The processing power ofgrid
computingwill be used byUniversity College London
(UCL)this year to develop treatments that
could be more effective in the treatment of people withHIV
.
More than 33 million people live with HIV worldwide and 2.5
million people became infected with the virus in 2007. More than
two million people died of an AIDS-related illnesses last year,
according to the Joint United
Nations Programme on HIV/AIDS.
The problem with treating the disease is that patients can build
resistance to the drugs they are given. The HIV virus can mutate
and change in different patients and this can make issuing the
right combination of drugs difficult.
In response, staff at UCL will be using the combined
supercomputing power of the UK and US 'national grids' to simulate
a patient's biological responses to drugs. Doctors currently work
by prescribing a course of drugs and then test whether these are
working. One of the goals of the project is for such 'trial and
error' methods to eventually be replaced by patient-specific
treatments tailored to a person's unique
genotype.
"To be able to tailor medical treatment to a person and their
ailments, instead of giving them some average course of treatment -
we're only going to get to that level of patient specificity if we
use computational science and high performance computing, of that
there can be no doubt," said
Peter Coveney
of the UCL Department of Chemistry.
The study will involve a sequence of simulation steps, performed
across several supercomputers on the UK's
National
Grid Service and the US TeraGrid, using computational power
roughly equivalent to that needed to perform a long-range weather
forecast.
"The method is an early example of what is called the
Virtual
Physiological Human (VPH). The idea behind the VPH is to link
networks of computers across the world to simulate the internal
workings of the human body," he said.
The VPH - mainly a research initiative at present - allows
scientists to simulate the effects of a drug and see what is
happening at the organ, tissue, cell and molecular level.
"This study represents a first step towards the ultimate goal of
'on-demand' medical computing, where doctors could one day 'borrow'
supercomputing time from the national grid to make critical
decisions on life-saving treatments," said Professor Coveney
Data will be processed using four national grid service
computers. Each computer facility comprises 64 dual CPU Intel
3.06GHz nodes and 4TB storage, while each data facility is
configured with 20 dual CPU Intel 3.06GHz nodes and 18TB Fibre SAN
storage, giving a total 44TB storage across all nodes available to
users of the NGS.
JANET Lightpath, the high speed
academic network, will provide end-to-end network capacity. The
network can provide speeds within a range of a few tens of Mbit/s
to a full 10Gbit/s, according to user requirements. Lightpaths can
also be extended internationally by connection via GÉANT, the
multi-gigabit pan-European education network, to reach other
national research and education networks.
Lightpath will also have dynamic provisioning, where a user (or
even an application), given suitable authorisation, can request a
link to be established on demand and then released once the
application has finished with it.
The university will also use the
Texas
Advanced Computing Centre Lonestar supercomputer, at the
University of Texas. The supercomputer is a
Dell Linux cluster, which comprises Dell PowerEdge 1955 blade
servers and possess a peak performance of more than 55
teraflops.
"We have some difficult questions ahead of us, such as how much
of our computing resources could be devoted to helping patients and
at what price. At present, such simulations - requiring a
substantial amount of computing power - might prove costly for the
National Health Service, but technological advances and those
in the economics of computing would bring costs down."
For the moment, Professor Coveney's group is continuing to look
at all the protease inhibitors in a similar way. The VPH initiative
will soon be under way with E72m of initial funding from the
EU.
Coveney hopes it will boost collaboration between clinicians and
scientists to explore the scope for patient-specific medical
treatments based on modern modelling and simulation methods, and
ultimately save lives.