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MICA: Psoriasis Stratification to Optimise Relevant Therapy (PSORT)

Funder: UK Research and InnovationProject code: MR/L011808/1
Funded under: MRC Funder Contribution: 5,054,540 GBP

MICA: Psoriasis Stratification to Optimise Relevant Therapy (PSORT)

Description

Psoriasis is a common, chronic, potentially disfiguring disease that affects more than 1 million people in the UK. It can cause considerable psychological and social disability. In the past 10 years there has been a dramatic improvement in clinical outcomes for patients with severe psoriasis due to the introduction of a new class of injectable drugs called biologics. These work by targeting specific parts of the immune system which are important in causing psoriasis. However, these drugs are very expensive (estimated annual cost is £10,000) and it remains the case that a significant number of patients fail to respond adequately. If we could predict which patients will do well with a particular biologic drug then we could devise new treatment plans that would be personalised for each patient rather than the current system of "trial and error" prescribing. This would be of added benefit to society as a whole since it could result in significant cost savings to the NHS and aid the pharmaceutical industry in development of new drugs. The programme of research in the Psoriasis Stratification to Optimise Relevant Therapy (PSORT) consortium aims to use existing knowledge about psoriasis, both clinical and scientific, our unparalleled patient base coupled to involvement of patient organisations and state-of -the-art investigative tools to develop tests that we can use in the clinic to help direct personalised treatments. Specific questions we will ask are: i) do levels of a drug in the blood and a patient's immune response to that drug effect outcome; ii) are there specific changes in the skin and blood that predict which drug is likely to be more useful in a particular patient; iii) is there variation in a patient's genetic make-up, linked to psoriasis and how drugs work, that may predict response to treatment; and iv) does bringing all the information collected in i-iii above, though computer based data analysis, have more power to predict response to treatment? Successfully achieving such a goal requires a number of important criteria to be met. Perhaps most importantly we need consent from large numbers of patients to enter studies and provide samples of blood and skin. From the start of the study, we have engaged with the Psoriasis Association (patient organisation) to ensure the study met with their approval. As a consequence of patient engagement, in the UK we have arguably the world's leading safety registry for patients receiving biologic drugs for psoriasis. During the lifetime of our proposal, it will have accumulated comprehensive information on 7,000 patients including responses (good and bad) to biologics. The PSORT consortium includes representatives from 4 of the largest psoriasis clinics in the UK. These will provide the source for patient recruitment. The experiments will take advantage of several factors. First, in contrast to many other chronic diseases, change in psoriasis severity is simple and accurate to determine after starting therapy. Second, target organ tissue (i.e. skin) can be sampled in a minimally invasive way by skin biopsy (patient feedback tells us that this is acceptable to them). Third, internationally competitive expertise exists across the consortium between investigators and collaborators in all of the scientific disciplines required to successfully deliver the programme. Fourth, appropriate research infrastructure exist at each of the three main centres namely Manchester, Newcastle and London. This includes the registry itself (Manchester) and NHS funded facilities (Newcastle and London). Finally, we have developed an extensive network of pharmaceutical company partners who bring specific expertise and resources to the programme. Not only will this help in achieving the short term goals but it will also provide the necessary platform for translating the outcomes into clinically useful tests.

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