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15 August, 2021 - 00:13 By Tony Quested

Qureight looking for fresh talent ahead of scale-up

Cambridge startup Qureight. which uses cloud-based technology to structure data sets in complex diseases is looking for fresh talent. 

The company’s tools are able to extract airways, blood vessels and tissue from Computed Tomography (CT) scans and quantitatively analyse this data. Qureight is working on the identification of different imaging biomarkers for the assessment of patients with Pulmonary Hypertension (PH).

Co-founder and chief scientific officer,  Dr Alessandro Ruggiero said: “The global drugs market for PH is over £6 billion annually and the amount of money spent on clinical trials is upwards of £100 million for every new drug asset. By using our tools, we can help biopharma save money and provide more accurate biomarkers for trial endpoints.”

The company recently appointed Dr Caroline Austin (VP and Head of Business Development Transactions at AstraZeneca) as its first non-executive director. In addition to her commercial experience, Dr Austin brings a scientific background in respiratory medicine to the company.

As the company expands to work across other complex diseases, it is in parallel processing a funding round to build its team and assets. It achieved pre-seed funding last summer led by CMS Ventures and is currently in advanced negotiations with several institutions to complete the next round of investment. 

Co-founder and CEO Dr Muhunthan Thillai said: “Qureight is on a significant growth curve. Our core platform can now handle complex images and paired data through multiple inputs and we are working on trial data sets from both Europe and North America.

“As we build our imaged based biomarkers, we are looking to expand the team in multiple areas; predominantly in software engineers and machine learning scientists.

“But we also need people to help further our commercial footprint into biopharma and so are announcing a range of roles over the next few months. It doesn’t matter what your background is – we are building a truly diverse company. If you are the best at what you do, then we want to hear from you.” 

The company’s first target was the disease Idiopathic Pulmonary Fibrosis (IPF), a scarring condition of the lungs. IPF causes a build-up of damaged lung tissue over time, which can lead to breathing problems and death.

Prior to 2014 there were no proven treatments for IPF but there are now two licensed drugs with a combined worldwide spend of £2 billion per year. A further 53 drugs are in clinical development, but one problem for biopharma is the use of limited metrics for drug success.

The antiquated use of breathing tests to look for change in disease severity is fraught with inaccuracies, resulting in a need to increase the number of trial patients (and therefore the cost) to identify the best endpoints for drug accuracy.  

By working on imaging and physiological data sets from institutions across the world, Qureight has been structuring complex data to create machine learning algorithms and track progression of the scar tissue in the lungs across multiple time points. 

The first iteration of these models is due to be unveiled at the European Respiratory Society meeting in Madrid next month and will show that IPF disease progression can be tracked using these novel imaging biomarkers. 

The company says this will prove invaluable for both patients and biopharma. In these complex lung diseases, Qureight is currently working with Takeda and Galapagos to quantify disease from current clinical trials.

As the platform grows with increasingly complex data, the goal of using structured data to track disease progression has started to move in other conditions. 

This will allow the company, founded in 2016, to hire new talent to expand both the cloud-based platform and the machine learning tools for disease progression. 

Prospective applicants with an interest in what Qureight is doing can find out more by emailing careers [at] qureight.com.

• PHOTOGRAPH: Qureight co-founder and CEO Dr Muhunthan Thillai

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