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Zeev Elkoshi Research and Development Department, Taro Pharmaceutical Industries Ltd, Haifa, IsraelCorrespondence: Zeev Elkoshi, Email zeev.elkoshi@gmail.comAbstract: Carcinogenic viruses (oncoviruses) can initiate cancer, but their impact on established cancer varies. Some of these viruses prolong survival while others shorten it. This study classifies oncoviruses into two categories: viruses which induce a strong CD8+T cell reaction in non-cancerous tissues, and viruses which induce a weak CD8+ T cell reaction in non-cancerous tissues. The classification proves useful in predicting the effect of oncoviruses on the prognosis of solid cancers. Therefore, while eliminating carcinogenic viruses in healthy individuals (for example by immunization) may be important for cancer prevention, this study suggests that only viruses which induce a weak CD8+ T cell reaction should be eradicated in established solid tumors. The model correctly predicts the effect of oncoviruses on survival for six out of seven known oncoviruses, indicating that immune modulation by oncoviruses has a prominent effect on prognosis. It seems that CD8+ T cell response to oncoviruses observed in infected benign tissues is retained in infected tumors. Clinical significance: the effect of oncoviruses on solid cancer prognosis can be predicted with confidence based on immunological responses when clinical data are unavailable.Keywords: carcinogenic viruses, oncoviruses, cancer prognosis, CD8+ T cell, Treg cells

Zeev Elkoshi Research and Development Department, Taro Pharmaceutical Industries Ltd, Haifa, IsraelCorrespondence: Zeev Elkoshi, Email zeev.elkoshi@gmail.comAbstract: A binary classification of the pathogenic immune reactions as anti-inflammatory high-Treg reactions or pro-inflammatory low-Treg reactions explains both the relatively low incidence rate of several types of cancer, and the relatively high incidence rate of herpes zoster cases diagnosed in the summer compared to cases diagnosed in the winter (in regions with temperate climate). This binary model also elucidates the longer survival of cancer patients diagnosed during the summer compared to these diagnosed in the winter. The three key elements of this explanation are: (a) the effect of sunlight on Treg production; (b) the evolvement of cancer from a low-Treg condition at early stage, to a high-Treg condition at advanced stage, and (c) the evolvement of herpes zoster from a high-Treg condition at pre-exudative stage to a low-Treg condition at acute exudative stage. A significant proportion of indolent tumors at the time of diagnosis (> 20%) is a prerequisite for a beneficial effect of sunlight on cancer incidence rate and prognosis. This prerequisite restricts the beneficial effect of diagnosis during summer to certain types of cancer. Clinical implication: the prognosis of early stage tumors may be improved by a course of corticosteroid (or other immunosuppressant) treatment.Keywords: cancer, herpes zoster, Treg cells, vitamin D, UV radiation, incidence rate, cancer prognosis

Zeev Elkoshi Research and Development Department, Taro Pharmaceutical Industries Ltd, Haifa, IsraelCorrespondence: Zeev Elkoshi Email zeev.elkoshi@gmail.comAbstract: In an earlier publication a binary model for chronic diseases classification has been proposed. According to the model, chronic diseases were classified as “high Treg” or “low Treg” diseases, depending on whether the immune response is anti- or pro-inflammatory and assuming that regulatory T cells are major determinants of the response. It turned out that most cancers are “high Treg” diseases, while autoimmune diseases are “low Treg”. This paper proposes a molecular cause for this binary response. The mechanism proposed depends on the effect of protein kinases on the immune system. Thus, protein kinases are classified as anti- or pro-inflammatory kinases depending on whether they drive “high Treg” or “low Treg” diseases. Observations reported in the earlier publication can be described in terms of anti-inflammatory kinase (AIK) or pro-inflammatory kinase (PIK) activity. Analysis of literature data reveals that the two classes of kinases display distinctive properties relating to their interactions with pathogens and environmental factors. Pathogens that promote Treg activity (“high Treg” pathogens) activate AIKs, while pathogens that suppress Treg activity (“low Treg” pathogens) activate PIKs. Diseases driven by AIKs are associated with “high Treg” pathogens while those diseases driven by PIKs are associated with “low Treg” pathogens. By promoting the activity of AIKs, alcohol consumption increases the risk of “high Treg” cancers but decreases the risk of some “low Treg” autoimmune diseases. JAK1 gain-of-function mutations are observed at high frequencies in autoimmune diseases while JAK1 loss-of-function mutations are observed at high frequencies in cancers with high tumor-infiltrating Tregs. It should also be noted that the corresponding two classes of protein kinase inhibitors are mutually exclusive in terms of their approved therapeutic indications. There is no protein kinase inhibitor that is approved for the treatment of both autoimmune diseases and “high Treg” cancers. Although there are exceptions to the conclusions presented above, these conclusions are supported by the great bulk of published data. It therefore seems that the binary division of protein kinases is a useful tool for elucidating (at the molecular level) many distinctive properties of cancers and autoimmune diseases.Keywords: protein kinases, regulatory T cells, autoimmunity, cancer, inflammation

