Methods for determining responsiveness to TYK2 inhibitors

Abstract

Disclosed are methods of treating psoriatic arthritis in a subject, comprising administering to the subject a TYK2 inhibitor (e.g., deuclavacitinib), wherein the method is dependent upon whether the subject exhibits certain levels of certain proteins in the subject's blood (e.g., plasma or serum) prior to or at an initial stage of administration of the TYK2 inhibitor. Also disclosed are methods of selecting a subject suffering from psoriatic arthritis for treatment with a TYK2 inhibitor, wherein the subject is selected based on the amount of one or more proteins in the subject's blood prior to treatment with the TYK2 inhibitor.

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) This application claims priority to U.S. Provisional Application No. 63 / 250,735, filed September 30, 2021, U.S. Provisional Application No. 63 / 257,407, filed October 19, 2021, and U.S. Provisional Application No. 63 / 330,308, filed April 12, 2022, all of which are incorporated by reference herein.

[0002] (Technical field) The present invention generally relates to a method of treating psoriatic arthritis in a subject, comprising administering a tyrosine kinase 2 (TYK2) inhibitor to the subject, the method being dependent on whether a certain level of a particular protein is present in the subject's blood prior to or at the beginning of administration of the TYK2 inhibitor.The present invention also relates to a method of selecting a subject suffering from psoriatic arthritis for treatment with a TYK2 inhibitor based on the amount of one or more particular proteins in the subject's blood prior to treatment with the TYK2 inhibitor.An embodiment of the present invention further relates to administering deuclavacitinib to the subject. [Background technology]

[0003] Inflammatory and autoimmune diseases, such as arthritis, inflammatory bowel disease, psoriasis, and psoriatic arthritis, are common problem diseases. Such conditions are often chronic or recurrent, and require long-term treatment to improve symptoms. However, many of the therapies that can treat these diseases do not provide sufficient clinical benefit to all patients who receive treatment. Furthermore, for patients who do not respond adequately to treatment, it may be costly to treat them before they can achieve therapeutic benefit. The ability to select effective treatments early after diagnosis is of great benefit to patients suffering from these conditions in terms of medical expenses and other costs and burdens, and also contributes to society.

[0004] Given the progressive and destructive nature of psoriatic arthritis and its comorbidities (e.g., cardiovascular disease, osteoporosis, and metabolic syndrome), delays in effective treatment in patients with psoriatic arthritis can have a significant impact on quality of life and physical function. Psoriatic arthritis can occur after the progression of psoriasis, and patients with psoriatic arthritis often present with a variety of symptoms and signs of disease. The Classification Criteria for Psoriatic Arthritis (CASPAR) includes features typical of psoriatic arthritis (e.g., psoriasis, nail disease, dactylitis, and negative serum rheumatoid factor).

[0005] There is a need in the art to develop new therapeutic strategies in the treatment of psoriatic arthritis, which can be used, for example, to predict a patient's response to therapy before or early in treatment.

[0006] The present invention meets such a need. The present invention provides a treatment strategy that can be used to identify patients with psoriatic arthritis who are likely to respond to treatment, i.e., treatment that includes a TYK2 inhibitor. The aim of the present invention is to provide more effective and / or more tolerable treatment for patients with psoriatic arthritis by identifying patients with psoriatic arthritis who are likely to respond to a TYK2 inhibitor. Such a treatment strategy can, for example, increase the probability that a patient will benefit from a TYK2 inhibitor treatment.

[0007] Summary of the Invention An embodiment of the present invention provides a method for identifying a disease in a subject susceptible to treatment with a TYK2 inhibitor, comprising determining the amount of one or more specific proteins in the subject's blood (e.g., whole blood, serum, or plasma), and a protein level above a certain threshold indicates a disease susceptible to treatment with a TYK2 inhibitor. The method may further comprise administering a TYK2 inhibitor to a patient with a disease identified as susceptible to treatment with a TYK2 inhibitor. Such a method may improve the efficacy of TYK2 inhibitor treatment by administering a TYK2 inhibitor to a portion of patients who respond better to a TYK2 inhibitor compared to the response of a patient population suffering from the same disease (including patients not belonging to the "subset of patients"). In an embodiment described herein, the disease is psoriatic arthritis.

[0008] Accordingly, one embodiment of the present invention relates to a method for selecting a patient with psoriatic arthritis for treatment with a TYK2 inhibitor, comprising: (a) measuring (or obtaining from measuring) one or more protein levels in a blood sample of the patient, wherein the one or more proteins are selected from β-defensin 2, interleukin (IL)-19, and IL-17A; (b) comparing each protein level measured in (a) to a threshold level for that protein; and (c) selecting the patient for treatment with a TYK2 inhibitor if the protein level of at least one of the one or more proteins measured in (a) is above the threshold level. As shown herein, a protein level above the threshold indicates that the patient's psoriatic arthritis is susceptible to treatment with a TYK2 inhibitor. The one or more proteins measured in (a) can include any one protein or any combination of proteins selected from β-defensin 2, IL-19, and IL-17A. These proteins can be measured from a serum or plasma sample of the patient.

[0009] In some embodiments, the methods further comprise measuring the amount of C-reactive protein in the blood sample, comparing the level of C-reactive protein in the blood sample to a threshold level of C-reactive protein, and selecting the patient for treatment with a TYK2 inhibitor if the level of β-defensin 2, IL-19, and / or IL-17A is above the threshold level for each protein, and if the level of C-reactive protein is above its threshold level. In certain embodiments of the methods described herein, the patient selected for treatment with a TYK2 inhibitor has a level of C-reactive protein in his blood that is above a predetermined threshold level of C-reactive protein.

[0010] In any of the above-mentioned embodiments, if the patient is selected for treatment with a TYK2 inhibitor, the method further comprises administering the TYK2 inhibitor to the patient. Further, in any of the above-mentioned embodiments, the TYK2 inhibitor can be deuclavacitinib.

[0011] Also, embodiments of the present invention relate to a method of treating psoriatic arthritis in a subject (e.g., a patient diagnosed with psoriatic arthritis), comprising: (a) measuring the level of one or more proteins selected from β-defensin 2, IL-19, and IL-17A in a blood sample (e.g., a serum sample or a plasma sample) of the subject; (b) comparing each of the levels of the proteins measured in (a) with a threshold level for the protein; and (c) administering a TYK2 inhibitor to the subject if the level of at least one protein measured in (a) is above its threshold level.In further embodiments, for example, at least two proteins are measured in (a), and if the levels of each of the two proteins measured in the blood sample are above their threshold level, a TYK2 inhibitor is administered to the subject.In one embodiment, the TYK2 inhibitor is deuclavacitinib.

[0012] Thus, in some embodiments described herein, the method comprises measuring (or obtaining from) the levels of two proteins (e.g., beta-defensin 2 and IL-19), and selecting the subject for treatment with or administering a TYK2 inhibitor to the subject if the measured levels of each of the two proteins in the sample are above its threshold level (e.g., the measured beta-defensin 2 in the sample is above a threshold level for beta-defensin 2 and the measured IL-19 in the sample is above a threshold level for IL-19). In certain embodiments, the method may comprise measuring the levels of all three proteins (i.e., beta-defensin 2, IL-19, and IL-17A), and selecting the subject for treatment with or administering a TYK2 inhibitor to the subject if the measured levels of any two of the three proteins are above a threshold level for that protein.

[0013] In some embodiments, the present invention provides a method for selecting a psoriatic arthritis patient for treatment with a TYK2 inhibitor, comprising comparing the levels of beta-defensin 2, IL-19, and / or IL-17A in the patient's blood to respective threshold levels (each protein having its own respective threshold level), and selecting the patient for treatment with the TYK2 inhibitor if the levels of beta-defensin 2, IL-19, and / or IL-17A in the blood are above the respective threshold levels. A further embodiment of the method also features administering the TYK2 inhibitor to the patient selected for treatment with the TYK2 inhibitor.

[0014] In some embodiments, the threshold level for each protein may be a pre-determined level based on, for example, protein levels measured in (i) a population of psoriatic arthritis patients previously treated with a TYK2 inhibitor and responsive to the TYK2 inhibitor, (ii) a population of psoriatic arthritis patients previously treated with a TYK2 inhibitor and unresponsive to the TYK2 inhibitor, and / or (iii) a population of psoriatic arthritis patients not treated with a TYK2 inhibitor. For example, in some embodiments, the threshold level for β-defensin 2 may be based on the median β-defensin 2 levels measured in blood samples from a population of psoriatic arthritis patients not treated with a TYK2 inhibitor. [Brief description of the drawings]

