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Since 2019, Matheon's application-oriented mathematical research activities are being continued in the framework of the Cluster of Excellence MATH+
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Dr. Max von Kleist

Head of research group

Freie Universität Berlin
Arnimallee 6
+49 (0) 30 838 75257

Research focus

Modelling, simulation, inference and optimal control in Systems Pharmacology

Projects as a project leader

  • CH20

    Stochasticity driving robust pattern formation in brain wiring

    Dr. Max von Kleist / Dr. Martin Weiser

    Project heads: Dr. Max von Kleist / Dr. Martin Weiser
    Project members: Marian Moldenhauer / Maureen Smith
    Duration: 01.06.2017 - 31.12.2019
    Status: running
    Located at: Freie Universität Berlin


    During brain development, synaptic connection patterns are formed in an extremely robust manner. As the interconnection patterns are much too complex to be encoded directly in the genome, they must emerge from simpler rules. In this project we investigate mechanistic stochastic models of axon growth and filopodial dynamics, checking whether their simulation leads to connection patterns and dynamics as observed in vivo, and with the same robustness.
  • CH-AP19

    Meth4SysPharm: Modeling methods for systems pharmacology and application to HIV-1

    Dr. Max von Kleist

    Project heads: Dr. Max von Kleist
    Project members: -
    Duration: 01.05.2015 - 30.04.2019
    Status: completed
    Located at: Freie Universität Berlin


    'Systems pharmacology' denotes the application of systems biology approaches to research questions arising in pharmacology. The aim is to understand the interaction of drugs with com- plex biological networks and to use this knowledge to develop- and improve medical therapy. Within the proposed project we will address unsolved mathematical challenges arising from this novel, interdisciplinary approach. We will integrate knowledge and data from three subtopics in order to study the mechanisms of drug resistance development in HIV-1, as a model system. In close cooperation with experts from the respective fields, the systems' response to drug interference, in terms of 'evolutionary dynamics' will be assessed alongside with the temporal resolution of drug interference ('drug action and pharmacokinetics') and their implications for the 'optimal use of therapy'. The proposed research program is expected to provide methodologi- cal advance that allows projecting these interrelations into measurable clinical outcomes, while addressing a relevant medical problem at the same time.
  • CH-AP20

    Integrative mathematical modeling of physiological- and molecular factors of osteoarthritis of the knee

    Dr. Max von Kleist

    Project heads: Dr. Max von Kleist
    Project members: -
    Duration: 01.05.2015 - 30.04.2019
    Status: completed
    Located at: Freie Universität Berlin


    Osteoarthritis of the knee (OAK) is a complex multi-factorial condition that is characterised by a lack of hyaline cartilage self repair 1, inflammation & pain 2. As for many other multi-factorial conditions, computational models may be useful tools of direct clinical relevance that allow studying the interaction of putative factors. Within this subproject, we want to develop a comprehensive computational model of cartilage homeostasis that will help us to understand and to evaluate the onset and progression of OAK. While the underlying mechanisms of OAK remain unknown, several factors have been previously associated with osteoarthritis and studied in isolation, such as cell density-dependent extracellular matrix (EM) generation 3,4, EM metabolism 5, the effect of nutrient gradients 5,6 and the influence of (mechano-) growth factors 7.

    Our research group has a broad expertise in interdisciplinary research in biomedicine 8,11 with a particular focus on mechanistic mathematical modelling 8,9 including in vitro to in vivo extrapolation, as well as the analysis of complex clinical samples 10. Within this consortium, we aspire to combine biochemical data from PrevOP subprojects SP1-3 (inflammation, cartilage self-repair & pain) and OVERLOAD projects SP5, 7-8 (fluid transport, mechano-sensitive signalling, cartilage self-repair), to successively develop mathematical models of cartilage homeostasis. Particularly, integration of results from OVERLOAD SP5 may allow to couple image-derived clinical data to metabolic events in the cartilage. The developed comprehensive model of OAK will further our understanding of the disease and the interplay of the mentioned factors, provide insights into disease mechanisms and strategies for its prevention (like, e.g. physical training). The aim of the project is thus to provide a translational framework between in vitro bio-molecular studies, ex vivo analysis, animal models and human patients with OAK (clinical projects in PrevOP/OVERLOAD).
  • CH4

    Optimal control of chemical reaction systems and application to drug resistance mitigating therapy

    Dr. Max von Kleist / PD Dr. Marcus Weber

    Project heads: Dr. Max von Kleist / PD Dr. Marcus Weber
    Project members: Dr. Wei Zhang
    Duration: -
    Status: completed
    Located at: Freie Universität Berlin


    Development and spread of drug resistant microorganisms is a major health issue which, accompanied by an attrition in drug development, is expected to worsen in the near future. The source of drug resistance development is the inadequate use of antimicrobials: Inadequate therapies insufficiently suppress susceptible strains, which may give rise to a drug resistant type. At the same time, inadequate therapy exerts enough selective pressure to provide the newly emerged resistant strain with a selective advantage that allows it to become fixed in the population. In recent years, we have elaborated the idea, that an optimal switching between existing antimicrobial drugs may mitigate drug resistance development in the individual. Drug resistance development is an intrinsically stochastic process. This process can be accurately described by the chemical master equation (CME). A major mathematical drawback is the fact that the CME cannot be solved directly due to its numerical complexity. Therefore, computation of an optimal control/therapy based on a direct numerical solution of the CME is usually not feasible. The aim of the proposed project is to mathematically characterize and develop optimal control policies derived from approximations of the CME, and to use the developed methods to suggest drug mitigating therapies to clinical partners in the field of HIV-1 and antibiotic resistance.