•  We deigned BioScape1, a concurrent agent-based modeling language for the stochastic simulation of complex processes in a reactive environment in 3D space.

•  BioScape is based on the Stochastic Pi-Calculus, and it is motivated by the need for individual based, continuous motion, and continuous space simulation in modeling complex systems.

•  The novel aspects BioScape, include syntactic primitives to declare the scope in space where species can move (!), diffusion rate ("), shape (#), and reaction distance, and an operational semantics that deals with the specifics of 3D locations, verifying reaction distance, and featuring random movement.

•  We defined a translation from BioScape to 3pi and prove its soundness with respect to the operational semantics.

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•  Biomaterials used for implants in the human body often lead to the development of the biofilm formation which are resistant to antibiotics and the immune system.

•  The current state of art lies in the

design and composition of the

biomaterials with antimicrobial agents.

•  Anti-adhesive and Antibacterial Bifunctional Polymers2 is one way to prevent biofilm growth.

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$8-'5#-)• Adhesion Phase: 2 Hours

(%"(5'-!%"-)•  Build a computational model that yields an optimal surface that has the least total number of live and dead bacteria with the highest percentage of dead bacteria.

•  Build computational models using BioScape for multifunctional coatings for application in biomedical systems.

Figure 1:Bifunctional Polymers of Pluronic-Lysozyme Conjugate

Experiment 1: Pluronic Unmodified Experiment 2: 1% Pl-Lys Experiment 3: 100% Pl-Lys •  108 Binding Sites in 1 cm2. •  In Silico: We consider substrate of 100µmX100µm which has 104 Binding Site. •  Simulation time : 1 unit of simulation time corresponds to 10 minutes of wet

lab. •  Rate Parameters

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$8<8$8"(8-)1.  A. Compagnoni, V. Sharma, Y. Bao, P. Bidinger, L. Bioglio, E. Bonelli, M. Libera, and S. Sukhishvili. Bioscape: A

modeling and simulation language for bacteria-materials interactions. In the proceedings of 3rd International Workshop on Interactions between Computer Science and Biology (CS2Bio), 2012.

2.  A. K. Muszanska, H. J. Busscher, A. Herrmann, H.C. van der Mei and W. Norde. Pluronic-lysozyme conjugates as anti-adhesive and antibacterial bifunctional polymers for surface coating. Biomaterials, 32:6333-6341, 2011.

%":%!":)3"&)<'#'$8)=%$@)•  The modeling and simulation framework helped in identifying

biological targets and biomaterials to treat biomaterials-associated infections (BAI).

•  In silico results are validated with the wet lab experiments.

•  Spatial information helped us visualize the bacterial colonization and surface construction.

•  In silico experiments can greatly reduce the time and cost for wet lab experiments.

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• Growth Phase: 18 Hours

•  Live/Dead % Bacteria and CFUs per unit in silico experiments

•  Summary of Wet Lab and In Silico experiments Adhesion Phase Growth Phase

•  Number of PEOs and Lysozymes in silico

Experiment 1: Pluronic Unmodified Experiment 2: 1% Pl-Lys Experiment 3: 100% Pl-Lys

attach@0.00000184, 2.0 kill@0.0001671, 1.0

Bac()@mspaceBac, stepBac, shapeBac(size, color) = ?kill().DeadBac() + !attach.LiveBac() + delay@1.0.(Bac() | Bac()) + mov.Bac()

LiveBac()@mspaceLiveBac, stepLiveBac, shapeLiveBac(size, color) = delay@0.1

DeadBac()@mspaceDeadBac, stepDeadBac, shapeDeadBac(size, color) = delay@0.1

PEO()@mspacePEO, stepPEO, shapePEO(size, color) = ?attach()

Lyso()@mspaceLyso, stepLyso, shapeLyso(size, color) = !kill()

•  Model interactions/behavior •  Bacteria is killed by Lysozyme. •  Bacteria attaches to PEO. •  Bacteria multiplies.

•  Concurrency, Stochasticity and 3D Space •  Bacteria-biomaterials interactions are highly

concurrent. •  Wet lab experiments are stochastic. •  3D space has 3 new attributes: shape (#), step

(") and movement space (!).

•  Process algebra •  Send/Receive Handshake (!/?) Figure 4: Reaction radius and Reaction rates

Figure 2: Process Model

Figure 3: 3D Space

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