•  Traditionally biomaterials development consists of designing a surface and testing its properties experimentally. This trial-and-error approach is limited because of the resources and time needed to sample a representative number of configurations in a combinatorially complex scenario.

•  Computational modeling is of significant importance in identifying best antibacterial materials to prevent and treat implant related biofilm infections.

•  We build a three dimensional computational model using BioScape1, an agent based modeling and simulation language to simulate varying configurations of surface coatings at a fraction of time.

•  The resulting computational model is able to reduce number of experiments and predict behavior.

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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#61$#'• Adhesion Phase: 2 Hours (Wet Lab)

5%827&$73/#'3<'$>8'&3456$!$73/!1'43281'• Visualization of Biofilm formation. • Construction and validation of stochastic computational model. •  Prediction of optimal surface configuration with minimal number of

attached bacteria and maximal proportion of dead bacteria.

• Multifunctional coatings – Assembly from first principles. • Viscosity, temperature, flow, … •  Include Tissue in the model.

Figure 1: Bifunctional Surface with Polymers Brushes and Pluronic-Lysozyme Conjugates

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. •  Reactions – Model Training Data

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%8<8%8/&8#'1.  A. Compagnoni, V. Sharma, Y. Bao, M. Libera, S. Sukhishvili, P. Bidinger, L. Bioglio, and E. Bonelli. BioScape: A modeling and simulation

language for bacteria-materials interactions. Electronic Notes in Theoretical Computer Science, 293(0):35 – 49, 2013. Proceedings of the Third International Workshop on Interactions between Computer Science and Biology (CS2Bio’12).

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.

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• Our model predicts that between 1 and 10% of conjugation in the initial concentration yields the minimal amount of bacteria with the maximal percentage of dead bacteria.

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• Growth Phase: 18 Hours (Wet Lab)

•  Total Number of Bacteria and % Dead Bacteria for varying % of Pluronic-Lysozyme conjugates

•  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@0.00001671, 1.0

Bac()@msBac, stepBac, shapeBac(size, color) = !attach.PBac() + mov.Bac()

PBac()@msPBac, stepPBac, shapePBac(size, color) = delay@0.000001.(PBac() | PBac()) + ?kill().DBac()

DBac()@msDBac, stepDBac, shapeDBac(size, color) = delay@0.1

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

Lyso()@msLyso, 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: movement space (!), step (") and shape (#).

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

Figure 2: Process Model

Figure 3: 3D Space

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•  Live/Dead % Bacteria and CFUs per unit In Silico Experiments

Training Data Validation Training Data

Validation Validation Validation