DOI
http://doi.org/10.1080/17460441.2018.1480608

Summary
Despite a burgeoning knowledge of the intricacies and mechanisms responsible for human disease, technological advances in medicinal chemistry, and more efficient assays used for drug screening, it remains difficult to discover novel and effective pharmacologic therapies. By reference to the primary literature and concepts emerging from academic and industrial drug screening landscapes, the authors propose that this disconnect arises from the inability to scale and integrate responses from simpler model systems to outcomes from more complex and human-based biological systems. Is opinion of the authors that further collaborative efforts combining target-based and phenotypic-based screening along with systems-based pharmacology and informatics will be necessary to harness the technological breakthroughs of today to derive the novel drug candidates of tomorrow.

Relevance for Complex Systems Knowledge
The authors point the attention on the use of models (including some omics approaches) and their applications in drug discovery evidencing that the attempts to overcome the reductionistic interpretation of a complex interaction like that of a drug with a living system continue to fail (in terms of enabling efficient new drug discovery) because “no cell model fully recapitulates all facets of the biology that occurs in vivo”.
A proposed strategy to overcome this stand point is to integrate data from multiple models representing different levels of complexity, taking in considerations also the dynamic component of pathological processes and disease. In a fundamental field such as that of the development of new therapies we need to adapt our research understanding its limitation in relation to the understanding of complexity and proceeding with the individuation of the best strategies to questioning the systems combining in a proper manner the currently available models and technologies.

Point of Strength
This opinion article depicts an interactive process for the development of the research in medicinal chemistry in relation to the biological complexity and the limitation of the experimental models evidencing a not efficient level of communication between the “wet-lab” and the bioinformatics that represent one of the current limitations. The development of a novel method could be obtained only with different type of scientific training and collaboration than is not demanded by typical reductionist approach, a challenge that should involve industry and academy in a joint educational effort.