3):321-331, 2014.

Cazzaniga P, Damiani C, Besozzi D, Colombo R, Nobile MS, Gaglio D, et al. Computational strategies for a system-level understanding of metabolism. Metabolites 4(4):1034-1087, 2014.

Amara F, Colombo R, Cazzaniga P, Pescini D, Csikász-Nagy A, et al. In vivo and in silico analysis of PCNA ubiquitylation in the activation of the Post Replication Repair pathway in S. cerevisiae. BMC Systems Biology 7(1):24, 2013.

Murabito E, Colombo R, Wu C, Verma M, Rehman S, Snoep J, Peng SL, et al. SupraBiology 2014: Promoting UK-China collaboration on Systems Biology and High Performance Computing. Quantitative Biology 1-8, 2015.

Conference Papers

Colombo R, Damiani C, Mauri G, Pescini D. Constraining Mechanism Based Simulations to Identify Ensembles of Parametrizations to Characterize Metabolic Features. Computational Intelligence Methods for Bioinformatics and Biostatistics, 2017.

Cumbo F, Nobile MS, Damiani C, Colombo R, Mauri G, Cazzaniga P. COSYS: A Computational Infrastructure for Systems Biology. Computational Intelligence Methods for Bioinformatics and Biostatistics, 2017.

Damiani C, Colombo R, Di Filippo M, Pescini D, Mauri G. Linking alterations in metabolic fluxes with shifts in metabolite levels by means of kinetic modeling. Italian Workshop on Artificial Life and Evolutionary Computation, pp. 138-148, 2016.

Di Filippo M, Damiani C, Colombo R, Pescini D, Mauri G. Constraint-based modeling and simulation of cell populations. Italian Workshop on Artificial Life and Evolutionary Computation, pp. 126-137, 2016.

Nobile MS, Pasi G, Cazzaniga P, Besozzi D, Colombo R, Mauri G. Proactive particles in swarm optimization: a self-tuning algorithm based on fuzzy logic. 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1-8, 2015.

Cazzaniga P, Colombo R, Nobile MS, Pescini D, Mauri G, Besozzi D. GPU-powered sensitivity analysis and parameter estimation of a reaction-based model of the post replication repair pathway in yeast. TICSP Series 63:109-110, 2013.

Book Chapters & Preprints

De Sanctis G, Colombo R, Damiani C, Sacco E, Vanoni M. Omics and Clinical Data Integration. In: Integration of Omics Approaches and Systems Biology for Clinical Applications, 2018.

Damiani C, Maspero D, Di Filippo M, Colombo R, Pescini D, Graudenzi A, et al. Integration of single-cell RNA-seq data into metabolic models to characterize tumour cell populations. bioRxiv 256644, 2018.

Damiani C, Colombo R, Molinari S, Pescini D, Gaglio D, Vanoni M, et al. An ensemble approach to the study of the emergence of metabolic and proliferative disorders via Flux Balance Analysis. arXiv preprint arXiv:1309.7696, 2013.

Justin Gross, BA

Associate Manager Operations

Bio

Justin Gross has a background in Business Administration with a focus on Industrial Management (B.A., Baden-Württemberg Cooperative State University), specializing in Marketing & Sales Management and HR Management. He is currently pursuing a Master of Business Administration (MBA, International University of Applied Sciences) with a focus on Corporate Finance, Business Development, and Corporate Strategy.

In a previous experience, as Assistant to the Managing Director, he contributed to strategic decision-making through performance analyses, market assessments, and executive reporting while coordinating cross-functional initiatives.

As Associate Manager Operations at IntiQuan he oversees key commercial and operational topics across Finance, HR, and Marketing, supporting the company’s strate-gic and organizational development. Working in an international environment, I take on project management responsibilities and contribute to strengthening internal structures and governance frameworks.

Publications

Timo Smieszek, PhD

Director Project Management & BD

Bio

Timo Smieszek has more than a decade of experience in computational modelling (mathematical – ODE and difference equation – models, individual-based simulations, statistical models) applied to health problems. Furthermore, he has extensive experience in working with data – the types of data he has worked with include wireless sensor data, census data, health questionnaire data, contact network data, electronic medical records data (primary care, specialist outpatient care, hospitals), claims data, registry data, surveillance data.

After his PhD conferred by ETH Zurich, Switzerland, he worked as a DAAD-funded postdoctoral fellow at the Center for Infectious Disease Dynamics at The Pennsylvania State University in the USA. After his postdoc, he moved to the government sector and joined Public Health England – first as a specialist infectious disease modeller; later he led a team of modellers and statisticians working on antimicrobial resistance. His scientific work informed national policies in the UK, e.g. the UK government’s ambition of halving inappropriate prescribing of antibiotics.

Moving from the public sector to industry, Timo joined IQVIA’s Real-World Evidence (RWE) line of business. He designed and led small to large RWE studies in project management and epidemiological functions. Study types included regulated safety studies, drug utilization studies, RW effectiveness studies based on electronic medical records and registry data. He has been awarded for leadership in a flagship project.

Timo joined IntiQuan in January 2022. His role is to provide senior support for modellers (particularly in managing projects) and to act as senior client partner in leading strategic discussions.

Publications

JOURNAL PUBLICATIONS

Contributions marked with * indicate shared first or last authorship.

1. Katzmann JL, Sorio-Vilela F, Dornstauder E, Fraas U, Smieszek T, Zappacosta S, Laufs U. Non-statin lipid-lowering therapy over time in very-high-risk patients: effectiveness of fixed-dose statin/ezetimibe compared to separate pill combination on LDL-C. Clinical Research in Cardiology 2020. https://doi.org/10.1007/s00392-020-01740-8

2. Smith DRM, Pouwels KB, Hopkins S, Naylor NR, Smieszek T, Robotham JV. Epidemiology and health-economic burden of urinary-catheter-associated infection in English NHS hospitals: a probabilistic modelling study. Journal of Hospital Infection 2019, 103 (1), 44-54.

3. Donker T, Smieszek T, Henderson KL, Walker TM, Hope R, Johnson AP, Woodford N, Crook DW, Peto T EA, Walker AS, Robotham JV. Using hospital network-based surveillance for antimicrobial resistance as a more robust alternative to self-reporting. PLOS One 2019, 14 (7), e0219994.

4. Pouwels KB, Muller-Pebody B, Smieszek T, Hopkins S, Robotham JV. Selection and co-selection of antibiotic resistances among Escherichia coli by antibiotic use in primary care: An ecological analysis. PLOS One 2019, 14 (6), e0218134.

5. Smieszek T*, Lazzari G*, Salathé M. Assessing the dynamics and control of droplet- and aerosol-transmitted influenza using an indoor positioning system. Scientific Reports 2019, 9 (1), 1-10.

6. Hope EC, Crump RE, Hollingsworth TD, Smieszek T, Robotham JV, Pouwels KB. Identifying English practices that are high antibiotic prescribers accounting for comorbidities and other legitimate medical reasons for variation. EClinicalMedicine 2018, 6, 36-41.

