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Banff International Research Station (BIRS) for Mathematical Innovation and Discovery

Drug design and development are costly and lengthy. Mathematical and computational modelling anchored in model-informed drug development (MIDD) and quantitative systems pharmacology (QSP) methodologies are integral to accelerating the R&D pipeline. In parallel, MIDD and QSP can be used to better understand the biological basis of drug responses and fuel new biomedical research paths. This workshop will bring together experts in the fields of MIDD and QSP with the goal of strengthening ties between industrial and academic researchers and advancing these exciting fields.

Pharmakologie und Arzneimittelentwicklung,    Angewandte Mathematik (allgem.)

University of Waterloo, Canada

The MCQMC conference series is a biennial meeting focused on Monte Carlo (MC) and quasi-Monte Carlo (QMC) methods in scientific computing. The conference attracts between 150 and 200 participants. Its aim is to provide a forum where leading researchers and users can exchange information on the latest theoretical developments and important applications of these methods. Recent conferences have attracted researchers in Markov chain Monte Carlo (MCMC). In a nutshell, MC methods study complex systems by simulations fed by computer-generated pseudorandom numbers. QMC methods replace these random numbers by more evenly distributed (carefully selected) numbers to improve their effectiveness. A large variety of special techniques are developed and used to make these methods more effective in terms of speed and accuracy. The conference focuses primarily on the mathematical study of these techniques, their implementation and adaptation for concrete applications, and their empirical assessment.

Statistik, Spieltheorie ,    Wissenschaftliches Rechnen und Datenwissenschaft

Fields Institute

This workshop aims to showcase the state-of-the-art mathematical and computational models that are in use in mathematical oncology, with a particular focus on the fourteen hallmarks of cancer. New modeling challenges arise from these hallmarks. Some of the hallmarks relate to the characteristics of the cancer cells themselves (sub-cellular and cellular level), while others include more global effects such as blood circulation, the immune response, the effect and role of the microenvironment, mechanical forces, and the microbiome. Matching the biological diversity of the cancer hallmarks, is the diversity of mathematical approaches and techniques that have been used and are in use to give insight into the growth and spread of cancer – for example, continuum and discrete models; ordinary and partial differential equation models; individual-based and agent-based models; hybrid models; deterministic and stochastic approaches; analytical and computational approaches. Many of these processes act on very different spatial and temporal scales. Hence a new integrated multiscale mathematical modeling framework is needed to include new aspects and insights, such as spatial stochastic models and local and non-local partial differential equation models.

Onkologie,    Systembiologie und mathematische Biologie

Fields Institute

This workshop aims to take a closer look at how mathematical and computational models can help answer clinically relevant questions and enhance multimodal treatments. Currently, a wide range of modelling approaches study cancer and have a crucial role in treatment delivery from answering questions related to cancer biology and treatment efficacy to directly helping with treatment delivery. In this workshop, we would like to bring together clinicians, biomedical experts, experimentalists, and mathematicians to explore some of the relevant questions on multimodal treatment modelling, efficacy, optimization, drug resistance and clinical delivery.

Onkologie,    Systembiologie und mathematische Biologie

Fields Institute

This workshop explores research in methods aimed at connecting mathematical models of cancer evolution and clinical data. It focuses on ecology and evolution of cancer. Traditionally, ecology and evolution have been the most “mathematical” (and perhaps the first mathematical) areas of biology. Mathematical contributions to these fields made in the 20th century are now fundamental parts of scientific knowledge. More recently, methods of ecology and evolution have found their way into oncology, bridging traditional molecular biology and mathematics including stochastic processes, dynamical systems, and nonlinear partial differential equations. New biological challenges lead to difficult mathematical problems and beautiful solutions, which are both innovative mathematically and impactful from the point of view of public health. These will be the focus of the proposed workshop .

Onkologie,    Systembiologie und mathematische Biologie

Fields Institute

Immunotherapies have revolutionized treatments for several types of cancers, but have been met with clinical trial failures in others. The idea of eliciting an immune response against a tumour is old, but we are only just beginning to harness the potential of the immune system to treat both solid and liquid tumours. To improve immunotherapeutic approaches requires understanding how the immune system interacts around and within a tumour, allowing us to establish effective immunotherapeutic protocols. Mathematical modelling can help identify the mechanisms at the heart of immunotherapeutic efficacy and design successful therapeutic regimens. Close collaboration between experimentalists, clinicians, and quantitative researchers in academia and industry is required to forward models for implementation. This workshop will focus on tightening the links between researchers in different fields to fuel immunotherapy success.

Onkologie,    Systembiologie und mathematische Biologie