POS1072 Icotrokinra, a Targeted Oral Peptide That Selectively Blocks the Interleukin-23-Receptor, for the Treatment of Moderate-to-Severe Plaque Psoriasis: Results Through Week 24 of the Phase 3, Randomized, Double-Blind, Placebo-Controlled ICONIC-LEAD Trial
Bibliographic record
Abstract
Background: Icotrokinra (ICO), a first-in-class, targeted oral peptide that selectively binds to the interleukin-23-receptor and inhibits signaling, demonstrated significant, durable skin clearance and a safety profile similar to placebo in Phase 2 studies in plaque psoriasis. Objectives: To report findings from the first Phase 3 ICO study in participants with moderate-to-severe plaque psoriasis. Methods: The pivotal, Phase 3, double-blind, placebo-controlled ICONIC-LEAD trial (NCT06095115) randomized adults and adolescents (≥12 years to <18 years) with moderate-to-severe plaque psoriasis (body surface area [BSA] ≥10%; Psoriasis Area Severity Index [PASI] ≥12; overall Investigator's Global Assessment [IGA] ≥3) 2:1 to once-daily (QD) ICO 200 mg through Week 24 or placebo through Week 16 followed by transition to ICO 200 mg QD. Co-primary endpoints were IGA 0/1 (clear [0]/almost-clear [1] skin and ≥2-grade improvement from baseline) and PASI 90 responses at Week 16. Results: ICONIC-LEAD randomized 684 participants (ICO=456; placebo=228). The co-primary endpoints were met: 65% ICO-treated vs 8% placebo-treated participants achieved IGA 0/1, and 50% vs 4%, respectively, achieved PASI 90 at Week 16 (both P<0.001). ICO completely cleared skin at significantly higher rates than placebo at Week 16 (IGA 0: 33% vs 1%; PASI 100: 27% vs <1%; both multiplicity-adjusted P<0.001). ICO response rates continued to increase through Week 24, including IGA 0/1 in 74%, PASI 90 in 65%, IGA 0 in 46%, and PASI 100 in 40% of participants. Similar proportions of ICO-treated and placebo-treated participants had ≥1 adverse events (49% in each group; most commonly nasopharyngitis and upper respiratory tract infection) and gastrointestinal-related events (6% per group) through Week 16. No safety signals emerged through Week 24. Conclusion: ICO demonstrated significantly higher rates of skin clearance and a favorable safety profile in adults and adolescents with moderate-to-severe plaque psoriasis. REFERENCES: NIL . Acknowledgements: NIL . Disclosure of Interests: Robert Bissonnette Advisory board member: AbbVie, Alumis, Amgen, Arcutis, Bausch Health, Boston, Bristol Myers Squibb/Celgene, Dermavant, Eli Lilly, Janssen, LEO Pharma, Nimbus, Novartis, Pfizer, Regeneron, UCB, VentyxBio, and Xencor, Speaker: AbbVie, Alumis, Amgen, Arcutis, Bausch Health, Boston, Bristol Myers Squibb/Celgene, Dermavant, Eli Lilly, Janssen, LEO Pharma, Nimbus, Novartis, Pfizer, Regeneron, UCB, VentyxBio, and Xencor, Shareholder: Innovaderm Research, Employee: Innovaderm Research, Consulstant: AbbVie, Alumis, Amgen, Arcutis, Bausch Health, Boston, Bristol Myers Squibb/Celgene, Dermavant, Eli Lilly, Janssen, LEO Pharma, Nimbus, Novartis, Pfizer, Regeneron, UCB, VentyxBio, and Xencor, Grants/honoraria: AbbVie, Alumis, Amgen, Arcutis, Bausch Health, Boston, Bristol Myers Squibb/Celgene, Dermavant, Eli Lilly, Janssen, LEO Pharma, Nimbus, Novartis, Pfizer, Regeneron, UCB, VentyxBio, and Xencor, Jennifer Soung Speaker: AbbVie, Amgen, Arcutis, Bristol Myers Squibb, Coval Biopharma, Dermavant, Eli Lilly, Janssen, KoBio Labs, LEO Pharma, National Psoriasis Foundation, Novartis, Pfizer, Regeneron, Sanofi, and UCB, Consultant: AbbVie, Amgen, Arcutis, Bristol Myers