7. Laager M, Mbilo C, Madaye EA, Naminou A, Léchenne M, Tschopp A, Smieszek T, Zinsstag J, Chitnis N. The importance of dog population contact network structures in rabies transmission. PLOS Neglected Tropical Diseases 2018, 12 (8), e0006680.

8. Pouwels KB, Freeman R, Muller-Pebody B, Rooney G, Henderson KL, Robotham JV*, Smieszek T*. Association between use of different antibiotics and trimethoprim resistance: going beyond the obvious crude association. Journal of Antimicrobial Chemotherapy 2018, 73 (6), 1700-1707.

9. Pouwels KB, Vansteelandt S, Batra R, Edgeworth JD, Smieszek T*, Robotham JV*. Intensive care unit (ICU)-acquired bacteraemia and ICU mortality and discharge: addressing time-varying confounding using appropriate methodology. Journal of Hospital Infection 2018, 99 (1), 42-47.

10. Smieszek T, Pouwels KB, Dolk FCK, Smith DRM, Hopkins S, Sharland M, Hay AD, Moore MV, Robotham JV. Potential for reducing inappropriate antibiotic prescribing in English primary care. Journal of Antimicrobial Chemotherapy 2018, 73 (suppl_2), ii36-ii43.

11. Pouwels KB, Dolk FCK, Smith DRM, Robotham JV*, Smieszek T*. Actual versus ‘ideal’antibiotic prescribing for common conditions in English primary care. Journal of Antimicrobial Chemotherapy 2018, 73 (suppl_2), 19-26.

12. Dolk FCK, Pouwels KB, Smith DRM, Robotham JV*, Smieszek T*. Antibiotics in primary care in England: which antibiotics are prescribed and for which conditions? Journal of Antimicrobial Chemotherapy 2018, 73 (suppl_2), ii2-ii10.

13. Pouwels KB, Dolk FCK, Smith DRM, Smieszek T*, Robotham JV*. Explaining variation in antibiotic prescribing between general practices in the UK. Journal of Antimicrobial Chemotherapy 2018, 73 (suppl_2), ii27-ii35.

14. Smith DRM, Dolk FCK, Pouwels KB, Christie M, Robotham JV*, Smieszek T*. Defining the appropriateness and inappropriateness of antibiotic prescribing in primary care. Journal of Antimicrobial Chemotherapy 2018, 73 (suppl_2), ii11-ii18.

15. Smith DRM, Dolk FCK, Smieszek T, Robotham JV, Pouwels KB. Understanding the gender gap in antibiotic prescribing: a cross-sectional analysis of English primary care. BMJ Open 2018, 8 (2), e020203.

16. Rosello A, Pouwels KB, De Cellès MD, Van Kleef E, Hayward AC, Hopkins S, Robotham JV, Smieszek T, Opatowski L, Deeny SR. Seasonality of urinary tract infections in the United Kingdom in different age groups: longitudinal analysis of The Health Improvement Network (THIN). Epidemiology & Infection 2018, 146 (1), 37-45.

17. Pouwels KB, Batra R, Patel A, Edgeworth JD, Robotham JV*, Smieszek T*. Will co-trimoxazole resistance rates ever go down? Resistance rates remain high despite decades of reduced co-trimoxazole consumption. Journal of Global Antimicrobial Resistance 2017, 11, 71-74

18. Donker T, Smieszek T, Henderson KL, Johnson AP, Walker AS, Robotham JV. Measuring distance through dense weighted networks: The case of hospital-associated pathogens. PLOS Computational Biology 2017, 13 (8), e1005622.

19. Pouwels KB, Van Kleef E, Vansteelandt S, Batra S, Edgeworth JD, Smieszek T*, Robotham JV*. Does appropriate empiric antibiotic therapy modify intensive care unit-acquired Enterobacteriaceae bacteraemia mortality and discharge? Journal of Hospital Infection 2017, 96 (1), 23-28.

20. Smieszek T*, Castell S*, Barrat A, Cattuto C, White PJ, Krause G. Contact diaries versus wearable proximity sensors in measuring contact patterns at a conference: method comparison and participants’ attitudes. BMC Infectious Diseases 2016, 16 (1), 1-14.

21. Krütli P, Rosemann T, Törnblom KY, Smieszek T. How to fairly allocate scarce medical resources: ethical argumentation under scrutiny by health professionals and lay people. PLOS One 2016, 11 (7), e0159086.

22. Smieszek T, White PJ. Apparently-Different Clearance Rates from Cohort Studies of Mycoplasma genitalium Are Consistent after Accounting for Incidence of Infection, Recurrent Infection, and Study Design. PLOS One 2016, 11 (2), e0149087.

23. Potter GE, Smieszek T, Sailer K. Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions. Network Science 2015, 3 (3), 298-325.

24. Smieszek T*, Barclay VC*, Seeni I, Rainey JJ, Gao H, Uzicanin A, Salathé M. How should social mixing be measured: comparing web-based survey and sensor-based methods. BMC Infectious Diseases 2014, 14 (1), 1-13.

25. Barclay VC*, Smieszek T*, He J, Cao G, Rainey JJ, Gao H, Uzicanin A, Salathé M. Positive network assortativity of influenza vaccination at a high school: implications for outbreak risk and herd immunity. PLOS One 2014, 9 (2), e87042.

26. Smieszek T, Salathé M. A low-cost method to assess the epidemiological importance of individuals in controlling infectious disease outbreaks. BMC Medicine 2013, 11 (1), 35.

27. Moser C, Stauffacher M, Smieszek T, Seidl R, Krütli P, Scholz RW. Psychological factors in discounting negative impacts of nuclear waste. Journal of Environmental Psychology 2013, 35, 121-131.

28. Smieszek T, Burri EU, Scherzinger R, Scholz RW. Collecting close-contact social mixing data with contact diaries: reporting errors and biases. Epidemiology & Infection 2012, 140 (4), 744.

29. Smieszek T, Balmer M, Hattendorf J, Axhausen KW, Zinsstag J, Scholz RW. Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model. BMC Infectious Diseases 2011, 11 (1), 115.

30. Smieszek T, Fiebig L, Scholz RW. Models of epidemics: when contact repetition and clustering should be included. Theoretical Biology and Medical Modelling 2009, 6 (1), 1-15.

31. Fiebig L, Smieszek T, Saurina J, Hattendorf J, Zinsstag J. Contacts between poultry farms, their spatial dimension and their relevance for avian influenza preparedness. Geospatial Health 2009, 4 (1), 79-95.

32. Smieszek T. A mechanistic model of infection: why duration and intensity of contacts should be included in models of disease spread. Theoretical Biology and Medical Modelling 2009, 6, 25.

33. Smieszek T. Unsicherheit, Werthaltungen und Handlungsblockaden. GAIA-Ecological Perspectives for Science and Society 2006, 15 (4), 251-254.

