Software toolkits for in silico screening of polymer excipients in drug formulations

用于药物配方中聚合物赋形剂计算机筛选的软件工具包

• 批准号: 2879915
• 金额: --
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2879915
• 关键词: Software; toolkits; silico; screening; polymer

Pharmaceutical formulation is a key step of the drug development process where the active pharmaceutical ingredient (API) is mixed with non-drug components (excipients) which degrade in the body, usually as a function of time or pH, releasing the API in the target tissue.Biocompatible polymers like cellulose derivatives or glycols are common excipients in tablet formulations. Polymer degradation, crystallinity and mechanical properties can be easily tuned by changing their molecular weight or by chemical functionalisation. These features in turn affect product shelf life, drug release time and effective API concentration in the gastrointestinal tract. Copolymers of PEG or PVA are particularly suitable to promote the uptake of poorly soluble drugs. However, their complex semicrystalline morphology varies with subtle changes incomposition and processing conditions, making their performance and API compatibility hard to predict.Selecting polymer excipients for drug formulations is a time-consuming, mostly trial-and-errorprocess. While in silico screening (cheminformatics, machine learning) is routinely employed in small molecule drug discovery, such tools are not readily applicable to polymers. Simulations of excipients are done using 'computational microscope' molecular dynamics (MD) techniques with off-the-shelf parameters, which cannot be tailored to specific excipients. This is due to several factors, namely the lack of automated parameterisation software - an issue Open Force Field, alarge industry backed consortium, is starting to tackle.Accurately describing polymer flexibility is key, as torsional degrees of freedom are directly related to aggregation and crystallinity. Overall, the lack of reliable workflows and tools for polymer screening of functional is an open challenge across the fields of biochemistry, formulation science, materials science.

药物配方是药物开发过程中的关键步骤，其中活性药物成分（API）与非药物成分（赋形剂）混合，这些成分在体内降解，通常作为时间或pH的函数，在靶组织中释放API。生物相容性聚合物如纤维素衍生物或乙二醇是片剂配方中常见的赋形剂。聚合物的降解、结晶度和机械性能可以很容易地通过改变分子量或化学功能化来调节。这些特性反过来又影响产品的保质期、药物释放时间和胃肠道内的有效原料药浓度。PEG或PVA共聚物特别适合促进难溶性药物的吸收。然而，它们复杂的半晶形态随着成分和加工条件的细微变化而变化，使得它们的性能和API兼容性难以预测。为药物配方选择聚合物赋形剂是一个耗时的、主要是反复试验的过程。虽然硅筛选（化学信息学，机器学习）通常用于小分子药物发现，但这些工具并不容易适用于聚合物。赋形剂的模拟使用“计算显微镜”分子动力学（MD）技术进行，具有现成的参数，不能针对特定的赋形剂进行定制。这是由几个因素造成的，首先是缺乏自动化参数化软件——一个由工业界支持的大型财团Open Force Field正开始解决这个问题。准确描述聚合物的柔韧性是关键，因为扭转自由度直接关系到聚合和结晶度。总的来说，缺乏可靠的工作流程和工具来筛选聚合物的功能是生物化学、配方科学、材料科学等领域的一个公开挑战。