ABCs of LNPs - Advanced Biophysical Characterisation of lipid nanoparticles for mRNA therapeutics

LNPs的高级生物物理表征（ABC）是Nanovation UK，STFC和NML之间的合作项目，旨在开发脂质纳米药物，为肝病创造一种具有成本效益和可获得的治疗方法。目前，肝脏疾病的唯一治愈性治疗是移植。减少进展为终末期肝硬化和肝癌的患者数量将对患者产生重大影响。使用脂质纳米颗粒（LNP）作为抗Covid-19 mRNA疫苗的递送载体，已经强调表明这些系统a）在人类中安全有效，B）可以以前所未有的速度开发，c）可以大规模生产，以及d）可以低成本（约100美元）生产。15英镑一剂）。基于LNP-mRNA的疗法已被证明可逆转肝纤维化，但由于LNP-mRNA递送至肝脏的效率低，需要重复的高剂量，这导致显著的不良毒性。因此，需要改进的LNP递送系统。推进LNP技术的一个主要突出挑战是缺乏对LNP结构如何影响其作为纳米药物的性能的理解。这意味着大多数发现程序主要依赖于对LNP的大型文库的经验筛选。在Nanovation，我们有一个新的脂质和LNP组合物库，以及LNP优化的基本设计，制造和测试周期。我们的LNP子集符合我们的评估质量标准，但表现不如预期。我们怀疑这是由于颗粒结构的影响，但量化这一点的能力有限。对我们最高性能LNP和低性能LNP结构之间的结构相似性/差异性进行科学理解是开发最大化LNP产品性能的方法的关键。本项目将应对这些挑战。

Advanced Biophysical Characterisation (ABCs) of LNPs is a collaborative project between Nanovation UK, STFC and NML to characterise lipid nanomedicines to create a cost-effective and accessible treatment for liver disease.?Currently, the only curative treatment for liver disease is transplantation. Reducing the number of patients progressing to end-stage liver cirrhosis and liver cancer will have a significant impact for patients.The use of lipid nanoparticles (LNPs) as delivery vehicle of the mRNA vaccines against Covid-19, has emphatically shown these systems a) are safe and effective in humans, b) can be developed at unprecedented speed, c) can be manufactured at scale and d) can be produced at low cost (approx. £15 a dose). LNP-mRNA based therapies have been proven to reverse liver fibrosis but, due to inefficient LNP-mRNA delivery to the liver, required repeated, high dosing which resulting in significant and adverse toxicity. Therefore improved LNP delivery systems are required.A major outstanding challenge in advancing LNP technologies is a lack of understanding of how LNP structure impacts their performance as nanomedicines. This means most discovery programs rely on primarily empirical screening of large libraries of LNPs. At Nanovation, we have a library of novel lipids and LNP compositions and a basic design, make and test cycle for LNP optimisation. Subsets of our LNPs fulfil our assessment quality criteria but do not perform as expected. We suspect this is due to the influence of particle structure but have a limited ability to quantify this. Generating scientific understanding of the structural similarities / differences between the structure of our highest performing LNPs and low performing LNPs is key to developing ways to maximise the performance of our LNP products. This project will address these challenges.