34. Hansmann R, Bernasconi P, Smieszek T, Loukopoulos P, Scholz RW. Justifications and self-organization as determinants of recycling behavior: The case of used batteries. Resources, Conservation and Recycling 2006, 47 (2), 133-159.

35. Müller-Herold U, Smieszek T, Peter P, Scheringer M, Morosini M. A simple measure for precautionary assessment of organic chemicals with respect to global cold condensation. Ecological Modelling 2006, 194 (1), 266-273.

PHD THESIS

36. Smieszek T. Models of epidemics: How contact characteristics shape the spread of infectious diseases. ETH Zurich, PhD dissertation, 2010. https://doi.org/10.3929/ethz-a-006109956

BOOK CHAPTERS

37. Scholz RW, Binder CR, Lang DJ, Smieszek T, Stauffacher M. Applying the HES framework. In: Scholz RW. Environmental Literacy in Science and Society. From Knowledge to Decisions. Cambridge University Press, 2011, 463-508.

Stéphan Benay, PhD

Modeling & Simulation Scientist

Bio

Coming soon

Publications

Publications:

Coming soon

Sebastian Blachuta, MD, MSc

Modeling & Simulation Scientist

Bio

Sebastian Blachuta has a background in biomedical engineering and medicine. He holds a Master’s degree in Biomedical Engineering, with a thesis on “Multi-class Image-to-Image Translation using Diffusion Models” for anomaly detection in medical images and a Doctor of Medicine degree with a thesis on “Dynamic Pedobarographic Assessment of the TN-Joint” for better understanding of postoperative kinematic changes in the weight bearing process.

His clinical background has enabled him to gain a deeper understanding of biological and clinical processes, helping to
bridge the gap between clinical practice and pharmacometric modelling. His biomedical engineering degree also focused on machine learning applications in medical applications, further enriching his expertise in this field.

Since September 2023, Sebastian has been working as a modelling and simulation scientist at IntiQuan.

Publications

Publications:

Coming soon

Charlotte Kern, PhD

Modeling & Simulation Scientist

Bio

Dr. Charlotte Kern is a resourceful bioengineer with a strong foundation in modelling & simulation and clinical pharmacology. With an interdisciplinary background in bioengineering and clinical sciences, Charlotte has gathered over 9 years of experience tackling diverse biological and pharmaceutical research questions in university hospitals, the pharmaceutical industry, and research institutes.

She holds an Engineering degree in Biotechnology and a MSc in Drug Design and Production from the University of Strasbourg. For her master thesis, Charlotte developed a novel screening platform for therapeutic antibodies at the Novartis Institutes for Biomedical Research in Basel. She later worked as a scientist at the Ecole Polytechnique Fédérale de Lausanne, and Johnson & Johnson, before pursuing a PhD in Clinical Pharmacology and Pharmacometrics at the University Hospital of Bern, which she completed with high honors. Her doctoral research focused on developing pharmacometric models based on clinical data in infectious diseases, particularly malaria and COVID-19. Her PhD thesis explored the pharmacology of ivermectin in malaria vector control within the BOHEMIA clinical trial. During her PhD, Charlotte received the Center for Artificial Intelligence in Medicine Young Researcher Award and the Clinical Research Prize from the Faculty of Medicine at the University of Bern for her pharmacometric modeling study of antiviral therapies against emerging SARS-CoV-2 variants of concern.

Charlotte has joined IntiQuan as a Modelling and Simulation Scientist in February 2025.

Publications

Journal articles (peer-reviewed)

Kamau Y.N., Tuwei M., Ominde K., Ngama M., Karisa J., Babu L., Muturi M., Lewa F., Mure F., Mwatasa M., Wanjiku C., Adetifa J., Kern C., Duthaler U., Hammann F., Rabinovich R., Chaccour C., Maia M., Mosquitocidal efficacy and pharmacokinetics of single-dose ivermectin versus three-day dose regimen for malaria vector control in comparison with albendazole and no treatment: an open-label randomized controlled trial. International Journal of Infectious Diseases, (2024) Nov 148:107236. doi: 10.1016/j.ijid.2024.107236. Epub 2024 Sep 6.
Kern C., Müller P., Chaccour C., Liechti M., Hammann F.*, Duthaler U.*, Pharmacokinetics of ivermectin metabolites and their activity against Anopheles stephensi mosquitoes, Malar J. (2023) Jun 24;22(1):194. doi: 10.1186/s12936-023-04624-0
Schöning V.*, Kern C.*, Chaccour C., Hammann F., Effectiveness of antiviral therapy in highly-transmissible variants of SARS-CoV-2: a modeling and simulation study, Frontiers in Pharmacology (2022), doi: 10.3389/fphar.2022.816429
Kern C. *, Schöning V.*, Chaccour C., Hammann F., Modeling of SARS-CoV-2 treatment effects for informed drug repurposing, Frontiers in Pharmacology (2021) doi:10.3389/fphar.2021.625678

Oral presentations

Kern C., Schöning V., Chaccour C., Hammann F., Pharmacometric modeling of antiviral therapy against emerging SARS-CoV-2 variants, Center for AI in Medicine Research Symposium (CAIM), Bern, Switzerland (2022)
Kern C., Schöning V., Chaccour C., Hammann F., In-host mathematical modeling of SARS-CoV-2 kinetics and simulation of molnupiravir antiviral effect in human, Swiss Society of Pharmacology and Toxicology Spring Meeting, SSPT, Bern, Switzerland (2022)

Posters (excerpt)

COVID-19

Kern C., Schöning V., Chaccour C., Hammann F., Designing impactful treatments against emerging SARS-CoV-2 variants, Day of Biomedical Research (DBMR), University of Bern, Switzerland (07.2022)
Kern C., Schöning V., Chaccour C., Hammann F., Modeling changes in SARS-CoV-2 variants within-host transmissibility on antiviral drug effect, 29th Population Approach Group in Europe Meeting (PAGE) (09.2021)
Schöning V., Kern C., Hammann F., Emerging highly transmissible variants of SARS-CoV-2 may be more susceptible to antiviral therapy than wild type strains, Schweizerische Gesellschaft für Allgemeine Innere Medizin, Frühjahrskongress (SGAIM-SGKPT) (05.2021)
Kern C., Schöning V., Chaccour C., Hammann F., Pharmacometric modeling of SARS-CoV-2 drug therapy: hit early – hit hard, Day of Biomedical Research (DBMR), University of Bern, Switzerland (11.2020)
Kern C., Schöning V., Chaccour C., Hammann F., Modeling the impact of tropical disease medications on SARS-CoV-2 kinetics, American Society of Tropical Medicine & Hygiene 69th annual meeting (ASTMH) (11.2020)

Ivermectin

Daptomycin

Kern C., Suenderhauf C., André P., Krähenbühl S., Buclin T., Hammann F., Development of a priori dosing nomograms for daptomycin in patients at Swiss university hospitals, 30th Population Approach Group in Europe Meeting (PAGE), Ljubljana, Slovenia (06.2022) https://www.page-meeting.org/default.asp?abstract=10017

Karsten Kuritz, PhD

Modeling & Simulation Scientist

Bio

Dr. Kuritz is an experienced modeler with broad expertise in biology, dynamical systems theory and data science. At IntiQuan, he focuses on population pharmacokinetic (popPK) and population pharmacokinetic/pharmacodynamic (PK/PD) modeling as well as systems pharmacology type of modelling across all phases of drug development.