[0015] [Figure 1A] FIG. 1A shows box plots of serum β-defensin 2 (BD2) levels (log2 values) in baseline healthy volunteers (NHV) and psoriatic arthritis (PsA) patients as described in the Examples. [Figure 1B] FIG. 1B is a scatter plot showing baseline values ​​of BD2 levels (log2 values, ng / L) measured in PsA patients as described in the Examples on the x-axis and baseline values ​​of PASI scores on the y-axis. [Figure 2A] FIG. 2A shows box plots of serum IL-19 levels (log2 values) at baseline in healthy volunteers (NHV) and PsA patients as described in the Examples. [Figure 2B] FIG. 2B is a scatter plot showing baseline values ​​of IL-19 levels (log2 values, ng / L) measured in PsA patients as described in the Examples on the x-axis and baseline values ​​of PASI scores on the y-axis. [Figure 3A] FIG. 3A shows box plots of serum IL-17A levels (log2 values) at baseline in healthy volunteers (NHV) and psoriatic arthritis (PsA) patients as described in the Examples. [Figure 3B] FIG. 3B is a scatter plot showing baseline values ​​of IL-17A levels (log2 values, ng / L) measured in PsA patients as described in the Examples on the x-axis and baseline values ​​of PASI scores on the y-axis. [Figure 4] Figure 4 shows box plots of baseline PASI scores for PASI75 non-responders and PASI75 responders in each treatment group (placebo, 6 mg deuclavacitinib (QD), and 12 mg deuclavacitinib (QD)) described in the Examples. QD refers to administration of a specific dose (6 mg deuclavacitinib or 12 mg deuclavacitinib) once a day. [Diagram 5] FIG. 5 shows box plots of baseline serum BD2 levels (ng / L) in PASI75 non-responders and PASI75 responders in each treatment group described in the Examples (placebo, 6 mg deucelavacitinib (QD), and 12 mg deucelavacitinib (QD)). [Figure 6] FIG. 6 shows box plots of baseline serum BD2 levels (ng / L) in ACR20 non-responders and ACR20 responders in each treatment group described in the Examples (placebo, 6 mg deucelavacitinib (QD), and 12 mg deucelavacitinib (QD)). [Figure 7] FIG. 7 is a bar graph showing PASI 75 response rates at week 16 for each treatment group described in the Examples for patients categorized according to baseline BD2 levels. The "all patients" group includes patients with high BD2 and patients with low BD2, where the "high BD2" group includes patients with baseline BD2 levels above the median of 9,265 ng / L, and the "low BD2" group includes patients with baseline BD2 levels below the median of 9,265 ng / L. The y-axis shows the PASI 75 response rate, and the response rate (%) for each treatment group in each group is shown above the bar graph. Error bars indicate 95% confidence intervals. [Figure 8]Figure 8 is a bar graph showing the ACR20 response rate at week 16 in each of the treatment groups described in the Examples for patients classified according to baseline BD2 levels. The "all patients" group includes patients with high BD2 and patients with low BD2, where the "high BD2" group includes patients with baseline BD2 levels above the median of 9,265 ng / L, and the "low BD2" group includes patients with baseline BD2 levels below the median of 9,265 ng / L. The y-axis shows the ACR20 response rate, and the response rate (%) for each treatment group in each group is shown above the bar graph. Error bars indicate 95% confidence intervals. [Figure 9] 9 shows line graphs of PASI75 response rates in each treatment group (placebo, 6 mg deuclavacitinib (QD), and 12 mg deuclavacitinib (QD)) for high BD2 (line graph left) and low BD2 (line graph right) patient groups over 16 weeks of treatment as described in the Examples. Error bars indicate 95% confidence intervals. [Figure 10] Figure 10 shows line graphs of ACR20 response rates in each treatment group (placebo, 6 mg deuclavacitinib (QD), and 12 mg deuclavacitinib (QD)) for high BD2 (line graph left) and low BD2 (line graph right) patient groups over 16 weeks of treatment as described in the Examples. Error bars indicate 95% confidence intervals. [Figure 11] Figure 11 is a bar graph showing the PASI75 response rate at week 16 in each treatment group described in the Examples, when patients are classified according to baseline BD2 levels (above or below the median) and baseline PASI scores (above or below the median) into four groups: high BD2 and high PASI, high BD2 and low PASI, low BD2 and high PASI, and low BD2 and low PASI. The "all patients" group includes all patients in the four groups. The PASI75 response rate is shown at the top of each bar. Error bars indicate 95% confidence intervals. [Figure 12]FIG. 12 shows box plots of baseline serum IL-19 levels (ng / L) in PASI75 non-responders and PASI75 responders in each treatment group described in the Examples (placebo, 6 mg deucelavacitinib QD, and 12 mg deucelavacitinib QD). [Figure 13] FIG. 13 shows box plots of baseline serum IL-19 levels (ng / L) in ACR20 non-responders and ACR20 responders in each treatment group described in the Examples (placebo, 6 mg deucelavacitinib (QD), and 12 mg deucelavacitinib (QD)). [Figure 14] FIG. 14 is a bar graph showing PASI 75 response rates at week 16 for each treatment group described in the Examples for patients categorized according to baseline IL-19 levels. The "all patients" group includes high and low IL-19 patients, where the "high IL-19" group includes patients with baseline IL-19 levels above the median of 36 ng / L, and the "low IL-19" group includes patients with baseline IL-19 levels below the median of 36 ng / L. The y-axis shows the PASI 75 response rate, and the response rate (%) for each treatment group in each group is shown above the bar graph. Error bars indicate 95% confidence intervals. [Figure 15] Figure 15 is a bar graph showing the ACR20 response rate at week 16 for each treatment group described in the Examples for patients classified according to baseline IL-19 levels. The "all patients" group includes high IL-19 and low IL-19 patients, where the "high IL-19" group includes patients with baseline IL-19 levels above the median of 36 ng / L, and the "low IL-19" group includes patients with baseline IL-19 levels below the median of 36 ng / L. The y-axis shows the ACR20 response rate, and the response rate (%) for each treatment group in each group is shown above the bar graph. Error bars indicate 95% confidence intervals. [Figure 16]Figure 16 shows line graphs of PASI75 response rates in each treatment group (placebo, 6 mg deuclavacitinib (QD), and 12 mg deuclavacitinib (QD)) for high IL-19 (line graph left) and low IL-19 (line graph right) patient groups over 16 weeks of treatment as described in the Examples. Error bars indicate 95% confidence intervals. [Figure 17] Figure 17 shows line graphs of ACR20 response rates in each treatment group (placebo, 6 mg deuclavacitinib (QD), and 12 mg deuclavacitinib (QD)) for high IL-19 (line graph left) and low IL-19 (line graph right) patient groups over 16 weeks of treatment as described in the Examples. Error bars indicate 95% confidence intervals. [Figure 18] Figure 18 is a bar graph showing the PASI75 response rate at week 16 in each treatment group described in the Examples, when patients are classified into four groups according to baseline IL-19 levels (above or below the median) and baseline PASI scores (above or below the median): high IL-19 and high PASI, high IL-19 and low PASI, low IL-19 and high PASI, and low IL-19 and low PASI. The "All Patients" group includes all patients in the four groups. The PASI75 response rate is shown at the top of each bar. Error bars indicate 95% confidence intervals. [Figure 19] FIG. 19 shows box plots of baseline serum IL-17A levels (ng / L) in PASI75 non-responders and PASI75 responders in each treatment group described in the Examples (placebo, 6 mg deucelavacitinib QD, and 12 mg deucelavacitinib QD). [Figure 20] FIG. 20 shows box plots of baseline serum IL-17A levels (ng / L) in ACR20 non-responders and ACR20 responders in each treatment group described in the Examples (placebo, 6 mg deucelavacitinib (QD), and 12 mg deucelavacitinib (QD)). [Figure 21]Figure 21 is a bar graph showing PASI75 response rates at week 16 for each treatment group described in the Examples for patients categorized according to baseline IL-17A levels. The "all patients" group includes high IL-17A and low IL-17A patients, where the "high IL-17A" group includes patients with baseline IL-17A levels above the median of 0.575 ng / L, and the "low IL-17A" group includes patients with baseline IL-17A levels below the median of 0.575 ng / L. The y-axis shows the PASI75 response rate, and the response rate (%) for each treatment group in each group is shown above the bar graph. Error bars indicate 95% confidence intervals. [Figure 22] Figure 22 is a bar graph showing the ACR20 response rate at week 16 for each treatment group described in the Examples for patients classified according to baseline IL-17A levels. The "all patients" group includes high IL-17A and low IL-17A patients, where the "high IL-17A" group includes patients with baseline IL-17A levels above the median of 0.575 ng / L, and the "low IL-17A" group includes patients with baseline IL-17A levels below the median of 0.575 ng / L. The y-axis shows the ACR20 response rate, and the response rate (%) for each treatment group in each group is shown above the bar graph. Error bars indicate 95% confidence intervals. [Figure 23] Figure 23 shows line graphs of PASI75 response rates in each treatment group (placebo, 6 mg deuclavacitinib (QD), and 12 mg deuclavacitinib (QD)) for high IL-17A (line graph left) and low IL-17A (line graph right) patient groups over 16 weeks of treatment as described in the Examples. Error bars indicate 95% confidence intervals. [Figure 24] Figure 24 shows line graphs of ACR20 response rates in each treatment group (placebo, 6 mg deuclavacitinib (QD), and 12 mg deuclavacitinib (QD)) for high IL-17A (line graph left) and low IL-17A (line graph right) patient groups over 16 weeks of treatment as described in the Examples. Error bars indicate 95% confidence intervals. [Diagram 25]Figure 25 is a bar graph showing the PASI75 response rate at week 16 in each treatment group described in the Examples, when patients are classified into four groups according to baseline IL-17A levels (above or below the median) and baseline PASI scores (above or below the median): high IL-17A and high PASI, high IL-17A and low PASI, low IL-17A and high PASI, and low IL-17A and low PASI. The "All Patients" group includes all patients in the four groups. The PASI75 response rate is shown at the top of each bar. Error bars indicate 95% confidence intervals. [Figure 26] Figure 26 is a forest plot showing odds ratio results for ACR20 responsiveness for each subgroup described in the Examples listed on the left, comparing 6 mg QD with placebo. The "N" in "Placebo" indicates the number of ACR20 responders in the placebo group, and the "N" in "Deucrava" indicates the number of ACR20 responders in the Deucrava treatment group (6 mg, QD). For example, there were 22 PsA patients in the Deucrava treatment group (6 mg, QD) who showed ACR20 responsiveness and were classified into the "high BD2" group. [Figure 27] Figure 27 is a forest plot showing odds ratio results for ACR20 responsiveness for each subgroup described in the Examples listed on the left, comparing 12 mg QD with placebo. The "N" for "Placebo" indicates the number of ACR20 responders in the placebo group, and the "N" for "Deucrava" indicates the number of ACR20 responders in the deucravacitinib treatment group (12 mg, QD). [Figure 28] Figure 28 is a forest plot showing odds ratio results for ACR20 responsiveness for each subgroup described in the Examples listed on the left, comparing Deucravacitinib (both arms) with placebo. The "N" for "Placebo" indicates the number of ACR20 responders in the placebo arm, and the "N" for "Deucrava" indicates the number of ACR20 responders in both Deucravacitinib arms combined. [Figure 29]Figure 29 is a forest plot showing odds ratio results for PASI75 response for each subgroup described in the Examples listed on the left, comparing 6 mg QD with placebo. The "N" for "Placebo" indicates the number of PASI75 responders in the placebo group, and the "N" for "Deucrava" indicates the number of PASI75 responders in the deucravacitinib treatment group (6 mg, QD). [Diagram 30] Figure 30 is a forest plot showing odds ratio results for PASI75 response for each subgroup described in the Examples listed on the left, comparing 12 mg QD with placebo. The "N" for "Placebo" indicates the number of PASI75 responders in the placebo group, and the "N" for "Deucrava" indicates the number of PASI75 responders in the deucravacitinib treatment group (12 mg, QD). [Diagram 31] Figure 31 is a forest plot showing odds ratio results for PASI75 response for each subgroup described in the Examples listed on the left, comparing Deucravacitinib (both arms) with placebo. The "N" for "Placebo" indicates the number of PASI75 responders in the placebo arm, and the "N" for "Deucrava" indicates the number of PASI75 responders in both Deucravacitinib arms combined. [Diagram 32] Figure 32 is a forest plot showing odds ratio results for PASI75 response for each subgroup described in the Examples listed on the left, comparing 6 mg QD with placebo, adjusting for baseline PASI scores. "N" for "Placebo" indicates the number of PASI75 responders in the placebo arm, and "N" for "Deucrava" indicates the number of PASI75 responders in the deucravacitinib arm (6 mg, QD). [Diagram 33] Figure 33 is a forest plot showing odds ratio results for PASI75 response for each subgroup described in the Examples listed on the left, comparing 12 mg QD with placebo, adjusting for baseline PASI scores. "N" for "Placebo" indicates the number of PASI75 responders in the placebo arm, and "N" for "Deucrava" indicates the number of PASI75 responders in the deucravacitinib arm (12 mg QD). [Diagram 34] Figure 34 is a forest plot showing odds ratio results for ACR20 responsiveness for each subgroup described in the Examples listed on the left, comparing 6 mg QD with placebo, adjusting for baseline DAS28. The "N" for "Placebo" indicates the number of ACR20 responders in the placebo group, and the "N" for "Deucrava" indicates the number of ACR20 responders in the deucravacitinib treatment group (6 mg, QD). [Diagram 35] Figure 35 is a forest plot showing odds ratio results for ACR20 responsiveness for each subgroup described in the Examples listed on the left, comparing 12 mg QD with placebo, adjusting for baseline DAS28. The "N" for "Placebo" indicates the number of ACR20 responders in the placebo group, and the "N" for "Deucrava" indicates the number of ACR20 responders in the deucravacitinib treatment group (12 mg, QD). [Diagram 36] FIG. 36 shows box plots of baseline serum CRP levels (mg / L) for PASI75 non-responders and PASI75 responders in each treatment group described in the Examples (placebo, 6 mg deucelavacitinib QD, and 12 mg deucelavacitinib QD). [Figure 37] FIG. 37 shows box plots of baseline serum CRP levels (mg / L) for ACR20 non-responders and ACR20 responders in each treatment group described in the Examples (placebo, 6 mg deucelavacitinib (QD), and 12 mg deucelavacitinib (QD)). [Figure 38] Figure 38 is a bar graph showing PASI75 response rates at week 16 for each treatment group described in the Examples for patients classified according to baseline CRP levels. The "all patients" group includes patients with high CRP and patients with low CRP, where the "high CRP" group includes patients with baseline CRP levels above the median of 8.31 ng / L, and the "low CRP" group includes patients with baseline CRP levels below the median of 8.31 ng / L. The y-axis shows the PASI75 response rate, and the response rate (%) for each treatment group in each group is shown above the bar graph. Error bars indicate 95% confidence intervals. [Figure 39]Figure 39 is a bar graph showing the ACR20 response rate at week 16 for each treatment group described in the Examples for patients classified according to baseline CRP levels. The "all patients" group includes patients with high CRP and patients with low CRP. Here, the "high CRP" group includes patients with baseline CRP levels above the median of 8.31 ng / L, and the "low CRP" group includes patients with baseline CRP levels below the median of 8.31 ng / L. The y-axis shows the ACR20 response rate, and the response rate (%) for each treatment group in each group is shown above the bar graph. Error bars indicate 95% confidence intervals. [Diagram 40] Figure 40 shows line graphs of PASI75 response rates in each treatment group (placebo, 6 mg deuclavacitinib (QD), and 12 mg deuclavacitinib (QD)) for high CRP (line graph left) and low CRP (line graph right) patient groups over 16 weeks of treatment as described in the Examples. Error bars indicate 95% confidence intervals. [Diagram 41] Figure 41 shows line graphs of ACR20 response rates in each treatment group (placebo, 6mg deuclavacitinib (QD), and 12mg deuclavacitinib (QD)) for high CRP (line graph left) and low CRP (line graph right) patient groups over 16 weeks of treatment as described in the examples. Error bars indicate 95% confidence intervals. [Diagram 42] Figure 42 is a bar graph showing the PASI75 response rate at week 16 in each treatment group described in the examples, when patients are classified according to baseline CRP level (above or below the median) and baseline PASI score (above or below the median) into four groups: high CRP and high PASI, high CRP and low PASI, low CRP and high PASI, and low CRP and low PASI. The "all patients" group includes all patients in the four groups. The PASI75 response rate is shown at the top of each bar. Error bars indicate 95% confidence intervals. [Figure 43A]Figure 43A is a line graph showing the percentage increase or decrease in serum BD2 levels from baseline in each treatment group over 16 weeks of treatment as described in the Examples. The y-axis shows the least squares mean, and the error bars show the standard error of the percentage increase or decrease from baseline. ***: P<0.001 vs. baseline, LS: least squares, SE: standard error [Figure 43B] FIG. 43B is a line graph showing the change from baseline in serum BD2 levels in PASI75 responders and non-responders in each treatment group over 16 weeks of treatment. The y-axis shows least squares means and standard errors adjusted for change from baseline. In the 12 mg QD treatment group, a significant decrease in serum BD2 levels was observed over time when comparing PASI75 responders to non-responders. Asterisks indicate significant differences between responders and non-responders. *: P<0.05, **: P<0.01 [Diagram 44] Figure 44 is a line graph showing the percentage increase or decrease in serum IL-19 levels from baseline in each treatment group over 16 weeks of treatment as described in the Examples. The y-axis shows the least squares mean, and the error bars show the standard error of the percentage increase or decrease from baseline. ***: P<0.001 vs. baseline, **: P<0.01 vs. baseline, *: P<0.05 vs. baseline, LS: least squares, SE: standard error [Diagram 45] Figure 45 is a line graph showing the percentage increase or decrease in serum IL-17A levels from baseline in each treatment group over 16 weeks of treatment as described in the Examples. The y-axis shows the least squares mean, and the error bars show the standard error of the percentage increase or decrease from baseline. ***: P<0.001 vs. baseline, *: P<0.05 vs. baseline, LS: least squares, SE: standard error [Diagram 46] Figure 46 is a line graph showing the rate of increase or decrease in serum CRP levels from baseline in each treatment group over 16 weeks of treatment as described in the Examples. The y-axis shows the least squares mean, and the error bars show the standard error of the rate of increase or decrease from baseline. ***: P<0.001 vs. baseline, *: P<0.05 vs. baseline, LS: least squares, SE: standard error DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] The features and advantages of the present invention may be more readily understood by those skilled in the art upon reading the following detailed description. It is understood that for clarity, certain features of the present invention that are described before or after the context of another embodiment may be combined to form a single embodiment. Conversely, various features of the present invention that are described in a single embodiment for brevity may also be combined to form subcombinations thereof.

[0017] Part of the present disclosure relates to identifying proteins and identifying specific protein levels for predicting the response of a subject's psoriatic arthritis to treatment comprising a TYK2 inhibitor. An embodiment of the present invention provides a method for determining whether a subject's psoriatic arthritis is amenable to treatment with a TYK2 inhibitor (e.g., deuclavacitinib), the method comprising determining the level of one or more specific proteins in the subject's blood (e.g., determining the level of one or more specific proteins in a whole blood, serum, or plasma sample), and a protein level above a specific threshold value for the protein indicates psoriatic arthritis amenable to treatment with a TYK2 inhibitor. The method may further comprise administering a TYK2 inhibitor to a subject with psoriatic arthritis determined to be amenable to treatment with a TYK2 inhibitor. Accordingly, an embodiment of the present invention provides a method for treating a subject with psoriatic arthritis, the method comprising (a) identifying a subject with psoriatic arthritis amenable to treatment with a TYK2 inhibitor (by a method described herein), and (b) administering a TYK2 inhibitor (e.g., deuclavacitinib) to the subject.

