Computationally efficient framework for diagnosing, understanding and predicting biphasic population growth.

Throughout the life sciences, biological populations undergo multiple phases of growth, often referred to as for the commonly encountered situation involving two phases. Biphasic population growth occurs over a massive range of spatial and temporal scales, ranging from microscopic growth of tumours over several days, to decades-long regrowth of corals in coral reefs that can extend for hundreds of kilometres. Different mathematical models and statistical methods are used to diagnose, understand and predict biphasic growth.

Culture of Bladder Cancer Organoids as Precision Medicine Tools.

Current in vitro therapeutic testing platforms lack relevance to tumor pathophysiology, typically employing cancer cell lines established as two-dimensional (2D) cultures on tissue culture plastic. There is a critical need for more representative models of tumor complexity that can accurately predict therapeutic response and sensitivity. The development of three-dimensional (3D) ex vivo culture of patient-derived organoids (PDOs), derived from fresh tumor tissues, aims to address these shortcomings.

Patient-Derived Explants as a Precision Medicine Patient-Proximal Testing Platform Informing Cancer Management.

Precision medicine approaches that inform clinical management of individuals with cancer are progressively advancing. Patient-derived explants (PDEs) provide a patient-proximal platform that can be used to assess sensitivity to standard of care (SOC) therapies and novel agents. PDEs have several advantages as a patient-proximal model compared to current preclinical models, as they maintain the phenotype and microenvironment of the individual tumor.