Abstract

Objective

Clinical trials ensure that pharmaceutical treatments are safe, efficacious, and effective for public consumption, but are extremely complex, taking up to 10 years and $2.6 billion to complete. One main source of complexity arises from the collaboration between actors, and network science methodologies can be leveraged to explore that complexity. We aim to characterize collaborations between actors in the clinical trials context and investigate trends of successful actors.

Materials and Methods

We constructed a temporal network of clinical trial collaborations between large and small-size pharmaceutical companies, academic institutions, nonprofit organizations, hospital systems, and government agencies from public and proprietary data and introduced metrics to quantify actors’ collaboration network structure, organizational behavior, and partnership characteristics. A multivariable regression analysis was conducted to determine the metrics’ relationship with success.

Results

We found a positive correlation between the number of successful approved trials and interdisciplinary collaborations measured by a collaboration diversity metric (P < .01). Our results also showed a negative effect of the local clustering coefficient (P < .01) on the success of clinical trials. Large pharmaceutical companies have the lowest local clustering coefficient and more diversity in partnerships across biomedical specializations.

Conclusions

Large pharmaceutical companies are more likely to collaborate with a wider range of actors from other specialties, especially smaller industry actors who are newcomers in clinical research, resulting in exclusive access to smaller actors. Future investigations are needed to show how concentrations of influence and resources might result in diminished gains in treatment development.

中文翻译：

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检查药物临床试验与药物批准合作网络中凝聚力和多样性之间的关联

摘要

客观的

临床试验确保药物治疗安全、有效且对公众有效，但极其复杂，需要长达 10 年和 26 亿美元才能完成。复杂性的一个主要来源来自参与者之间的合作，并且可以利用网络科学方法来探索这种复杂性。我们的目标是在临床试验背景下描述参与者之间的合作，并调查成功参与者的趋势。

材料和方法

我们根据公共和专有数据构建了大型和小型制药公司、学术机构、非营利组织、医院系统和政府机构之间临床试验合作的时间网络，并引入了量化参与者合作网络结构、组织行为和伙伴关系特征。进行了多变量回归分析以确定指标与成功的关系。

结果

我们发现成功批准的试验数量与通过合作多样性指标衡量的跨学科合作之间存在正相关关系 ( P  < .01)。我们的结果还显示局部聚类系数 ( P  < .01) 对临床试验的成功有负面影响。大型制药公司的本地聚集系数最低，生物医学专业领域的合作伙伴关系更加多样化。

结论

大型制药公司更有可能与来自其他专业的范围更广的参与者合作，尤其是在临床研究中新来的较小的行业参与者，从而获得与较小参与者的独家访问权。未来的调查需要显示影响力和资源的集中如何导致治疗开发的收益减少。