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
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.
Journal ArticlesHelmlinger, 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
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
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
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
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
Dr. Benjamin Guiastrennec is an experienced pharmacometrician and R enthusiast. Over the years, he has gained experience in planning and performing PK-PD modeling and simulation analyses in various therapeutic areas from early to late drug development stages. Benjamin has a strong interest in data visualization and developed several R packages for model diagnostics such as amget, modelviz or the new xpose.
Benjamin graduated from the school of pharmacy of Montpellier (France) and obtained a master of Pharmacokinetics from the school of pharmacy of Marseille (France). He then pursued a PhD program at the university of Uppsala (Sweden) focusing on the mechanism-based modeling of processes involved in oral drug absorption. Through his education Benjamin was also part of a postdoctoral fellowship program between the university at Buffalo (NY, USA) and Novartis (NJ, USA) and had the opportunity to be an exchange student with the university of California, San Francisco (CA, USA). Benjamin joined the IntiQuan team in 2019.
Guiastrennec B, Sonne DP, Bergstrand M, Vilsbøll T, Knop FK, Karlsson MO. Model-Based Prediction of Plasma Concentration and Enterohepatic Circulation of Total Bile Acids in Humans. CPT Pharmacometrics Syst. Pharmacol., 7:603–612, 2018
Guiastrennec B, Ramachandran G, Karlsson MO, Kumar AKH, Bhavani PK, Gangadevi NP, Swaminathan S, Gupta A, Dooley KE, Savic RM. Suboptimal Antituberculosis Drug
Concentrations and Outcomes in Small and HIV-Coinfected Children in India Recommendations for Dose Modifications. Clin. Pharmacol. Ther., 104(4):733–741, 2018
Guiastrennec B, Söderlind E, Richardson S, Peric A, Bergstrand M. In Vitro and In Vivo Modeling of Hydroxypropyl Methylcellulose (HPMC) Matrix Tablet Erosion Under Fasting and Postprandial Status. Pharm Res, 34:847–859, 2017
Guiastrennec B, Sonne DP, Hansen M, Bagger JI, Lund A, Rehfeld JF, Alskär O, Karlsson MO, Vilsbøll T, Knop FK, Bergstrand M. Mechanism–Based Modeling of Gastric Emptying Rate and Gallbladder Emptying in Response to Caloric Intake. CPTPharmacometrics Syst. Pharmacol, 5:692–700, 2016
Guiastrennec B, Wollenberg L, Forrest A and Ait–Oudhia S. AMGET, an R–Based Postprocessing Tool for ADAPT 5. CPT Pharmacometrics & Syst. Pharmacol. 2(7):1–10, 2013
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
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
Darius Schweinoch is an experienced modeler, who worked on a broad range of biological and pharmaceutical research questions. Coming from an interdisciplinary background (Cell Biology (B. Sc.), Bioinformatics (M. Sc.)), Darius’ research mainly focused on the field of systems biology. In his Master studies, Darius developed models to study the hepatic clearance of uptake-limited drugs based on in vitro data and applied PBPK modeling. His PhD studies at the Institute of Bioinformatics of the University Medicine in Greifswald focused on mathematical modeling to answer research questions regarding the antiviral innate immune response and the replication of Hepatitis C Virus (HCV) under drug treatment. During this time, Darius was awarded the Add-On Fellowship for Interdisciplinary Life Science of the Joachim Herz Stiftung and worked in close collaboration with scientists from numerous backgrounds (biologists, informaticians, statisticians). He further gained hands-on experience in the analysis of biological and medical data using statistical and machine learning methods. Since August 2020, Darius is a Modeling and Simulation Scientist at IntiQuan.
Schweinoch, Darius, et al. “Mechanistic modeling explains the dsRNA length-dependent activation of the RIG-I mediated immune response.” Journal of Theoretical Biology (2020): 110336.
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.
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.
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.
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.
Dr. Venelin Mitov is a highly skilled modeler and software engineer, holding a Ph.D. and a M.Sc. degree in Computational Biology, and a B.Sc. degree in Computer Science. His profile combines a strong mathematical and computer science background with almost a decade of experience in machine learning and statistical modelling.
Venelin has had a dynamic career path spanning both, industry and academia. His main personal strengths are his analytical mindset, combined with a motivation to excel in any professional and scientific challenge. He is a proficient R programmer (developer of a dozen of R-packages; owner of 3 CRAN packages), and he masters several other languages, including C++, Java, and Matlab. During his Ph.D. and post-doctoral studies, he has specialized in population and quantitative trait evolution models, with applications to epidemiological, macro-evolutionary, and stem-cell data. In 2019, his Ph.D. thesis entitled “Phylogenetic Comparative Methods in the Era of Big Data” has been nominated for the ETH silver medal for an outstanding Ph.D. dissertation. More about his open source research projects can be found on his portfolio web-page.
