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Artificial intelligence: key to optimizing clinical decisions in cancer patients

“The OPS (Oncology Precision System) starts from the genetic characteristics of each patient and is capable of proposing the best combination of treatments currently available against cancer personalized for each patient, as well as estimating the probability of five-year survival in each case”

No one is unaware of the impact that COVID19 has had on the health system and its impact on other pathologies. From a bird’s eye view, 1.2 million fewer surgeries were performed in 2020 than in 2019 (the year in which 5.39 million consultations were performed in Spain in all healthcare resources). Reduction in surgical activity that was accompanied, reasonably, by a reduction in diagnoses and, therefore, in surgical indications.

This situation, which was not normal in 2021 either, has generated a queue of patients who are not on the radar of the health system (and therefore, outside the statistics), which are gradually beginning to emerge as activity normalizes. But given the queue generated, it is stressing the system to try to catch up. As an example, just to normalize surgical care pressure, in 2021 no less than 6.5 million surgical interventions would have to have been performed, 17% more than in 2019. This situation is more worrying in the case of patients with some type of Of cancer. To put some national figures for the year 2020 (the last year for which we have data, but already with the impact of the pandemic), compared to 2019: in the year 2020, just over 4 million biopsies were performed, hovering around almost 5, 5 million biopsies in 2019. 5.64 million Day Hospital sessions were performed in 2020, just one million less than the previous year. And most notably, in 2020, 860,000 cancer patients were diagnosed, almost 90,000 fewer people than in 2019, which demonstrates the healthcare pressure we suffered in the midst of the pandemic.

This is assuming that patients may arrive with a greater progression of their disease, an increase in the complexity and intensity of treatment (or adjuvant treatments) and a worse prognosis, with the consequent decrease in survival. This complexity is increased by the wide variety of treatments available and by the irruption of personalized medicine, through highly innovative treatments such as, for example, cell apoptosis, which KeyZell has been betting on.

The approach to improving this situation goes through the search for efficiencies in the oncology patient care process, causing the effect of solving more with the same resource capacity. That is, causing the venturi effect and thereby increasing patient safety by seeking to do to each patient only what needs to be done, at the right time and in the best possible way. The chances of recovery and survival depend on this.

The efficiency of the healthcare process is key at two moments, which will condition the rest of the patient’s healthcare process:

Diagnosis and staging of the tumor , which must be as precise as possible. The oncological diagnosis is complex for different reasons: the possible existence of metastatic tumors and the different moments of evolution of the disease (staging), among others. The quality of the diagnostic means and the interpretation of the data is essential for an accurate diagnosis, which will mark the success of the following steps in the care process.

Therapeutic decisions : The moment of the therapeutic decision is also highly complex, being decisive for the care path of each patient and their possible recovery and survival. The stage of the tumor, the circumstances of the patient and the possible existence of other pathologies, the infinity of existing therapeutic alternatives (which can be main or adjuvant, and within the former, different lines of treatment), and the constant innovations in therapeutic matters oncology will influence the optimization and precision that are taken.

A precise treatment in a framework as complex as the one described can only be managed through the support of artificial intelligence that orders the data and that the existing knowledge manages the variables to be considered in decision making and makes predictions of results according to the therapeutic decisions made, fundamentally in patient survival and reduction of side effects.

In this line, the Oncology Precision System developed by KeyZell stands out, a company that, based in Seville and with international coordination in different countries, has developed a “machine learning”. In other words, a solution that goes beyond artificial intelligence, allowing patterns to be identified in the analysis of massive data and, most importantly, making predictions. Therefore, the OPS (Oncology Precision System) starts from the genetic characteristics of each patient and is capable of proposing the best combination of treatments currently available against personalized cancer for each patient, as well as estimating the probability of survival at five years in each case.

If it is always important to be efficient, not only in medicine but in any human activity, now it is vital. And never better said, because in patients with cancer pathology, the time of action is essential. And given the limitation of resources (also inherent in any organization, whether public or business), it is mandatory to seek the best therapeutic alternative for the care process of each patient, which will help to redistribute care pressure, reduce the necessary resources and increase safety. of the patient in the first instance and, finally, their survival.

And that precision, given the limitation of the human brain (although there are several brains thinking together, due to decisions in committees or similar formulas), fortunately can be supported with technological solutions, such as the one mentioned by KeyZell. Not to mention that these solutions also polish the subjectivity that characterizes us as human beings, which is not mitigated with more brains thinking together. Doctor Marañón used to say that we are subjective because we are subjects. To be objective we would have to be objects. And fortunately, the objectivity of technology comes to collect the knowledge and expertise of many to make it available to each clinical professional as support for the decisions that their patient’s care will require.

Antonio Burgueño Jerez
Director of Enclave Salud and the Venturi Project



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