Prior to joining IntiQuan in 2021, Karsten Kuritz developed mathematical tools for the analysis of single cell data and for the control of heterogeneous cell populations.

He is passionate about innovation and excels in creatively approaching interdisciplinary problems. His training as both a biologist and control engineer/data scientist helps him to communicate and integrate computational results into project decisions.

Publications

Journal articles (peer reviewed)

Kuritz, K., Stöhr, D., Maichl, D. S., Pollak, N., Rehm, M., and Allgöwer, F. “Reconstructing temporal and spatial dynamics from single-cell pseudotime using prior knowledge of real scale cell densities”. In: Scientific Reports 10.1 (2020), p. 3619. doi: 10.1038/s41598-020-60400-z.

Colbrook, M. J., Botev, Z. I., Kuritz, K., and MacNamara, S. “Kernel density estimation with linked boundary conditions”. In: Studies in Applied Mathematics (2020). doi: 10.1111/sapm.12322.

Kuritz, K., Zeng, S., and Allgöwer, F. “Ensemble Controllability of Cellular Oscillators”. In: IEEE Control Systems Letters 3.2 (2019), pp. 296–301. doi: 10.1109/lcsys.2018.2870967.

Kuritz, K., Stöhr, D., Pollak, N., and Allgöwer, F. “On the relationship between cell cycle analysis with ergodic principles and age-structured cell population models”. In: Journal of Theoretical Biology 414 (2017), pp. 91–102. doi: 10.1016/j.jtbi.2016.11.024.

Thomaseth, C., Kuritz, K., Allgöwer, F., and Radde, N. “The circuit-breaking algorithm for monotone systems”. In: Mathematical Biosciences 284 (2017), pp. 80–91. doi: 10.1016/j.mbs.2016.09.002.

Conference proceedings (peer reviewed)

Imig, D., Kuritz, K., Pollak, N., Rehm, M., and Allgöwer, F. “Death patterns resulting from cell cycle-independent cell death”. In: IFAC-PapersOnLine 51.19 (2018). 7th Conference on Foundation of Systems Biology in Engineering FOSBE 2018, pp. 90–93. doi: 10.1016/j.ifacol.2018.09.028.

Kuritz, K., Imig, D., Dyck, M., and Allgöwer, F. “Ensemble control for cell cycle synchronization of heterogeneous cell populations”. In: IFAC-PapersOnLine 51.19 (2018). 7th Conference on Foundation of Systems Biology in Engineering FOSBE 2018, pp. 44–47. doi: 10.1016/j.ifacol.2018.09.034.

Book chapters

Kuritz, K., Halter, W., and Allgöwer, F. “Passivity-Based Ensemble Control for Cell Cycle Synchronization”. In: Emerging Applications of Control and Systems Theory: A Festschrift in Honor of Mathukumalli Vidyasagar. Ed. by R. Tempo, S. Yurkovich, and P. Misra. Cham: Springer International Publishing, 2018, pp. 1–13. doi: 10.1007/978-3-319-67068-3_1.

Conference Talks

Kuritz, K. and Allgöwer, F. “Ensemble control for cellular oscillators: One ring to rule them all”. Workshop: Analysis, Control, and Learning of Dynamic Ensemble and Population Systems. IFAC World Congress. Virtual, 2020.

Kuritz, K., Stöhr, D., Pollak, N., and Allgöwer, F. “Reconstructing dynamic processes from high dimensional snap shot data”. Int. Conf. on Systems Biology of Human Disease. Heidelberg, 2017.

Kuritz, K., Stöhr, D., Pollak, N., and Allgöwer, F. “Reconstructing dynamic processes from high dimensional snap shot data”. Int. Conf. on Systems Biology. Blacksbourg, VA, 2017.

Kuritz, K. and Allgöwer, F. “Determining protein level variations along the cell cycle from snap-shot population measurements”. Workshop on Computational Models in Biology and Medicine. Cologne, 2014.

Poster presentations (excerpt)

Kuritz, K. and Allgöwer, F. “Broadcast control of oscillating cell populations”. EMBO | EMBL Symposium: Biological Oscillators: Design, Mechanism, Function. Heidelberg, 2018.

Kuritz, K. and Allgöwer, F. “Therapy design by broadcast control of oscillating cell populations”. Curious2018 – Future Insight. Darmstadt, 2018.

Kuritz, K., Stöhr, D., Pollak, N., and Allgöwer, F. “Reconstructing dynamic processes from high dimensional snap shot data”. Int. Conf. on Systems Biology. Blacksbourg, VA, 2017.

Kuritz, K., Stöhr, D., Pollak, N., Rehm, M., and Allgöwer, F. “Reconstructing dynamic processes from high dimensional snap shot data”. CSHL 9th Single Cell Analyses Meeting. 2017.

Kuritz, K., Müller, F., Pollak, N., and Allgöwer, F. “Too Young to Die: Age Structured Population Models Capture Cell Cycle Dependent Apoptosis from Snapshot Data”. Int. Conf. on Systems Biology of Human Disease. Boston, MA, 2016.

Kuritz, K. and Allgöwer, F. “Inferring cell-cycle dependent signalling with age-structured population models”. Int. Conf. on Systems Biology of Human Disease. Heidelberg, 2015.

Kuritz, K., Radde, N., and Olayioye, M. “Multi-scale modeling reveals membrane domain variations as mechanism behind augmented ErbB receptor activation”. In: 14th International Conference on Systems Biology. Copenhagen, 2013.

Kuritz, K., Kearns, J. D., Bukhalid, R., Harms, B. D., Nielsen, U. B., and Schoeberl, B. “Deciphering paradoxical responses to RAF inhibitors – new insights in the MAPK cascade”. In: 12th International Conference on Systems Biology. Heidelberg, 2011.

Emily Behrens, PhD Candidate

Modeling & Simulation Scientist

Bio

Emily Behrens is a pharmacist by training with experience in the clinical sector and specialized expertise in pharmacometrics. In 2022, she joined the Department of Clinical Pharmacy at the University of Hamburg as a PhD student, focusing on population pharmacokinetics, model–informed drug development, and precision dosing.

