Case Studies

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Dredged Material Disposal Capping Thickness

The objective was to determine depth of capping material on a contaminated mud dumping ground. Estimates were obtained using automated image analysis of sub-bottom sonar images. Estimates were ground truthed using alternative modalities.

Genomic Ancestry Analyses

The objective was to provide consumer-level personalised information about ancestry and paeleogenomics, using mitochondrial and Y chromosome SNP data. Corresponding maternal and paternal history were then displayed in an online application in the form of interactive maps and text descriptions.

Ore Trains -- Discrete Event System Modelling

The objective was to maximise throughput in an ore train and tipper system through discrete event simulation modelling under different management scenarios. The project involved data analysis, and development of a simulation model. The model was used to plan and schedule investment.

Fairy Penguins Monitoring

The objective was to develop a framework for monitoring the health and condition of a colony of fairy penguins. The framework was implemented as part of the environmental monitoring programme for a major infrastructure development. The analysis was automated as a series of R scripts which are run on a regular basis as part of routine monitoring.

Genomics using the Cloud

The objective was to develop analysis and visualisation tools for deploying large scale genomic data-mining in a cloud-based distributed computing environment. Both backend offline analysis and online interactive visualisation, tabulation and search functionality have been provided for a genomics research company to support augmented pharmaceutical trials.

Optimisation of an Application-Specific Computer System

The objective was to optimise the design of multiprocessor distributed high performance computer systems. The project involved development of a system to perform optimisations, delivering the best balance across cost, performance and energy targets. The approach used involved evolutionary optimisation to search large solution spaces.

Image Analysis For Automated Histopathology

The objective was to recognise pathologies from histopathology preparations. The solution was based on a powerful combination of mathematical morphology and machine learning. The solution was implemented to proof of concept stage, and specifications for device standard product were developed. The client undertook final device standard engineering.

Fish Stocks

The objective was to review the monitoring program for and evaluate captured data for fish stock levels as assessed by an annual trawl survey. The objective was to assess the impact of dredging upon local fish stocks, and to develop decision criteria to identify possible impacts on fish species. A linked project involved development of an analysis framework for the analysis of recreational fishery data, taking account of angler effort, experience and seasonality.

Dredging Water Quality

The objective was to develop a framework for decision making about remedial actions for turbidity arising from the plume associated with dredging a shipping channel. The project involved integration of multiple lines of evidence and multiple data sets, and relating these information sources to environmental management objectives. The framework was also used to define a formal process for cessation of monitoring when turbidity levels had returned to background, after the cessation of dredging.

Air Quality Impacts of Metal Refining

The objective was to measure the impact of refinery operations on air quality in adjacent communities. Large and complex data sets from nearby monitoring stations were used to assess air quality, and to identify the determinants of air quality (both operational and meteorological). Sophisticated models of wind effects were used to identify the major foci of emissions. It was demonstrated that even under extreme circumstances, the air quality was well within environmental health guidelines.

Diagnostic -- Hosted Applications

The objective was to develop and implement a server-based multi-marker diagnostic for a specific condition. A pre-authorised clinical laboratory sends marker information to the server, and receives a diagnosis based on the measured variables provided. A complete report of the diagnosis and risk assessment is provided in PDF form. Additionally, an online administration interface is provided for control of user, role and access privileges. The system is engineered to medical device standards.

Expert Witness Evaluation of Sources of Contamination

The objective was to identify sources of contamination in a medicinal product, by a combination of mathematical modelling, statistical analysis and use of nuclear magnetic resonance data. We were able to demonstrate that materials in a defendant's premises were not responsible for contamination of a pharmaceutical product. The work involved a combination of advanced statistical analysis, modern analytical chemistry, and an ability to communicate clearly but authoritatively. The court accepted the evidence.

Waste Management Risk Assessment

The objective was to estimate the probability of contaminating local apiaries with American Foul Brood disease, from a proposed new waste management facility. The project required a review of the environmental and behavioural factors affecting contamination with Foul Brood, and quantitative modelling of the probability of transmission based on these factors. Probability was expressed as the mean time between infections. The outcome was an understanding of the risks of contamination, leading to the development of new mitigation strategies.

Ovarian Cancer -- Diagnostic Device

The objective was to development and validate a multi-biomarker signature (essentially a statistical description of the relationships between the markers and the disease status expressed as a probability) for the diagnosis of ovarian cancer. The new diagnostic signature outperforms current diagnostics in terms of sensitivity and specificity. This external data review and analysis was a key factor in the client's ability to licence the product. The diagnostic has been delivered internationally, and further large scale trials are under way.

Sepsis Diagnostic

The objective was to develop a blood-based diagnostic for sepsis, using gene expression markers. The requirement was to discover and optimise a marker panel that would distinguish between systemic inflammatory response syndrome without bacterial involvement, and full bacterial sepsis. The project involved data-mining from large databases of gene expression data, and validation of diagnostic performance using advanced statistical methods. The client's diagnostic is currently being implemented in a major hospital, and negotiations with major international diagnostic companies are in progress.

Validation of a New Wheat Quality Assessment

The objective was to demonstrate the accuracy and precision of a novel analytical technique for various indices of wheat quality. The project involved experimental design and protocol development for studies to support marketing of a new technique to measure the quality of wheat. The new technique offers substantial cost, accuracy and precision benefits over current methods, but it was necessary to develop a formal process to demonstrate this. Objective verification of test performance was a crucial business need, and had to be completed in an environment of potentially hostile review.

Immuno-Histochemistry -- Automated Workflows

The objective was to provide a secure platform for management of data, and common analysis workflows for a biotech company developing a new proteomics platform. The business objectives were to allow rapid but reliable analysis of complex multidimensional data by non-specialists. The project delivered an online data-storage and analysis system for customer-specific laboratory data. An administration interface was provided to control user, role and access privileges. Individual users can select from amongst the uploaded data sets and perform a variety of analyses with publication-ready graphs and tabulations output.

Large Scale Clinical Simulation For Programme Risk Assessment

The objective was to evaluate a range of Phase III respiratory trial design options under a range of variability, drop out and effect scenarios. Emphron's ability to parallelise computations in our super computer environment allowed the client to consider a much more comprehensive set of options and scenarios. As the client reviewed results, new options and questions were generated. The parallel application of 8,000 compute cores allowed these questions to be answered overnight. The client made substantial improvements to the programme design on the basis of these results, which were instrumental in a significantly increased capital raise.

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