* our design: dna killer automata

* Our Design: DNA Killer Automata* Our Design: DNA Killer Automata

Existing Cancer Therapies

• Expensive

• Inefficient

• Inaccurate

• Serious Side Effects

1. DKA enter cells through injection

2. DKA detect the presence of cancer in the cell

3. DKA releases GCVTPs if all cancer indicators are detected

4. GCVTPs propagate to nearby cancer cells through homologous GJIC

5. After propagation, GCVTPs have entered over 90% of all cancer cells

DNA Killer Automaton (DKA)DNA Killer Automaton (DKA)

The Intelligent NanomedicineThe Intelligent Nanomedicine

Shaoshan Liu and Jean-Luc GaudiotShaoshan Liu and Jean-Luc GaudiotElectrical Engineering & Computer Science Dept., The Henry Samueli Electrical Engineering & Computer Science Dept., The Henry Samueli

School of EngineeringSchool of EngineeringUniversity of California, IrvineUniversity of California, Irvine

Using nanotechnology to build an automaton that cures cancer at the Using nanotechnology to build an automaton that cures cancer at the molecular level.molecular level.

* Simulation: a discrete cellular automaton model* Simulation: a discrete cellular automaton model

ExperimentExperiment

DKADKA

CytotoxinCytotoxinEnzymeEnzyme

CellCell

mRNAmRNAGJICGJIC

Object Oriented SimulationObject Oriented Simulation

Level 1Level 1

Level 2Level 2

Level 3Level 3

0

10

20

30

40

50

60

70

80

90

100

0.25 0.8 1.3 2.05 8.3 14.25 18.9 59

Percentage of Cancer Cells Entered by DKAs

Pe

rce

nta

ge

of

Ca

nc

er

Ce

lls

Kil

led

10% cancer cells

50% cancer cells

100% cancer cells

0

10

20

30

40

50

60

70

80

90

100

Number of DKAs Used

Perc

en

tag

e o

f C

an

cer

Cell

s K

ille

d

10% cancer cells

50% cancer cells

100% cancer cells

YesStartDKA

No

PositivediagnosisReleasecytotoxin

Negativediagnosis

Cytotoxinpropagation

DKAtermination

Cancer indicatorpresent

Cancer indicatorabsent

DKA AlgorithmDKA Algorithm

* Conclusion* Conclusion Our software simulation model Our software simulation model suggests that thesuggests that the bystander bystander effect effect facilitates the propagation of DKA. facilitates the propagation of DKA. Also, our simulation results suggest Also, our simulation results suggest imply that the efficacy of DKA is imply that the efficacy of DKA is linearly dependent on its dose and the linearly dependent on its dose and the degree of connectivity between degree of connectivity between cancer cells. cancer cells.

E = const. * D * NE = const. * D * N

Efficacy of cancer cell killingEfficacy of cancer cell killing

DKA efficacy Vs. DKA doseDKA efficacy Vs. DKA dose

DKA efficacy Vs. number of cells hit DKA efficacy Vs. number of cells hit

3-Stage Simulation3-Stage Simulation

•Distribution of Distribution of DKADKA

•Cancer detectionCancer detection

•Cytotoxin Cytotoxin propagationpropagation