A survey of open questions in adaptive therapy: Bridging mathematics and clinical translation

eLife, Journal Year: 2023, Volume and Issue: 12

Published: March 23, 2023

Adaptive therapy is a dynamic cancer treatment protocol that updates (or ‘adapts’) decisions in anticipation of evolving tumor dynamics. This broad term encompasses many possible protocols patient-specific dose modulation or timing. maintains high levels burden to benefit from the competitive suppression treatment-sensitive subpopulations on treatment-resistant subpopulations. evolution-based approach has been integrated into several ongoing planned clinical trials, including metastatic castrate resistant prostate cancer, ovarian and BRAF-mutant melanoma. In previous few decades, experimental investigation adaptive progressed synergistically with mathematical computational modeling. this work, we discuss 11 open questions The are split three sections: (1) integrating appropriate components models (2) design validation dosing protocols, (3) challenges opportunities translation.

Language: Английский

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Role of Fluid Dynamics in Infectious Disease Transmission: Insights from COVID-19 and Other Pathogens

Trends in Sciences, Journal Year: 2024, Volume and Issue: 21(8), P. 8287 - 8287

Published: June 1, 2024

The spread of infectious diseases such as COVID-19 depends on complex fluid dynamics interactions between pathogens and phases, including individual droplets multiphase clouds. Understanding these is crucial for predicting controlling disease spread. This applies to human animal exhalations, coughs sneezes, well bursting bubbles that create micron-sized in various indoor outdoor environments. By exploring case studies this regard, study examines the emerging field transmission, focusing flows, interfacial turbulence, pathogens, traffic, aerosol ventilation, breathing microenvironments. These results indicate increased ventilation rates local methods can effectively reduce concentration SARS-CoV-2-laden aerosols immediate spaces individuals. In a displacement-ventilated room, both neutral unstable conditions were more effective removing breathed from air, regardless presence test subjects. However, stable may increase risk infection individuals living confined spaces. Thus, findings are useful providing practical guidance managing airborne infections. HIGHLIGHTS Fluid affect transmission explored flow, dispersion, respiratory zones Increased SARS-CoV-2 Displacement eliminates under Cramped damp environments GRAPHICAL ABSTRACT

Language: Английский

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Prostate-specific antigen dynamics predict individual responses to intermittent androgen deprivation

Nature Communications, Journal Year: 2020, Volume and Issue: 11(1)

Published: April 9, 2020

Abstract Intermittent androgen deprivation therapy (IADT) is an attractive treatment for biochemically recurrent prostate cancer (PCa), whereby cycling on and off can reduce cumulative dose limit toxicities. We simulate prostate-specific antigen (PSA) dynamics, with enrichment of PCa stem-like cell (PCaSC) during as a plausible mechanism resistance evolution. Simulated PCaSC proliferation patterns correlate longitudinal serum PSA measurements in 70 patients. Learning dynamics from each cycle leave-one-out study, model simulations predict patient-specific evolution overall accuracy 89% (sensitivity = 73%, specificity 91%). Previous studies have shown benefit concurrent therapies ADT both low- high-volume metastatic hormone-sensitive PCa. Model based response the first IADT identify patients who would docetaxel, demonstrating feasibility potential value adaptive clinical trials guided by mathematical models intratumoral evolutionary dynamics.

Language: Английский

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Classical mathematical models for prediction of response to chemotherapy and immunotherapy

PLoS Computational Biology, Journal Year: 2022, Volume and Issue: 18(2), P. e1009822 - e1009822

Published: Feb. 4, 2022

Classical mathematical models of tumor growth have shaped our understanding cancer and broad practical implications for treatment scheduling dosage. However, even the simplest textbook been barely validated in real world-data human patients. In this study, we fitted a range differential equation to volume measurements patients undergoing chemotherapy or immunotherapy solid tumors. We used large dataset 1472 with three more per target lesion, which 652 had six data points. show that early response shows only moderate correlation final response, demonstrating need nuanced models. then perform head-to-head comparison classical are widely field: Exponential, Logistic, Classic Bertalanffy, General Gompertz model. Several provide good fit measurements, model providing best balance between goodness number parameters. Similarly, when fitting data, general Bertalanffy yield lowest mean absolute error forecasted indicating these could potentially be effective at predicting outcome. summary, quantitative benchmark state-of-the art growth. publicly release an anonymized version original first set evaluation

Language: Английский

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Treatment of evolving cancers will require dynamic decision support

Annals of Oncology, Journal Year: 2023, Volume and Issue: 34(10), P. 867 - 884

Published: Sept. 28, 2023

Cancer research has traditionally focused on developing new agents, but an underexplored question is that of the dose and frequency existing drugs. Based modus operandi established in early days chemotherapies, most drugs are administered according to predetermined schedules seek deliver maximum tolerated only adjusted for toxicity. However, we believe complex, evolving nature cancer requires a more dynamic personalized approach. Chronicling milestones field, show impact schedule choice crucially depends processes driving treatment response failure. As such, heterogeneity evolution dictate one-size-fits-all solution unlikely-instead, each patient should be mapped strategy best matches their current disease characteristics objectives (i.e. 'tumorscape'). To achieve this level personalization, need mathematical modeling. In perspective, propose five-step 'Adaptive Dosing Adjusted Personalized Tumorscapes (ADAPT)' paradigm integrate data understanding across scales derive schedules. We conclude with promising examples model-guided personalization call action address key outstanding challenges surrounding collection, model development, integration.

