Interspecies Scaling of Antibody–Drug Conjugates (ADC) for the Prediction of Human Clearance
Abstract
:1. Introduction
- To apply the ROE only to those drugs that had at least three animal species.
- Considering a real life situation where three animal species may not be available, two-animal species allometric scaling was performed to evaluate if it was possible to predict human clearance of ADCs with two-species allometric scaling using only simple allometry.
- The authors Li et al. used a single species scaling for the prediction of human clearance of ADCs. The species used by the authors was monkey. Although it is widely believed that the predicted human clearance can be fairly accurate using the monkey clearance values alone, there is no analysis with other species such as rat and mice for ADCs. Therefore, in this study, the clearance data from mice or rat were used to evaluate if the predicted human clearance values of ADCs are comparable with the monkey.
- Li et al. [9] used three allometric exponents (0.75, 0.85, and 1.0) for a single-species scaling for monkeys. The exponent 0.75 is a theoretical allometric exponent, exponent 0.85 was taken from Deng et al. [6,7] for the prediction of human clearance from monkey data, and the authors explored exponent 1.0. A study by Oitate et al. [8] indicated that the exponent 0.79 was the most suitable exponent for the prediction of human clearance of antibodies from monkey. Therefore, in this study, exponent 0.79 was also used for a single-species scaling by rounding it to 0.80.
2. Methods
2.1. Simple Allometry
2.2. Product of MLP and Clearance (MLP × Clearance)
2.3. Product of Brain Weight and Clearance (Br WT × Clearance)
2.4. Two-Species Scaling
2.5. One-Species Scaling
2.6. Statistical Analysis
3. Results
3.1. Three-Species Allometric Scaling
3.2. Application of MLP:
3.3. Two-Species Allometric Scaling
3.4. One-Species Allometric Scaling
4. Discussion
5. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Drugs | CL (mL/day) | Drugs | CL (mL/day) |
---|---|---|---|
DNIB0600A | Polatuzumab vedotin | ||
Mouse | 0.18 | Mouse | 0.11 |
Rat * | 3.98 | Rat * | 4 |
Monkey | 46.55 | Monkey | 24.2 |
Human | 854 | Human | 1015 |
DMOT4039A | Pinatuzumab vedotin | ||
Mouse | 0.19 | Mouse | 0.12 |
Monkey | 96.6 | Monkey | 32.9 |
Human | 1400 | Human | 966 |
DSTP3086S | Brentuximab vedotin | ||
Mouse | 0.20 | Mouse * | 0.50 |
Rat | 2.37 | Rat | 2.25 |
Monkey | 46.9 | Monkey | 51.1 |
Human | 574 | Human | 742 |
T-DM1 (total antibody) | T-DM1 (conjugate) | ||
Mouse | 0.16 | Mouse | 0.38 |
Rat | 1.62 | Rat | 4.6 |
Monkey | 16.1 | Monkey | 41.9 |
Human | 343 | Human | 600 |
Thiomab (New) total antibody | Thiomab (New) conjugate | ||
Mouse | 0.10 | Mouse | 0.40 |
Rat | 2.15 | Rat | 6.03 |
Monkey | 20.37 | Monkey | 54.25 |
Human | 200 | Human | 759 |
Anti-5T4 (New) (total antibody) | Anti-5T4 (New) (conjugate) | ||
Mouse | 0.39 | Mouse | 0.68 |
Rat | 3.3 | Rat | 4.8 |
