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.

药物制剂是药物开发过程的关键步骤，其中活性药物成分（API）与非药物成分（赋形剂）混合，所述非药物成分（赋形剂）通常作为时间或pH的函数在体内降解，从而在靶组织中释放API。生物相容性聚合物如纤维素衍生物或二醇是片剂制剂中常见的赋形剂。聚合物降解、结晶度和机械性能可以通过改变其分子量或化学官能化来轻松调节。这些特征进而影响产品的保质期、药物释放时间和胃肠道中的有效API浓度。PEG或PVA的共聚物特别适合于促进难溶性药物的吸收。然而，它们复杂的半结晶形态会随着组成和加工条件的微妙变化而变化，这使得它们的性能和API相容性难以预测。为药物制剂选择聚合物赋形剂是一个耗时的，主要是试错的过程。虽然计算机筛选（化学信息学、机器学习）通常用于小分子药物发现，但此类工具并不容易适用于聚合物。使用“计算显微镜”分子动力学（MD）技术和现成的参数进行赋形剂的模拟，这些参数不能针对特定的赋形剂进行调整。这是由于几个因素，即缺乏自动化参数化软件-一个大型行业支持的联盟Open Force Field开始解决的问题。准确描述聚合物柔性是关键，因为扭转自由度与聚集和结晶度直接相关。总的来说，缺乏可靠的工作流程和功能性聚合物筛选工具是生物化学、配方科学和材料科学领域的一个公开挑战。