[0018] TYK2 is a member of the Janus kinase (JAK) family of non-receptor tyrosine kinases and has been shown to be crucial in downstream regulation of IL-12, IL-23, and type I interferon receptor signaling cascades in both mice and humans (mouse: Ishizaki, M. et al., "Involvement of tyrosine kinase-2 in both the IL-12 / Th1 and IL-23 / Th17 axes in vivo," J. Immunol., 187:181-189 (2011); Prchal-Murphy, M. et al., "TYK2 kinase activity is required for functional type I interferon responses in vivo," PLoS One, 7:e39141 (2012); human: Minegishi, Y. et al., "Human tyrosine kinase 2 deficiency reveals its requisite roles in multiple cytokine signals involved in innate and acquired immunity," Immunity, 25:745-755 (2006)). TYK2-deficient mice are resistant to experimental models of colitis, psoriasis, and multiple sclerosis (Ishizaki, M. et al., "Involvement of tyrosine kinase-2 in both the IL-12 / Th1 and IL-23 / Th17 axes in vivo," J. Immunol., 187:181-189 (2011); Oyamada, A. et al., "Tyrosine kinase 2 plays critical roles in the pathogenic CD4 T cell responses for the development of experimental autoimmune encephalomyelitis," J. Immunol., 183:7539-7546 (2009)).In humans, individuals expressing inactive mutants of TYK2 are free from multiple sclerosis and possibly other autoimmune diseases (Couturier, N. et al., "Tyrosine kinase 2 variant influences T lymphocyte polarization and multiple sclerosis susceptibility," Brain, 134:693-703 (2011)). Gene-wide association studies have shown that other variants in TYK2 are associated with autoimmune diseases (e.g., Crohn's disease, psoriasis, systemic lupus erythematosus, and rheumatoid arthritis), further demonstrating the importance of TYK2 in autoimmunity (Ellinghaus, D. et al., "Combined Analysis of Genome-wide Association Studies for Crohn's Disease and Psoriasis Identifies Seven Shared Susceptibility Loci," Am. J. Hum. Genet., 90:636-647 (2012); Graham, D. et al., "Association of polymorphisms across the tyrosine kinase gene, TYK2 in UK SLE families," Rheumatology (Oxford), 46:927-930 (2007); Eyre, S. et al., "High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis," Nat. Genet., 44:1336-1340 (2012).

[0019] The present invention relates to a method for identifying a subject suitable for treatment with a TYK2 inhibitor (e.g., deuclavacitinib). Generally, the subject suffers from an inflammatory disease or an autoimmune disease (e.g., psoriatic arthritis (PsA)). In some embodiments, the subject's disease is more likely to respond to a TYK2 inhibitor (e.g., deuclavacitinib) than not.

[0020] In some embodiments, the method comprises determining one or more protein levels in a blood sample (e.g., serum or plasma sample) of a subject, and comparing the protein levels to a threshold level. Wherein, a protein level above the threshold level indicates that the subject's disease is likely to respond to a TYK2 inhibitor (e.g., deuclavacitinib), and a protein level below the threshold level indicates that the subject's disease is not likely to respond to a TYK2 inhibitor (e.g., deuclavacitinib). The protein can include one or more of β-defensin 2 (BD2), IL-19, and IL-17A. In some embodiments, the method further comprises administering a TYK2 inhibitor (e.g., deuclavacitinib) to the subject.

[0021] For example, in some embodiments, subjects with psoriatic arthritis who are likely to respond to a TYK2 inhibitor (e.g., duravacitinib) have a baseline blood BD2 level above a predefined threshold BD2 level. In some embodiments, such threshold BD2 level is predefined by evaluating BD2 levels in a psoriatic arthritis patient population that has not been previously treated with a TYK2 inhibitor. In other embodiments, such threshold BD2 level is predefined by evaluating BD2 levels in a psoriatic arthritis patient population that has previously been treated with a TYK2 inhibitor and is responsive to the TYK2 inhibitor, and a psoriatic arthritis patient population that has previously been treated with a TYK2 inhibitor and is not responsive to the TYK2 inhibitor.

[0022] In another embodiment, as above, based on the baseline level of IL-19 or IL-17A of the subject.For example, in some embodiments, the subject of psoriatic arthritis that is likely to respond to TYK2 inhibitor (e.g., duravacitinib) has a baseline level of IL-19 in blood that is above a predetermined threshold level of IL-19.The baseline level of IL-19 can be used to determine whether the subject's psoriatic arthritis is likely to respond to TYK2 inhibitor in combination with the baseline level of BD2 of the subject and / or the baseline level of IL-17A of the subject.

[0023] Thus, in various embodiments described herein, the levels of one or more proteins (e.g., one or more of BD2, IL-19, and IL-17A) are assessed to select subjects for treatment with a TYK2 inhibitor (e.g., to identify subjects for administration of deuclavacitinib or another TYK2 inhibitor). In further embodiments, a combination of two or more proteins (e.g., any two or more of BD2, IL-19, and IL-17A) is used in the methods described herein.

[0024] In any of the embodiments described herein, a subject's baseline level of C-reactive protein (CRP), in combination with the subject's baseline levels of BD2, IL-19, and / or IL-17A, can be used to select a subject for treatment with a TYK2 inhibitor, or to predict or determine whether a subject's disease will respond to TYK2 inhibitor treatment.

[0025] In any of the embodiments described herein, a subject's baseline level of one or more clinical scores, in combination with the subject's baseline levels of BD2, IL-19, and / or IL-17A (and, where appropriate, the level of CRP), can be used to select a subject for treatment with a TYK2 inhibitor, or to predict or determine whether a subject's disease will respond to TYK2 inhibitor treatment.

[0026] In some embodiments, the present invention provides a method for treating PsA in a subject, comprising administering deuclavacitinib to the subject. The subject exhibits a certain protein level in a sample of one or more body fluids (e.g., whole blood, plasma, or serum) before or at the beginning of administration of deuclavacitinib. The certain protein may be one or more proteins described herein (e.g., BD2, IL-19, and / or IL-17A). As shown herein, higher levels of the protein improve the clinical benefit of deuclavacitinib administration, and PsA patients with higher baseline levels of one or more of the proteins (before treatment with a TYK2 inhibitor) respond better to deuclavacitinib than PsA patients with relatively lower baseline levels of the protein. Thus, blood levels of BD2, IL-19, and / or IL-17A can be used to identify patients with psoriatic arthritis who are amenable to treatment with a TYK2 inhibitor (e.g., deuclavacitinib).

[0027] Further, an embodiment of the present invention provides a method for selecting a subject (e.g., a PsA patient) for treatment with a TYK2 inhibitor (e.g., deuclavacitinib), comprising measuring the level of one or more proteins in a blood sample (e.g., a serum sample or a plasma sample) of the patient and comparing the protein level to a threshold level, where a protein level above the threshold level indicates that the patient's PsA is amenable to treatment with a TYK2 inhibitor (e.g., deuclavacitinib), and a protein level below the threshold level indicates that the patient's PsA is not amenable to treatment with a TYK2 inhibitor. The measured proteins may include one or more of beta-defensin 2 (BD2), IL-19, and IL-17A. As described above, each of these proteins may be used alone or as one of a composite index to identify PsA patients likely to respond to treatment including a TYK2 inhibitor (e.g., deuclavacitinib). In a further embodiment, the level of C-reactive protein (CRP) in the blood may be considered. In certain embodiments, the method further comprises administering a TYK2 inhibitor (e.g., deuclavacitinib) to a patient whose protein level is above that threshold.

[0028] In some embodiments, the baseline Psoriasis Area and Severity Index (PASI) score of PsA patients is used (combined with the level of one or more proteins described herein) to determine whether the patient's psoriatic arthritis is responsive or likely to respond to TYK2 inhibitors (e.g., deuclavacitinib). Psoriasis Area and Severity Index (PASI) is a quantitative assessment method that measures the severity of psoriasis symptoms based on the extent of lesions and plaque formation. PASI scores are used to assess baseline and response to treatment of psoriasis and PsA. The response measurement PASI75 is a binary result that indicates a 75% or greater improvement in PASI score from baseline PASI score.

[0029] In one embodiment, the present invention provides a method for identifying a subject with psoriatic arthritis amenable to treatment with a TYK2 inhibitor (e.g., deuclavacitinib), comprising determining the levels of BD2, IL-19, and / or IL-17A in the subject's blood (e.g., whole blood, serum, or plasma), wherein high levels of BD2, IL-19, and / or IL-17A (high levels being levels above a particular threshold level of each protein) indicate that the subject's psoriatic arthritis is amenable to treatment with a TYK2 inhibitor. In one of the above embodiments, the subject's baseline CRP level and / or baseline PASI score are also used in combination with the subject's baseline blood levels of BD2, IL-19, and / or IL-17A to assess whether the subject's psoriatic arthritis is amenable to treatment with a TYK2 inhibitor (e.g., deuclavacitinib).

[0030] In some embodiments, the threshold level used to indicate that a certain protein level is "high" is determined based on the blood level of the certain protein of the comparison group measured from the sample (e.g., whole blood, plasma, or serum) of the comparison group.In some embodiments, the comparison group is a group of healthy subjects (subjects who have not been diagnosed with psoriatic arthritis or other inflammatory or autoimmune conditions).In other embodiments, the comparison group is a group of subjects diagnosed with psoriatic arthritis.In some such embodiments, the comparison group is a group of subjects diagnosed with psoriatic arthritis, and samples (e.g., whole blood, plasma, or serum) are taken from these subjects before any treatment with TYK2 inhibitors (e.g., before any treatment with deuclavacitinib).

[0031] In some embodiments, the comparison group includes at least 50, at least 75, at least 100, at least 150, or at least 200 subjects.

[0032] In some embodiments, the measured level of the protein is mathematically transformed (eg, by taking the log2 value of the measured concentration of the protein in the sample).

[0033] The threshold level of a protein is generally a predetermined score or value, which may be calculated, for example, as a percentile (e.g., the 10th, 20th, 30th, 40th, 50th (median), 60th, 70th, 80th, or 90th percentile) or as the average (e.g., mathematically transformed level) of the levels of a particular protein in the blood of a comparison group, or as otherwise described herein.

[0034] In many embodiments, each specific protein has its own threshold level.For example, threshold level is determined for each specific protein.In other embodiments, threshold level is a composite value calculated based on two or more values ​​of specific protein.In this embodiment, a score can be calculated for each patient based on the blood levels of two or more specific proteins of the patient, and the score for each patient can be compared with the composite value.

[0035] Generally, protein levels above the threshold are designated “high,” while protein levels below the threshold are designated “low.” In certain embodiments, the threshold level is the median.

[0036] In some embodiments, a threshold level of a particular protein is used to classify subjects into "low level" or "high level" groups of the protein, where subjects with levels below the threshold level are classified into the "low level" group and subjects with levels above the threshold are classified into the "high level" group.

[0037] In one embodiment, the threshold level is determined by listing all possible levels of protein measured in a particular patient population (e.g., psoriatic arthritis patients), determining the median of the listed levels, and setting this median as the threshold level.

[0038] In some embodiments, the threshold level is determined from measured levels of the protein in a patient population that has been diagnosed with psoriatic arthritis and that has not received a TYK2 inhibitor for a minimum period of time (eg, at least 3, 6, 9, 12, or 24 months) prior to sampling.

[0039] For example, in an embodiment using the median level as the threshold level, samples (e.g., blood samples) are obtained from subjects (e.g., about 50, 75, 100, 150, 200 or more subjects) who meet certain clinical criteria for psoriatic arthritis and have not been treated with a TYK2 inhibitor, and the level of one or more proteins in each sample is determined. The proteins may include β-defensin 2, IL-19, and IL-17A. The raw data may be appropriately processed. The median value of the protein data (raw data or processed data) may then be used as the threshold level of the protein, and may be used to classify subjects as "low level" or "high level".

[0040] The classification of "low level" or "high level" described herein can be used to determine whether or not to administer a TYK2 inhibitor to a subject, or whether or not to select a subject for treatment with a TYK2 inhibitor.

[0041] Thus, in some embodiments, a threshold level of a protein may be used to classify PsA patients into a "low level" or "high level" group for a particular protein. Here, the threshold level is determined by listing all possible levels of a protein measured in the blood (e.g., serum) of a PsA patient, determining the median value from the listed protein levels, and taking the median value as the threshold level. In this specification, the threshold level may be referred to as a median threshold. Prior to treating psoriatic arthritis with a TYK2 inhibitor, blood sampling may be performed to assess the median value of a particular protein. If the level of a particular protein in a sample (e.g., plasma or serum) is higher than the median threshold, the PsA patient may be classified as a "high level," and if the level of a particular protein in a sample (e.g., plasma or serum) is equal to or lower than the median threshold, the PsA patient may be classified as a "low level." The particular protein may be one or more of the proteins described herein (e.g., BD2, IL-19, and / or IL-17A).

[0042] Methods for measuring protein levels in a sample of bodily fluid (e.g., whole blood, plasma, or serum samples) are known to those skilled in the art. These methods include, but are not limited to, immunoassays (e.g., ELISA and its variants (e.g., radioimmunoassay (RIA) and single molecule array (Simoa) immunoassay)), SDS-polyacrylamide electrophoresis (SDS-PAGE) mass spectrometry, proximity ligation assay (PLA), and SomaLogic's proteomic affinity assay.

[0043] As mentioned above, in some embodiments, the threshold level of a particular protein is a pre-determined value. Such pre-determined value may be based on the median or other values ​​mentioned above, or may be based on other data analysis or other methods. Regardless of the pre-determined value criterion, a subject (e.g., a PsA patient) may be classified as "high level" if the protein level in the blood is above a pre-determined value, and may be classified as "low level" if the protein level in the blood is below a pre-determined value.