Language: Английский

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A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

npj Systems Biology and Applications, Journal Year: 2024, Volume and Issue: 10(1)

Published: July 5, 2024

Abstract This article reviews the current knowledge and recent advancements in computational modeling of cell cycle. It offers a comparative analysis various paradigms, highlighting their unique strengths, limitations, applications. Specifically, compares deterministic stochastic models, single-cell versus population mechanistic abstract models. detailed helps determine most suitable framework for research needs. Additionally, discussion extends to utilization these models illuminate cycle dynamics, with particular focus on viability, crosstalk signaling pathways, tumor microenvironment, DNA replication, repair mechanisms, underscoring critical roles progression optimization cancer therapies. By applying crucial aspects therapy planning better outcomes, including drug efficacy quantification, discovery, resistance analysis, dose optimization, review highlights significant potential insights enhancing precision effectiveness treatments. emphasis intricate relationship between therapeutic strategy development underscores pivotal role advanced techniques navigating complexities dynamics implications therapy.

Language: Английский

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Toward mechanistic medical digital twins: some use cases in immunology

Frontiers in Digital Health, Journal Year: 2024, Volume and Issue: 6

Published: March 7, 2024

A fundamental challenge for personalized medicine is to capture enough of the complexity an individual patient determine optimal way keep them healthy or restore their health. This will require computational models sufficient resolution and with mechanistic information provide actionable clinician. Such are increasingly referred as medical digital twins. Digital twin technology health applications still in its infancy, extensive research development required. article focuses on several projects different stages that can lead specific-and practical-medical twins modeling platforms. It emerged from a two-day forum problems related twins, particularly those involving immune system component. Open access video recordings discussions available.

Language: Английский

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Cancer modeling: From mechanistic to data-driven approaches, and from fundamental insights to clinical applications

Journal of Computational Science, Journal Year: 2020, Volume and Issue: 46, P. 101198 - 101198

Published: Aug. 12, 2020

Cancer is still one of the major causes death worldwide. Even if its comprehension improving continuously, complexity and heterogeneity this group diseases invariably make some cancer cases incurable lethal. By focusing only on or two cancerous molecular species simultaneously, traditional in vitro vivo approaches do not provide a global view disease are sometimes unable to generate significant insights about cancer. In silico techniques increasingly used oncology domain for their remarkable integration capacity. basic research, vast number mathematical computational models has been implemented past decades, allowing better understanding these complex diseases, generating new hypotheses predictions, guiding scientists towards most impactful experiments. Although clinical uptake such limited, treatment strategies currently under investigation phase I II trials. Besides being responsible therapeutic ideas, could play role optimizing trial design patient stratification. This review provides non-exhaustive overview according intrinsic features. contributions science discussed, using hallmarks as guidance. Subsequently, models, that part ongoing trials, addressed. forward-looking section, issues need adequate regulatory processes related advances model technologies discussed.

Language: Английский

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Improving cancer treatments via dynamical biophysical models

Physics of Life Reviews, Journal Year: 2021, Volume and Issue: 39, P. 1 - 48

Published: Oct. 19, 2021

Language: Английский

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Forecasting Individual Patient Response to Radiation Therapy in Head and Neck Cancer With a Dynamic Carrying Capacity Model

International Journal of Radiation Oncology*Biology*Physics, Journal Year: 2021, Volume and Issue: 111(3), P. 693 - 704

Published: June 5, 2021

PurposeTo model and predict individual patient responses to radiation therapy.Methods MaterialsWe modeled tumor dynamics as logistic growth the effect of a reduction in carrying capacity, motivated by on microenvironment. The was assessed weekly volume data collected for 2 independent cohorts patients with head neck cancer from H. Lee Moffitt Cancer Center (MCC) MD Anderson (MDACC) who received 66 70 Gy standard daily fractions or accelerated fractionation. To response therapy patients, we developed new forecasting framework that combined learned rate capacity fraction (δ) distribution measurements given test estimate δ, which used patient-specific outcomes.ResultsThe fit MCC high accuracy δ fixed across all patients. an cohort MDACC comparable using cohort, showing transferability rate. predicted outcomes 76% sensitivity 83% specificity locoregional control 68% 85% disease-free survival inclusion 4 on-treatment measurements.ConclusionsThese results demonstrate our simple mathematical can describe variety dynamics. Furthermore, combining historically observed few allowed accurate prediction outcomes, may inform treatment adaptation personalization. therapy. We outcomes. measurements. These

Language: Английский

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