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SmartMarker - Clinical Validation of Biomarkers by Smart Data Analyses

Periodic Reporting for period 1 - SmartMarker (SmartMarker - Clinical Validation of Biomarkers by Smart Data Analyses)

Reporting period: 2015-06-01 to 2015-09-30

SmartMarker aims at providing a commercial infrastructure that allows to transform heterogeneous patient health information, typically stored in multiple clinical and health IT systems, into standardized, comparable, consistent, and queryable data. The goal of this infrastructure is to conduct retrospective clinical biomarker validation studies and to foster effective treatments to marker-defined patient subgroups. By this, SmartMarker will dramatically ease the process of clinical biomarker validation.

The primary objective of SmartMarker Phase 1 was to research the technical and business basis for this infrastructure. We wanted to prove our concept of clinical biomarker validation in cardiology based on EHR records. Technical challenges shall be identified when implementing this infrastructure on a large scale. Finally, we wanted to further specify the technical architecture of our proposed infrastructure. Regarding business modelling and market assessment, the objective was developing a business plan and a roadmap to commercialization that will serve as a basis for a Phase 2 proposal preparation. Different risks to be considered in the commercial implementation shall be detected and the corresponding contingency plans be defined.

During this process, we have performed a deep market analysis aiming to define SmartMarker market (geographic scope, customers, competitors…) and commercial strategies (including dissemination and communication of the infrastructure). Finally we aimed at analysing the regulatory framework in different target countries and defining the strategy to protect our IP. A limited number of countries have been evaluated during Phase 1.
The aim of SmartMarker is to provide a commercial infrastructure that allows to transform heterogeneous patient health information, typically stored in multiple clinical and health IT systems, into standardized, comparable, consistent, and queryable data. The goal of this infrastructure is to conduct retrospective clinical biomarker validation studies and to foster effective treatments to marker-defined patient subgroups. Our ambition is to dramatically ease the process of clinical biomarker validation starting in the cardiology domain. We propose a research infrastructure that allows meaningful data access to large-scale integrated data repositories. Exploitation of the electronic medical records will allow pragmatic and low cost, but still robust and appropriate analytical retrospective study methods to measure the prognostic and predictive outcome of clinical biomarkers on large patient collections.

In a feasibility study with 500k patient lives we could show that it is possible to perform large scale biomarker validation studies on the basis of available patient data. They can serve as an alternative to prospectively designed clinical trials which are the conventional approach to validate predictive biomarkers, but are still an expensive and time-consuming procedure, and work on a relatively small number of patients.

An in-depth IPR analysis revealed that the SmartMarker platform may not be protected by means of a patent as it lacks the technical feature and technical contribution requirements which would determine its patentability. Instead, SmartMarker IPR shall be protected by means of copyright which is bestowed to the authors due to the simple fact that they have created the software platform. The technology report revealed that there exist some solutions to integrate informatics platforms to patient's clinical care information but most are developed for local use between North American academic institutions, research centres and hospitals. There is a strong market opportunity in Europe, whether manage to overcome certain barriers of political, economic and ethical themes.

The SmartMarker team also produced a detailed business plan describing products and services as well as the SmartMarker management team consisting of experienced entrepreneurs in the eHealth sector. The market analysis revealed biomarkers and phenotypes as one of the “hot threads” of diagnostics and drug development in pharmaceutical and biomedical research, with applications in early disease identification, identification of potential drug targets, prediction of the response of patients to medications, help in accelerating clinical trials, and personalized medicine. The biomarker market generated $13.6 billion in
2011 and is expected to grow to $25 billion by 2016. Competition is still fairly low with providers mainly addressing the US market. A detailed three phase strategy and implementation for fast market penetration has been developed. We expect to make significant revenue beginning in the first year after the funding phase, reaching the break-even in 3-5 years. Regarding financial requirements, we don't expect large financial support for technical developments after SmartMarker Phase II. However, a significant budget will be needed for marketing and rapid market penetration.
In the feasibility study we could show that it is possible to perform large scale biomarker validation studies on the basis of available patient data. We were able to access about half a million patient records which appeared to be large enough to find already known correlations between biomarkers and clinical outcome. However, for regression models with multiple influential variables which are needed to identify previously unknown correlations, the current data basis is too small. In Phase II, we aim for working on ten to twenty times more data from different hospitals for biomarker validation studies. We identified several other challenges that can and shall be addressed in phase II of SmartMarker.

Regarding IPR related issues, we engaged the Intellectual Property agency Clark, Modet & Co for an in-depth technology due diligence and a technology positioning. The results in a nutshell are that they not recommend protecting the SmartMarker platform by means of a patent as they consider that it lacks the technical feature and technical contribution requirements which would determine its patentability. Instead, they recommend protection by means of Copyright which is bestowed to the authors due to the simple fact that they have created the software platform.

The technology report revealed that there are many solutions available to integrate informatics platforms to patient's clinical care information but most are developed for local use between North American academic institutions, research centres and hospitals. This means that there is a good market opportunity in Europe, if we manage to overcome certain political, economic and ethical barriers.

In the business plan, we defined our product and services and gave an overview about the management team of a future SmartMarker company. We identified biomarkers and phenotypes as one of the “hot threads” of diagnostics and drug development in pharmaceutical and biomedical research, with applications in early disease identification, identification of potential drug targets, prediction of the response of patients to medications, help in accelerating clinical trials, and personalized medicine. The biomarker market generated $13.6 billion in 2011 and is expected to grow to $25 billion by 2016. Competition is still fairly low with providers mainly addressing the US market. A detailed three phase strategy and implementation for fast market penetration has been developed. We expect to make significant revenue beginning in the first year, reaching the break-even in 3-5 years. Regarding financial requirements, we don't expect large financial support for technical developments after SmartMarker Phase II. However, a significant budget will be needed for marketing and rapid market penetration.
F2. Boxplots for the biomarkers BNP, ejection fraction and QRS duration
F5. Regression curve for influence of QRS duration on the occurrence of left bundle branch block
F3. Distribution of age for subgroups of patients with/without mentioning of ischemic heart disease
F1. Distribution of age in the study population
F4. Regression curve for influence of ejection fraction on the occurrence of heart failure