Nov 17, 2014
Tissue Phenomics: From Biomarker Discovery to Clinical Diagnostic Assay Commercialization
Dr. Thomas Nifong, Executive Vice President, Diagnostic Tests, Definiens, Boston, Massachusetts, USA
Definiens’ Cognition Network Technology®, CNT, provides detailed tissue biomarker readouts from digital pathology slides, and enables the correlation of this information with clinical outcome and genomic data, an approach known as Tissue Phenomics. The manual approach to analyzing tissue provides mostly limited, qualitative information. However using CNT, thousands of quantitative, reproducible tissue biomarker features such as histologic scores, intensity measurements, morphologic parameters, and object enumeration have been extracted from all types of tissue stains, including H&E, IHC, ISH, and FISH digital images. Those features have been successfully mined for biomarker signatures for patient stratification, prognostication, and improved molecular diagnostic measurements. With the recent focus on immunotherapy, immunoprofiling of the tumor microenvironment has become a particularly important application of Definiens’ CNT, with clinical relevance demonstrated in both prognostic and predictive settings. The goal at Definiens is to see these phenomics-based assays implemented in the clinical setting to aid in individualized patient care. Although the technical aspects of performing image analysis-based diagnostics with an efficient workflow in the clinical setting have been well documented, diagnostics companies must still navigate a complex regulatory and reimbursement environment in order to commercialize an assay. The regulatory oversight of laboratory developed tests, LDTs, and companion diagnostics will likely increase in both the U.S. and Europe in the near future, and we have looked at ways to meet these requirements through laboratory-based PMAs and partnered IVDs. We have also explored some of the reimbursement and commercialization strategies that can be used along with our CNT to deploy Tissue Phenomics in personalized medicine in the U.S. and globally.