Monkey | 27.1 | Monkey | 52.6 |
Human | 360 | Human | 700 |
ADC1 | |||
Mouse | 0.13 | ||
Monkey | 36.7 | ||
Human | 756 |
Drugs | Coefficient | Exponent | Observed | Predicted | Ratio * |
---|---|---|---|---|---|
DSTP3086S (total antibody) | |||||
Simple | 11.7 | 1.06 | 574 | 1052 | 1.83 |
Brain weight | 155.7 | 2.06 | 574 | 709 | 1.23 |
T-DM1 (total antibody) | |||||
Simple | 5.37 | 0.89 | 343 | 236 | 0.69 |
T-DM1 (conjugate) | |||||
Simple | 14.3 | 0.91 | 600 | 683 | 1.14 |
DNIB0600A (rat data were added to Li et al.’s original data) (total antibody) | |||||
Simple | 13.7 | 1.07 | 854 | 1313 | 1.54 |
Brain weight | 182.5 | 2.08 | 854 | 886 | 1.04 |
Brentuximab vedotin (mouse data were added to Li et al.’s original data) (total antibody) | |||||
Simple | 13 | 0.90 | 742 | 595 | 0.80 |
Thiomab (total antibody) | |||||
Simple | 6.5 | 1.03 | 200 | 517 | 2.58 |
Brain weight | 86.9 | 2.03 | 200 | 345 | 1.73 |
Thiomab (conjugate) | |||||
Simple | 18.3 | 0.95 | 759 | 1027 | 1.35 |
Polatuzumab vedotin (total antibody) (rat data were added to Li et al.’s original data) (total antibody) | |||||
Simple | 8.91 | 1.06 | 1015 | 795 | 0.78 |
Brain weight | 119 | 2.06 | 1015 | 537 | 0.53 |
Anti-5T4 (total antibody) ** | |||||
Simple | 9.9 | 0.82 | 360 | 323 | 0.90 |
Anti-5T4 (conjugate) ** | |||||
Simple | 17.3 | 0.85 | 700 | 640 | 0.91 |
Drugs | Exponent | Observed | Predicted | Predicted |
---|---|---|---|---|
3 species, SA | SA | MLP | ||
Brentuximab vedotin | ||||
Methods | 0.90 | 742 | 595 | 274 |
Ratio | 0.80 | 0.37 | ||
T-DM1 (total antibody) | ||||
Methods | 0.89 | 343 | 236 | 111 |
Ratio | 0.69 | 0.32 | ||
T-DM1 (conjugate) | ||||
Methods | 0.91 | 600 | 683 | 319 |
Ratio | 1.14 | 0.53 | ||
Thiomab (conjugate) | ||||
Methods | 0.95 | 759 | 1027 | 478 |
Ratio | 1.35 | 0.63 | ||
Anti-5T4 (total antibody) | ||||
Methods | 0.82 | 360 | 323 | 151 |
Ratio | 0.90 | 0.42 | ||
Anti-5T4 (conjugate) | ||||
Methods | 0.85 | 700 | 640 | 288 |
Ratio | 0.91 | 0.41 |
Drugs | Coefficient | Exponent | Predicted | Observed | Ratio * |
---|---|---|---|---|---|
DNIB0600A | |||||
Mouse, monkey | 12.1 | 1.08 | 1190 | 854 | 1.39 |
Mouse, rat | 21.8 | 1.23 | 3981 | 854 | 4.66 |
Rat, monkey | 14.5 | 0.93 | 753 | 854 | 0.88 |
DMOT4039A | |||||
Mouse, monkey | 21.3 | 1.21 | 3640 | 1400 | 2.60 |
Polatuzumab vedotin | |||||
Mouse, monkey | 6.6 | 1.04 | 543 | 1015 | 0.53 |
Mouse, rat | 28.8 | 1.42 | 12,007 | 1015 | 11.83 |
Rat, monkey | 10.3 | 0.68 | 185 | 1015 | 0.18 |
Pinatuzumab vedotin | |||||
Mouse, monkey | 8.46 | 1.08 | 832 | 966 | 0.86 |
ADC1 | |||||
Mouse, monkey | 9.38 | 1.09 | 962 | 756 | 1.27 |
Brentuximab vedotin | |||||
Mouse, monkey | 16.6 | 0.89 | 728 | 742 | 0.98 |
Mouse, rat | 5.1 | 0.59 | 63 | 742 | 0.08 |
Rat, monkey | 11.6 | 1.18 | 1745 | 742 | 2.35 |
DSTP3086S | |||||
Mouse, monkey | 12.4 | 1.09 | 1277 | 574 | 2.22 |
Mouse, rat | 9.3 | 0.98 | 598 | 574 | 1.04 |
Rat, monkey | 11.4 | 1.13 | 1386 | 574 | 2.41 |