Squibb, Coval Biopharma, Dermavant, Eli Lilly, Janssen, KoBio Labs, LEO Pharma, National Psoriasis Foundation, Novartis, Pfizer, Regeneron, Sanofi, and UCB, Investigator: AbbVie, Amgen, Arcutis, Bristol Myers Squibb, Coval Biopharma, Dermavant, Eli Lilly, Janssen, KoBio Labs, LEO Pharma, National Psoriasis Foundation, Novartis, Pfizer, Regeneron, Sanofi, and UCB, Adelaide Hebert Honoraria: Pfizer, Dermavant, Arcutis, Incyte, Alphyn, Beiersdorf, Galderma, Ortho Dermatologics, and Almirall, DSMB: Sanofi-Regeneron, Ortho Dermatologics, and Aphyn, Grants: Janssen, LEO Pharma, Ortho Dermatologics, Dermavant, Arcutis, Takeda, and Eli Lilly, Andrew Pink Educational support: AbbVie, Almirall, Amgen, BI, Bristol Myers Squibb, Galderma, Janssen, LEO Pharma, Lilly, Novartis, Pfizer, Sanofi, and UCB, Advisor/Speaker: AbbVie, Almirall, Amgen, BI, Bristol Myers Squibb, Galderma, Janssen, LEO Pharma, Lilly, Novartis, Pfizer, Sanofi, and UCB, Investigator: AbbVie, Almirall, Amgen, BI, Bristol Myers Squibb, Galderma, Janssen, LEO Pharma, Lilly, Novartis, Pfizer, Sanofi, and UCB, Andreas Pinter Advisor: AbbVie, Almirall Hermal, Amgen, Biogen Idec, BioNTech, Boehringer Ingelheim, Celgene, Celltrion, Eli Lilly, Galderma, GSK, Hexal, Janssen-Cilag GmbH, Klinge Pharma, LEO Pharma, MC2, Medac, Merch Serono, Mitsubishi, MSD, Novartis, Pascoe, Pfizer, Regeneron, Roche, Sandoz Biopharmaceuticals, Sanofi Genzyme, Schering-Plough, Tigercat Pharma, UCB, and Zuellig Pharma, Speakers Honoraria: AbbVie, Almirall Hermal, Amgen, Biogen Idec, BioNTech, Boehringer Ingelheim, Celgene, Celltrion, Eli Lilly, Galderma, GSK, Hexal, Janssen-Cilag GmbH, Klinge Pharma, LEO Pharma, MC2, Medac, Merch Serono, Mitsubishi, MSD, Novartis, Pascoe, Pfizer, Regeneron, Roche, Sandoz Biopharmaceuticals, Sanofi Genzyme, Schering-Plough, Tigercat Pharma, UCB, and Zuellig Pharma, Grants and/or participated in clinical trials: AbbVie, Almirall Hermal, Amgen, Biogen Idec, BioNTech, Boehringer Ingelheim, Celgene, Celltrion, Eli Lilly, Galderma, GSK, Hexal, Janssen-Cilag GmbH, Klinge Pharma, LEO Pharma, MC2, Medac, Merch Serono, Mitsubishi, MSD, Novartis, Pascoe, Pfizer, Regeneron, Roche, Sandoz Biopharmaceuticals, Sanofi Genzyme, Schering-Plough, Tigercat Pharma, UCB, and Zuellig Pharma, Yuling Shi: None declared, Joseph F. Merola Consultant: AbbVie, Amgen, Astra-Zeneca, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Dermavant, Eli Lilly, Incyte, Janssen, LEO Pharma, Moonlake, Novartis, Pfizer, Sanofi-Regeneron, Sun, and UCB, Megan Miller Stock/stock options: Johnson & Johnson, Employee: Johnson & Johnson, Joseph Cafone Stock/stock options: Johnson & Johnson, Employee: Johnson & Johnson, Jing Zhi Jiang Stock/stock options in: Johnson & Johnson, Employee: Johnson & Johnson, Cynthia DeKlotz Stock/stock options: Johnson & Johnson, Employee: Johnson & Johnson, Mark Lebwohl Employee: Mount Sinai, Consultant: Almirall, AltruBio Inc., Apogee, Arcutis, AstraZeneca, Atomwise, Avotres, Boehringer Ingelheim, Bristol Myers Squibb, Castle Biosciences, Celltrion, CorEvitas, Dermavant Sciences, Dermsquared, Evommune, Inc., Facilitation of International Dermatology Education, Forte Biosciences, Galderma, Genentech, Incyte, LEO Pharma, Meiji Seika Pharma, Mindera, Pfizer, Sanofi-Regeneron, Seanergy, Strata, Takeda, Trevi, and Verrica, Research funds: AbbVie, Arcutis, Avotres, Boehringer Ingelheim, Cara Therapeutics, Clexio, Dermavant Sciences, Eli Lilly, Incyte, Inozyme, Janssen, Pfizer, Sanofi-Regeneron, and UCB. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".