KeyZell revolutionizes the fight against lung and breast cancer with an Artificial Intelligence tool

The Spanish biotechnology startup KeyZell, in alliance with the technology company Iakan, has presented an Artificial Intelligence solution capable of recommending personalized treatments for lung and breast cancer to medical professionals, taking into account the individual characteristics of each patient and their type of cancer.

MADRID, 10 (MEDIA SERVICE)

The Spanish biotechnology startup KeyZell, in alliance with the technology company Iakan, has presented an Artificial Intelligence solution capable of recommending personalized treatments for lung and breast cancer to medical professionals, taking into account the individual characteristics of each patient and their type of cancer.

The company noted that Keyzell OPS helps oncologists make more accurate decisions by enabling personalized medicine, reducing recurrence, overmedication, hospitalization time, treatment costs, follow-up through all clinical phases, and , above all, has a positive impact on the quality of life of patients.

In this sense, he stressed that currently health professionals are forced to make decisions “with a high level of uncertainty”, since each patient may have a different response to treatment. In addition, current protocols involve high levels of toxicity, “which increases the suffering and side effects of those affected, being key to personalize treatments as much as possible and to know their level of effectiveness in each case.”

Keyzell OPS is based on a ‘machine learning’ system in continuous learning, which feeds on thousands of data from medical records, creating machine learning models from the medical experience collected over the years, “which was wasted given the difficulty of managing such a volume of data effectively, in order to optimize decision making”.

The company emphasizes that the use of this system also speeds up response times for patients, since it has a positive impact on oncologists’ management times, increases the quality of follow-up and allows complications to be dealt with quickly, improving personalized patient care . “The oncologist simply enters the patient’s data on the platform and it breaks down the most suitable treatments for him in the form of a ranking.”

OPS, whose industrial property has been obtained thanks to the Keyzell team, has been trained with the help of lakan technology from millions of data on cancer, from different cohorts around the world. Keyzell OPS has been “trained” with over 100,000 records. It includes recognition of diagnostic images and considers more than 30 variables of clinical data, ranging from data on the tumor, organ, state, together with the sequencing reading with biomarkers, among others, which makes it possible to predict which drug and/or combination of drugs with the highest success rate.

Currently, it is available for breast cancer and lung cancer. In the first case, it is a ‘machine learning’ model for predicting survival created from breast cancer registries of patients in the US and at the Puebla Hospital in Mexico; and, in the second, an effectiveness and toxicity prediction model, with lung cancer registries from hospitals in Spain.

In addition, KeyZell has several lines of research and training open for other types of cancer, and is developing an even more advanced version of Keyzell OPS for multi-omic precision medicine, with a security model based on Blockchain technology.

(SERVIMEDIA) 10-MAY-2022 14:09 (GMT +2) S/gja

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See here the complete article of La Vanguardia.

Dr Nabil Hajji

Dr Nabil Hajji

World-renowned expert in the field of oncology, recognized for establishing the mechanism underlying the resistance of classical antitumor treatments in various types of cancer, related to the epigenetic mechanism that controls apoptosis and the tumor microenvironment.

Dr Nabil Hajji

Dr Nabil Hajji

World-renowned expert in the field of oncology, recognized for establishing the mechanism underlying the resistance of classical antitumor treatments in various types of cancer, related to the epigenetic mechanism that controls apoptosis and the tumor microenvironment.

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