Zeev Elkoshi Research and Development Department, Taro Pharmaceutical Industries Ltd, Haifa, IsraelCorrespondence: Zeev Elkoshi Email zeev.elkoshi@gmail.comAbstract: In an earlier publication, a binary classification of chronic diseases has been proposed. Chronic diseases were classified as “high Treg” or “low Treg” diseases depending on whether the pro-inflammatory or the anti-inflammatory arms of the immune response are deficient. The present work uses this model to analyze the interplay between cancer and the immune system, based on published literature. The work leans upon the etiology of alcohol and tobacco-related malignancies. The main conclusions are: triggers of specific “high Treg” immune reaction promote most non-hematologic cancers, whereas triggers of “low Treg” immune reaction promote lymphomas. The opposite is also true: triggers of specific “high Treg” immune reaction suppress lymphoma, whereas triggers of “low Treg” immune reaction suppress non-hematologic cancers. Both lymphoma and autoimmune diseases are “low Treg” conditions. For this reason, both are promoted by the same panel of “low Treg” bacteria and parasites and are inhibited by “high Treg” triggers. For example, alcohol consumption, a “high Treg” trigger, protects against lymphoma and autoimmune hypothyroidism. In addition, the same immune-modulatory drugs are effective in the treatment of both lymphoma and autoimmune diseases. Like other cancers, lymphoma transforms from a “low Treg” type at early stage of the disease into a “high Treg” type at advanced stages. However, lymphoma is distinguished from most other cancers by the length of time it dwells at an indolent “low Treg” state (many years) before lymphoma cells sensitivity to transforming growth factor-beta is impaired. This impairment stimulates the switch from “low Treg” into “high Treg” response and results in immune escape. The application of this analysis to the pharmacological activity of checkpoint inhibitors forecasts that checkpoint inhibitors would not be effective in low-grade, indolent lymphomas. As of now, checkpoint inhibitors are approved for the treatment of advanced lymphoma only.Keywords: regulatory T cells, lymphoma, cancer, alcohol consumption, cigarette smoking, checkpoint inhibitors, high Treg, low Treg, inflammation, autoimmune diseases, immune escape

Zeev Elkoshi Taro Pharmaceutical Industries, Haifa Bay, IsraelCorrespondence: Zeev Elkoshi Email Zeev.elkoshi@taro.co.ilAbstract: Acute diseases start with an insult and end when insult disappears. If the trauma induces an immune reaction (which happens in most cases), this reaction must be terminated with some type of resolution mechanism, when the cause of the trauma ceases. Chronicity develops if insult is permanent or if the resolution mechanism is defective. Another way to reach disease chronicity is a positive feedback loop, whereby the immune reaction activates an internal, insult-like reaction. A distinction between chronic states characterized by a persistent, low suppressive effect and those characterized by a persistent, high suppressive effect of regulatory T cells (Treg), is proposed. This two-class division represents two ways to reach chronicity: (a) by maintaining inflammatory reaction long after insult disappears (“low Treg”), or (b) by suppressing inflammatory reaction prior to the disappearance of insult (“high Treg”). This two-class division may explain the strong association between certain pathogens and cancer, on one hand, and between several other pathogens and autoimmunity, on the other hand. The weak association between autoimmune diseases and HIV infection and the relatively weak association between autoimmune diseases and cancer may be elucidated as well. In addition, the model rationalizes why immune-modulating drugs, which are effective in cancer, are also effective in “high Treg” viral infections, while corticosteroids, which are generally effective in autoimmune diseases, are also effective in other “low Treg” diseases (such as asthma, atopic dermatitis, and “low Treg” infections) but are not effective in solid malignancies and “high Treg” infections. Moreover, the model expounds why certain bacteria inhibit tumor growth and why these very bacteria induce autoimmune diseases.Keywords: Treg cells, cancer, autoimmunity, inflammation, chronic diseases, immune-therapy, corticosteroids

