Translatability scoring in drug development: eight case studies

Abstract

Translational medicine describes the transfer of basic in vitro and in vivo data into human applications. In the light of low rates of market approvals for new medical entities, better strategies to predict the risk of drug development should be used to increase output and reduce costs. Recently, a scoring system to assess the translatability of early drug projects has been proposed. Here eight drugs from different therapeutic areas have been subjected to a retrospective test-run in this system fictively located at the phase II-III transition. The scores gained here underline the importance of biomarker quality which is pivotal to decrease the risk of the project in all cases. This is particularly evident for gefitinib. The EGFR mutation status is a breakthrough biomarker to predict therapeutic success which made this compound clinically acceptable, and this is plausibly reflected by a considerable increase of the translatability score. For psychiatric and Alzheimer's drugs, and for a CETP-inhibitor, the lack of suitable biomarkers and animal models is reflected by a low translatability score, well correlating with the excessive translational risk in these areas. These case studies document the apparent utility of the scoring system, at least under retrospective conditions, as the scores correlate with the outcomes at the level of market approval. Prospective validation is still missing, but these case studies are encouraging.

Animal models of chemically induced intestinal inflammation: Predictivity and ethical issues

“…The predictivity of the disease model itself will substantially depend on the efforts towards optimization and scientific validation of the model, both in terms of resemblance and transferability to humans. Recently, many authors have underlined the importance of identifying biomarkers in the drug discovery process and proposed the ideal features of a disease model (Fitzgerald, 2005;Sams-Dodd, 2006;Wendler & Wehling, 2012). Indeed, clinical information can be integrated in model development and optimization (choice of biomarkers, tests that can measure relevant disease parameters) and, once its validity is established, it can be further used as a standard for the comparison with other disease models.…”

“…In order to facilitate transfer from in vitro or in vivo studies to clinical applications, several decision points should be established to evaluate the translational value of a drug project (Wendler & Wehling, 2012) and assess the translatability of the study in the early stage, for example by applying a scoring system. A recently proposed score assessed several parameters including availability and quality of in vitro and in vivo results, preclinical and clinical biomarkers, and clinical as well as personalized medicine aspects (Wendler & Wehling, 2012).…”

“…A recently proposed score assessed several parameters including availability and quality of in vitro and in vivo results, preclinical and clinical biomarkers, and clinical as well as personalized medicine aspects (Wendler & Wehling, 2012).…”

The safety, efficacy and regulatory triangle in drug development: Impact for animal models and the use of animals

“…A strong and objective outcome measure that has clear relevance to the clinical disease is imperative for translation (Wendler and Wehling, 2012;Stroh et al, 2014). When the etiology of a disease is incompletely understood (e.g., mood disorders, autoimmune diseases, and neurodegenerative disorders), translation has especially suffered, primarily from unintentional focus on targeting epiphenomena (Jucker, 2010;'t Hart et al, 2005;Webb, 2014).…”

Unknown unknowns in biomedical research: does an inability to deal with ambiguity contribute to issues of irreproducibility?

“…As a consequence, the credibility and value of the biomedical research enterprise has been undermined [6,7,8] leading to concerns regarding its continued level of funding. The scope of the reproducibility issue has been further compounded by the addition of the shortcomings of the translational research process that underpin aspects of the clinical attrition rate in drug discovery [4,9,10] prompted by "the assumption that translation, rather than fundamental understanding, is the choke point of progress in the application of science to societal problems" [11].…”