Recent food crises show the importance of having effective means of food
identification and analysis. Many tests have been developed to monitor
food, but analysis of the resulting data is highly problematic.
Mathematical techniques developed by Dr Julie Wilson at the University of
York allow complex mixtures to be analysed and interpreted. They have
enabled the Food and Environment Research Agency (Fera) to maximize the
information available from food testing, resulting in improved food safety
and authentication worldwide, and underpin the analytical testing services
delivered by Fera. The techniques have been incorporated into a bespoke
Matlab based solution which is now routinely used by Fera's Chemical
and Biochemical Profiling section in the specialist testing services
which Fera provides across the food storage and retail, agri-environment
and veterinary sectors to over 7,500 customers in over 100 countries. In
addition, the techniques are used in Fera's research, supporting around
£8M worth of work to develop a wide range of global applications including
the determination of disease-related biomarkers, contaminant detection,
food traceability and the development of drought- and disease-resistant
Impact: BEAST software has widespread applications with impacts on
public health policy, service
provision and awareness, and in other contexts such as commercial disputes
and criminal cases.
Beneficiaries: Public agencies such as health bodies and criminal
courts; ultimately, global and
local populations subject to infectious disease epidemic and pandemic
outbreaks in which BEAST
is used to inform the response.
Significance and Reach: BEAST is critical software that has been
used to understand the spread
of and to inform the response to global pandemics such as H1N1 swine-flu.
It is also used to
determine disease origin and transmission issues in specific situations
(e.g. in criminal cases). The
reach of this software is therefore both global and local.
Attribution: Rambaut (UoE) co-led the phylogenetic research and
developed BEAST with
Drummond (Auckland, NZ). The subsequent epidemic and pandemic analyses
were variously led
by Rambaut and Pybus (Oxford) and by Ferguson (Imperial College London).
The International HapMap project was a major international research
collaboration to map the structure of common human genetic variation
across populations from Europe, Asia and Africa. Mathematical Scientists
from the University of Oxford played key roles in the development of
statistical methods for the project, along with its overall design and
management of the International HapMap Project.
Companies have used HapMap as the primary resource to design genome-wide
microarrays to make novel discoveries in, for example, pharmacogenetic
studies. The size of this market is estimated at $1.25 billion.
One novel discovery has led to a genetic test that is predictive of
sustained viral suppression in patients treated for chronic hepatitis C.
An estimated 2.7 to 3.9 million people are affected by HCV infection. This
test is sold commercially by the company LabCorp and is a significant
contributor to the company's testing volume. Finally, the project has been
important in widening the public understanding of genetic variation.
In a series of papers published from 1999 on, Aitken (Maxwell Institute)
and collaborators applied Bayesian statistics to develop a methodology for
the quantification of judicial evidence derived from forensic analyses.
They proposed and implemented procedures for (i) determining the optimal
size of samples that should be taken from potentially incriminating
material (such as drugs seized); and (ii) the estimation of likelihood
ratios characterising evidence provided by multivariate hierarchical data
(such as the chemical composition of crime-scene samples). Their
procedures have been recommended in international guideline documents
(including a 2009 publication by the United Nations Office on Drugs and
Crime) and have been routinely used by forensic science laboratories
worldwide since 2008. The research has therefore had an impact on the
administration of justice, leading to a better use of evidence and
accompanying judicial and economic benefits. Examples are given from
laboratories in Australia, Sweden and The Netherlands.