Sustained Release Formulations of Therapeutic Antibodies

这项申请寻求开发一种长效的抗体仓库配方，使用反向闪光 Optimeos生命科学公司正在商业化的纳米沉淀(IFNP)平台。微粒库 几十年来，各种配方都经过了测试，以提供持续释放。传统的治疗方法是 被包裹在不溶于水的聚合物基质中，随着聚合物的降解而释放。传统的 微球结构有很大的局限性，包括治疗含量低和治疗稳定性差。 因此，目前还没有上市的蛋白质微粒储存库。相比之下，微粒 由Optimeos生产的是通过将纳米颗粒聚集在一起来产生机械强度高的 纳米复合微粒。这些纳米颗粒是由iFNP生产的，这是一种可扩展的连续工艺，用于 包覆水溶化合物。纳米颗粒结构允许更高的负载并形成 保护壳，将限制抗体在延长释放期间的不稳定性。 IFNP技术已被广泛研究用于多肽递送，并证明了其治疗效果。 仓库中的内容比现有方法和受控释放的当前可能含量高出10倍 个人资料从3周到3个月以上不等。拟议的研究将延长iFNP持续的 从多肽到蛋白质的释放技术。三种肿瘤坏死因子α抗体形式将 进行评估，以确定技术的适用范围。这些结构-VHH单一结构域 纳米抗体、Fab片段和免疫球蛋白抗体--正变得越来越复杂。这项拟议的研究将使 通过解决关键的过程风险--化学风险，将iFNP技术转化为更复杂的生物制剂 和包膜抗体在加工和释放过程中的结构不稳定性--通过三个目标： 1)目标1：鉴定使用iFNP生产的具有20-40wt%功能性VHH的VHH微粒制剂。 2)目标2：在1个月和3个月内从微粒中产生活性VHH的持续释放，每周 稳定性评估表明，释放的VHH 90%是原生的和正常的。 3)目标3：将目标1和目标2的研究成果应用于Fab和Ig G抗体的包埋，生产 持续释放超过1个月和3个月，释放的抗体&gt；90%是天然的和功能性的。 将使用VHH抗体作为初始模型来评估iFNP的性能，因为它们很快 注射后清除。配方设计将建立在使用iFNP的多肽递送规则的基础上 这一过程是在普林斯顿大学和Optime os之间的STTR赠款下制作的。密钥稳定性 测量(ELISA法、SEC、质谱仪)将通过与积分分子公司的合作进行。 这些结果将推广到其他抗体，使我们能够扩展到其他疾病的治疗。 迅速地。至关重要的是，持续输送抗体以外的蛋白质可以使疫苗或酶 使用拟议工作确定的相同配方原则的替换申请。

This application seeks to develop a long-acting depot formulation for antibodies, using the inverse Flash NanoPrecipitation (iFNP) platform being commercialized by Optimeos Life Sciences. Microparticle depot formulations have been tested for decades to provide sustained release. The therapeutic is traditionally entrapped in a water-insoluble polymer matrix, with release proceeding as the polymer degrades. The traditional microparticle structure has significant limitations, including low therapeutic content and poor therapeutic stability. Consequently, there are currently no marketed microparticle depots for proteins. By contrast, the microparticles produced by Optimeos are formed by aggregating nanoparticles together to produce mechanically strong nanocomposite microparticles. The nanoparticles are produced by iFNP, a scalable and continuous process for encapsulating water-soluble compounds. The nanoparticle structure permits much higher loadings and forms a protective shell that will limit antibody instability during extended release. The iFNP technology has been extensively studied for peptide delivery, with demonstrated therapeutic weight content in the depot up to 10 times higher than currently possible with existing methods, and controlled release profiles ranging from 3 weeks to more than 3 months. The proposed research will extend the iFNP sustained release technology from peptides to proteins. Three Tumor Necrosis Factor alpha (TNFα) antibody formats will be evaluated to determine the scope of applicability of the technology. These constructs – a VHH single domain nanobody, a Fab fragment, and an IgG antibody – are of increasing complexity. This proposed study will enable the translation of the iFNP technology to more complex biologics by addressing the key process risks – chemical and structural instability of the encapsulated antibody during processing and release – through three aims: 1) Aim 1: Identify VHH microparticle formulations, produced using iFNP, with 20-40 wt% functional VHH. 2) Aim 2: Generate sustained release of active VHH over 1 and 3 months from microparticles, with weekly stability assessments indicating released VHH is > 90% native and functional. 3) Aim 3: Apply Aim 1 and Aim 2 findings to the encapsulation of Fab and IgG antibodies, producing sustained release over 1 and 3 months with released antibody > 90% native and functional. The performance of iFNP will be evaluated using VHH antibodies as an initial model because they are rapidly cleared following injection. Formulation design will build on the rules derived for peptide delivery using the iFNP process, produced under an STTR grant between Princeton University and Optimeos. Key stability measurements (ELISA, SEC, mass spectrometry) will be conducted via a collaboration with Integral Molecular. These results will be generalizable to other antibodies, allowing us to expand into the treatment of other diseases rapidly. Crucially, sustained delivery of proteins other than antibodies could enable vaccine or enzyme replacement applications using the same formulation principles identified by the proposed work.