Qualiquantitative benefit/risk assessment method suitable for the physiological activity of natural matrices-based therapeutic or beneficial products with respect to that of other products with pharmacological or nutraceutical activity based on synthetic molecules

A computer-implemented method for providing a benefit/risk score for a therapeutic product of interest used to treat a pathology or pathological state, said method comprising:

• (1) performing a transcriptomic data analysis comprising:
• (1.1) providing one or more samples of a biological substrate representing the pathology or pathological state treated by said therapeutic product;
• (1.2) contacting said one or more of samples with said therapeutic product or a reference drug known to treat said pathology or pathological state;
• (1.3) extracting ribonucleic acid (RNA) from each of said samples in 1.1 and 1.2;
• (1.4) identifying differentially expressed genes (DEGs) in each of samples 1.2 with respect to said samples 1.1, and determining the changes in gene expression for each DEG relative to the samples in 1.1, thereby obtaining fold change values for each of said DEG;
• and
• (1.5) determining, by use of a data processor, numerical values representing the variation of gene expression in 1.4 in terms of magnitude and directionality of one or more biological activities related to the differential expression of said DEGs by pathway enrichment and functional analysis;
• (2) determining a benefit score comprising:
• (2.1) selecting one of more biological activities from 1.5 that are associated with said pathology or pathological state to be treated by the therapeutic product of interest;
• (2.2) converting the numerical values of 1.5, by use of a data processor, into absolute values;
• and
• (2.3) summing, by use of a data processor, said absolute values of each of the one or more biological activities from 2.2 thereby obtaining a benefit score for the therapeutic product of interest;
• (3) determining a risk score comprising:
• (3.1) providing a listing of side effects associated with the reference drug of 1.2;
• (3.2) identifying determining one or more biological activities associated with said side effects;
• (3.3) identifying a relationship between the gene expression in 1.4 and said one or more biological activities in 3.2 using an in-silico model of said pathology or pathological state by pathway and functional analysis;
• (3.4) identifying the degree of regulation of each of said one or more biological activity in 3.2 by inputting, in a data processor, the fold change value for each of said DEG in 1.4 to said in-silico model using pathway and functional analysis, and transforming said degree of regulation into absolute numerical values;
• and
• (3.5) obtaining a risk score of the therapeutic product of interest by summing, through use of a data processor, the absolute numerical values in 3.4;
• (4) providing a benefit/risk score for the therapeutic product of interest as the ratio of the benefit score value obtained in 2.3 and the risk score value obtained in 3.5.