固相萃取技术及其在体内药物分析中的应用

目的了解固相萃取技术的新进展及其在体内药物分析中的应用情况。方法介绍固相萃取基本原理、填料种类和自动化操作等,并对该技术在体内药物分析中的应用进行综述。结果与结论固相萃取技术萃取回收率高、易于自动化,能有效去处样品中的杂质,适于体内药物分析中生物样品的预处理。     

重组蛋白药物的研究进展

近二十几年来蛋白质药物发展迅速。目前有近百种重组蛋白药物上市,几千种处于研发状态。欧美在蛋白质药物研究上整体实力强,在全球有较大的市场。我国重组蛋白药物的研发起步较晚,但发展较快。本文分析了国际和国内蛋白质药物的研发趋势,针对我国基因重组蛋白药物领域现状及存在的问题提出了相应的建议,对国内蛋白质药物研究具有一定的参考价值。     

Intact protein analysis in the biopharmaceutical field

In recent years, a growing number of biopharmaceutical proteins have been produced and are already available, or will be soon available, in the market. These molecules are more complex to analyze than conventional low molecular weight drugs, and thus need powerful analytical approaches for the entire development and delivery process. This review summarizes the analytical techniques available for intact protein determination and the main development steps in which they are applicable. A strong emphasis has been put on separation techniques, liquid chromatography and electrophoretic techniques, but mass spectrometry and spectroscopic approaches are also mentioned. Overall, we highlight how several analytical strategies are necessary to obtain global information.     

How much do the public sector and the private sector contribute to biopharmaceutical R&D?

When examining the prices of new medicines, the question of how much the private and public sectors have contributed to their R&D is often raised. Contributions can be assessed in terms of the investment, authorship of publications, marketing authorizations and intellectual property rights associated with biopharmaceutical R&D. This review of the empirical evidence underlines the complementary and interwoven nature of the private and public sectors in supporting biopharmaceutical R&D. Both sectors invest in and contribute to biopharmaceutical R&D, with the public sector predominantly focusing on basic research and the private sector mainly targeting medicine discovery and development. Public-sector investment generates additional private-sector investment.     

Enhanced normograms and pregnancy outcome analysis in nonhuman primate developmental toxicity studies

The incidence of spontaneous pregnancy/infant losses is highly variable in long-tailed macaques (cynomolgus monkey), making it potentially difficult to ascertain test item-related effects in developmental toxicity studies. Therefore, pregnancy normograms had been developed by Jarvis et al. [1] to aid in the distinction of normal (e.g. test facility background) versus non-normal pregnancy outcomes. These normograms were mostly derived from embryo-fetal development studies and from PPND studies with a postnatal phase limited to seven days. However, the enhanced pre- and postnatal developmental (ePPND) study paradigm has essentially replaced these former study types. This work aims at providing enhanced normograms (e-normograms) in the context of regulatory ePPND studies. Survival functions for the prenatal phase (286 control pregnancies) and the postnatal phase (222 live infants) were estimated using the Kaplan-Meier estimator. Normograms were generated from survival curves and pseudo-study simulations. Data were available from two test facilities with comparable EU-compliant animal husbandry. Pregnancy duration/outcome as well as survival functions did not differ significantly between test facilities indicating that this husbandry system yields comparable developmental observations across different test facilities, at least in this NHP species. These novel e-normograms were developed for pregnant long-tailed macaques and provide an extended postnatal period up to three months, a new concept of separate normograms for the prenatal and the postnatal period, specific information on the perinatal phase events, a prediction of expected number of live infants for group size management, and the option to evaluate effects on pregnancy duration through distinction of live births and infant losses.     

Verification and Validation of Computational Models Used in Biopharmaceutical Manufacturing: Potential Application of the ASME Verification and Validation 40 Standard and FDA Proposed AI/ML Model Life Cycle Management Framework

A wide variety of computational models covering statistical, mechanistic, and machine learning (locked and adaptive) methods are explored for use in biopharmaceutical manufacturing. Limited discussion exists on how to establish the credibility of a computational model for application in biopharmaceutical manufacturing. In this work, we tried to use the American Society of Mechanical Engineers (ASME) Verification and Validation 40 (V&V 40) standard and FDA proposed AI/ML model life cycle management framework for Software as a Medical Device (SaMD) in biopharmaceutical manufacturing use cases, by applying to a set of curated hypothetical examples. We discussed the need for standardized frameworks to facilitate consistent decision making to enable efficient adoption of computational models in biopharmaceutical manufacturing and alignment of existing good practices with existing frameworks. In the study of our examples, we anticipate existing frameworks like V&V 40 can be adopted.     

武汉生物医药产业重点技术需求分析与建议

摘 要 目的：为武汉生物医药产业发展提供技术服务平台建设等建议。方法: 通过文献检索、实地考察、问卷调查、专家咨询等方法,了解并分析武汉生物医药产业存在的问题及重点技术需求。结果与结论:提出了当前武汉生物医药产业重点技术需求和促进医药产业健康发展的建议。     

Evaluation of the use of partition coefficients and molecular surface properties as predictors of drug absorption: a provisional biopharmaceutical classification of the list of national essential medicines of Pakistan

Background and the purpose of the study

Partition coefficients (log D and log P) and molecular surface area (PSA) are potential predictors of the intestinal permeability of drugs. The aim of this investigation was to evaluate and compare these intestinal permeability indicators.

Methods

Aqueous solubility data were obtained from literature or calculated using ACD/Labs and ALOGPS. Permeability data were predicted based on log P, log D at pH 6.0 (log D_6.0), and PSA.

Results

Metoprolol''s log P, log D_6.0, and a PSA of <65 Å correctly predicted 55.9%, 50.8% and 54.2% of permeability classes, respectively. Labetalol''s log P, log D_6.0 and PSA correctly predicted 54.2%, 64.4% and 61% of permeability classes, respectively. Log D_6.0 correlated well (81%) with Caco-2 permeability (P_app). Of the list of national essential medicines, 135 orally administered drugs were classified into biopharmaceutical classification system (BCS). Of these, 57 (42.2%), 28 (20.7%), 44 (32.6%), and 6 (4.4%) were class I, II, III and IV respectively.

Conclusion

Log D_6.0 showed better prediction capability than log P. Metoprolol as permeability internal standard was more conservative than labetalol.     

Triple helices’ perspectives on the availability of human and financial capital for biopharmaceutical innovation in select Central European ecosystems

Here, we examine the perspective of triple helix actors (i.e., those in academia, government, and industry) related to the availability of human and financial capital in select Central European ecosystems. The actors perceive the lack of venture capital to be the top reason hindering the development of the biopharmaceutical industry in their region. The human capital area with the greatest shortage was the computational sciences/informatics. This was followed by clinical trials and regulatory affairs. The present paper should be of interest to scholars and those engaged in the biopharmaceutical industry and regional development.