[0044] In some embodiments, the threshold level need not be used to classify subjects into "low level" or "high level" groups, but is used to identify subjects (e.g., PsA patients) for treatment with a TYK2 inhibitor, and optionally administer a TYK2 inhibitor to the subject, as described herein. In a further embodiment, the TYK2 inhibitor is deuclavacitinib.

[0045] Thus, as described herein, the levels of one or more proteins in a subject's blood can be used to predict the responsiveness of a subject's PsA to a TYK2 inhibitor (e.g., deuclavacitinib). The present invention provides relationships between certain protein levels and clinical outcomes useful for determining the responsiveness of a subject's PsA to treatment with a TYK2 inhibitor (e.g., deuclavacitinib). Part of the present invention provides methods and kits for predicting the outcome of a subject treated with a TYK2 inhibitor based on the level of one or more certain proteins in the subject's blood prior to treatment. Further embodiments of the present invention relate to methods for treating a subject with PsA with a TYK2 inhibitor, the subject having been determined to be susceptible to treatment with a TYK2 inhibitor. In one embodiment, the method comprises determining one or more protein levels in a subject's sample (e.g., a blood sample (e.g., whole blood, serum, or plasma)), where the one or more proteins are selected from BD2, IL-19, and IL-17A, and for at least one of the one or more proteins whose level is determined, the protein exhibits a level in the sample that is above a threshold protein level, thereby indicating that the subject's PsA is responsive to or susceptible to treatment with a TYK2 inhibitor. A further embodiment comprises administering a TYK2 inhibitor to the subject. In one embodiment, the TYK2 inhibitor is deuclavacitinib.

[0046] In some embodiments, responding to a TYK2 inhibitor may refer to achieving a particular clinical outcome (e.g., PASI75 response, ACR20 response, etc.) after a minimum treatment period (e.g., 8 weeks, 10 weeks, 12 weeks, 14 weeks, or 16 weeks) with a TYK2 inhibitor (e.g., duravacitinib). For example, a PsA patient responding to a TYK2 inhibitor may refer to achieving a PASI75 response 12 weeks after starting treatment with a TYK2 inhibitor. In further embodiments, responding to a TYK2 inhibitor may refer to achieving a PASI75 response 16 weeks after starting treatment with a TYK2 inhibitor.

[0047] In any of the embodiments described herein, the TYK2 inhibitor can be deuclavacitinib. Deuclavacitinib has the formula (I): [ka] It is also known as 6-(cyclopropanecarboxamide)-4-((2-methoxy-3-(1-methyl-1H-1,2,4-triazol-3-yl)phenyl)amino)-N-(methyl-d3)pyridazine-3-carboxamide, having the structure:

[0048] Deuclavacitinib is a selective TYK2 inhibitor undergoing clinical trials for the treatment of inflammatory and autoimmune diseases (e.g., psoriasis, psoriatic arthritis, lupus, lupus nephritis, Sjogren's syndrome, ulcerative colitis, Crohn's disease, and ankylosing spondylitis). Deuclavacitinib is disclosed in commonly assigned U.S. Patent No. RE47,929 E, the contents of which are incorporated herein by reference in their entirety. Other TYK2 inhibitors include, for example, those described in WO 2012 / 000970, WO 2012 / 035039, WO 2013 / 174895, WO 2015 / 091584, WO 2015 / 032423, WO 2017 / 040757, WO 2018 / 071794, WO 2018 / 075937, WO 2019 / 023468, US 2015 / 0045349, US 2015 / 0094296, and US 2016 / 0159773, the contents of each of which are incorporated by reference in their entirety.

[0049] In any of the embodiments and methods described herein in which the TYK2 inhibitor is deuclavacitinib, the dose of deuclavacitinib that may be administered to the subject may range from about 1 mg to about 40 mg per day. For example, in some embodiments of the methods described herein, a dose of 3 mg, 6 mg, 12 mg, 15 mg, or 36 mg of deuclavacitinib is administered to the subject per day. Such a daily dose may be administered once a day, or in two or more divided doses (e.g., if the total daily dose is 12 mg, 12 mg may be administered once a day, or two 6 mg doses, or three 4 mg doses).

[0050] In some embodiments, the present invention provides a kit for identifying PsA patients to be treated with a TYK2 inhibitor. The kit can be useful for predicting the responsiveness of a subject's PsA to a TYK2 inhibitor. In some embodiments, the kit includes a kit for measuring the level of one or more proteins (e.g., BD2, IL-19, and / or IL-17A) in a sample, and / or a kit for comparing the level of one or more proteins in a sample to one or more standards, where the standards are based on protein levels measured in a patient population with the disease that has not been treated with a TYK2 inhibitor. Alternatively, the standards can be based on protein levels measured in a patient population with the disease that has been previously treated with a TYK2 inhibitor and has responded to the TYK2 inhibitor, and a patient population that has previously been treated with a TYK2 inhibitor and has not responded to the TYK2 inhibitor.

[0051] In any of the embodiments described herein, a TYK2 inhibitor (eg, deuclavacitinib) may be administered to a subject in combination with one or more other agents.

[0052] In the context of the present invention, a subject, in particular a human subject, may also be referred to as a patient.

[0053] Any definitions set forth herein take precedence over definitions set forth in any patent, patent application, and / or published patent application that is incorporated herein by reference. Any statements from any patent, patent application, and / or published patent application, or other document that are incorporated by reference are incorporated by reference to the extent that there is no conflict between such statements and this specification, in which case any conflicting statements will not be incorporated by reference.

[0054] Any measurement may contain experimental error, which is within the scope of the present invention.

[0055] (Example) The present invention is further illustrated by the following examples, which are used only to illustrate the present invention and its practice, and are not to be construed as limiting the scope and nature of the present invention.

[0056] In this double-blind, phase 2 study, 203 patients with psoriatic arthritis were randomized into three groups to receive deuclevacitrinib 6 mg once daily (N=70), deuclevacitrinib 12 mg once daily (N=67), or placebo (N=66). All patients were diagnosed with active psoriatic arthritis according to the Classification Criteria for Psoriatic Arthritis (CASPAR). Criteria for active disease required a tender joint count of ≥3, a swollen joint count of ≥3, and a C-reactive protein level greater than 3 mg / L. Other inclusion criteria included the following: the presence of at least one plaque of psoriatic disease and failure to have been previously treated successfully with nonbiologic disease-modifying antirheumatic drugs, nonsteroidal anti-inflammatory drugs, or steroids. Regarding treatment history, approximately 70% of subjects were naïve and had not received any prior biological therapy, while 30% or less had been treated unsuccessfully or were intolerant to one TNF inhibitor (TNF = tumor necrosis factor, also known as TNFα). Subjects were randomly classified according to prior TNF inhibitor use (yes / no) and body weight (<90 kg and ≥90 kg).

[0057] Baseline serum protein levels were measured at various times during 16 weeks of treatment with deucelavacitinib. A large number of proteins were investigated, and of those investigated, beta-defensin 2 (BD2), IL-19, and IL-17A were found to have levels predictive of clinical benefit to deucelavacitinib. BD2 levels were measured in serum samples by ELISA, and serum IL-19 and IL-17A levels were measured using ultrasensitive Simoa technology.

[0058] In addition, baseline (pre-treatment) protein levels were compared between healthy volunteers and PsA patients. Data from 60 healthy volunteers matched for age, sex, and weight to the PsA patients were used for comparison.

[0059] Clinical measures included Psoriasis Area and Severity Index (PASI) score for cutaneous psoriasis, American College of Rheumatology 20 (ACR20) response, Psoriatic Arthritis Disease Activity Score (PASDAS), Health Status Questionnaire Disability Index (HAQ-DI), and Disease Activity Score 28-CRP (DAS28). To evaluate various protein predictive measures of clinical response to deucrucitinib, baseline protein concentrations in responders and non-responders defined by ACR20 or PASI75 at week 16 were compared across groups (placebo, deucrucitinib 6 mg once daily, and deucrucitinib 12 mg once daily).

[0060] (result) Baseline protein levels in PsA patients: Among the proteins evaluated, BD2, IL-19, and IL-17A were found to be predictive of clinical outcome in PsA patients. Furthermore, baseline serum concentrations of BD2, IL-19, and IL-17A were higher in patients with psoriatic arthritis (compared to levels in healthy volunteers) and were significantly associated with the severity of skin lesions as measured by the PASI score. Baseline serum β-defensin 2 levels were significantly higher in PsA patients than in healthy volunteers (p<0.0001). Figure 1A shows box plots of serum β-defensin 2 concentrations (log2 values, y-axis) in healthy volunteers (NHV, left box plot) and patients with psoriatic arthritis (PsA, right box plot). As shown in Figure 2A (IL-19) and Figure 3A (IL-17A), baseline serum IL-19 and IL-17A levels were also significantly higher in PsA patients than in healthy volunteers (p<0.0001, respectively). In baseline PsA patients (before treatment with deuteranoplast or placebo), certain serum protein levels correlate with the PASI score. Figure 1B shows a graph with baseline β-defensin 2 levels on the x-axis (ng / L, log2 value) and baseline PASI score on the y-axis. Here, baseline β-defensin 2 levels correlate with baseline PASI score (Spearman's rank correlation coefficient, or ρ=0.56; p<0.0001). Furthermore, as shown in Figure 2B, baseline IL-19 levels correlate with baseline PASI score (ρ=0.5; p<0.0001), and as shown in Figure 3B, baseline IL-17A levels correlate with baseline PASI score (ρ=0.4; p<0.0001). Baseline CRP levels did not show a strong correlation with baseline PASI score (ρ=0.14; p=0.04). Pearson correlation analysis was performed to determine any associations between baseline BD2, IL-19, or IL-17A levels and baseline CRP levels in PsA patients. Pearson correlation analysis was also performed to determine any associations between serum protein levels and baseline disease activity using the disease activity assessment measures: PASI, DAS28, HAQ-DI, and PASDAS. Baseline BD2 expression levels (log2 values) were weakly correlated with baseline CRP levels (log2 values) with a correlation coefficient of 0.2 (p-value = 0.00526). Baseline BD2 expression levels (log2 values) were correlated with baseline PASI scores with a correlation coefficient of 0.57 (p-value < 0.0001). Baseline BD2 expression did not show a strong or statistically significant correlation with baseline values ​​of other disease activity measures (correlation coefficients for baseline DAS28, HAQ-DI, or PASDAS were 0.04 (p-value=0.60015), 0.06 (p-value=0.38953), and 0.12 (p-value=0.08699), respectively). Similar results were obtained for baseline levels of IL-19 and IL-17A. Baseline log2 IL-19 expression was weakly correlated with baseline log2 CRP levels (correlation coefficient=0.27; p-value=0.000012) and with baseline PASI scores (correlation coefficient=0.58; p-value<0.0001). On the other hand, the baseline value of IL-19 expression (log2 value) did not show a strong correlation with the baseline values ​​of other activity evaluation criteria (the correlation coefficients of the baseline values ​​of DAS28, PASDAS, and HAQ-DI were 0.12 (p value = 0.08929), 0.15 (p value = 0.03972), and 0.16 (p value = 0.02192), respectively).Regarding IL-17A, baseline log2 values ​​of IL-17A expression correlated with baseline log2 values ​​of CRP levels (correlation coefficient = 0.3; p-value = 1e-05) and with baseline PASI scores (correlation coefficient = 0.46; p-value < 0.0001), but did not show strong or statistically significant correlations with baseline values ​​of other disease activity assessment measures (correlation coefficients for baseline DAS28, PASDAS, and HAQ-DI were 0.06 (p-value = 0.40389), 0.14 (p-value = 0.04863), and 0.13 (p-value = 0.06776), respectively).

[0061] Correlations between baseline clinical scores and response status: The relationship between baseline PASI scores and PASI75 or ACR20 response status at Week 16, and between baseline DAS28 scores and ACR20 response at Week 16, was evaluated. The median baseline PASI scores and baseline DAS28 scores were 6.6 and 5.1, respectively. The median baseline PASI scores were calculated from the 165 subjects with PASI75 response data (see Table 1 below). A two-sample t-test was performed for each treatment group to determine whether baseline mean scores differed between responders and non-responders. A Wilcoxon rank sum test (Mann-Whitney U test) was also performed for each treatment group to determine differences in baseline median scores between responders and non-responders. [Table 1]

[0062] Additionally, a logistic regression model was used to determine whether baseline disease scores (dichotomized into high and low baseline groups by the median baseline score) were associated with response status. The model provided odds ratios for each treatment group versus placebo for the high and low baseline groups. The p-values ​​for the interaction terms were used to identify whether the odds ratios (ORs) were significantly different between the high and low baseline groups. - The model to assess the relationship between baseline PASI scores and PASI75 responses was PASI75(Y / N) = treatment group + PASI baseline group + treatment group*PASI baseline group + TNF inhibitor use + baseline weight (As used herein, "baseline weight" refers to the subject's weight (kg, continuous variable)). - The model to evaluate the relationship between baseline PASI score and ACR20 response was ACR20(Y / N) = treatment group + PASI baseline group + treatment group*PASI baseline group + TNF inhibitor use + baseline body weight (continuous variable) It was. - The model to assess the relationship between baseline DAS28 and ACR20 response was: ACR20(Y / N) = treatment group + DAS28 baseline group + treatment group*DAS28 baseline group + TNF inhibitor use + baseline body weight (continuous variable) It was.

[0063] Using the statistical comparisons and logistic regression models described above, PASI baseline scores correlated at a statistically significant level with PASI75 response status, but did not correlate statistically significantly with any of the other subjects tested. Figure 4 and the table below show the correlation data between PASI baseline scores and PASI75 response status.

[0064] FIG. 4 shows box plots of baseline PASI scores by PASI75 response status in each treatment group. The solid horizontal line of each box indicates the median of the box plot, and the dashed horizontal line indicates the median baseline PASI score (6.6) for all 165 patients in all box plots (165 subjects with PASI75 data). Table 2 shows p-values ​​for the t-test and Wilcoxon rank sum test described above. Table 3 shows the number of patients in each treatment group according to response status (PASI75 responder or non-responder) and baseline score status (above or below the median baseline PASI score (6.6) for all 165 patients with PASI75 data). Table 4 shows the odds ratio results for the logistic regression model used to predict PASI75 response from baseline PASI scores. [Table 2]

Table 3

Table 4

[0065] The odds ratio results shown in Table 4 above indicate the value of the correlation between treatment and PASI75 response status in a particular patient group (all patients, patients with baseline PASI scores above the median of 6.6 (high PASI baseline), and patients with baseline PASI scores below the median of 6.6 (low PASI baseline)). Each odds ratio (OR) in the first six rows indicates the ratio of (i) the likelihood of a PASI75 response with a particular treatment (6 mg QD or 12 mg QD) and (ii) the likelihood of a PASI75 response without treatment (placebo). An odds ratio greater than 1 indicates a higher likelihood of achieving a PASI75 response with treatment, whereas an odds ratio less than 1 indicates a lower likelihood of achieving a PASI75 response with treatment. An odds ratio of 1 indicates that the treatment does not affect the PASI75 response. The ORs in the first two rows indicate the ORs comparing the 6 mg QD or 12 mg QD groups with the placebo group in all patients. Here, PASI75(Y / N) = treatment group + TNF inhibitor use + baseline body weight (continuous variable). The ORs in lines 3-6 show the results of PASI75(Y / N) = treatment group + PASI baseline group + treatment group * PASI baseline group + TNF inhibitor use + baseline body weight (continuous variable). For example, in line 3, the odds ratio is 6.94 when comparing 6 mg QD with placebo in patients with baseline PASI scores above the median of 6.6. The last two lines of Table 4 show interaction terms. For example, in line 7, the odds ratio is calculated as 5.51 by adding two odds ratios (a: odds ratio for 6 mg QD vs. placebo in the high PASI baseline group and b: odds ratio for 6 mg QD vs. placebo in the low PASI baseline group) (i.e., comparing the odds ratios of 6.94 and 1.26). The results, shown in Table 4, indicate that in each treatment group, high PASI baseline scores conferred significant treatment benefit (significantly more likely to achieve PASI 75 with deucelabacitinib treatment than with placebo).

[0066] Correlation of baseline protein levels and response state Baseline levels of certain serum proteins (BD2, IL-19, and IL-17A) were found to be predictive of important clinical outcomes (e.g., ACR20 and PASI75). Box plots of baseline protein levels by response were generated. Horizontal lines indicate median protein levels at baseline. Two-sample t-tests were performed in each treatment group to determine whether mean baseline serum protein levels differed between responders and non-responders. Wilcoxon rank sum tests (Mann-Whitney U test) were also performed to evaluate differences in median serum protein levels between responders and non-responders. Additionally, bar graphs were generated of ACR20 and PASI75 response rates at week 16 in each treatment group for all patients (those with high and low protein levels dichotomized by median baseline levels). Line graphs of ACR20 and PASI75 response rates over time in each treatment group were generated for those with high and low protein levels. Logistic regression models were also used to assess the correlation between baseline protein levels and clinical outcomes. The median baseline serum levels of specific proteins in patients with PsA are listed below. - Median β-Defensin 2 (BD2): 9,265ng / L - Median IL-19: 36ng / L - Median IL-17A: 0.575ng / L - Median C-reactive protein (CRP): 8.31mg / L

[0067] dichotomy In certain analyses described herein, patients are dichotomized into "high" and "low" groups by median value (e.g., of the proteins listed above or other criteria), with the high group having values ​​above the median and the low group having values ​​below or equal to the median.

[0068] β-Defensin 2 (BD2) The median baseline level of β-defensin 2 (for all 200 patients with baseline BD2 data) was 9,265 ng / L. Figures 5 and 6 show box plots of non-responders and responders at week 16 (PASI75 and ACR20 response status, respectively) in each treatment group. The dashed horizontal line corresponds to the median baseline BD2 level, and the solid horizontal line of each box indicates the median baseline BD2 level for that box plot. Table 5 shows p values ​​for each treatment group for comparing mean or median baseline BD2 levels of responders and non-responders; for t-tests comparing means, BD2 levels were log2 transformed before calculating the responder and non-responder means. [Table 5]

[0069] Figures 7 and 8 are bar graphs showing the response rates for each treatment group achieving PASI75 or ACR20 response status at week 16 for subjects with baseline BD2 levels above the median ("BD2 high") or below the median ("BD2 low"). In the BD2 high group, PASI75 response rates were higher in both the 6 mg QD and 12 mg QD treatment groups compared to the placebo group, whereas in the BD2 low group, no significant differences in PASI75 response rates were observed between treatment and placebo groups. Similar results were observed for ACR20 response rates.

[0070] Table 6 below shows the number of responders and non-responders in the low and high BD2 groups by treatment group. [Table 6]

[0071] Figures 9 and 10 show line graphs of the response rates (PASI75 and ACR20, respectively) over time for the high BD2 group and the low BD2 group. A dose-dependent change in the PASI75 response rate over time was observed in the high BD2 group, but not in the low BD2 group. Furthermore, the ACR20 response rate over time to duravacitinib was higher in the high BD2 group than in the placebo group, but not in the low BD2 group. In addition, PsA patients were divided into four groups according to baseline BD2 levels and baseline PASI levels (high BD2 and high PASI, high BD2 and low PASI, low BD2 and high PASI, and low BD2 and low PASI). Table 7 shows the number of PsA patients in each of the four groups. Figure 11 shows a bar graph showing the PASI75 response status at week 16 in each treatment group for all patients classified into the four groups. The bar graph shows that baseline BD2 levels and baseline PASI levels are associated with PASI75 response. High baseline BD2 levels were associated with better PASI75 response to duravacitinib in both the high and low PASI groups. These results indicate that higher baseline BD2 levels are associated with better clinical efficacy with treatment with TYK2 inhibitors as assessed by both ACR20 and PASI75. [Table 7]

[0072] Additionally, logistic regression models were fitted for the response measures ACR20 and PASI75 to obtain odds ratios for the duravacitinib treatment group versus placebo in the high and low BD2 groups. The following logistic regression models were used: -ACR20 response status: ACR20(Y / N) = treatment group + BD2 group + treatment group*BD2 group + TNF inhibitor use + baseline body weight (continuous variable) -For PASI75 response status: PASI75(Y / N) = treatment group + BD2 group + treatment group*BD2 group + TNF inhibitor use + baseline body weight (continuous variable)

[0073] The p-values ​​of the interaction terms were used to identify whether there was a significant difference between the high and low BD2 groups in the OR for achieving a response. Figures 26-31 are forest plots summarizing the logistic regression results of these models (for BD2 and other biomarkers described herein), where "N" for "Placebo" and "Deucrava" indicates the number of responders in that group. The statistical models used to analyze the impact of baseline BD2 levels were run with each treatment group (6 mg QD, 12 mg QD, and placebo) as a separate predictor (see Figures 26, 27, and Table 8A for ACR20 results; Figures 29, 30, and Table 9A for PASI75 results) and with the Deucravacitinib treatment group together (see Figure 28 and Table 8B for ACR20 results; Figure 31 and Table 9B for PASI75 results). [Table 8]

[0074] The first two rows of Table 8A show odds ratios comparing the probability of response to 6 mg or 12 mg duravacitinib versus placebo in all patients (high BD2 and low BD2 groups) using ACR20(Y / N)=treatment group+TNF inhibitor use+baseline weight (continuous variable). The odds ratios in rows 3-8 show the results obtained from ACR20(Y / N)=treatment group+BD2 group+treatment group*BD2 group+TNF inhibitor use+baseline weight (continuous variable). The last two rows show interaction terms. For example, row 7 shows the ratio of (a) the odds ratio of 6 mg QD versus placebo in the high BD2 group and (b) the odds ratio of 6 mg QD versus placebo in the low BD2 group (i.e., comparing ORs of 4.54 and 1.44). This ratio was higher than the null hypothesis (i.e., 1), but was not statistically significant.

[0075] The results of Table 8A, Figure 26, and Figure 27 indicate that the high BD2 group shows a significant therapeutic effect at any dose of deuclavacitinib (as shown by the significantly higher probability of achieving ACR20 with deuclavacitinib treatment compared to the probability of achieving ACR20 in the placebo group), but the low BD2 group does not show a significant therapeutic effect. Similarly, the ACR20 results in Figure 28 and Table 8B show that deuclavacitinib provides a significant therapeutic effect only in the high BD2 group (see the second row of Table 8B). [Table 9] [Table 10]

[0076] Figures 29-31, Table 9A, and Table 9B show similar analysis results for PASI75 response. The results in Figures 29, 30, and Table 9A imply that the high BD2 group shows a significant treatment effect at any dose of deuclavacitinib (as shown by the significantly higher probability of reaching PASI75 with deuclavacitinib treatment compared to the probability of reaching PASI75 in the placebo group) (see lines 3 and 4), while the low BD2 group does not show a significant treatment effect (see lines 5 and 6). Furthermore, the treatment effect at each dose (comparison of odds ratio of treatment effect with deuclavacitinib to odds ratio of response with placebo) is significantly higher in the high BD2 group than in the low BD2 group (see lines 7 and 8).

[0077] The PASI75 response results in Figure 31 and Table 9B indicate that deuclavacitinib provides a significant therapeutic effect only in the high BD2 group (see the second row of Table 9B), and that the therapeutic effect is significantly higher in the high BD2 group than in the low BD2 group (see the last row of Table 9B). [Table 11]

[0078] In the logistic regression model, no adjustment was made for baseline disease activity. In order to take into account any potential confounding of baseline disease activity, a second model was used in which adjustment was made for baseline disease activity. Figures 32-35 are forest plots summarizing the results of this second model. Here, Tables 10 and 11 show the results of the odds ratios of BD2 in this model. [Table 12]

[0079] Figure 34, Figure 35, and Table 10 show the results of the second model for ACR20 response status. The above table shows the odds ratio results for ACR20 response status at week 16, adjusted for baseline DAS28. The first two rows of Table 10 show the odds ratios and p-values ​​of achieving an ACR20 response, using ACR20(Y / N)=treatment group+TNF inhibitor use+baseline weight (continuous variable)+baseline DAS28 (continuous variable) for all patients (high BD2 and low BD2), adjusted for baseline DAS28. The odds ratios show the odds ratios comparing 6mg or 12mg with placebo. These results show that the probability of achieving an ACR20 response is significantly higher in the duravacitinib treatment group than in the placebo group, even after adjusting for baseline DAS28.

[0080] The results shown in lines 3-6 of Table 10 were obtained using ACR20(Y / N)=treatment group*BD2 group+TNF inhibitor use+baseline weight (continuous variable)+baseline DAS28 (continuous variable). Lines 3-4 show odds ratio results for the high BD2 group. These results show that the probability of achieving an ACR20 response in each duke labacitinib treatment group was significantly higher than the probability of achieving an ACR20 response in the placebo group in high BD2 patients after adjustment for baseline DAS28. In contrast, such significant odds ratio results were not observed in the low BD2 group (see lines 5 and 6 of Table 10). These results show that there is a correlation between high baseline BD2 levels and significant clinical benefit from treatment with a TYK2 inhibitor, regardless of baseline DAS28 (as shown by the significantly higher probability of achieving ACR20 with TYK2 inhibitor treatment compared to the probability of achieving ACR20 with placebo).

[0081] The results shown in rows 7 and 8 of Table 10 were obtained using the same model used in rows 3-6. Although these results from the interaction terms are not statistically significant, they are consistent with the other results and show that (a) the odds ratio of achieving an ACR20 response with deuclavacitinib treatment vs. placebo in the high BD2 group and (b) the odds ratio of achieving an ACR20 response with deuclavacitinib treatment vs. placebo in the low BD2 group are mathematically greater than the null hypothesis (i.e., 1). In other words, the odds ratio of responding to deuclavacitinib treatment (measured by ACR20) vs. the odds ratio of responding to placebo is higher in the high BD2 group than in the low BD2 group. [Table 13]

[0082] Figure 32, Figure 33, and Table 11 show the results of a similar model for PASI75 response status. The above table shows the results of the odds ratios for PASI75 status at week 16 adjusted for baseline PASI score. The first two rows of Table 11 show the odds ratios and p-values ​​of achieving a PASI75 response when adjusted for baseline PASI score, using PASI75(Y / N)=treatment group+TNF inhibitor use+baseline weight (continuous variable)+baseline PASI score (continuous variable) for all patients (high BD2 and low BD2). The odds ratios show the odds ratios comparing 6 mg or 12 mg with placebo. These results show that even after adjusting for baseline PASI score, the probability of achieving a PASI75 response was significantly higher in the duravacitinib treatment group than in the placebo group.

[0083] The results shown in lines 3-6 of Table 11 were obtained using PASI75(Y / N)=treatment group*BD2 group+TNF inhibitor use+baseline body weight (continuous variable)+baseline PASI score (continuous variable). Lines 3 and 4 show odds ratio results for the high BD2 group. It shows that for high BD2 patients, after adjusting for baseline PASI score, the probability of reaching a PASI75 response in each duke lavacitinib treatment group was significantly higher than the probability of reaching PASI75 in the placebo group. In contrast, such significant odds ratio results were not observed in the low BD2 group (see lines 5 and 6 of Table 11). These results show that there is a significant correlation between high baseline BD2 levels and clinical benefit from treatment with a TYK2 inhibitor, regardless of baseline PASI score (as shown by the significantly higher probability of achieving PASI75 with TYK2 inhibitor treatment compared to the probability of achieving PASI75 in the placebo group).

[0084] The results shown in rows 7 and 8 of Table 11 were obtained using the same model used in rows 3 to 6. (a) The odds ratio of achieving PASI 75 after treatment with deuclavacitinib or placebo in the high BD2 group compared with (b) the odds ratio of achieving PASI 75 after treatment with deuclavacitinib or placebo in the low BD2 group are statistically significantly higher than the null hypothesis (i.e., 1). These results indicate that, even after adjusting for PASI baseline values, high BD2 levels are correlated with a significantly higher clinical benefit of TYK2 inhibitor treatment compared with placebo (as indicated by the significantly higher odds ratio of achieving PASI 75).