Her doctoral work contributed to the EU project UNITE4TB, supporting the development of novel anti–tuberculosis treatment strategies through quantitative, model–based approaches. Her work includes evaluating and refining population PK models, investigating variability and identifiability to strengthen model–based inference, and translating these insights into study design recommendations. She has also conducted external model evaluation to assess predictive performance across cohorts and clinical settings, helping advance implementable model–informed precision dosing. She also contributed to clinical pharmacokinetic research in special patient populations, including critically ill patients receiving renal replacement therapy.

Publications

Journal Articles

Behrens, E. and Wicha SG. (2025) Interoccasion variability in population pharmacokinetic models: identifiability, influence, interdependencies and derived study design recommendations, Journal of Pharmacokinetics and Pharmacodynamics, doi: 10.1007/s10928-025-09966-7

Wansing, EM. et al. (2025) Towards precision dosing of vancomycin in patients with allogeneic hematopoietic stem cell transplantation: a comparison of published population pharmacokinetic models, Antimicrobial Agents and Chemotherapy, doi: 10.1128/aac.00257-25

Behrens, E. et al. (2026) Towards model-informed precision dosing of clofazimine, moxifloxacin, and terizidone/cycloserine in the treatment of drug-resistant tuberculosis: An external model evaluation study, Tuberculosis, doi: 10.1016/j.tube.2026.102744

Behrens, E. et al. (2026) Prospective study of pharmacokinetics in critically ill patients undergoing continuous hemodialysis with and without acute-on-chronic liver failure, Annals of Intensive Care, doi: 10.1016/j.aicoj.2026.100082

Conference Talks

Behrens, E. et al. (2024) Moxifloxacin in tuberculosis therapy: External pharmacometrics model evaluation for Bayesian forecasting as a step towards model-informed precision dosing, German Pharmaceutical Society (DPhG) Annual Meeting 2024, Münster, Germany

Behrens, E. et al. (2024) On our way to personalized therapy: Using therapeutic drug monitoring data of moxifloxacin for an external pharmacokinetic model evaluation, International Workshop on Clinical Pharmacology of TB drugs, Virtual Meeting

Wansing, EM. et al. (2024) Vergleich populationspharmakokinetischer Vancomycin-Modelle bei stammzelltransplantierten Patienten, Gemeinsame Doktorandentagung Klinische Pharmazie, Hamburg, Germany

Behrens, E. et al. (2025) Isavuconazole pharmacokinetics in critically ill patients with acute-on-chronic liver failure and continuous hemodialysis: An observational study, ISAP-EPASG joint Anti-Infective PK/PD Symposium, Vienna, Austria

Posters

Behrens, E., Wicha, SG. (2023) Influence of interoccasion variability on parameter estimates of a population pharmacokinetic model under various sparse study designs, Population Approach Group Europe Conference (PAGE 2023), A Coruna, Spain

Behrens, E., Wicha, S.G. (2023) Sparse sampling in clinical study design: Evaluation of the influence of interoccasion variability on parameter estimates of a population pharmacokinetic model, German Pharmaceutical Society (DPhG) Annual Meeting 2023, Tübingen, Germany

Behrens, E. et al. (2024) External evaluation of pharmacometrics models of moxifloxacin for Bayesian forecasting in the treatment of tuberculosis, Population Approach Group Europe Conference (PAGE 2024), Rome, Italy

Wansing, EM. et al. (2024) Vergleich populationspharmakokinetischer Vancomycin-Modelle bei stammzelltransplantierten Patienten, DGKPha Jahrestagung 2024, Hamburg, Germany

Sébastien Lorenzo, MSc

Modeling & Simulation Scientist

Bio

Sébastien Lorenzo has senior experience in pharmacometrics and statistics for the clinical pharmacology components of drug development, hands-on experience in exposure–response analyses and population PK and PK/PD modeling and simulation, and study statistician for clinical pharmacology trials.

Support and lead of statistical and pharmacometric activities across diverse Oncology and Hematology programs, contributing to key drug development decisions, regulatory submission strategies, and the preparation of documentation for health authority interactions.

Publications

Journal Publications

Combes FP, Sy SKB, Li YF, Lorenzo S, Dasgupta K, Kapoor S, Hoch M, Ho YY. Dose Justification for Asciminib in Patients with Philadelphia Chromosome-Positive Chronic Myeloid Leukemia with and Without the T315I Mutation. Clin Pharmacokinet. 2024 Sep;63(9):1301-1312. doi: 10.1007/s40262-024-01411-1. Epub 2024 Sep 7. PMID: 39243304; PMCID: PMC11450061.

Francois Pierre Combes, Ying Fei Li, Sherwin K.B. Sy, Sebastien Lorenzo, Kohinoor Dasgupta, Shruti Kapoor, Matthias Hoch, Yu-Yun Ho; Justification for Asciminib Dosing in Patients with Philadelphia Chromosome-Positive Chronic Myeloid Leukemia (Ph+ CML-CP) with and without the T315I Mutation. Blood 2022; 140 (Supplement 1): 6791–6792. doi: https://doi.org/10.1182/blood-2022-163078

Combes FP, Li YF, Hoch M, Lorenzo S, Ho YY, Sy SKB. Exposure-Efficacy Analysis of Asciminib in Philadelphia Chromosome-Positive Chronic Myeloid Leukemia in Chronic Phase. Clin Pharmacol Ther. 2022 Nov;112(5):1040-1050. doi: 10.1002/cpt.2699. Epub 2022 Jul 31. PMID: 35776072.

Li YF, Combes FP, Hoch M, Lorenzo S, Sy SKB, Ho YY. Population Pharmacokinetics of Asciminib in Tyrosine Kinase Inhibitor-Treated Patients with Philadelphia Chromosome-Positive Chronic Myeloid Leukemia in Chronic and Acute Phases. Clin Pharmacokinet. 2022 Oct;61(10):1393-1403. doi: 10.1007/s40262-022-01148-9. Epub 2022 Jun 28. Erratum in: Clin Pharmacokinet. 2022 Oct;61(10):1475-1476. doi: 10.1007/s40262-022-01166-7. PMID: 35764773.

Li YF, Combes FP, Hoch M, Lorenzo S, Sy SKB, Ho YY. Correction to: Population Pharmacokinetics of Asciminib in Tyrosine Kinase Inhibitor-Treated Patients with Philadelphia Chromosome-Positive Chronic Myeloid Leukemia in Chronic and Acute Phases. Clin Pharmacokinet. 2022 Oct;61(10):1475-1476. doi: 10.1007/s40262-022-01166-7. Erratum for: Clin Pharmacokinet. 2022 Oct;61(10):1393-1403. doi: 10.1007/s40262-022-01148-9. PMID: 35976571.

Marbury T, El-Hashimy M, Blumenstein L, Letellier F, Sengupta T, Lorenzo S, Preston RA. Pharmacokinetics and Safety of Multiple-Dose Alpelisib in Participants with Moderate or Severe Hepatic Impairment: A Phase 1, Open-Label, Parallel Group Study. J Cancer. 2023 May 21;14(9):1571-1578. doi: 10.7150/jca.82736. PMID: 37325049; PMCID: PMC10266244.