Objective: To evaluate the bioequivalence of two enteric-coated formulations of omeprazole, Losec (reference) and Omepradex (test). It is hypothesised that formulation differences may be accentuated following multiple-dose administration, and that testing after multiple administration may therefore provide a more sensitive assessment of bioequivalence. Study participants and design: The study comprised two parts: an in vitro dissolution test and an in vivo bioavailability study. The latter was a randomised, two-way crossover comparative study after a single dose and after multiple doses in healthy volunteers. Forty subjects were randomly allocated to receive either test or reference product, once daily in the morning, and blood samples were taken on days 1 and 5. Standard pharmacokinetic analyses were performed, and analysis of variance (ANOVA) was used to compare the log-transformed variables in a model including terms for treatment, subject and period. Results: Although both products meet the formal requirements specified by the United States Pharmacopoeia (USP) for enteric-coated articles, the in vitro dissolution experiments revealed widely differing properties for the two tested products. Less than 10% of the drug content was recovered from the Omepradex formulation following a pre-exposure to pH 3 or 4, compared with over 90% recovered from the Losec formulation. These findings were in agreement with the results of the in vivo bioavailability study, which showed that the two products differed in both their rate and extent of absorption after a single dose and following multiple doses. The products failed the bioequivalence test for area under the plasma concentration-time curve (AUC) and maximum plasma drug concentration (C) after a single dose [AUC: test/reference ratio 0.85, 90% confidence interval (0.76-0.95); C: test/reference ratio 0.85, 90% confidence interval (0.75-0.95)], and the difference between the formulations was even more pronounced after multiple doses [AUC: test/reference ratio 0.73, 90% confidence interval (0.65-0.83); C: test/reference ratio 0.71, 90% confidence interval (0.63-0.81)]. Conclusions: These data suggest that bioequivalence studies on enteric-coated proton pump inhibitors should include both single- and multiple-dose elements to be fully decisive. The two omeprazole products failed to show bioequivalence, with the observed differences being even more apparent after multiple doses, as postulated. Based on this study, the two products may not be considered either therapeutically equivalent or interchangeable. [ABSTRACT FROM AUTHOR]

Corticosteroids and immunosuppressive drugs can alleviate the symptoms of most autoimmune diseases and induce remission by restraining the autoimmune attack and limiting the damage to the target tissues. However, four autoimmune non-degenerative diseases-adult advanced type 1 diabetes mellitus, Hashimoto's thyroiditis, Graves' disease, and advanced primary biliary cholangitis-are refractory to these drugs. This article suggests that the refractoriness of certain autoimmune diseases is due to near-total loss of secreting cells coupled with the extremely low regenerative capacity of the affected tissues. The near-complete destruction of cells responsible for secreting insulin, thyroid hormones, or biliary HCO 3 - diminishes the protective effects of immunosuppressants against further damage. The slow regeneration rate of these cells hinders tissue recovery, even after drug-induced immune suppression, thus preventing remission. Although the liver can fully regenerate after injury, severe primary biliary cholangitis may impair this ability, preventing liver recovery. Consequently, these four autoimmune diseases are resistant to immunosuppressive drugs and corticosteroids. In contrast, early stages of type 1 diabetes and early primary biliary cholangitis, where damage to secreting cells is partial, may benefit from immunosuppressant treatment. In contrast to these four diseases, chronic degenerative autoimmune conditions like multiple sclerosis may respond positively to corticosteroid use despite the limited regenerative potential of the affected tissue (the central nervous system). The opposite is true for acute autoimmune conditions like Guillain-Barré syndrome., Competing Interests: ZE is employed by Taro Pharmaceutical Industries Ltd., (Copyright © 2024 Elkoshi.)