[0085] For PASI75, a separate logistic regression model was used to evaluate the predictive value of baseline BD2 levels and baseline PASI scores dichotomized according to their respective medians. From this model, odds ratios were calculated for each treatment group versus placebo for each of the four baseline BD2·PASI groups (i.e., high BD2·high PASI, high BD2·low PASI, low BD2·high PASI, and low BD2·low PASI (see Figure 11)). The model was: PASI75(Y / N)=treatment group+baseline BD2·PASI group+treatment group*baseline BD2·PASI group+TNF inhibitor use+baseline body weight (continuous variable). Table 12 shows the results of this model. [Table 14]

[0086] The first two rows in Table 12 are identical to the first two rows in Table 9 and show the odds ratios for all patients comparing 6 mg QD or 12 mg QD with placebo, using PASI75(Y / N)=treatment group+TNF inhibitor use+baseline body weight (continuous variable). The odds ratios in rows 3-10 show the results from PASI75(Y / N)=treatment group+BD2·PASI baseline group+treatment group*BD2·PASI baseline group+TNF inhibitor use+baseline body weight (continuous variable). For example, 29.67 in row 3 is the odds ratio of achieving a response in the 6 mg QD treatment group vs. placebo group in patients with BD2 levels above the median and baseline PASI scores above the median.

[0087] The results in Table 12 show that for both deucelavacitinib treatment arms, the high BD2·high PASI group had a significantly higher probability of responding to deucelavacitinib (as indicated by PASI75) compared to the probability of responding to placebo (see rows 3 and 4), but not the low BD2·high PASI group (see rows 7 and 8). A similar significant treatment effect was seen for the high BD2·low PASI group in the 12 mg QD treatment arm compared to placebo.

[0088] IL-19 A similar analysis was performed for baseline IL-19 levels measured in PsA patients. The median baseline IL-19 level (for all 201 patients with baseline IL-19 data) was 36 ng / L. Figures 12 and 13 show box plots of non-responders and responders at week 16 (PASI75 and ACR20 response status, respectively) in each treatment group. The dashed horizontal lines correspond to the median baseline IL-19 levels, and the solid horizontal lines of each box show the median baseline IL-19 levels for that box plot. Table 13 shows p values ​​for each treatment group for comparing mean or median baseline IL-19 levels for responders and non-responders; for t-tests comparing means, IL-19 levels were log2 transformed before calculating the responder and non-responder means. [Table 15]

[0089] As shown in Figure 12, in the placebo group, baseline IL-19 levels were higher in PASI75 non-responders than in PASI75 responders, whereas in the deuclavacitinib treatment group, baseline IL-19 levels were higher in PASI75 responders than in PASI75 non-responders. These results indicate that PsA patients with higher baseline IL-19 levels had better cutaneous response to deuclavacitinib compared to patients with lower baseline IL-19 levels.

[0090] Furthermore, as shown in Figure 13, baseline IL-19 levels were higher in ACR20 non-responders than in ACR20 responders in the placebo group. In contrast, baseline IL-19 levels were higher in responders than in non-responders in the deuclavacitinib-treated group. These results indicate that PsA patients with higher baseline IL-19 levels had better joint responses to deuclavacitinib than patients with lower baseline IL-19 levels.

[0091] Figures 14 and 15 are bar graphs showing the response rates of each treatment group reaching PASI75 or ACR20 response status at week 16 for patients in the high and low IL-19 groups (dichotomized according to median IL-19 baseline levels). The PASI75 response rates in both the 6 mg QD and 12 mg QD treatment groups in the high IL-19 group were higher than the response rates in the placebo group. This result was not observed in the low IL-19 group (see Figure 14). For the ACR20 response rate, a more pronounced treatment effect (indicating a dose-response effect of duravacitinib) was observed in the high IL-19 group than in the low IL-19 group (see Figure 15).

[0092] Table 14 below shows the number of responders and non-responders in the low and high IL-19 groups (classified by median IL-19 levels in PsA patients) by treatment group. [Table 16]

[0093] Figures 16 and 17 show line graphs of response rates (PASI75 and ACR20, respectively) over time for the high and low IL-19 baseline groups. A dose-dependent change in PASI75 response over time was observed in the high IL-19 group, but not in the low IL-19 PsA patients. Furthermore, the ACR20 response rate over time was higher with duravacitinib compared to the placebo response rate in the high IL-19 group, but not in the low IL-19 group. PsA patients were also divided into four groups (high IL-19 and high PASI, high IL-19 and low PASI, low IL-19 and high PASI, and low IL-19 and low PASI) according to baseline IL-19 levels (above or below the median) and baseline PASI levels (above or below the median). Table 15 below shows the number of patients in each of the above groups. Figure 18 is a bar graph showing the PASI75 response status at week 16 in each treatment group for all patients classified into the above four groups. The bar graph shows that baseline IL-19 levels correlate with PASI75 response even for patients in the low PASI group (see "high IL-19, low PASI" group in Figure 18). [Table 17]

[0094] A logistic regression model was fitted for BD2 as described above. For the response measure ACR20, odds ratios were calculated for each treatment group vs. placebo in the high and low IL-19 groups. The model used for ACR20 was ACR20(Y / N)=treatment group+IL-19 group+treatment group*IL-19 group+TNF inhibitor use+baseline weight (continuous variable). The p-value for the interaction term was used to identify whether the OR of achieving an ACR20 response (treatment group vs. placebo) was significantly different between the high and low IL-19 groups. The same regression model was used for PASI75 response status: PASI75(Y / N)=treatment group+IL-19 group+treatment group*IL-19 group+TNF inhibitor use+baseline weight (continuous variable). For the results of the logistic regression model for PASI75 (see Table 17), the odds ratio for the high IL-19 group could not be calculated because there were no PASI75 responders in the high IL-19 placebo group (see Table 15). Interaction terms to assess the difference in odds ratios between the high and low IL-19 groups for PASI75 response could also not be calculated. Figures 26-31 are forest plots summarizing the logistic regression results of these models (for IL-19 and other biomarkers described herein). Statistical models used to analyze the impact of baseline IL-19 levels were run with each treatment group (6 mg QD, 12 mg QD, and placebo) as a separate predictor (see Figure 26, Figure 27, and Table 16A for ACR20 results; Figure 29, Figure 30, and Table 17A for PASI75 results) and with the duravacitinib treatment group together (see Figure 28 and Table 16B for ACR20 results; Figure 31 and Table 17B for PASI75 results). [Table 18]

[0095] The results shown in Figure 26, Figure 27, and Table 16A show that for the high IL-19 group, the odds of responding to deuce ravacitinib (achieving an ACR20 response) were statistically significantly higher than the odds of achieving an ACR20 response in the placebo group in each treatment group, but not in the low IL-19 group, and the treatment effect was higher in the high IL-19 group (numerically higher in the 6 mg QD group and statistically significantly higher in the 12 mg QD group) than in the low IL-19 group (as shown by the odds ratios of achieving ACR20 in response to deuce ravacitinib vs. placebo). [Table 19]

[0096] The results shown in FIG. 28 and Table 16B indicate that deuclavacitinib provides a significant therapeutic effect in the high IL-19 group (see the second row of Table 16B), and that the therapeutic effect is significantly greater in the high IL-19 group than in the low IL-19 group (see the last row of Table 16B). [Table 20] [Table 21]

[0097] The results in Figures 29-31, Table 17A, and Table 17B show that the effect of deuclavacitinib was significant overall in achieving PASI 75. No statistically significant difference in treatment effect was observed in the low IL-19 group (see lines 3 and 4 of Table 17A and line 2 of Table 17B).

[0098] Separate logistic regression models were fitted depending on baseline IL-19 expression and response status as described above for BD2. Tables 18 and 19 show the results of the second model that takes into account baseline disease activity, as described below. [Table 22]

[0099] Figure 34, Figure 35, and Table 18 show the results of the second model according to ACR20 response status. The above table shows the results of the odds ratio for ACR20 response status at week 16, adjusted for baseline DAS28. The first two rows of Table 18 are the same as the first two rows of Table 10. As mentioned above, these two rows show the results for all patients (high IL-19 and low IL-19). The first two rows of Table 18 show the odds ratio and p-value of achieving ACR20 response when adjusted for baseline DAS28, comparing 6 mg or 12 mg with placebo for all patients (high IL-19 and low IL-19). The results show that even after adjusting for baseline DAS28, the probability of achieving ACR20 is significantly higher in the duravacitinib treatment group than in the placebo group.

[0100] The results shown in rows 3-6 of Table 18 were obtained using ACR20(Y / N)=treatment group*IL-19 group+TNF inhibitor use+baseline body weight (continuous variable)+baseline DAS28 (continuous variable). Rows 3 and 4 show the odds ratio results for the high IL-19 group. After adjusting for baseline DAS28, the probability of achieving ACR20 in high IL-19 patients was significantly higher than the probability of achieving ACR20 in the placebo group. In contrast, no such significant odds ratio results were found in the low IL-19 group (see rows 5 and 6 of Table 18). These results indicate that there is a correlation between high baseline IL-19 levels and significant clinical benefit from treatment with TYK2 inhibitors, regardless of baseline DAS28 (as shown by the significantly higher probability of achieving ACR20 with duravacitinib treatment than with placebo).

[0101] The results shown in rows 7 and 8 of Table 18 were obtained using the same model used in rows 3-6. The interaction results were significant for the 12 mg dose, and the results for both doses showed that (a) the odds ratio of response to deuclavacitinib vs. placebo in the high IL-19 group and (b) the odds ratio of response to deuclavacitinib vs. placebo in the low IL-19 group were calculated to be higher than the null hypothesis (i.e., 1). These results indicate that high IL-19 levels are associated with a higher odds ratio of response to TYK2 inhibitor treatment (as indicated by achieving ACR20) compared to placebo, even after accounting for baseline DAS28 scores, compared to low IL-19 levels.

[0102] Figure 32, Figure 33, and Table 19 show the results of the odds ratios according to PASI75 status, adjusted for baseline PASI scores. Because there were no PASI75 responders in the high IL-19 placebo arm, odds ratios could not be calculated for each high IL-19 treatment arm. Therefore, interaction terms could not be calculated to assess whether the odds ratios differed between the high and low IL-19 arms. [Table 23]

[0103] The results shown in Table 19 were obtained using PASI75(Y / N)=treatment group+IL-19 group+treatment group*IL-19 group+TNF inhibitor use+baseline body weight (continuous variable)+baseline PASI score. The results in rows 1 and 2 show that patients in both treatment groups obtained a significant treatment benefit even after adjusting for baseline PASI score (as shown by the significantly higher probability of achieving PASI75 with duravacitinib treatment compared to the probability of achieving PASI75 with placebo treatment). The results in rows 3 and 4 show that the low IL-19 group did not obtain a significant treatment benefit. This result is consistent with the conclusion that higher baseline IL-19 levels result in a greater treatment benefit.

[0104] Table 20 shows the results of the logistic regression model when patients were classified into four groups based on baseline serum IL-19 levels dichotomized according to their respective medians (as described above in BD2) and baseline PASI scores: high IL-19·high PASI, high IL-19·low PASI, low IL-19·high PASI, and low IL-19·low PASI. As there were no PASI75 responders in the high IL-19 placebo arm, results could not be calculated for the high IL-19·high PASI and high IL-19·low PASI groups. The results in Table 20 show that low IL-19 patients did not benefit from duravacitinib treatment compared to placebo, regardless of baseline PASI. [Table 24]

[0105] IL-17A A similar analysis was performed for baseline IL-17A levels. The median baseline IL-17A level (for all 202 patients with baseline IL-17A data) was 0.575 ng / L. Figures 19 and 20 show box plots of non-responders and responders at week 16 (PASI75 and ACR20 response status, respectively) in each treatment group, with the dashed horizontal lines corresponding to the median baseline IL-17A levels and the solid horizontal lines of each box showing the median baseline IL-17A levels for that box plot. Table 21 shows p values ​​for each treatment group for comparing mean or median baseline IL-17A levels for responders and non-responders; for t-tests comparing means, IL-17A levels were log2 transformed before calculating the responder and non-responder means. [Table 25]

[0106] Baseline IL-17A levels were higher in PASI75 non-responders than PASI75 responders in the placebo group, but higher in responders than non-responders in the deuclavacitinib treatment group (see Figure 19). Higher levels of IL-17A (like BD2 and IL-19) can be used to identify patients with better cutaneous response to deuclavacitinib compared to responses in patients with lower levels of IL-17A. Similar results were seen with ACR20 (see Figure 20).

[0107] Figures 21 and 22 are bar graphs showing the response rates of each treatment group reaching PASI75 or ACR20 response status at week 16 for patients in the high and low IL-17A groups (dichotomized according to median baseline levels of IL-17A). PsA patients with IL-17A levels above the median ("high IL-17A" group) had higher PASI75 response rates in both the 6 mg QD and 12 mg QD treatment groups compared to placebo, whereas PsA patients with baseline IL-17A levels below the median ("low IL-17A" group) had no significant difference in PASI75 response. Similarly, ACR20 response rates were higher in both the 6 mg QD and 12 mg QD treatment groups compared to placebo in the high IL-17 group, whereas no difference in ACR20 response rates was observed between the treatment groups in patients in the low IL-17 group. Table 22 below shows the number of responders and non-responders in the IL-17A low and IL-17A high patient groups (categorized by median baseline serum IL-17 levels measured in PsA patients) by treatment group. [Table 26]

[0108] Figures 23 and 24 show line graphs of response rates (PASI75 and ACR20, respectively) over time for the high and low baseline IL-17A groups. A dose-dependent change in PASI75 response over time was observed in the high IL-17A group, but not in the low IL-17A PsA patients. Furthermore, the high IL-17A group showed a higher ACR20 response rate over time in the duce lavacitinib treatment group compared to placebo, but the low IL-17A group did not.

