Background: Productivity in drug R&D continues seeing significant attrition in
clinical stage testing. Approval of new molecular entities proceeds with slow pace specifically
when it comes to chronic, age-related diseases, calling for new conceptual approaches,
methodological implementation and organizational adoption in drug development.
Methods: Detailed phenotyping of disease presentation together with comprehensive representation
of drug mechanism of action is considered as a path forward, and a big data spectrum
has become available covering behavioral, clinical and molecular characteristics, the
latter combining reductionist and explorative strategies. On this basis integrative analytics in
the realm of Systems Biology has emerged, essentially aiming at traversing associations into
causal relationships for bridging molecular disease specifics and clinical phenotype surrogates
and finally explaining drug response and outcome.
Results: From a conceptual perspective bottom-up modeling approaches are available, with
dynamical hierarchies as formalism capable of describing clinical findings as emergent properties of an underlying
molecular process network comprehensively resembling disease pathology. In such representation biomarker
candidates serve as proxy of a molecular process set, at the interface of a corresponding representation of drug
mechanism of action allowing patient stratification and prediction of drug response. In practical implementation
network analytics on a protein coding gene level has provided a number of example cases for matching disease
presentation and drug molecular effect, and workflows combining computational hypothesis generation and experimental
evaluation have become available for systematically optimizing biomarker candidate selection.
Conclusion: With biomarker-based enrichment strategies in adaptive clinical trials, implementation routes for
tackling development attrition are provided. Predictive biomarkers add precision in drug development and as
companion diagnostics in clinical practice.