The risk of cancer is higher in patients with asthma compared to those with allergic rhinitis for many types of cancer, except for certain cancers where a contrasting pattern is observed. This study offers a potential explanation for these observations, proposing that the premalignant levels of circulating transforming growth factor-β (TGF-β), IL-1β, and IL-6 as well as the reactivity of the TGF-β/Smad signaling pathway at the specific cancer site, are crucial factors contributing to the observed disparities. Circulating TGF-β, IL- β and IL-6 levels also help clarify why asthma is positively associated with obesity, Type 2 diabetes, hypertension, and insulin resistance, whereas allergic rhinitis is negatively linked to these conditions. Furthermore, TGF-β/Smad pathway reactivity explains the dual impact of obesity, increasing the risk of certain types of cancer while offering protection against other types of cancer. It is suggested that the association of asthma with cancer and metabolic dysregulations is primarily linked to the subtype of neutrophilic asthma. A binary classification of TGF-β activity as either high (in the presence of IL-1β and IL-6) or low (in the presence or absence of IL-1β and IL-6) is proposed to differentiate between allergy patients prone to cancer and metabolic dysregulations and those less prone. Glycolysis and oxidative phosphorylation, the two major metabolic pathways utilized by cells for energy exploitation, potentially underlie this dichotomous classification by reprogramming metabolic pathways in immune cells., Competing Interests: ZE was employed by the company Taro Pharmaceutical Industries Ltd., (Copyright © 2024 Elkoshi.)

Tumor-infiltrating lymphocytes are extensively used as prognostic biomarkers in cancer. Regulatory T cells (Tregs) or CD8+ T cells frequencies in tumor site, or their ratio, are the most common markers used to assess prognosis. This work offers a possible explanation for the opposite correlations between intra-tumoral Tregs and survival, associated with different types of cancer. The complexity involved with the selection of a preferred marker, including the effect of variability, is presented and discussed. The lymphocytes frequency ratio is proposed as the marker of choice in most types of cancer. The ratio correlates directly with survival, irrespective of cancer type and is also less variable than the frequencies of each of the two lymphocytes, if these frequencies correlate with each other in the tumor microenvironment. However, if the frequency of one of the two lymphocytes is highly variable, abandoning the ratio in favor of the lymphocyte with less variable frequency will improve correlation with survival, especially when the intra-tumoral frequencies of the two species are inversely correlated. It is plausible, that the best prognostic marker selected this way, will be also be the best predictor of checkpoint inhibitor therapy success., Competing Interests: The author is an employee of Taro Pharmaceutics, Israel., (Copyright © 2022 Elkoshi.)

Competing Interests: Author ZE is employed by Taro Pharmaceutical Industries Ltd.

The present article compares, side-by-side, cancer and autoimmune diseases in terms of innate and adaptive immune cells involvement, MHC Class I and Class II expression, TGFβ effect, immune modulating drugs effect and the effect of reactive oxygen species. The change in the inflammatory immune reaction during the progress of cancer and the effect of this change on the comorbidity of autoimmune diseases and cancer are discussed. The similar inflammatory properties of autoimmune diseases and early cancer, and the contrasting inflammatory properties of autoimmune diseases and advanced cancer elucidate the increased incidence of many types of cancer in patients with pre-existing autoimmune diseases and the decreased cancer-specific mortality of these patients. Stage-dependent effects of reactive oxygen-species on tumor proliferation are an additional probable cause for these epidemiological observations. The relationship: {standardized incidence ratio (SIR)} > {cancer-specific hazard ratio (HR)} for cancer patients with a history of autoimmune diseases is substantiated and rationalized., Competing Interests: ZE is employed by Taro Pharmaceutical Industries Ltd., (Copyright © 2022 Elkoshi.)

A binary model for the classification of chronic diseases has formerly been proposed. The model classifies chronic diseases as "high Treg" or "low Treg" diseases according to the extent of regulatory T cells (Treg) activity (frequency or function) observed. The present paper applies this model to severe acute respiratory syndrome coronavirus 2 (SARS - CoV - 2) infection. The model correctly predicts the efficacy or inefficacy of several immune-modulating drugs in the treatment of severe coronavirus disease 2019 (COVID-19) disease. It also correctly predicts the class of pathogens mostly associated with SARS-CoV-2 infection. The clinical implications are the following: (a) any search for new immune-modulating drugs for the treatment of COVID-19 should exclude candidates that do not induce "high Treg" immune reaction or those that do not spare CD8+ T cells; (b) immune-modulating drugs, which are effective against SARS-CoV-2, may not be effective against any variant of the virus that does not induce "low Treg" reaction; (c) any immune-modulating drug, which is effective in treating COVID-19, will also alleviate most coinfections; and (d) severe COVID-19 patients should avoid contact with carriers of "low Treg" pathogens., Competing Interests: ZE is employed by Taro Pharmaceutical Industries Ltd., (Copyright © 2021 Elkoshi.)