[0109] In addition, PsA patients were divided into four groups (high IL-17A and high PASI, high IL-17A and low PASI, low IL-17A and high PASI, and low IL-17A and low PASI) according to baseline IL-17A expression level (above or below the median) and baseline PASI level (above or below the median). Table 23 shows the number of patients in each of the above groups. Figure 25 is a bar graph showing the PASI75 response status at week 16 in each treatment group for all patients classified into the above four groups. The bar graph shows that baseline IL-17A levels and baseline PASI levels correlate with PASI75 response to deuce lavacitinib, and that baseline IL-17A levels correlate with PASI75 response to deuce lavacitinib even for patients in the low PASI group (see "high IL-17A, low PASI" group in Figure 25). [Table 27]

[0110] Logistic regression models were fitted as described above for BD2 and IL-19. For the response measures ACR20 and PASI75, odds ratios for each treatment group versus placebo were calculated for the high and low IL-17A groups. The model used for ACR20 was ACR20(Y / N)=treatment group+IL-17A group+treatment group*IL-17A group+TNF inhibitor use+baseline weight (continuous variable). The same model was used for PASI75 response status: PASI75(Y / N)=treatment group+IL-17A group+treatment group*IL-17A group+TNF inhibitor use+baseline weight (continuous variable). The p-values ​​for the interaction terms were used to identify whether the ORs of achieving a response were significantly different between the high and low IL-17A groups. Figures 26-31 are forest plots summarizing the logistic regression results of these models (for IL-17A and other biomarkers described herein). The statistical models used to analyze the impact of baseline IL-17A levels were run with each treatment group (6 mg QD, 12 mg QD, and placebo) as a separate predictor (see Figures 26, 27, and Table 24A for ACR20 results; Figures 29, 30, and Table 25A for PASI75 results) and with the duovacitrinib treatment group together (see Figure 28 and Table 24B for ACR20 results; Figure 31 and Table 25B for PASI75 results). [Table 28] [Table 29] [Table 30] [Table 31]

[0111] High baseline IL-17A levels correlated with significant treatment benefit, as shown by significantly higher odds of achieving ACR20 and PASI75 in response to deuce ravasitinib compared to placebo (see Figure 28 and Table 24B, line 2 for ACR20 results; Figure 31 and Table 25B for PASI75 results). This was observed at each treatment dose (see Figure 26, Figure 27, and Table 24A, lines 3 and 4 for ACR20; Figure 29, Figure 30, and Table 25A, lines 3 and 4 for PASI75). No such results were seen in the low IL-17A group (see Table 24B and Table 25B, line 3, and Table 24A and Table 25A, lines 5 and 6). Furthermore, compared to the low IL-17A group, the high IL-17A group had a calculated higher ACR20 therapeutic effect (see lines 7 and 8 of Table 24A and the last line of Table 24B) and a statistically significantly higher PASI75 therapeutic effect (see lines 7 and 8 of Table 25A and the last line of Table 25B).

[0112] Separate logistic regression models were fitted according to baseline serum IL-17 levels and response status as described above for BD2 and IL-19. Tables 26 and 27 show the results of a second model that takes into account baseline disease activity, as described below. [Table 32] Table 26 shows the results of the second model for ACR20 response status. The table shows the odds ratio results for ACR20 response status at week 16, adjusted for baseline DAS28 (see also Figures 34 and 35). The first two rows of Table 26 show that even after adjusting for baseline DAS28, the odds of achieving an ACR20 response are significantly higher in the ducevacitinib treatment group than in the placebo group for all patients (high and low IL-17A).

[0113] The results shown in lines 3-6 of Table 26 were obtained using ACR20 (Y / N) = treatment group * IL-17A group + TNF inhibitor use + baseline body weight (continuous variable) + baseline DAS28 (continuous variable). Lines 3 and 4 show odds ratio results for the high IL-17A group. These results show that for high IL-17A patients, the probability of achieving ACR20 in each duke labacitinib treatment group was significantly higher than the probability of achieving an ACR20 response in the placebo group after adjusting for baseline DAS28. In contrast, no such significant odds ratio results were observed in the low IL-17A group (see lines 5 and 6 of Table 26). These results indicate that higher baseline IL-17A levels correlate with significant treatment response, regardless of baseline DAS28 (as shown by a significantly higher probability of achieving ACR20 with deucelabacitinib treatment compared with placebo).

[0114] The results shown in rows 7 and 8 of Table 26 were obtained using the same model used in rows 3-6. Although these results from the interaction terms are not statistically significant, they are consistent with the other results and show that (a) the odds ratio of response to deucelavacitinib vs. placebo in the high IL-17A group compared with (b) the odds ratio of response to deucelavacitinib vs. placebo in the low IL-17A group is computationally greater than the null hypothesis (i.e., 1). [Table 33]

[0115] Table 27 shows the odds ratio results for PASI75 status, adjusted for baseline PASI scores. The first two rows of Table 27 show the odds ratio results for PASI75 status at week 16 for all patients (high IL-17A and low IL-17A), when adjusted for baseline PASI scores. These results are therefore identical to those shown in the first two rows of Tables 11 and 19.

[0116] The results in rows 3-6 of Table 27 are based on PASI75(Y / N)=treatment group*IL-17A group+TNF inhibitor use+baseline weight (continuous variable)+baseline PASI score (continuous variable). Figures 32 and 33 show forest plots summarizing the results of the above models. Rows 3 and 4 show odds ratio results for the high IL-17A group. These results show that for high IL-17A patients after adjusting for baseline PASI score, the probability of achieving a PASI75 response in each duke lavacitinib treatment group was significantly higher than the probability of achieving a PASI75 response in the placebo group. In contrast, such significant odds ratio results were not seen in low IL-17A patients (see rows 5 and 6 of Table 27). These results indicate that higher baseline IL-17A levels correlate with greater clinical benefit from TYK2 inhibitor treatment compared to placebo treatment (as demonstrated by achieving PASI 75), regardless of baseline PASI score.

[0117] The results shown in rows 7 and 8 of Table 27 were obtained using the same model used in rows 3-6. (a) The odds ratio of achieving PASI75 after treatment with deucrucitinib or placebo in the high IL-17A group compared with (b) the odds ratio of achieving PASI75 after treatment with deucrucitinib or placebo in the low IL-17A group are statistically significantly higher than the null hypothesis (i.e., 1). These results show that high IL-17A levels, compared with low IL-17A levels (as shown by reaching PASI75), are associated with significantly higher odds ratios of responding to treatment with a TYK2 inhibitor (compared to placebo), even after adjusting for PASI baseline values.

[0118] For PASI75 response status, separate logistic regression models were used to assess the predictive value of baseline IL-17A levels and baseline PASI scores, each dichotomized as described above. From this model, odds ratios were calculated for each treatment group versus placebo for each of the four baseline IL-17A vs. PASI groups (i.e., high IL-17A vs. high PASI, high IL-17A vs. low PASI, low IL-17A vs. high PASI, and low IL-17A vs. low PASI (see Figure 25)). The model was: PASI75(Y / N)=treatment group+baseline IL-17A vs. PASI group+treatment group*baseline IL-17A vs. PASI group+TNF inhibitor use+baseline body weight (continuous variable). The results of this model are shown in Table 28. [Table 34]

[0119] In Table 28, the first two rows show odds ratios comparing the probability of achieving PASI75 with each deucelavacitinib treatment group versus placebo, using PASI75(Y / N)=treatment group+TNF inhibitor use+baseline body weight (continuous variable). Odds ratios in rows 3-10 show results from PASI75(Y / N)=treatment group+IL-17A·PASI baseline+treatment group*IL-17A·PASI baseline+TNF inhibitor use+baseline body weight (continuous variable). In both treatment groups, patients with high baseline IL-17A levels (as indicated by PASI75) had a significantly higher probability of responding to deucelavacitinib compared to placebo, regardless of baseline PASI score status (see rows 3, 4, 5, and 6). In contrast, this was not the case for many patients with low baseline IL-17A levels (see lines 7, 9, and 10). Among the low IL-17A patients, only the low IL-17A·high PASI group showed a statistically significant increased probability of responding to duravacitinib compared to the probability of responding to placebo (see line 8).

[0120] C-reactive protein (CRP) Analyses similar to those shown for other proteins were also performed on baseline levels of CRP measured in patients with PsA. The median baseline CRP level (for all 203 patients with baseline CRP data) was 8.31 mg / L. Figures 36 and 37 show box plots of non-responders and responders (PASI75 and ACR20 response status, respectively) in each treatment group at week 16. The dashed horizontal lines correspond to the median baseline CRP levels, and the solid horizontal line of each box indicates the median baseline CRP level for that box plot. Table 29 shows p-values ​​for each treatment group for comparing mean or median baseline CRP levels between responders and non-responders; for t-tests comparing means, CRP levels were log2 transformed before calculating the means for responders and non-responders. Baseline CRP levels were significantly higher only in responders in the 12 mg QD treatment group for PASI75 and ACR20, respectively, but there were no significant differences between responders and non-responders in the placebo or 6 mg QD treatment groups. [Table 35]

[0121] Patients were dichotomized into low CRP group (patients with baseline CRP levels below the median) and high CRP group (patients with baseline CRP levels above the median). Table 30 shows the number of responders and non-responders in the low and high CRP groups by treatment group. [Table 36]

[0122] Figures 38 and 39 are bar graphs showing the response rates of each treatment group reaching PASI75 or ACR20 response status at week 16 for the high and low CRP groups. For both the high and low CRP groups, the PASI75 response rate showed a dose-response effect, with the response rate in the 6 mg declavacitinib treatment group being higher than the response rate in the placebo group, and the response rate in the 12 mg declavacitinib treatment group being even higher than the 6 mg treatment group. Similar results were obtained for the ACR20 response rate, except that there was no difference in the response rate between the 6 mg and 12 mg treatment groups in the low CRP group.

[0123] Figures 40 and 41 are line graphs of the response rates (PASI75 and ACR20, respectively) over time for the high and low CRP groups. The duravacitinib treatment group showed a higher response rate than the placebo group, but no difference in response was observed between the high and low CRP groups.

[0124] In addition, PsA patients were divided into four groups according to the baseline CRP level and baseline PASI level (high CRP and high PASI, high CRP and low PASI, low CRP and high PASI, and low CRP and low PASI). Table 30 shows the number of PsA patients in each of the above four groups. [Table 37]

[0125] Figure 42 is a bar graph of PASI75 response status in each treatment group for all patients divided into the four groups described above at Week 16. The bar graph shows that baseline CRP levels are not consistently associated with PASI75 response.

[0126] Logistic regression models were fitted as described above for the other proteins. For the response measures ACR20 and PASI75, models were fitted to obtain odds ratios for treatment versus placebo in the high and low CRP groups. For the first logistic regression model, the following was used: -ACR20 response status: ACR20(Y / N)=treatment group+CRP group+treatment group*CRP group+TNF inhibitor use+baseline body weight (continuous variable) - PASI75 response status: PASI75(Y / N) = treatment group + CRP group + treatment group*CRP group + TNF inhibitor use + baseline body weight (continuous variable)

[0127] The p-values ​​of the interaction terms were used to identify whether the odds ratios of achieving a response were significantly different between the high and low CRP groups. Figures 26-31 are forest plots summarizing the logistic regression results of these models (for CRP and the biomarkers described herein). Tables 32 and 33 show the odds ratio results for CRP. The statistical models used to analyze the impact of baseline CRP levels were run with each treatment group (6 mg QD, 12 mg QD, and placebo) as a separate predictor (see Figures 26, 27, and Table 32A for ACR20 results; Figures 29, 30, and Table 33A for PASI75 results) and with the duocravacitinib treatment group together (see Figure 28 and Table 32B for ACR20 results; Figure 31 and Table 33B for PASI75 results). [Table 38]

[0128] The results in Figure 26, Figure 27, and Table 32A show that there is no difference in the treatment effect between the high CRP group and the low CRP group. The high CRP group and the low CRP group showed a treatment effect at both doses of deuclevacitinib (as shown by the higher probability of achieving ACR20 with treatment compared to placebo). The treatment effect was not statistically significant only in the 6 mg treatment group in the high CRP group (see line 3), but was significant in the 12 mg treatment group (see line 4) and at both doses in the low CRP group (see lines 5 and 6). There was no significant treatment effect (odds ratio of response to deuclevacitinib or placebo) difference between the high CRP group and the low CRP group at either treatment dose (the interaction term was not statistically significant (see the last two lines of Table 32A)). [Table 39]

[0129] The ACR20 results in Figure 28 and Table 32B show that the treatment effect (odds ratios for responding to deucelabacitinib or placebo) was significant in the high and low CRP groups (see rows 2 and 3 of Table 32B), and no significant difference in treatment effect was observed between the high and low CRP groups (see last row of Table 32B). [Table 40]

[0130] Figure 29, Figure 30, and Table 33A show the results of a similar analysis for PASI75 response. The results show that there is no consistent difference in response to TYK2 inhibitor treatment at any dose of deucravacitinib in the high and low CRP groups. Patients in the high CRP group showed a significant treatment response at both doses (as shown by the significantly higher probability of responding to deucravacitinib compared to the probability of responding to placebo) (see lines 3 and 4). Patients in the low CRP group also showed an increased probability of responding to deucravacitinib at both doses compared to the probability of responding to placebo (see lines 5 and 6). Furthermore, this probability was statistically significantly increased in the 12 mg QD group (see line 6). The interaction term was not statistically significant, and at both doses, the treatment effect (as measured by the odds ratios of responding to deucelabacitinib or placebo) was not significantly different between the high and low CRP groups. [Table 41]

[0131] The PASI75 results in Figure 31 and Table 33B show that there is a treatment effect (higher probability of responding to placebo than to deucelavacitinib) in both the high and low CRP groups (see rows 2 and 3 of Table 33B). The treatment effect (odds ratio of responding to deucelavacitinib or placebo) was not significantly different between the high and low CRP groups (see the last row of Table 33B).

[0132] The logistic regression model was not adjusted for baseline disease activity. To account for any potential confounding of baseline disease activity, a second model was used that adjusted for baseline disease activity. Figures 32-35 are forest plots summarizing the results of this second model. Here, Tables 34 and 35 show the odds ratio results for CRP in this model. [Table 42]

[0133] Table 34 shows the results of the second model for ACR20 response status. The table shows the odds ratio results for ACR20 response status at week 16, adjusted for baseline DAS28. The first two rows of Table 34 show the odds ratios and p-values ​​for achieving an ACR20 response for all patients (high and low CRP) using ACR20(Y / N)=treatment group+TNF inhibitor use+baseline weight (continuous variable)+baseline DAS28 (continuous variable) when adjusted for baseline DAS28. The odds ratios show the odds ratios comparing 6mg or 12mg with placebo. These results show that the probability of achieving an ACR20 response is significantly higher in the duravacitinib treatment group than in the placebo group, even after adjusting for baseline DAS28.

