Population PK/PD Modeling and Simulation to Predict the Comparative Long-Term Efficacy of Olokizumab in Rheumatoid Arthritis Patients
Yuri Kosinsky, Ivan Azarov, Kirill Zhudenkov, Kirill Peskov, Sergey Grishin, Alina Egorova, Yuliya Berezovskaya, Maria Lemak, Mikhail Samsonov, Eugen Feist · 2026
Read Population PK/PD Modeling and Simulation to Predict the Comparative Long-Term Efficacy of Olokizumab in Rheumatoid Arthritis Patients by Yuri Kosinsky, Ivan Azarov, Kirill Zhudenkov, Kirill Peskov, Sergey Grishin, Alina Egorova, Yuliya Berezovskaya, Maria Lemak, Mikhail Samsonov, Eugen Feist (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13665878.txt.
Description
Yuri Kosinsky and nine co-authors present a 2026 modeling study on a drug for rheumatoid arthritis, a disease in which the immune system attacks the joints. The drug, olokizumab, blocks a signal protein and matched a leading rival drug in trials over twenty-four weeks. The team asked how it would fare over a full year, at two dosing gaps, without running a new long trial.
They built math models of how the drug moves through the body and acts on disease scores, using pooled data from late-stage trials. Fake trials run on a computer then forecast one-year response rates for both dosing gaps, the rival drug, and a placebo. Both drug arms looked alike and beat the placebo. Checks against published data backed the forecasts, and starting inflammation levels helped shape each patient's path.
Catalog record
| CREATOR | Yuri Kosinsky, Ivan Azarov, Kirill Zhudenkov, Kirill Peskov, Sergey Grishin, Alina Egorova, Yuliya Berezovskaya, Maria Lemak, Mikhail Samsonov, Eugen Feist |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 35 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |