Product optimisation of a novel new melanoma therapy using advanced microscopy and biomarkers to enhance the commercialisation of this technology.

黑色素瘤或皮肤癌是男性和女性最常见的第五大癌症，仅在英国每天就有超过6人死于黑色素瘤。在过去的十年里，免疫疗法在治疗这种疾病方面显示出了巨大的前景，但只有50%多的患者对这种治疗有反应。S每名患者的治疗费用高达数千英镑，而且严重不良反应的数量相对较高，因此显然存在对新的替代疗法的临床需求尚未得到满足。KLAS Treateutics为这种癌症提供了一种独特的解决方案，它提供了一种替代疗法，既可以单独使用，也可以与当前的治疗方法结合使用。我们的技术是通过使用一种称为光动力疗法(PDT)的过程来工作的。光被用来激活我们的化合物，称为KLAS-PDT，然后它将原本无害的氧气转化为一种高活性的形式，从而杀死癌细胞。通过刺激人体免疫系统，KLAS-PDT可以与现有的免疫疗法相结合，大大降低成本，改善患者结果。该项目旨在通过生成一个数据包来确定光激活和剂量方案的最佳参数，从而加强这项令人兴奋的新技术的商业化。使这项技术更接近于实现患者的实际利益，同时开发可以继承和翻译的新方法，用于分析我们最终的临床数据。

Melanoma, or skin cancer, is the 5th most common cancer in both men and women and kills more than 6 people each day in the UK alone. In the last decade, immunotherapies have shown great promise in treating this disease, but with just over 50% of patients respond to this treatment. With a price-tag running at 100's of thousands of pounds for treatment per patient and a relatively high number of serious adverse effects, there is a clear unmet clinical need for new alternative treatments.KLAS therapeutics offers a unique solution to this, by providing an alternative therapy for this cancer that can be used both independently and in combination with current treatments. Our technology works by utilising a process known as photodynamic therapy (PDT). Light is used to activate our compound, known as KLAS-PDT, which then converts otherwise harmless oxygen into a hyper reactive form that kills the cancer cells. By stimulating the body's immune system, KLAS-PDT can be combined with existing immunotherapies leading to significantly reduced cost and improved patient outcomes.This project seeks to enhance the commercialisation of this exciting new technology, by generating a data package that will confirm the optimal parameters for light activation and dosing regimen. Rendering the technology closer to achieving actual patient benefit while at the same time developing new methods that can be carried forward and translated for the analysis of our eventual clinical data.