Molecular Pharmaceutics最新文献

{"title":"","authors":"Samiksha Dewangan, Nidhi Singh, Omkar Kailas Gaikwad, Rudra Chakravarti, Priyanka Das, Dipanjan Ghosh, Sreya Gupta* and Pallab Datta*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":"22 8","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.molpharmaceut.5c00684","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Shashikant Ray, Sarah Jacques, Utibeabasi Ettah, Shaodong Dai, Hanmant K. Gaikwad, Robert I. Scheinman, Krishna M. G. Mallela and Dmitri Simberg*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":"22 8","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.molpharmaceut.5c00540","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Else Holmfred*, Page Chamberlain and Stefan Stürup, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":"22 8","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.molpharmaceut.5c00522","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Espen Fritschka,  and , Gabriele Sadowski*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":"22 8","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.molpharmaceut.5c00552","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Magdalena Jurczyk, Ryszard Smolarczyk, Monika Musiał-Kulik, Joanna Ciepła, Sybilla Matuszczak, Tomasz Cichoń, Justyna Czapla, Marcelina Bochenek, Aleksander Foryś, Dorota Wrześniok, Artur Beberok and Katarzyna Jelonek*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":"22 8","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.molpharmaceut.5c00215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"Girisha Sagar, Barnabas Wilson*, Geetha Kannoth Mukundan, Kalpana Divekar and Josephine Leno Jenita, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":"22 8","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.molpharmaceut.5c00277","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Roadmap for Commercial Nanomedicine Development: Integrating Quality by Design Principles with Pharmaceutical Nanotechnology.","authors":"Rahul Maheshwari, Devesh Kapoor, Suryanarayana Polaka, Sankha Bhattacharya, Bhupendra Prajapati","doi":"10.1021/acs.molpharmaceut.5c00056","DOIUrl":"10.1021/acs.molpharmaceut.5c00056","url":null,"abstract":"<p><p>Integrating Quality by Design (QbD) principles into nanomedicine development marks a paradigm shift from traditional empirical approaches to more systematic risk-based strategies. This review explores the application of QbD in pharmaceutical nanotechnology, focusing on nanoliposomes as a drug and gene delivery model. We examine various QbD models, including factorial, Plackett-Burman, Box-Behnken, and Taguchi experimental designs, alongside response optimization methods such as artificial neural networks (ANNs), mathematical optimization, and overlay plots. A comparison of QbD versus conventional optimization techniques highlights the potential of QbD to improve process efficiency, reduce variability, and enhance product quality. Case studies demonstrate the practical application of QbD in developing nanoliposomal formulations for treating complex diseases such as diabetes, cardiovascular diseases, rheumatoid arthritis, and CNS disorders. Furthermore, we discuss the regulatory and industrial considerations for commercializing nanoliposomal-based therapies, emphasizing FDA guidelines and the challenges associated with scaling up nanomedicine production. Different from available reviews in the field, this review uniquely integrates diverse QbD models with nanoliposome development, offering practical insights. Also, we aimed to bridge laboratory research with industrial scale-up and regulatory requirements. Overall, the present review critically contrasts QbD with conventional methods, using real case studies to highlight its superiority in ensuring product quality, consistency, and efficiency.</p>","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":" ","pages":"4337-4372"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the Effects of Charge Mutations on the Second Osmotic Virial Coefficient for Therapeutic Antibodies via Coarse-Grained Molecular Simulations and Deep Learning Methods.","authors":"Hassan Shahfar, Christopher J Roberts","doi":"10.1021/acs.molpharmaceut.5c00673","DOIUrl":"10.1021/acs.molpharmaceut.5c00673","url":null,"abstract":"<p><p>The impact of various charge mutations on the second osmotic virial coefficient was examined for three model therapeutic monoclonal antibodies (MAbs) at representative formulation pH values by using coarse-grained (CG) molecular modeling. The wild-type of each mAb was characterized experimentally in previous work, showing a range of behaviors spanning from weak protein self-interactions to strong electrostatically driven attractions or repulsions as a function of pH at low ionic strength. The performance and accuracy of the underlying CG model in identifying key residues that contribute strongly to electrostatically driven self-interactions were validated experimentally in prior work with a relatively small number of candidate mutations. The present work focused on computationally exploring a large number of potential mutations (∼10²-10⁵) for each mAb as a case study for an algorithm that could provide a means to assess how altering surface charge distributions affects protein self-interactions quantified