poem predictive oncology via general engineering modeling · synopsis views of engineering...

Synopsis Views of Engineering Modeling The Proposed Computational Thread

POEM – Predictive Oncology viageneral Engineering Modeling

Prof. Gianpaolo Ruocco, PhD

Academic Spin-off “iBMB”

Potenza, December 2016


A 2-parts presentation

A brief mention of engineering modeling for life sciencesA possible kick-off format for a perspective collaboration


Potentials and Opportunities

Virtualization through computational modeling

Modeling with CFD (Computational Fluid Dynamics)softwareAn essential tool in analysis and design in a variety ofindustrial sectors



Computational Bioscience

CFD is being employed in a variety of medical fields, aswell



Two future visions for personalized care

In-silico patient availability, or virtualizationSuperimposition with current diagnostic imaging, oraugmented reality



Deeper insights in research, and even in routine care

With a model that is properly devised and validated within-vitro/clinical data:

extraction of all kinds of relevant informationvirtual exploration and exercise of pharmacokinetics andpharmacodynamics for new, sustainable protocolsnew tools for surgery. . . you name it



Why should we be attracted by this idea?

predictive oncology studies and tools are available in theassociated literature by the dozen, but . . .no-one as ever attacked this problem with general CFDsoftwares that we master



Why should we be attracted by this idea?

Advantages of this strategy:viable model sits right on doctor’s desk, with limitedsoftware and maintenance costsvarious tumor/patient models can be generated at once atlittle costswith regards to PET/MRI/CT/US imaging, compliance withOS resources ensures highest potential of generatedgraphics and superimposition


From imaging to mathematics

Just about “anything” that is transported in nature can bedescribed in a general continuum by a governing transportequation, for general variable φ:

∂ρφ

∂t+ v · ∇φ = D∇2φ± S

starting from imaging, we acquire the geometry andassume any tissue feature and occurrence, to come upwith the in-silico replica


Main features of a tentative model

1 Tissue microscopic topology, describing density and cellfraction in a given situation

2 Interstitial pressure, which depends on the dynamic tissuetopology at any point in the situation

3 Cell activity, depending on local metabolic activity which isincreased for tumor cells

4 Nutrients, metabolites, cancer hallmark parameters anddrugs, whose governing equations are intertwined tosimulate the realistic behaviour of tumors



which and how many hallmark parameters are to bemodelled (from definitions by Hanahan and Weinberg, Cell2011)?among others, Tang et al. PLOS ONE 9 1 2014successfully used a comprehensive PDE-based model,enforcing a Tumor Angiogenesis Factor (TAF)



Then, the perspective model could take into account thefollowing:

1 Local interstitial pressure p via geometry considerations(local cell and vascular densities)

2 Cell cycle parameter A due to local budget of nutrients andmetabolites

3 Interstitial fluid velocity V via Darcy’s law on p4 V increments diffusion D in 4 transport PDEs:

∂ρφ

∂t= D+∇2φ± S

where φ stands alternatively for concentrations of nutrientcO2, metabolite cCO2, TAF (depending on local value of A)cTAF , and drug cd


Role of each φ variable

oxygen concentration cO2As glucose, amino acids, fatty acids, vitamins andmicronutrients are hydrophilic, they do not easily permeateacross cell’s plasma membraneFor sake of simplicity cO2 could be the representative localnutrient for DNA, RNA and proteins synthesis, affectingtumor cell metabolism, angiogenesis, growth andmetastasis



carbon dioxide concentration cCO2Metabolic wastes accumulation occurs during tumorgrowth process due to inefficient drainage, causingreduced cell activity and biosynthesis up to necrosis.For sake of simplicity cCO2 could be the representative cellwaste metabolite, affecting tumor growth



TAF concentration cTAFTAF could underlie a variety of biological capabilities,qualified as rational condition for neoplastic diseases.As tumor cells rapidly consume nutrients, hypoxia occurs inthe center of avascular tumors once a given threshold isreached, causing local TAF secretion to favor new vesselsto sprout from existing ones towards hypoxia regions



drug concentration cdThe effect of anti-angiogenic drugs is to reach a localconcentration above a given threshold in order to lower theTAF release rate or inducing direct apoptosis; whilecytotoxic drugs above a given threshold induce DNAdamage to tumor cell in order to prevent or limit cellreplication


Role of each source term Sφ

SO2 consists of:1 a positive term due to the oxygen released by blood cells

supplied locally by blood vessel, depending on pressuredifference across vessel wall and vessel size

2 a negative term due to the oxygen uptake by cells,proportional to the local A value



SCO2 consists of:1 a positive term due to the carbon dioxide release rate,

proportional to the local A value2 a negative term due to the carbon dioxide uptake by blood

cells supplied locally by blood vessels, depending onpressure difference across vessel wall and vessel size



STAF consists of:1 a positive term due to the TAF release rate, proportional to

the local cO2 value2 a negative term due to the TAF uptake by blood cells

supplied locally by blood vessels, depending on pressuredifference across vessel wall and vessel size



Sd consists of:1 term being positive or negative, due to the drug released

locally or uptaken by blood cells supplied by local bloodvessels, depending on pressure difference across vesselwall and vessel size

2 a negative term due to the drug natural decay


A teaser calculation

cancer progression in time, through multiple stages: tumorinitiation/avascular growth/transition to vascular growth


A teaser calculation

a successful therapy in time: tissue features are restored


Bibliometric data and contacts

ORCID record:http://orcid.org/0000-0001-5342-3208

SCOPUS Author ID: https://www.scopus.com/authid/detail.uri?authorId=7005837421

h-index=11, with average h-index'4 (own Engineering Sector)

E-mail: [email protected]

Voice: +39 0971 205454

Web page: http://www2.unibas.it/CFDnova

http://orcid.org/0000-0001-5342-3208

https://www.scopus.com/authid/detail.uri?authorId=7005837421

https://www.scopus.com/authid/detail.uri?authorId=7005837421

http://www2.unibas.it/CFDnova

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