The human brain is complex,
individual even in its mechanics, and has evolved
many barriers to foreign particles. Therefore, moving
a promising molecular therapy from lab to practice
requires a process of understanding the disease
in a individual, getting across the brain barriers,
and directing the therapy to the right place with
sufficient dose. Quantitative transport modeling
is the required foundation for many such advances,
on different time scales, for medical impact. This
talk will describe one application and list many
others. This seeming diversity of aims coheres by
the unity of the mathematics required for modeling
these various phenomena, as well as a remarkable
unity in the imaging methods that are required to
derive the individual-specific parameters that the
models need.
The application detailed
in the talk will be: delivering therapeutics directly
into brain. We set up general equations for the
distribution of variously delivered material. The
structure of these and of their solutions clarifies
the requirements for in-vivo data that are required
to predict this distribution, and for optimal design
of supporting devices and delivery methods. The
physics is friction-dominated continuum mechanics,
kinetic theory, and the connection between diffusion
and random walk. We illustrate the results with
images from animal and human studies.
There are other applications:
improving systemic delivery is an obvious one. Another
is to use a model of the mechanics of brain response
to a tumor to predict cancer cell migration pathways;
and to direct diagnostics and therapeutics to likely
locations of tumor recurrence. Simulating growth
mechanics as well as the deformation of the brain
tissue under pressure will allow new applications
of computational anatomy including structure--function
correlations and comparative anatomy. We can go
beyond designing how to enter the brain. We can
analyze how one may better exclude cells which (for
example) breach the walls in multiple sclerosis;
or expel wastes when (as in Alzheimer's) they fail
to flush through the intercellular spaces. A detailed
model will open the search space for new attacks
on such problems.
Dr. Raghavan is
the president and cofounder of Therataxis, LLC.
Previously, he was vice president for modeling,
analysis and software for Image-guided Neurologics,
and prior to that, a professor in the computer
science and radiology departments at Johns Hopkins
University. He founded the Center for Information-enhanced
Medicine (CieMed) at the National University
of Singapore, devoted to exploring computational
biomedicine based on three-dimensional imaging.
He earned his doctorate
in the physics of magnetism at the University
of Wisconsin and has since contributed to the
development of imaging sensor materials, image
analysis integrating models and data, and biomedical
simulations, including brain physiology and
drug transport. His current research interests
are focused upon the simulation and control
of molecular and cell therapies and on pattern
formation during tissue and organ growth. He
has founded companies in telemedicine, medical
simulation and visualization, and data presentation.
He has 102 publications and fifteen patent filings
to date.
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