in terms of the second osmotic virial coefficient. The results for a set exhaustive or near-exhaustive range of single-, double-, and triple-mutations indicate that simple design rules such as changing the total net charge or trying to identify \"charge patches\" are not robust for providing predictable improvements in protein self-interactions based on electrostatic interactions, and the approach here can provide an efficient way to make predictions based on physics-based force fields. The molecular simulations were also used as a data generator for a deep neural network and explored an extensive number (∼10⁴-10⁶) of mutations for identifying sequences that improve protein self-interactions. Cross-validation of the output of MLP (multilayer perceptron) with the molecular simulations demonstrated high computational efficiency and prediction accuracy, highlighting its utility as an effective tool for accelerating candidate selection in therapeutics design.</p>","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":" ","pages":"5021-5036"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent Advances in mRNA-LNP Delivery Systems for Extrahepatic Organs: A Review.","authors":"Ying Bai, Li Cui, Tianshu Liu, Zhen Wang, Haiyan Cao, Shukun He, Jiani Qiu, Yingxin Li, Yilan Zhou, Jiawei Shi, Jing Wang","doi":"10.1021/acs.molpharmaceut.5c00385","DOIUrl":"10.1021/acs.molpharmaceut.5c00385","url":null,"abstract":"<p><p>Lipid nanoparticles (LNPs) as gene delivery vectors have revolutionized the therapeutic paradigm in mRNA therapy. The pH-dependent lipid components can prevent endosomal retention of mRNA and promote the cytoplasmic translation of therapeutic proteins. However, current technologies still face two core challenges: the nonspecific liver accumulation rate of 30-90% after systemic administration, which is an organ targeting issue, and the inefficient cytoplasmic delivery with only 1-4% of nucleic acids escaping from endosomes. These problems severely limit their application in the treatment of extrahepatic diseases. This review systematically elaborates on the molecular composition and structure-function relationship of LNPs and explores the causes of their extrahepatic delivery obstacles. At the same time, we propose innovative strategies to enhance organ selectivity and endosomal escape efficiency. Additionally, through existing preclinical studies, key bottlenecks such as immune response control and quality control in large-scale production for the clinical translation of current technologies are revealed, providing a multidisciplinary theoretical framework for the development of the next generation of intelligent LNPs.</p>","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":" ","pages":"4474-4493"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drug Solubility in Human Colonic Fluids and Comparison to Small Intestinal and Simulated Fluids.","authors":"Sebastian Steigert, Joachim Brouwers, Tim Vanuytsel, Anders Borde, Eva M Karlsson, Astrid Olivefors, Christer Tannergren, Patrick Augustijns","doi":"10.1021/acs.molpharmaceut.5c00500","DOIUrl":"10.1021/acs.molpharmaceut.5c00500","url":null,"abstract":"<p><p>Colonic drug absorption is a prerequisite for a drug's suitability for colon-targeted and extended-release formulations. Since drug solubility is a key factor for uptake in the gastrointestinal tract, reliably estimating solubility in the human colon is essential for determining the feasibility of such formulation approaches. To date, our understanding of colonic drug solubility, how it compares to the proximal small intestine, and how it is linked to luminal fluid composition is limited by the scarcity of reference data available. Therefore, this study aimed to measure and compare the apparent solubility of eight drugs with varying physicochemical properties (apixaban, danoprevir, dexloxiglumide, febuxostat, fenofibrate, rofleponide, ticagrelor and tofacitinib) in pooled aspirates from the proximal human colon and small intestine, along with simulated media and buffers commonly used in solubility assessment. Additionally, the composition of the pooled luminal fluids was characterized. Whereas solubility in colonic and small intestinal fluids was comparable for most drugs, the small intestine's solubilizing capacity clearly exceeded that of the colon for the lipophilic drugs fenofibrate and ticagrelor. Extensive degradation of danoprevir was observed in both luminal fluids. Prediction of small intestinal solubility of the lipophilic compounds fenofibrate and ticagrelor was improved in fasted state simulated intestinal fluid compared to blank buffer, although the solubilizing capacity of the human fluids was only captured partially. Fasted state simulated colonic fluid solely improved the colonic solubility prediction of fenofibrate, while the prediction of ticagrelor remained outside the 2-fold prediction error threshold. Solubilities of all other drugs were predicted reasonably well in blank buffers and simulated media. The results generated in this study may serve as reference data for the validation of improved in vitro and in silico tools for colonic drug solubility prediction.</p>","PeriodicalId":52,"journal":{"name":"Molecular Pharmaceutics","volume":" ","pages":"4855-4864"},"PeriodicalIF":4.5,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}