Origin: Development of a compact, time efficient and safe medical diagnostic machine

Informacje na temat projektu

Origin

Identyfikator umowy o grant: 867397

DOI

10.3030/867397

Projekt został zamknięty

Data podpisania przez KE 11 Maja 2019

Data rozpoczęcia 1 Maja 2019

Data zakończenia 31 Sierpnia 2019

Finansowanie w ramach

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Koszt całkowity

€ 71 429,00

Wkład UE

€ 50 000,00

Koordynowany przez

DIAPATH SPA
Italy

Periodic Reporting for period 1 - Origin (Origin: Development of a compact, time efficient and safe medical diagnostic machine)

Okres sprawozdawczy: 2019-05-01 do 2019-08-31

Podsumowanie kontekstu i ogólnych celów projektu

The World Health Organisation (WHO) estimates that nearly every family in the world is affected by cancer, causing one in six deaths worldwide. Globally, it's estimated that 42 million people suffered from cancer, over double the 19 million estimated sufferers in 1990.
The first step to diagnose a patient with cancer is the removal of a small amount of tissue; the study of the removed specimen is crucial for the correct diagnosis and therefore it has a high impact in the survival rates. To provide an accurate and complete diagnosis, the sample in question must be stored in an optimal manner. Tissue processing describes the process of sampling tissues and treating them with chemicals so that they do not undergo continuous degradation (fixation). After this treatment, other chemicals are used in order to make the tissue firm enough to be cut into micrometric sections. A subsequent staining and mounting onto a slide allow operators to highlight the structural patterns of the tissue for diagnosis.
The aim of ORIGIN is to provide a process, which reduces the steps with respect to the current process, decreasing both the amount of chemicals and materials required while decreasing the possibility of failure in every step. Origin unique value proposition improves the efficiency of the fixing step, while reducing the risk of failure due to the avoidance chemical cross – contamination. Only paraffin and formalin will be used, keeping the samples safe. Reduction in the use of chemicals and mismatching of reagents during replace of tissue processor by operator also means savings in plastic packaging.

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

To ensure Origin technical feasibility, the design of functionalities and the new methodology to process tissue simples has been detailed. The plan to develop an innovative software with fault prediction capabilities through IA functionalities has been detailed. An ambitious plan to clinically validate the equipment has been devised with the test in real environment conditions in five European reference hospitals during a period of 12 months. The technical plan to achieve a ready to market product has been traced with detail and extension over 24 months. The workplan has been organised in 5 work packages and an estimation of the resources needed has been calculated.
To ensure Origin commercial feasibility, its potential market has been identified, with hospitals and clinic laboratories where the product has to be addressed and with the clients’ needs identified. A commercial plan has been carefully stablished, selecting key countries. The sales model and pricing strategy has been defined in a hybrid model with direct sales and also renting plans. Diapath has built a dissemination and communication plan to raise the awareness amongst every potential customer, which includes the organisation of workshops, attending tradeshows and an increased presence in scientific publications and specialized media. The IP assessment has taken in account the patent portfolio of the company and the current patent application for Origin, which will ensure the company freedom-to-operate in the near future.
Finally, to ensure Origin financial feasibility, Diapath has analysed and forecasted the overall costs related to the production, the commersialisation of Origin and based on this has built three possible revenue scenarios.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

Despite the advances in the development of new technologies, there is currently no product on the market with the similar added-value of reliability, efficiency and operator protection.
- Reliability, safety and efficient system to process tissue samples and reduce the risk of failure during tissue processing. Origin’s instrument reliability is on the estimation, prevention and management of high levels of “lifetime” engineering uncertainty and risks of failure. The redundancy system based due the duplication and triplication of critical components or functions of a system to increase the reliability of the system, usually in the form of a backup or fail-safe, or to improve actual system performance. In a triply redundant system, the system has three sub-components, all three of which must fail before the system fails.
- Increased productivity: Origin increases productivity, due to the possibility to process in 30 minutes up to 600 samples. Processing chamber with a capacity of 5 to 8 litres, can hold up to a maximum of 300 samples, (only two models can process 405 and 600 samples). It has a suction system integrated.
- Use fewer chemicals and not exposition to cancerogenic and dangerous chemicals during the working day. Infiltration with paraffin is designed to eliminate the number and volume of reagents/chemicals (alcohol, xylene or xylene substitutes) used in the tissue processing.
- Low cost of the system maintenance
- Less impact of the system and its consumables in the environment
- Low cost and manage of reagents/chemical waste/ reagent savings of waste disposal per year. Origin avoids the pollution of the molten paraffin with xylene, again saving both time and reagents.
- A.I. based intelligent algorithms: The Origin Technology has the S.Y.N.A.P.S.E the Deep Prediction Analytics Software. A sophisticated Machine Learning and Deep Learning algorithms drive precise and continuous failure prediction.

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