The Carlo Oncology Suite V2 is a deterministic, browser‑native modelling framework designed to provide transparent educational insight into tumour growth, treatment interactions, resistance emergence, and drug behaviour. The suite consists of six documents: a master ethical overview, a mathematical oncology primer, a full engine specification, a mathematical appendix and model library, a developer handbook, and companion notes. Together, these documents define a reproducible modelling system built entirely on deterministic principles. All randomness is removed, all transitions are explicit, and all outputs are fully traceable to their parameters and initial conditions. It is not a clinical tool and does not offer diagnostic, predictive, or therapeutic guidance. Instead, it presents a clear mathematical environment for understanding the structural behaviour of oncology models under controlled, reproducible conditions. Version 2 represents a substantial refinement over V1. All models have been rebuilt with stricter determinism, clearer operator structure, expanded resistance dynamics, improved pharmacokinetic behaviour, and a more explicit separation between growth geometry and treatment effects. The mathematical substrate has been reorganised for clarity, the ethical boundaries have been strengthened, and the companion notes have been expanded to support responsible educational use. V2 also introduces a unified operator interpretation layer, collapse‑and‑rebound mapping, and a more transparent sensitivity structure. The included models cover exponential, logistic, generalised logistic, Gompertz, and Von Bertalanffy growth; treatment kill terms; pharmacokinetic drug dynamics; two‑population resistance behaviour; mutation flow; collapse and rebound mapping; operator interpretation; and sensitivity analysis. Each model is presented with clear mathematical structure and reinforced ethical boundaries to prevent misinterpretation or clinical misuse. The Carlo Oncology Suite V2 is intended for researchers, students, and developers who require conceptual clarity when exploring mathematical oncology. It provides a stable foundation for understanding how tumour systems behave under constraints, how treatment schedules interact with growth dynamics, and how resistance emerges from structural rules. All components are designed to be reproducible, transparent, and free of external dependencies. Author: Matthew Arthur Carlo Version: V2 Date: July 6th 2026 keywords: mathematical oncology deterministic modelling tumour dynamics tumour growth models logistic growth gompertz model von bertalanffy model exponential growth pharmacokinetics drug concentration modelling treatment response chemotherapy radiotherapy targeted therapy immunotherapy resistance modelling sensitive and resistant populations mutation flow models optimisation control theory dose scheduling deterministic engines browser-native modelling single-file engines reproducible simulations clarity-focused modelling educational modelling conceptual modelling tumour microenvironment modelling phase portraits dynamical systems stability analysis carrying capacity modelling tumour heterogeneity modelling deterministic seedspace modelling model library mathematical appendix oncology primer deterministic simulation loops pure functions no dependencies tumour treatment trade-offs toxicity modelling parameter uncertainty sensitivity analysis deterministic visualisation canvas-based modelling svg-based modelling tumour trajectory analysis resistance takeover modelling bolus dosing periodic dosing pulsed dosing ramp dosing deterministic pharmacokinetics tumour-drug interaction modelling immune interaction sketch spatial diffusion sketch deterministic modelling philosophy clarity minimalism transparency reproducibility ethical modelling responsible modelling non-clinical modelling educational oncology tools deterministic engine specification developer handbook conceptual companion notes modelling reflections modelling context deterministic research artefacts carlo ecosystem carlo oncology suite tumour modelling frameworks deterministic computational oncology deterministic browser engines tumour modelling education tumour modelling research tumour modelling tools tumour modelling clarity tumour modelling transparency tumour modelling reproducibility tumour modelling ethics tumour modelling philosophy deterministic cancer modelling deterministic tumour simulation deterministic treatment simulation deterministic resistance simulation deterministic drug simulation deterministic optimisation deterministic dose scheduling deterministic tumour dynamics deterministic modelling suite deterministic oncology suite deterministic modelling notes deterministic modelling companion deterministic modelling appendix deterministic modelling primer deterministic modelling specification deterministic modelling handbook Contact: For enquiries or research questions related to this work, email matthewcarlo.research@gmail.com
Matthew Arthur Carlo (Mon,) studied this question.