Abstract
Integrative understanding of preclinical and clinical data is imperative to enable informed decisions and reduce the attrition rate during drug development. The volume and variety of data generated during drug development have increased tremendously. A new information model and visualization tool was developed to effectively utilize all available data and current knowledge. The Knowledge Plot integrates preclinical, clinical, efficacy and safety data by adding two concepts: knowledge from the different disciplines and protein binding.Internal and public available data were gathered and processed to allow flexible and interactive visualizations. The exposure was expressed as the unbound concentration of the compound and the treatment effect was normalized and scaled by including expert opinion on what a biologically meaningful treatment effect would be.The Knowledge Plot has been applied both retrospectively and prospectively in project teams in a number of different therapeutic areas, resulting in closer collaboration between multiple disciplines discussing both preclinical and clinical data. The Plot allows head to head comparisons of compounds and was used to support Candidate Drug selections and differentiation from comparators and competitors, back translation of clinical data, understanding the predictability of preclinical models and assays, reviewing drift in primary endpoints over the years, and evaluate or benchmark compounds in due diligence comparing multiple attributes.The Knowledge Plot concept allows flexible integration and visualization of relevant data for interpretation in order to enable scientific and informed decision-making in various stages of drug development. The concept can be used for communication, decision-making, knowledge management, and as a forward and back translational tool, that will result in an improved understanding of the competitive edge for a particular project or disease area portfolio. In addition, it also builds up a knowledge and translational continuum, which in turn will reduce the attrition rate and costs of clinical development by identifying poor candidates early.
Highlights
Translational Medicine is the discipline focusing on improving drug discovery and development by bridging the gap between basic research, clinical development and clinical practice
This paper describes the Knowledge Plot, a new translational framework for effective and flexible integration of preclinical and clinical data using a project-centric approach
The Treatment Effect is normalized into the Treatment Effect Index by using the reference value
Summary
Translational Medicine is the discipline focusing on improving drug discovery and development by bridging the gap between basic research, clinical development and clinical practice. It is imperative to visualize data to be able to explore and integrate biomarkers from preclinical and clinical studies for multiple compounds (for benchmarking, differentiation and to compare forerunners) side-by side for informed decisions This requires aggregation of a large amount of data and a holistic scientific understanding of all biomarkers. A platform that addresses this requires seamless access of data from clinical trials and preclinical studies It needs to encompass a framework for harmonizing the interpretation of different types of data, gathered from various species, patient populations and therapeutic areas. The platform should, both technically and organizationally, allow use and reuse of data retrieved from internal and external sources as well as outputs from pharmacokinetic and pharmacodynamic modeling and simulations (PKSTM). Export of data to other applications for visualization and integration is key to ensure flexibility
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