[0134] The results shown in lines 3-6 of Table 34 were obtained using ACR20(Y / N)=treatment group*CRP group+TNF inhibitor use+baseline weight (continuous variable)+baseline DAS28 (continuous variable). These results show that in patients with high CRP, after adjusting for baseline DAS28, each duravacitinib treatment group had a higher probability of achieving an ACR20 response than the placebo group (see lines 3 and 4). Furthermore, statistically significant odds ratios were reached in the high-dose treatment groups (see line 4). In patients with low CRP, after adjusting for baseline DAS28, each duravacitinib treatment group had a significantly higher probability of achieving an ACR20 response than the placebo group (see lines 5 and 6).

[0135] The results shown in rows 7 and 8 of Table 34 were obtained using the same model used in rows 3 to 6. These results from the interaction terms were not statistically significant, indicating that in both treatment groups, the odds ratios of reaching ACR20 after TYK2 inhibitor treatment or placebo in the high CRP group were not statistically different from the odds ratios of reaching ACR20 after TYK2 inhibitor treatment or placebo in the low CRP group, even after adjusting for baseline DAS28 scores. [Table 43]

[0136] Table 35 shows the results of a similar model for PASI75 response status. The table shows the results of the odds ratios for PASI75 status at week 16 adjusted for baseline PASI score. The first two rows of Table 35 show the odds ratios and p-values ​​for achieving a PASI75 response for all patients (high and low CRP) using PASI75(Y / N)=treatment group+TNF inhibitor use+baseline weight (continuous variable)+baseline PASI score (continuous variable) when adjusting for baseline PASI score. Odds ratios show odds ratios comparing 6mg or 12mg with placebo. These results show that even after adjusting for baseline PASI score, the probability of achieving a PASI75 response is significantly higher in the duce lavacitinib treatment group than in the placebo group.

[0137] The results shown in rows 3-6 of Table 35 were obtained using PASI75(Y / N)=treatment group*CRP group+TNF inhibitor use+baseline weight (continuous variable)+baseline PASI score (continuous variable). Rows 3 and 4 show odds ratio results for the high CRP group. In patients with high CRP, after adjusting for baseline PASI score, the probability of each duke labacitinib treatment group achieving a PASI75 response was significantly higher than the probability of the placebo group achieving PASI75.

[0138] These results show that in patients with high CRP, after adjusting for baseline PASI scores, the probability of each deucelavacitinib treatment group achieving PASI 75 was significantly higher than the probability of the placebo group achieving PASI 75 (see lines 3 and 4). In patients with low CRP, after adjusting for baseline PASI scores, the probability of each deucelavacitinib treatment group achieving a PASI response was higher than the probability of the placebo group achieving a PASI 75 response (see lines 5 and 6), with statistically significant odds ratios being reached in the 12 mg QD group (see line 6).

[0139] The results shown in rows 7 and 8 of Table 35 were obtained using the same model used in rows 3 to 6. The results from the interaction terms show that, even after adjusting for baseline PASI scores, there were no significant differences in the odds ratios of achieving PASI 75 after TYK2 inhibitor treatment or placebo between the low and high CRP groups in both treatment arms.

[0140] Separate logistic regression models were used for PASI75 to assess the predictive value of baseline CRP levels and baseline PASI scores, each dichotomized as described above. From this model, odds ratios were calculated for each treatment group versus placebo for each of the four baseline CRP vs. PASI groups (i.e., high CRP vs. high PASI, high CRP vs. low PASI, low CRP vs. high PASI, and low CRP vs. low PASI (see Figure 42)). The model was PASI75(Y / N)=treatment group+baseline CRP vs. PASI groups+treatment group*baseline CRP vs. PASI groups+TNF inhibitor use+baseline body weight (continuous variable). Table 36 shows the results of this model. [Table 44]

[0141] In Table 36, the first two rows show odds ratios comparing 6 mg QD or 12 mg QD with placebo for all patients, using PASI75(Y / N)=treatment group+TNF inhibitor use+baseline weight (continuous variable). The odds ratios in rows 3-10 show results from PASI75(Y / N)=treatment group+CRP·PASI baseline group+treatment group*CRP·PASI baseline group+TNF inhibitor use+baseline weight (continuous variable). For example, 18.381 in row 3 is the odds ratio comparing the probability of achieving a response in the 6 mg QD treatment group with the probability of achieving a response in the placebo group for patients with a CRP level above the median and a PASI baseline score above the median.

[0142] The results in Table 36 show that in both treatment groups, the high CRP / high PASI group was significantly more likely to respond to deuxlavacitinib (as indicated by PASI75) compared to placebo (see rows 3 and 4), whereas the high CRP / low PASI group did not. In low CRP patients, only the low CRP / high PASI group receiving the high dose showed a significant treatment effect (see row 8). These results indicate that high baseline CRP levels alone are not consistently associated with response to treatment.

[0143] conclusion The results described herein indicate that baseline levels of BD2, IL-19, and IL-17A can be used to predict responsiveness to TYK2 inhibitor therapy and to select PsA patients for treatment. Higher baseline levels of these biomarkers were associated with clinical response. Patients with higher baseline expression of the IL-23 pathway biomarkers BD2, IL-19, and IL-17A were more likely to benefit from deuxiuravacitinib compared to placebo in treating the skin and joint manifestations of psoriatic arthritis.

[0144] Additionally, BD2, IL-19, and IL-17A are decreased over time by TYK2 inhibitor treatment, as shown in Figures 43A and 43B, 44, and 45, respectively. Other proteins, such as CRP, are also decreased over time by TYK2 inhibitor treatment (see Figure 46). However, baseline levels of these proteins were not consistently associated with clinical response to TYK2 inhibitor treatment.

[0145] While the present invention has been particularly described and illustrated with reference to preferred embodiments thereof, it will be understood by those skilled in the art in light of this disclosure that various changes in form and detail may be made therein without departing from the scope of the invention as encompassed by the appended claims.

Claims

1. A pharmaceutical composition comprising a TYK2 inhibitor for treating a patient with psoriatic arthritis, wherein the patient with psoriatic arthritis treated with the pharmaceutical composition has one of the following: (a) measuring the level of one or more proteins selected from beta-defensin 2, IL-19, and IL-17A in a blood sample from a patient with psoriatic arthritis; (b) comparing each level of the protein measured in (a) to a threshold level of that protein; and (c) the level of at least one of the one or more proteins measured in (a) is above a threshold level for that protein; A pharmaceutical composition selected by the formula:

2. The pharmaceutical composition of claim 1, wherein the one or more proteins include beta-defensin 2.

3. The pharmaceutical composition of claim 1, wherein the one or more proteins include IL-19.

4. The pharmaceutical composition of claim 1, wherein the one or more proteins include IL-17A.

5. The pharmaceutical composition of claim 1, wherein the blood sample is a serum sample or a plasma sample, and the one or more proteins include at least two proteins selected from beta-defensin 2, IL-19, and IL-17A.

6. 6. The pharmaceutical composition of claim 5, wherein the TYK2 inhibitor is deuclavacitinib.

7. A pharmaceutical composition comprising a TYK2 inhibitor for treating a human subject suffering from psoriatic arthritis, wherein the human subject suffering from psoriatic arthritis: For each of two or more proteins selected from beta-defensin 2, IL-19, and IL-17A, the level of the protein in the blood of a human subject is above a threshold level for that protein. A pharmaceutical composition selected under the condition:

8. The pharmaceutical composition of claim 7, wherein the two or more proteins include beta-defensin 2 and IL-19.

9. The pharmaceutical composition of claim 7, wherein the two or more proteins include beta-defensin 2 and IL-17A.

10. The pharmaceutical composition of claim 7, wherein the two or more proteins include IL-19 and IL-17A.

11. The pharmaceutical composition of claim 7, wherein the two or more proteins include beta-defensin 2, IL-19, and IL-17A.

12. 8. The pharmaceutical composition of claim 7, wherein the TYK2 inhibitor is deuclavacitinib.

13. A pharmaceutical composition for treating psoriatic arthritis in a human subject, comprising a TYK2 inhibitor, (a) measuring the level of one or more proteins selected from beta-defensin 2, IL-19, and IL-17A in a blood sample from a human subject; (b) comparing each level of the protein measured in (a) to a threshold level of that protein; and (c) administering the pharmaceutical composition to the human subject if the level of at least one of the one or more proteins measured in (a) is above a threshold level for that protein. A pharmaceutical composition comprising:

14. 14. The pharmaceutical composition of claim 13, wherein the one or more proteins include beta-defensin 2.

15. 14. The pharmaceutical composition of claim 13, wherein the one or more proteins include IL-19.

16. The pharmaceutical composition of claim 13, wherein the one or more proteins include IL-17A.

17. The pharmaceutical composition of claim 13, wherein the blood sample is a serum sample or a plasma sample, and the one or more proteins include at least two proteins selected from beta-defensin 2, IL-19, and IL-17A.

18. 14. The pharmaceutical composition of claim 13, wherein the TYK2 inhibitor is deuclavacitinib.

19. 19. The pharmaceutical composition according to claim 18, characterized in that deuclavacitinib is administered to a human subject at a dose of 6 mg or more per day.

20. 19. The pharmaceutical composition according to claim 18, characterized in that deuclavacitinib is administered to a human subject at a dose of 12 mg or more per day.

21. 1. A pharmaceutical composition for treating a human subject with psoriatic arthritis, comprising a TYK2 inhibitor, identifying that the level of one or more proteins selected from beta-defensin 2, IL-19, and IL-17A in the blood of a human subject suffering from psoriatic arthritis is above a threshold level, and that each of said proteins is associated with that threshold level; and then administering the pharmaceutical composition to the human subject. A pharmaceutical composition comprising:

22. 22. The pharmaceutical composition of claim 21, wherein the TYK2 inhibitor is deuclavacitinib.

23. A pharmaceutical composition comprising a TYK2 inhibitor for treating a patient with psoriatic arthritis, wherein prior to administration of the pharmaceutical composition, the patient with psoriatic arthritis undergoes one of the following: levels of beta-defensin 2 in the blood above the threshold level of beta-defensin 2; the level of IL-19 in the blood is above the threshold level of IL-19; Blood levels of IL-17A exceed the threshold level of IL-17 A pharmaceutical composition identified as meeting one or more of the following criteria:

24. The pharmaceutical composition of claim 23, wherein the TYK2 inhibitor is deuclavacitinib.

25. A pharmaceutical composition comprising a TYK2 inhibitor for treating psoriatic arthritis in a subject, wherein the subject has been identified as having a blood level of beta-defensin 2 above a threshold level of beta-defensin 2, a blood level of IL-19 above a threshold level of IL-19, a blood level of IL-17A above a threshold level of IL-17, or any combination thereof.

26. A pharmaceutical composition comprising a TYK2 inhibitor for treating a patient with psoriatic arthritis, wherein the patient with psoriatic arthritis treated with the pharmaceutical composition has one of the following: (a) containing a certain level of one or more proteins (wherein the one or more proteins include one or more of β-defensin 2, IL-19, and IL-17A) in a blood sample from a patient with psoriatic arthritis; (b) the protein level of (a) is above a threshold level for each of the proteins; A pharmaceutical composition selected by the formula:

27. 27. The pharmaceutical composition of claim 26, wherein the one or more proteins include beta-defensin 2.

28. 27. The pharmaceutical composition of claim 26, wherein the one or more proteins include IL-19.

29. 27. The pharmaceutical composition of claim 26, wherein the one or more proteins include IL-17A.

30. A pharmaceutical composition comprising a TYK2 inhibitor for treating a patient with psoriatic arthritis, wherein the patient with psoriatic arthritis treated with the pharmaceutical composition has one of the following: (a) the presence of consistent levels of beta-defensin 2 in blood samples from patients with psoriatic arthritis; and (b) the level of β-defensin 2 in (a) exceeds a threshold level of β-defensin 2 A pharmaceutical composition selected by the formula:

31. A pharmaceutical composition comprising a TYK2 inhibitor for treating a patient with psoriatic arthritis, wherein the patient with psoriatic arthritis treated with the pharmaceutical composition has one of the following: (a) the presence of IL-19 at a consistent level in blood samples from patients with psoriatic arthritis; and (b) the level of IL-19 in (a) exceeds a threshold level of IL-19; A pharmaceutical composition selected by the formula:

32. A pharmaceutical composition comprising a TYK2 inhibitor for treating a patient with psoriatic arthritis, wherein the patient with psoriatic arthritis treated with the pharmaceutical composition has one of the following: (a) the presence of IL-17A at a consistent level in blood samples from patients with psoriatic arthritis; and (b) the IL-17A level in (a) exceeds the threshold level of IL-17A; A pharmaceutical composition selected by the formula:

33. The pharmaceutical composition of claims 26 to 32, wherein the TYK2 inhibitor is deuclavacitinib.

34. 34. The pharmaceutical composition of claim 33, for administering 6 mg or more of deuclavacitinib per day to said patient with psoriatic arthritis.

35. 34. The pharmaceutical composition of claim 33, for administering 12 mg or more of decravacitinib per day to said patient with psoriatic arthritis.

36. Use of a TYK2 inhibitor for the manufacture of a medicament for treating psoriatic arthritis in a patient, wherein the patient to be treated with the medicament has: (a) measuring the level of one or more proteins selected from beta-defensin 2, IL-19, and IL-17A in a blood sample from the patient; (b) comparing each level of the protein measured in (a) to a threshold level of that protein; and (c) the level of at least one of the one or more proteins measured in (a) is above a threshold level for that protein; Use, selected by a method characterized by:

37. The use described in claim 36, wherein the TYK2 inhibitor is deuclavacitinib.

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