• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Biotechnology Progress >Strategic Biopharmaceutical Portfolio Development: An Analysis of Constraint-Induced Implications
【24h】

Strategic Biopharmaceutical Portfolio Development: An Analysis of Constraint-Induced Implications

机译：战略性生物制药产品组合开发：约束诱导的涵义分析

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Optimizing the structure and development pathway of biopharmaceutical drug portfolios are core concerns to the developer that come with several attached complexities. These include strategic decisions for the choice of drugs, the scheduling of critical activities, and the possible involvement of third parties for development and manufacturing at various stages for each drug. Additional complexities that must be considered include the impact of making such decisions in an uncertain environment. Presented here is the development of a stochastic multi-objective optimization framework designed to address these issues. The framework harnesses the ability of Bayesian networks to characterize the probabilistic structure of superior decisions via machine learning and evolve them to multi-objective optimality. Case studies that entailed three- and five-drug portfolios alongside a range of cash flow constraints were constructed to derive insight from the framework where results demonstrate that a variety of options exist for formulating nondominated strategies in the objective space considered, giving the manufacturer a range of pursuable options. In all cases limitations on cash flow reduce the potential for generating profits for a given probability of success. For the sizes of portfolio considered, results suggest that naively applying strategies optimal for a particular size of portfolio to a portfolio of another size is inappropriate. For the five-drug portfolio the most preferred means for development across the set of optimized strategies is to fully integrate development and commercial activities in-house. For the three-drug portfolio, the preferred means of development involves a mixture of in-house, outsourced, and partnered activities. Also, the size of the portfolio appears to have a larger impact on strategy and the quality of objectives than the magnitude of cash flow constraint.
机译：优化生物制药产品组合的结构和开发路径是开发人员面临的核心问题，它具有一些附加的复杂性。这些包括药物选择的战略决策，关键活动的安排以及每种药物在不同阶段的第三方参与开发和生产的可能。必须考虑的其他复杂性包括在不确定的环境中做出此类决策的影响。这里介绍的是旨在解决这些问题的随机多目标优化框架的开发。该框架利用贝叶斯网络的能力，通过机器学习表征高级决策的概率结构，并将其演化为多目标最优性。构建了涉及三药和五药组合以及一系列现金流约束条件的案例研究，以从框架中获得洞察力，结果表明，存在多种选择，可以在所考虑的目标空间中制定非主导策略，从而为制造商提供了一系列选择可选项。在所有情况下，现金流量的限制都会降低在给定成功概率下产生利润的可能性。对于所考虑的投资组合的大小，结果表明，天真地将针对特定投资组合大小的最优策略应用于另一种规模的投资组合是不合适的。对于五药组合，在一系列优化策略中，最优选的开发方式是将内部开发和商业活动完全整合。对于三药组合，首选的开发方式包括内部，外包和合作活动的混合。同样，与现金流量约束的规模相比，投资组合的规模似乎对战略和目标质量的影响更大。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号