A procedure based on release rates is proposed for the establishment of dissolution specifications that ensure the bioequivalence of a test and a reference product. This procedure, which confines Cmax (the maximum concentration of the drug in vivo) and AUCinfinity (the area under the time-concentration curve, extrapolated to infinity) values within any desired range (relative to a reference product), can be used as an alternative to the methods presented in the FDA guidance1 or the USP.2 The method is appropriate for zero-order or first-order release products with linear Level A in vitro/in vivo correlations (IVIVC). Based on the result that the relative difference in Cmax must always be smaller than the relative difference in the absorption rate constants (for any test and reference products of a given drug), the "minimum range" specifications are set. These specifications, which are identical for both zero-order and first-order release products, are of general validity. They depend only on the relative extents of release, but are otherwise drug or formulation independent. For certain extended release products demonstrating a constant release rate that is unaffected by dissolution conditions (thus allowing the assumption of Level A IVIVC), the "minimum range" dissolution limits are applicable even when in vivo data is not available. If the reference product in vivo data is available, wider limits (which are product specific) may be set. If the drug disposition is monoexponential, the specifications generated are the widest possible. They are termed the "ideal" specifications. In the case of a multiexponential disposition, the limits set by the procedure will (generally) not be the widest possible. Although the method is based on one-compartment models, it is essentially model independent in the sense that microscopic modeling is redundant for its application.

Purpose: To investigate dissolution data variability and its origins., Methods: The Weibull function with four parameters t0 (dissolution lag-time), K (the rate parameter), beta (the shape parameter) and D (the fraction dissolved as t-->infinity), is used to describe the dissolution curve. The variance of the dissolution data is expressed in terms of these parameters and their individual variances sigma t02, sigma K2, sigma beta 2, and sigma D2. These four variances originate from variable physical properties of the dosage units and from a variable dissolution environment. Therefore, dissolution data variability depends on both, the functional form of the curve and on the variance of the physical conditions. The use of this method enables the elucidation of the sources of dissolution data variability., Results: In the case of a sigmoidal dissolution curve (beta > 1), data variance is zero as dissolution begins (following dissolution lag-time). This initial variance diverges when the dissolution curve is non-sigmoidal (with beta < 1) but assumes a finite value, proportional to the dissolution lag-time variance (sigma t02) when the data fits a regular first order rate curve (beta = 1). Following a long dissolution time, data variance attains a constant value equal to the dissolution extent variance, sigma D2. When the dissolution curve is sigmoidal and the variability related to the dissolution extent is sufficiently small (sigma D/D < < 1), a maximum in the variance is expected at some intermediate time point (corresponding to the curve inflection point, when the main source of variability is dissolution lag-time t0, or around t = 1/K + t0, when the main sources of variability are the rate parameter K or the shape parameter beta). When the curve is sigmoidal (beta > 1) and the main source of variability relates to the dissolution extent, the overall variance grows with time all the way to the plateau of the dissolution curve. With a non-sigmoidal dissolution curve (beta < or = 1), data variability decreases with time soon after dissolution begins. In that case, if the main source of variability is the dissolution lag-time (t0), the variance decreases all the way to the plateau of the dissolution curve. If the dissolution extent, D, is the main source of variability, a minimum in the variance is expected at some intermediate time point. The dissolution relative variance, on the other hand, diverges as dissolution begins and decreases with time at least until 63% of the drug is released, irrespective to the Weibull parameter values. Later, it may decrease or increase, attaining a fixed value (sigma D2/D2) at the plateau of the dissolution curve., Conclusions: The particular time dependence of dissolution data variance is well defined in terms of the Weibull shape parameters and their individual variances. Dissolution data variability may decrease or increase with time long the curve. It may attain a maximum or a minimum value at some intermediate time point. It may converge or diverge as dissolution begins. When the dissolution data is well fitted to the Weibull function, the sources of data variability (in terms of the Weibull parameters) may be elucidated. The variability of dissolution data originates from physical sources but is also dependent on the functional form of the curve.