Gajewska M, Blumenstein L, Kourentas A, Mueller-Zsigmondy M, Lorenzo S, Sinn A, Velinova M, Heimbach T. Physiologically Based Pharmacokinetic Modeling of Oral Absorption, pH, and Food Effect in Healthy Volunteers to Drive Alpelisib Formulation Selection. AAPS J. 2020 Oct 18;22(6):134. doi: 10.1208/s12248-020-00511-7. PMID: 33070288.

Csonka D, Hazell K, Waldron E, Lorenzo S, Duval V, Trandafir L, Kobalava ZD. A phase-1, open-label, single-dose study of the pharmacokinetics of buparlisib in subjects with mild to severe hepatic impairment. J Clin Pharmacol. 2016 Mar;56(3):316-23. doi: 10.1002/jcph.590. Epub 2015 Sep 14. PMID: 26183800; PMCID: PMC5049450.

Dutreix C, Lorenzo S, Wang Y. Comparison of two endogenous biomarkers of CYP3A4 activity in a drug-drug interaction study between midostaurin and rifampicin. Eur J Clin Pharmacol. 2014 Aug;70(8):915-20. doi: 10.1007/s00228-014-1675-0. Epub 2014 May 21. PMID: 24839948; PMCID: PMC4088993.

Dutreix C, Munarini F, Lorenzo S, Roesel J, Wang Y. Investigation into CYP3A4-mediated drug-drug interactions on midostaurin in healthy volunteers. Cancer Chemother Pharmacol. 2013 Dec;72(6):1223-34. doi: 10.1007/s00280-013-2287-6. Epub 2013 Oct 2. PMID: 24085261; PMCID: PMC3834177.

del Corral A, Dutreix C, Huntsman-Labed A, Lorenzo S, Morganroth J, Harrell R, Wang Y. Midostaurin does not prolong cardiac repolarization defined in a thorough electrocardiogram trial in healthy volunteers. Cancer Chemother Pharmacol. 2012 May;69(5):1255-63. doi: 10.1007/s00280-012-1825-y. PMID: 22294470; PMCID: PMC3337405.

Posters

Tomás Sou, Sebastien Lorenzo, Romain Sechaud, Hans-Jochen Weber (2024) Population PK/PD modelling to evaluate the effect of siremadlin and disease features on platelet dynamics in haematological malignancies, Population Approach Group Europe (PAGE Meeting), Rome – Italy

Tomás Sou, Christophe Meille, Sebastien Lorenzo, Romain Sechaud (2023) Population PK/PD modelling of platelet dynamics for dose selection in patients with haematological malignancies, Population Approach Group Europe (PAGE Meeting), A Coruña – Spain

Sebastien Lorenzo, Kai Grosch (2018), Statisticians in the Pharmaceutical Industry (PSI), Amsterdam, The Netherland

Alessio Tonello, MSc

Modeling & Simulation Scientist

Bio

Alessio Tonello is an engineer specializing in the application of modeling and simulation techniques to study biological systems. He earned his Master’s degree in Biomedical Engineering with honours from Università degli Studi di Padova, Italy. For his master’s thesis, he collaborated with the Endocrinology, Diabetes & Metabolism Division at Mayo Clinic, USA, to develop a semi-mechanistic mathematical model quantifying the action of glucagon on the liver and its role in the progression of type 2 diabetes.

Alessio furthered his research expertise as a graduate research fellow, where he expanded on his thesis project using a non-linear mixed-effects modeling (NLMEM) approach. He then transitioned to the pharmaceutical industry, undertaking an internship in the Clinical Pharmacometrics group at Roche. There, he worked on a research project titled “Optimization of Numerical Approaches for Pharmacometrics”, which deepened his knowledge of numerical methods in modeling and simulation software. This experience also provided him with valuable insights into the impact of modeling and simulation on drug development.

Since June 2024, Alessio is working as a modeling and simulation scientist at IntiQuan.

Publications

CONFERENCE ARTICLES

Tonello A., Laurenti M., Cobelli C., Vella A., Dalla Man C.; 1564-P: Impaired Insulin Secretion Increases Glucagon Action on the Liver. Diabetes 20 June 2023; 72 (Supplement_1): 1564–P.

CONFERENCE TALKS

Tonello A., Steiert B., Log-transformed ODEs improve numerics within specific scenarios in population modeling. Basel Modeling & Simulation Seminar 2024.

Christian Tönsing, PhD

Modeling & Simulation Scientist

Bio

Dr. Christian Tönsing is an experienced modeler working in the field of Systems Biology and Computational Biology since 2011.

He has several years of experience in model development for non-linear and highly complex systems. Christian has a background in Physics and started his research in Systems Biology and Data Analysis at the Physics department at the University of Freiburg, Germany. Over the past years, he worked on statistical approaches for data analysis and numerical optimization methods for parameter estimation in ordinary differential equations.

During his PhD and post-doctoral studies, he developed methods for the quantitative modeling of human diseases and applied for diverse biological systems. Applications range from infectious disease modeling for the Zika virus (ZIKV) and for the SARS-CoV-2 corona virus, over custom statistical approaches for breast cancer research, to data-based mechanistic models for signaling pathways of hematopoiesis in red blood cells.

Using MATLAB and R, he applied diverse mathematical methods related to statistical inference, uncertainty and identifiability analysis in interdisciplinary research collaborations in close collaboration with wet-lab partners.

He joined the IntiQuan team in October 2022

Publications

Journal articles (peer-reviewed)

Adlung L., Stapor P., Tönsing C., Schmiester L., Schwarzmüller L.E., Wang D., Timmer J., Klingmüller U., Hasenauer J., Schilling M. (2021) Cell-to-cell variability in JAK2/STAT5 pathway components and cytoplasmic volumes define survival threshold in erythroid progenitor cells. Cell Reports 36, 109507

Wieland F.-G., Hauber A. L., Rosenblatt M., Tönsing C., Timmer J. (2021) On structural and practical identifiability. Current Opinion in Systems Biology, 25, 60-69

Tönsing C., Timmer J., Kreutz C. (2019) Optimal paths between parameter estimates in nonlinear ODE systems using the nudged elastic band method. Frontiers in Physics, 7:149

Bernhardt S., Tönsing C., Mitra D., Erdem N., Müller-Decker K., Korf U., Kreutz C., Timmer J., Wiemann S. (2019) Functional proteomics of breast cancer metabolism identifies GLUL as responder during hypoxic adaptation. Journal of Proteome Research, 18 (3), 1352-1362

Tönsing C., Timmer J., Kreutz C. (2018) Profile likelihood-based analyses of infectious disease models. Statistical Methods in Medical Research, 27(7), 1979–1998

