Sponsorship of drug and device studies by the manufacturing company

From The Embassy of Good Science

Sponsorship of drug and device studies by the manufacturing company

What is this about?

More and more clinical trials are being conducted all over the world as technology is advancing at a very fast pace. Many of these trials include companies that are bound to have great profits if the trial pans out. Sponsorship of drug and device studies by the manufacturing companies often leads to more favorable efficacy results with an industry bias becoming a real problem. [1]

  1. Lundh A, Lexchin J, Mintzes B, et al. Industry sponsorship and research outcome. Cochrane Database Syst Rev 2017; 2: MR000033.

Why is this important?

When drug and device studies are conducted, results that are unfavorable to the sponsor can pose great financial risks to the sponsor companies. Several factors can explain the relationship between sponsorship and favorable outcomes, including a variety of biasing choices in the design, conduct, and reporting of studies.[1] Inferior competing treatment alternatives may be chosen as well as less clinically relevant primary outcomes that have a better chance of achieving a significant effect. [2] Of course, there is also another perspective, meaning that the observed success rates seen in industry-sponsored trials are also rooted in the way commercial sponsors invest in product development meaning that only proposals with promising data and a high likelihood of success progress to RCT testing.[3]

The higher success rates seen in industry-sponsored research are expected and can be explained by extensive research, development efforts, and multimillion dollars investments.[4]

  1. Lundh A, Lexchin J, Mintzes B, et al. Industry sponsorship and research outcome. Cochrane Database Syst Rev 2017; 2: MR000033.
  2. Djulbegovic B, Kumar A, Miladinovic B, et al. Treatment success in cancer: industry compared to publicly sponsored randomized controlled trials. PLoS One 2013; 8: e58711.
  3. Fries JF, Krishnan E. Equipoise, design bias, and randomized controlled trials: the elusive ethics of new drug development. Arthritis Res Ther 2004; 6: R250-5.
  4. DiMasi JA, Hansen RW, Grabowski HG. The price of innovation: new estimates of drug development costs. J Health Econ 2003; 22: 151–185.

For whom is this important?

What are the best practices?

To manage conflict of interests, which is inevitable and must always be declared, it is important to maximize transparency in industry-funded research. Some of the proposed approaches include a carefully constructed advisory board with specific responsibilities as well as strict guidelines to protect research quality.[1] It is important to fully disclose financial, personal, and professional interests. Oversight by an independent third party is recommended as well as pre-registration of the study. The role of commercial partners must be defined and the relationship has to be continuously monitored. [2] The scientific community has improved recently in regards to some of the key indicators of research reproducibility and transparency. This includes information on funding, conflict of interests statements, and an increase in protocol and data sharing. There is also a growing number of fully available texts, although the majority of texts are still not fully available. Nevertheless, confusion about research transparency still exists, and even though there has been some improvement, the scientific community is far from perfect in terms of research transparency and reproducibility.[3]

  1. Plottel GS, Adler R, Jenter C, et al. Managing conflicts and maximizing transparency in industry-funded research. AJOB Empir Bioeth 2020; 11: 223–232.
  2. Cullerton K, Adams J, Forouhi N, et al. What principles should guide interactions between population health researchers and the food industry? Systematic scoping review of peer-reviewed and grey literature. Obes Rev 2019; 20: 1073–1084.
  3. Wallach JD, Boyack KW, Ioannidis JPA. Reproducible research practices, transparency, and open access data in the biomedical literature, 2015-2017. PLoS Biol 2018; 16: e2006930.

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