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Prediction of Human Pharmacokinetics Profile of Monoclonal Antibody Using hFcRn Transgenic Mouse Model

Human pharmacokinetics (PK) profiles of monoclonal antibodies (mAbs) are usually predicted using non-human primates (NHP), but this comes with drawbacks in terms of cost and throughput. Therefore, we established a human PK profile prediction method using human neonatal Fc receptor (hFcRn) transgenic...

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Published in:Biological & pharmaceutical bulletin 2021/03/01, Vol.44(3), pp.389-395
Main Authors: Nakamura, Genki, Ozeki, Kazuhisa, Takesue, Hiroaki, Tabo, Mitsuyasu, Hosoya, Ken-ichi
Format: Article
Language:English
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Summary:Human pharmacokinetics (PK) profiles of monoclonal antibodies (mAbs) are usually predicted using non-human primates (NHP), but this comes with drawbacks in terms of cost and throughput. Therefore, we established a human PK profile prediction method using human neonatal Fc receptor (hFcRn) transgenic mice (TgM). We administered launched 13 mAbs to hFcRn TgM and measured the concentration in plasma using electro-chemiluminescence immunoassay. This was then used to calculate PK parameters and predict human PK profiles. The mAbs showed a bi-phased elimination pattern, and clearance (CL) (mL/d/kg) and distribution volume at steady state (Vdss) (mL/kg) ranges were 11.0 to 131 and 110 to 285, respectively. There was a correlation in half-life at elimination phase (t1/2β) between hFcRn TgM and humans for 10 mAbs showing CL of more than 80% in the elimination phase (R2 = 0.714). Human t1/2β was predicted using hFcRn TgM t1/2β; 9 out of 10 mAbs were within 2-fold the actual values, and all mAbs were within 3-fold. Regarding the predicted CL values, 7 out of 10 mAbs were within 2-fold the human values and all mAbs were within 3-fold. Furthermore, even on day 7 the predicted CL values of 8 out of 10 mAbs were within 2-fold the observed value, with all mAbs within 3-fold. These results suggest human PK profiles can be predicted using hFcRn TgM data. These methods can accelerate the development of antibody drugs while also reducing cost and improving throughput.
ISSN:0918-6158
1347-5215
DOI:10.1248/bpb.b20-00775