Raue A., Steiert B., Schelker M., Kreutz C., Maiwald T., Hass H., Vanlier J., Tönsing C., Adlung L., Engesser R., Mader W., Heinemann T., Hasenauer J., Schilling M., Höfer T., Klipp E., Theis F., Klingmüller U., Schöberl B., Timmer J. (2015) Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems. Bioinformatics, btv405

Tönsing C., Timmer J., Kreutz C. (2014) Cause and cure of sloppiness in ordinary differential equation models. Physical Review E 90, 023303

PhD Thesis

Tönsing, C. (2020) Quantitative modeling of human diseases – methods and applications, Ph.D. Thesis, Institute of Physics, University of Freiburg, Germany doi: 10.6094/unifr/165962

Selected Posters

Tönsing, C. et al. (2022) Likleihood-ratio statistic for the finite-sample case in nonlinear ODE models, 8th Conference on Systems biology of Mammalian Cells (SBMC), Heidelberg, Germany

Tönsing, C. et al. (2019) Optimal paths between parameter estimates in nonlinear ODE systems, Dutch Bioinformatics & Systems Biology Conference, Lunteren, Netherlands

Tönsing, C. et al. (2016) Cause and cure of sloppiness in ordinary differential equation models, 6th Conference on Systems Biology of Mammalian Cells (SBMC), Munich, Germany

Tönsing, C. et al. (2013) Using experimental design methods to reduce the sloppiness of an ODE model, International Conference on Systems Biology (ICSB), Copenhagen, Denmark

Tönsing, C. et al. (2012) Experimental design for parameter estimation: Are ODE models ‘sloppy’?, 4th Conference on Systems Biology of Mammalian Cells (SBMC), Leipzig, Germany

Annabelle Walz, PhD

Modeling & Simulation Scientist

Bio

Annabelle Walz is a trained biologist with a background in infectious diseases (M. Sc.) and microbiology (Ph. D.). Annabelle graduated with highest honors from Swiss Tropical and Public Health Institute and the University of Basel in close collaboration with Medicines for Malaria Venture. Her research focused on drug discovery and translational medicine, e.g. studying drug resistance and drug MoA, assay development for efficacy testing (in vitro, in/ex vivo), and assessing the potential of phytomedicines as starting point for the development of novel drugs. Key projects comprise the development of an automated data analysis algorithm for an in vitro bioassay and the establishment of an in vitro-in silico drug-drug interaction assay that allows to predict combined drug effects in mice and humans.

Working as a scientific collaborator and doctoral student, Annabelle has gathered more than six years of experience in drug discovery and development on preclinical projects involving international collaborations with partners from industry, NGOs, and universities.

Annabelle has joined IntiQuan as a modeling and simulation scientist in April 2024.

Publications

Journal Publications

Hellingman A., Göttle N.L., Walz A., Brancucci N.M.B., Wittlin S., Mäser P., Rottman M. (2026) Using Next Generation Chemiluminescent Probes to Improve the Plasmodium falciparum in vitro Parasite Reduction Ratio (PRR) Assay. ACS Infectious Diseases. Doi: 10.1021/acsinfecdis.5c00924

Walz A., Lehmann U., Duthaler U., Mäser P., Wittlin S. (2024) In vivo antimalarial efficacy of Artemisia afra powder suspensions. Phytomedicine. Doi: 10.1016/j.phymed.2024.155644.

Walz A., Sax S., Scheurer C., Tamasi B., Mäser P., Wittlin S. (2024) Incomplete Plasmodium falciparum growth inhibition following piperaquine treatment translates into increased parasite viability in the in vitro parasite reduction ratio assay. Front. Cell. and Infect. Microbiol. Doi: 10.3389/fcimb.2024.1396786

Hellingman A., Sifoniou K., Buser T., Thommen B.T., Walz A., Passecker A., Collins J., Hupfeld M., Wittlin S., Witmer K., Brancucci N.M.B. (2024). Next generation chemiluminescent probes for antimalarial drug discovery. ACS Infect Dis. 10(4):1286-1297. Doi: 10.1021/acsinfecdis.3c00707

Walz A., Duffey M., Aljayyoussi G., Sax S., Leroy D., Besson D., Burrows J.N., Cherkaoui-Rbati M.H., Go-beau N., Westwood M.A., Siethoff C., Gamo F.J., Mäser P., Wittlin S. (2023) The parasite reduction ratio (PRR) assay version 2: standardized assessment of Plasmodium falciparum viability after antimalarial treatment in vitro. Pharmaceuticals, 16(2):163. Doi: 10.3390/ph16020163

Wicha S.G., Walz A., Cherkaoui-Rbati M.H., Bundgaard N., Kuritz K., Gumpp C., Gobeau N., Möhrle J., Rottmann M., Demarta-Gatsi C. (2022) New in vitro interaction-parasite reduction ratio assay for early derisk in clinical development of antimalarial combinations. Antimicrobial Agents and Chemotherapy. 66(11). Doi: 10.1128/aac.00556-22

Radohery G.F.R.*, Walz A.*, Gumpp C., Cherkaoui-Rbati M.H., Gobeau N., Gower J., Davenport M.D., Rottmann M., McCarthy J.S., Möhrle J.J., Rebelo M., Demarta-Gatsi C., Khoury D.S. (2022) Parasite viabil-ity as a measure of in vivo drug activity in preclinical and early clinical antimalarial drug assessment. Antimicrobial Agents and Chemotherapy. 66(7). Doi: 10.1128/aac.00114-22. *Equal contribution.

Walz A., Leroy D., Andenmatten N., Mäser P., Wittlin S. (2019) Anti-malarial ozonides OZ439 and OZ609 tested at clinically relevant compound exposure parameters in a novel ring-stage survival assay. Malaria Journal. 18(1):427. Doi: 10.1186/s12936-019-3056-8

Jourdan J., Walz A., Matile H., Schmidt A., Wu J., Wang X., Dong Y., Vennerstrom J.L., Schmidt R.S., Wittlin S., Mäser P. (2019) Stochastic protein alkylation by antimalarial peroxides. ACS Infectious Diseases. 5(12):2067-2075. Doi: 10.1021/acsinfecdis.9b00264

Conference Posters

Walz A. et al. (2023) In vivo antimalarial activity of Artemisia afra. BioMalPar XIX: biology and pathology of the malaria parasite, Heidelberg, Germany

Walz A. et al. (2022) In vitro parasite reduction ratio assay: version 2.0. Keystone malaria symposium: confronting challenges from drug discovery to treatment, Breckenridge, USA

Diego Vera Yunca, PhD

Modeling & Simulation Scientist

Bio

Diego Vera Yunca is an experienced modeler and a biochemist by training. He obtained his MSc and PhD with honors from the University of Navarra (Spain). Afterward, Diego joined Uppsala University as a postdoctoral researcher. His research has been focused on the development of pharmacometric models based on preclinical and/or clinical data from different therapeutic areas for over 7 years.

