Summary
- Profile Type
- Technology offer
- POD Reference
- TOIT20230524013
- Term of Validity
- 24 May 2023 - 23 May 2025
- Company's Country
- Italy
- Type of partnership
- Research and development cooperation agreement
- Investment agreement
- Targeted Countries
- All countries
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General information
- Short Summary
- An Italian start-up, from an university spinoff, has started working on oncology predictions based on transport phenomena. These prediction, when successful, will be a gigantic leap forward for all mankind. The potential applications of this technology are countless: from clinic to drug trials, towards true personalised medicine. The company is looking for international partner under research and technical cooperation agreeements. A cooperation under financial agreement is also considered.
- Full Description
-
This small spinoff of a South Italy based University performs research activity in the field of Computer Aided Engineering (CAE) technologies as applied to life science.
Its core activities deals with the complex scenario of cancer growth and fight. The inherent technological, social and ethical impacts of this project has a clear definition and consistence: the implementation of a virtual patient software will improve clinical treatment and drug development.
Breast cancer is one of the most common types of cancer in women worldwide. While advancements in medical research have led to improved treatments and survival rates, accurately predicting the progression and prognosis of breast cancer remains a significant challenge. Computational prognosis of breast cancer involves the use of advanced algorithms and machine learning techniques to analyze large amounts of clinical data to predict the progression of breast cancer and patient outcomes. In particular, deterministic models can be cast that are based on mathematical equations that describe the physical and biological processes underlying cancer growth and treatment. These models typically require a large amount of data, including patient-specific clinical and biological data, to calibrate and validate the model. Once the model is validated, it can be used to predict cancer growth and treatment outcomes for individual patients.
There are several reasons why the discipline of computational prognoses of breast cancer is important and should be studied and empowered in medical oncology:
- improved accuracy and personalized treatment: computational prognoses can provide more accurate predictions of disease progression and personalized treatment plans for individual patients.
- patient stratification: computational prognoses can help identify patients who should be treated with a given neoadjuvant therapy in a given time window, depending on the personal burden and the risk of developing breast cancer with may be surgically removed with more impactful ways.
- accelerating research: computational prognoses can help accelerate the pace of medical research by providing a tool for analyzing large amounts of clinical and computational data.
- better resource allocation: accurate predictions of disease progression and patient outcomes can help allocate medical resources more effectively and efficiently.
Based on its expertise on CAE, coupled with all applicable occurrences of physics, chemistry and biology, the spinoff is able to perform prognoses of the outcome of breast carcinoma following neoadjuvant therapy, even before the patient undergoes it. This tool allow oncologists to realize at will virtual scenarios of the disease. The technology has reached TRL=9 for the case of olaparib and trastuzumab treatments.
The spinoff is willing to cooperate with international partners under research and technical cooperation agreements, in order to achieve a complete development of technology and the first viable product. A cooperation under financial agreement, instead, will help the Italian company to outsource those activities where a technical collaboration is needed. - Advantages and Innovations
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Innovation:
Oncology predictions exist by the dozen in the available scientific literature. Nonetheless, nobody has ever attacked this topic by means of off-the-shelf engineering software, which allows for immediate deployment, easy maintenance, flexible adaptation to personalised medicine.
Advantages:
By reducing the cost of in-silico description of tumors, the number of patients to be virtualized and cured will increase greatly. This new approach will allow oncologists to realize at will virtual scenarios of the disease, and pharma companies to experiment perspective drugs in new, sustainable ways.
Time is ripe to start using such technology, based on both a visionary approach and a rigorous attitude which stems from the research activity of the proponent group. - Stage of Development
- Available for demonstration
- Sustainable Development Goals
- Goal 3: Good Health and Well-being
Partner Sought
- Expected Role of a Partner
-
A joint effort is sought with both research and financial organisations, to help coagulate the proper partnership.
In the first case, oncology knowledge-base organizations that will help consolidate the intended goal: complete the spectrum of neoadjuvant therapies on which to perform the prognoses.
In the second case, a proper financial aid will help outsource those few areas where technical collaboration is currently needed.
A list of main research activities follows:
1. locate and implement proper partnership for clinical data: patient analysis data, imaging, disease course and outcomes. More partnerships are sought to widen the technology breadth.
2. execute automatic rendition, capture and extraction of actual tissue features, and generation of 3D geometry. IT outsourcing is needed to complete the work pipeline.
3. perform Machine Learning algorithms application to the present models.
5. realize proper end-user interface, for viable implementation in clinical frameworks.
6. select recipient entities for financial/technological/commercial speculation and follow-ups. - Type and Size of Partner
- University
- SME 50 - 249
- R&D Institution
- Big company
- SME <=10
- Other
- SME 11-49
- Type of partnership
- Research and development cooperation agreement
- Investment agreement
Dissemination
- Technology keywords
- 03004007 - Pharmaceutics
- 06001012 - Medical Research
- 06001005 - Diagnostics, Diagnosis
- 01004001 - Applications for Health
- 06001003 - Cytology, Cancerology, Oncology
- Market keywords
- 05001001 - Diagnostic services
- 02006009 - Other computer services
- 05001007 - Other diagnostic
- 05007006 - Computer-aided diagnosis and therapy
- 05005014 - Oncology
- Targeted countries
- All countries