Strategic biopharmaceutical portfolio development: An analysis of constraint-induced implications
Strategic biopharmaceutical portfolio development: An analysis of constraint-induced implications
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DOI：
10.1021/bp070410s
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发表时间：
2008-05-01
影响因子：
2.9
通讯作者：
Farid, Suzanne S.
中科院分区：
文献类型：
--
作者：
George, Edmund D.;Farid, Suzanne S.
优化生物制药药物组合的结构和开发途径是开发人员关注的核心问题，同时也伴随着一些复杂性。这些包括药物选择的战略决策，关键活动的安排，以及在每种药物的不同阶段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。这里提出了一个随机多目标优化框架的发展，旨在解决这些问题。该框架利用贝叶斯网络的能力，通过机器学习表征卓越决策的概率结构，并将其进化为多目标最优性。案例研究包括三种和五种药物组合以及一系列现金流约束，以从框架中获得洞察力，结果表明，在考虑的客观空间中，存在多种选择来制定非主导策略，为制造商提供一系列可追求的选择。在所有情况下，对现金流的限制都会降低在给定成功概率下产生利润的潜力。对于所考虑的投资组合规模，结果表明，天真地将特定规模的投资组合的最佳策略应用于另一个规模的投资组合是不合适的。就五种药物组合而言，在整套优化战略中最优选的开发手段是将内部开发和商业活动充分结合起来。对于三种药物组合，首选的开发手段包括内部、外包和合作活动的混合。此外，投资组合的规模似乎比现金流量限制的大小对战略和目标质量的影响更大。
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.