During his PhD, Diego worked on the development of disease models and drug effect models for a rare disease (acute intermittent porphyria), and tumor size and overall survival models for metastatic colorectal cancer. As a postdoc, he joined an IHI project called COMBINE to develop a translational PKPD modelling workflow that could improve the translation of preclinical results into clinical trials to fight antimicrobial resistance. While carrying out these projects, Diego worked with multidisciplinary teams from universities, research institutions and industry partners.

Diego has joined IntiQuan as a modelling and simulation scientist in February 2025.

Publications

JOURNAL ARTICLES

Vera-Yunca D, Córdoba KM, Parra-Guillen ZP, Jericó D, Fontanellas A, Trocóniz IF. Mechanistic modelling of enzyme-restoration effects of new recombinant liver-targeted proteins in acute intermittent porphyria.
British Journal of Pharmacology. 2022 Jul;179(14):3815-3830. doi: 10.1111/bph.15821.
Vera-Yunca D, Parra-Guillen ZP, Girard P, Trocóniz IF, Terranova N. Relevance of primary lesion location, tumour heterogeneity, and genetic mutation demonstrated through tumour growth inhibition and overall survival modelling in metastatic colorectal cancer. British Journal of Clinical Pharmacology. 2022 Jan;88(1):166-177. doi: 10.1111/bcp.14937.
Parra-Guillen ZP, Fontanellas A, Jiang L, Jericó D, Martini P, Vera-Yunca D, Hard M, Guey LT, Troconiz IF. Disease pharmacokinetic-pharmacodynamic modelling in acute intermittent porphyria to support the development of mRNA-based therapies. British Journal of Pharmacology. 2020 Jul;177(14):3168-3182. doi: 10.1111/bph.15040. Erratum in: British Journal of Pharmacology. 2021 Feb;178(4):997. doi: 10.1111/bph.15317.
Vera-Yunca D, Girard P, Parra-Guillen ZP, Munafo A, Trocóniz IF, Terranova N. Machine Learning Analysis of Individual Tumor Lesions in Four Metastatic Colorectal Cancer Clinical Studies: Linking Tumor Heterogeneity to Overall Survival. AAPS Journal. 2020 Mar 16;22(3):58. doi: 10.1208/s12248-020-0434-7.
Vera-Yunca D, Serrano-Mendioroz I, Sampedro A, Jericó D, Trocóniz IF, Fontanellas A, Parra-Guillén ZP. Computational disease model of phenobarbital-induced acute attacks in an acute intermittent porphyria mouse model. Molecular Genetics and Metabolism. 2019 Nov;128(3):367-375. doi: 10.1016/j.ymgme.2018.12.009.

ORAL PRESENTATIONS

Vera-Yunca D, Parra-Guillen ZP, Girard P, Trocóniz IF, Terranova N. Semi-mechanistic modeling of tumor size and overall survival including machine learning-derived tumor heterogeneity. PAGE 2021. https://www.page-meeting.org/default.asp?abstract=9690

POSTERS

Vera-Yunca D, Friberg LE. Assessing clinical outcomes of nosocomial pneumonia patients with a pharmacometric multistate model. PAGE 2024. https://www.page-meeting.org/default.asp?abstract=10962
Vera-Yunca D, Friberg LE. A multistate model for the analysis of clinical outcomes in nosocomial pneumonia patients. ECCMID 2024.
Vera-Yunca D, Friberg LE. A translational semi-mechanistic pharmacokinetic-pharmacodynamic framework to design animal studies: Application to linezolid and vancomycin. PAGE 2023. https://www.page-meeting.org/default.asp?abstract=10498
Vera-Yunca D, Córdoba KM, Parra-Guillén ZP, Jericó J, Fontanellas A, Trocóniz IF. Towards a mechanistic modelling platform to support development of new treatments in acute intermittent porphyria. ACoP12 (2021).
Parra-Guillén ZP, Vera-Yunca D, Jiang L, Hard M, Guey LT, Trocóniz IF. Disease pharmacokinetic-pharmacodynamic (PKPD) modelling to support the development of gene therapy treatments for rare diseases. PAGE 2019. https://www.page-meeting.org/default.asp?abstract=8909
Vera-Yunca D, Serrano-Mendioroz I, Trocóniz IF, Fontanellas A, Parra-Guillén ZP. Pharmacokinetic-Pharmacodynamic model for Acute Intermittent Porphyria in porphyric mice treated with a new recombinant PBGD protein. PAGE 2019. https://www.page-meeting.org/default.asp?abstract=8880
Vera-Yunca D, Serrano-Mendioroz I, Trocóniz IF, Fontanellas A, Parra-Guillén ZP. Disease modelling of repeated acute attacks in an acute intermittent porphyria mouse model. PAGE 2018. https://www.page-meeting.org/?abstract=8675

LET'S EXPLORE HOW WE CAN BE HELPFUL

Meet IntiQuan Team

All IntiQuan team members are recognized experts in modeling & simulation

OUR TEAM MEMBERS HAVE EXCELLENT EXPERTISE IN MODELING & SIMULATION, ADVANCED ANALYTICS, AND DRUG DEVELOPMENT

Stefan Wetzel, PhD

Managing Director

Bio

Henning Schmidt, PhD

Chief Scientific Officer

Bio

Petra Jauslin, PhD

Senior Director Modeling & Simulation

Bio

Daniel Kaschek, PhD

Director Modeling & Simulation

Bio

Anne Kümmel, PhD

Director Modeling & Simulation

Amit Taneja, PhD

Director Modeling & Simulation

Bio

Darius Schweinoch, PhD

Associate Director Modeling & Simulation

Bio

Riccardo Colombo, PHD

VP, Expert Partner at PLG supporting IntiQuan

Bio

Justin Gross, BA

Associate Manager Operations

Bio

Timo Smieszek, PhD

Director Project Management & BD

Bio

Stéphan Benay, PhD

Modeling & Simulation Scientist

Bio

Sebastian Blachuta, MD, MSc

Modeling & Simulation Scientist

Bio

Charlotte Kern, PhD

Modeling & Simulation Scientist

Bio

Karsten Kuritz, PhD

Modeling & Simulation Scientist

Bio

Emily Behrens, PhD Candidate

Modeling & Simulation Scientist

Bio

Sébastien Lorenzo, MSc

Modeling & Simulation Scientist

Bio

Alessio Tonello, MSc

Modeling & Simulation Scientist

Bio

Christian Tönsing, PhD

Modeling & Simulation Scientist

Bio

Annabelle Walz, PhD

Modeling & Simulation Scientist

Bio

Diego Vera Yunca, PhD

Modeling & Simulation Scientist

Bio

LET'S EXPLORE HOW WE CAN BE HELPFUL

All IntiQuan team members
are recognized experts
in modeling & simulation

OUR TEAM MEMBERS HAVE EXCELLENT
EXPERTISE IN MODELING & SIMULATION, ADVANCED ANALYTICS, AND DRUG DEVELOPMENT