Starting from February 2020, Venelin joined IntiQuan as a modeling and simulation scientist. In this role he conducts modeling and simulation analyses across all phases of drug discovery and development, with emphasis on:
A leader in clinical pharmacology with cross-functional domain expertise supporting various therapeutic areas (small molecules, biologics and biosimilars) with about 3 decades of experience in pharmaceutical industry. Professional experience includes rationalizing concepts, design considerations, planning, execution and analyzing discovery ADME/DMPK, nonclinical and clinical pharmacology studies. Development experience encompasses of developing 505(b)(1) and 505(b)(2) regulatory pathway programs – end to end discovery led candidate nomination, IND and clinical development up to market authorization. Drug development experiences comprises of numerous INDs/CTAs (>70), clinical pharmacology programs to support NDA, and Biosimilar/BLA strategy. From a regulatory perspective interacted with global regulatory agencies (i.e., FDA, MCC, EMA, MHRA, TPD, TGA, DCGI etc.) for various meetings (i.e., FDA’s Type A, B and C meetings).
Nils Bundgaard comes from an interdisciplinary background having studied Molecular Medicine (B. Sc) and Systems Biology (M. Sc.). In his Master studies he has gained extensive knowledge in Infectious disease and Immunity, Neuroscience and Cancer biology. He has experience in building multiscale models combining agent-based and mechanistic modelling using likelihood-free parameter estimation for parameterization on high performance computing cluster environments. He joined IntiQuan in August 2021.
Lydia Burgert is a diversely trained modeler with a background in biotechnology (B. Sc.) and epidemiology (M. Sc.). Lydia received her PhD at the Swiss Tropical and Public Health Institute and the University of Basel in close collaboration with the Medicines for Malaria Venture. Her research focused on using mathematical modelling to support the development of new antimalarial drugs. She employed different approaches including pharmacometric analysis, agent-based models and machine learning methods to investigate the translation of antimalarial efficacy indices from translational drug development up to population impact. Before joining IntiQuan, she was responsible for the initiation of a multi-year project at the Tropical and Public Health Institute bringing together stakeholders from pharmaceutical industry, academia, and global-health agencies to shape the target product profiles of future antimalarial interventions
Lydia is part of the IntiQuan team since September 2021.
Burgert L, Rottmann M, Wittlin S, Gobeau N, Krause A, Dingemanse J, Möhrle JJ, Penny MA. Ensemble modeling highlights importance of understanding parasite-host behavior in preclinical antimalarial drug development. Sci Rep. 2020 Mar 10;10(1):4410. doi: 10.1038/s41598-020-61304-8. PMID: 32157151; PMCID: PMC7064600.
Burgert L, Zaloumis S, Dini S, Marquart L, Cao P, Cherkaoui M, Gobeau N, McCarthy J, Simpson JA, Möhrle JJ, Penny MA. Parasite-Host Dynamics throughout Antimalarial Drug Development Stages Complicate the Translation of Parasite Clearance. Antimicrob Agents Chemother. 2021 Mar 18;65(4):e01539-20. doi: 10.1128/AAC.01539-20. PMID: 33526486; PMCID: PMC8097426.
Camponovo F, Lee TE, Russell JR, Burgert L, Gerardin J, Penny MA. Mechanistic within-host models of the asexual Plasmodium falciparum infection: a review and analytical assessment. Malar J. 2021 Jul 10;20(1):309. doi: 10.1186/s12936-021-03813-z. PMID: 34246274; PMCID: PMC8272282.
Reiker T, Golumbeanu M, Shattock A, Burgert L, Smith TA, Filippi S, Cameron E, Penny Machine learning approaches to calibrate individual-based infectious disease models, medRxiv 2021.01.27.21250484; doi: https://doi.org/10.1101/2021.01.27.21250484 (accepted at Nature Communications)
Burgert et al. (2020), “Model informed target product profiles of long acting injectables for use as seasonal malaria prevention”, 2020 Annual Meeting American Society of Tropical Medicine and Hygiene
Burgert et al. (2020), “Investigation of parasite-host dynamics in antimalarial drug development reveals a disconnect in experimental endpoints”, 2020 Annual Meeting American Society of Tropical Medicine and Hygiene
Burgert (2019), “Ensemble modeling highlights importance of understanding parasite-host behaviour in preclinical antimalaria drug development“ (Talk), Epidemics7 – International Conference on Infectious Disease Dynamics, Charleston, USA
Weber, F.D., Bielicki, J., Rodieux, F., van den Anker, J., and Pfister, M. Selb-stmedikation und Adhärenz in der Pädiatrie. Pädiatrie 04/2015, 2015.
Weber, F.D., Weinhofer, I., Einwich, A., Forss-Petter, S., Muneer, Z., Maier, H., Weber, W.H.A., and Berger, J. Evaluation of retinoids for induction of the redun-dant gene abcd2 as an alternative treatment option in x-linked adrenoleukodys-trophy. PLOS ONE, 2014.
Weber, F.D., Wiesinger, C., Forss-Petter, S., Regelsberger, G., Einwich, A., Weber, W.H.A., Köhler, W., Stockinger, H., and Berger, J. X-linked adrenoleukodystro-phy: very long-chain fatty acid metabolism is severely impaired in monocytes but not in lymphocytes. Human Molecular Genetics, 2014.
Weber, F., Siska, P., Kramer, M., Zulehner, N., Hackl, S., and Wesierska-Gádek, J. Combining an fptase inhibitor with cisplatin facilitates induction of apoptosis in human a549 lung cancer cells. Journal of Experimental Therapeutics & Oncology, 2011.