In spite of ongoing advances in science and technology, it has taken significantly longer than expected for a basic drug discovery to be translated into a treatment for human diseases. Only around 0.1% of the new drug candidates can finally receive approval from the US Food and Drug Administration (FDA), with a cost of $2.6 billion for each approved drug. Almost 90% of the drug candidates failed before they ever tested in human trials, which is known as “the valley of death”; and around 50% of the drugs that have entered into clinical trials died in their phase III trials (Li et al., 2020; Seyhan, 2019). The failure rate of clinical trials of drugs has actually increased over recent years despite the increasing predictability of tests on cell/molecular or animal models (Leenaars et al., 2019). The main reasons are inadequate effectiveness or badly side effects (Waring et al., 2015). Therefore, it is crucial to improve the success rate of the translation of drugs and cut down the translation lags (Ogier et al., 2019; Parrish et al., 2019). Most of the previous studies on translational research for drugs have focused on the roadblocks hindering the success of “bench-to-bedside” translation, such as insufficient research funding (Hörig et al., 2005), imperfect reward system Fishburn (2013), knowledge gap between basic and clinical scientists Rocca (2017), misuse of statistical methods (Vidgen & Yasseri, 2016), difficulty in cohort recruitment (Segura-Bedmar & Raez, 2019), irreproducibility of basic experiments (Jarvis & Williams, 2016), and insufficient understanding of translational science Seyhan (2019). To clear these roadblocks, interdisciplinary research, especially those involving both basic and clinical science, has been highly recommended as one of the solutions to accelerate drug translation (Ameredes et al., 2015; Bahney et al., 2016; Rocca, 2017). On the one hand, drug translation is an intricate task that requires a range of diverse skills, such as pharmacology, epidemiology, statistics, genetics, clinical studies and computer science (Kumar & Sattigeri, 2018). Interdisciplinary research has shown the effectiveness to breed and amplify innovations during the process of translation (Xu et al., 2015) and improve the quality and reproducibility of research Barba (2016), by allowing scientists in various disciplines to exchange innovative ideas and share their resources and experience (C. Zhang et al., 2018). Moreover, interdisciplinary collaborations between researchers from various organizations including funding agencies and government departments bring more funding and higher clinical impact to translational research (Gil-Garcia et al., 2019). But on the other hand, other studies have indicated several drawbacks of interdisciplinary research and collaborations for translational medicine, such as communication gaps (Grippa et al., 2018), time-consuming (Bu, Ding, Xu, et al., 2018), leadership (Folkman et al., 2019), and intellectual barriers (Banner et al., 2019). Establishing a persistent and stable interdisciplinary research team is definitely a challenge Seyhan (2019). Hence, interdisciplinary research arguably plays many roles in the translation of drug discoveries, yet it has been a subject of few quantitative studies in the translational research for drugs. Besides, previous studies on interdisciplinary research focused mainly on the perspectives of journals (L. Zhang et al., 2016), articles (Leydesdorff & Ivanova, 2021), and authors (Bu, Ding, Xu, et al., 2018). However, in the process of translating drug discoveries into therapies, there is a variety of research types. In particular, the biomedical studies can be classified into seven different categories by using the translational triangle of biomedicine originally proposed by (Weber, 2013): animal related research (A), cell/molecular related research (C) and human related research (H) and the combinations of these three (i.e., AC, AH, CH, ACH). In this paper, we divided drug research into the corresponding seven categories: (1) A-A; (2) C-C; (3) H-H; (4) A-C; (5) A-H; (6) C-H; and (7) A-C-H. (1), (2) and (4) are research within basic science; (3) research within clinical science; (5), (6) and (7) are research involving both basic science and clinical science. To our best knowledge, the patterns and the roles of the different kinds of research in translational process for drugs, which can provide us insights on how to shorten the translation lags in drug research and development, have not been deeply examined in the extant studies. For example, would more persistent and stable interdisciplinary research involving both basic science and clinical science lead to better results in the translation of drugs? The more diverse the research, the more likely the translation of drugs will be successful?