T-DM1 | |||||
Mouse, monkey | 5.3 | 0.89 | 231 | 343 | 0.67 |
Mouse, rat | 5.4 | 0.87 | 219 | 343 | 0.64 |
Rat, monkey | 5.8 | 0.92 | 291 | 343 | 0.85 |
Thiomab | |||||
Mouse, monkey | 5.6 | 1.03 | 445 | 200 | 2.23 |
Mouse, rat | 11.6 | 1.21 | 1982 | 200 | 9.91 |
Rat, monkey | 7 | 0.85 | 259 | 200 | 1.30 |
Anti-5T4 | |||||
Mouse, monkey | 9.7 | 0.82 | 316 | 360 | 0.88 |
Mouse, rat | 10.7 | 0.85 | 388 | 360 | 1.08 |
Rat, monkey | 10 | 0.80 | 299 | 360 | 0.83 |
Species | Predicted | Prediction Ratio | ||||||
---|---|---|---|---|---|---|---|---|
E 0.75 | E 0.80 | E 0.85 | E 1.0 | E 0.75 | E 0.80 | E 0.85 | E 1.0 | |
DNIB0600A (observed human CL = 854 mL/day) | ||||||||
Mouse | 82 | 123 | 185 | 630 | 0.10 | 0.14 | 0.22 | 0.74 |
Rat | 272 | 361 | 479 | 1114 | 0.32 | 0.42 | 0.56 | 1.30 |
Monkey | 440 | 511 | 594 | 931 | 0.52 | 0.60 | 0.70 | 1.09 |
DMOT4039A (observed human CL = 1400 mL/day) | ||||||||
Mouse | 86 | 130 | 196 | 665 | 0.06 | 0.09 | 0.14 | 0.48 |
Monkey | 914 | 1061 | 1233 | 1932 | 0.65 | 0.76 | 0.88 | 1.38 |
DSTP3086S (observed human CL = 574 mL/day) | ||||||||
Mouse | 90 | 135 | 204 | 693 | 0.16 | 0.24 | 0.35 | 1.21 |
Rat | 163 | 215 | 286 | 665 | 0.28 | 0.38 | 0.50 | 1.16 |
Monkey | 444 | 515 | 598 | 938 | 0.77 | 0.90 | 1.04 | 1.63 |
TDM1 (observed human CL = 343 mL/day) | ||||||||
Mouse | 73 | 109 | 165 | 560 | 0.21 | 0.32 | 0.48 | 1.63 |
Rat | 111 | 147 | 195 | 455 | 0.32 | 0.43 | 0.57 | 1.33 |
Monkey | 152 | 177 | 205 | 322 | 0.44 | 0.52 | 0.60 | 0.94 |
Polatuzumab vedotin (observed human CL = 1015 mL/day) | ||||||||
Mouse | 46 | 70 | 105 | 356 | 0.05 | 0.07 | 0.10 | 0.35 |
Rat | 185 | 245 | 325 | 756 | 0.18 | 0.24 | 0.32 | 0.74 |
Monkey | 199 | 231 | 268 | 420 | 0.20 | 0.23 | 0.26 | 0.41 |
Pinatuzumab vedotin (observed human CL = 966 mL/day) | ||||||||
Mouse | 56 | 83 | 126 | 427 | 0.06 | 0.09 | 0.13 | 0.44 |
Monkey | 311 | 361 | 420 | 658 | 0.32 | 0.37 | 0.43 | 0.68 |
ADC1 (observed human CL = 756 mL/day) | ||||||||
Mouse | 60 | 90 | 136 | 462 | 0.08 | 0.12 | 0.18 | 0.61 |
Monkey | 348 | 404 | 469 | 735 | 0.46 | 0.53 | 0.62 | 0.97 |
Brentuximab vedotin (observed human CL = 742 mL/day) | ||||||||
Mouse | 55 | 82 | 123 | 420 | 0.07 | 0.11 | 0.17 | 0.57 |
Rat | 154 | 204 | 271 | 630 | 0.21 | 0.28 | 0.36 | 0.85 |
Monkey | 483 | 561 | 652 | 1022 | 0.65 | 0.76 | 0.88 | 1.38 |
Thiomab (observed human CL = 200 mL/day) | ||||||||
Mouse | 44 | 66 | 99 | 338 | 0.22 | 0.33 | 0.50 | 1.69 |
Rat | 147 | 195 | 259 | 602 | 0.74 | 0.98 | 1.29 | 3.01 |
Monkey | 193 | 224 | 260 | 407 | 0.96 | 1.12 | 1.30 | 2.04 |
Anti-5T4 (observed human CL = 360 mL/day) | ||||||||
Mouse | 177 | 266 | 400 | 1361 | 0.49 | 0.74 | 1.11 | 3.78 |
Rat | 226 | 299 | 397 | 924 | 0.63 | 0.83 | 1.10 | 2.57 |
Monkey | 256 | 297 | 345 | 541 | 0.71 | 0.83 | 0.96 | 1.50 |
ADCs | Observed CL | Predicted CL (mL/day) | Predicted Ratio | ||
---|---|---|---|---|---|
(mL/Day) | Exponent 1.0 | Average * | Exponent 1.0 | Average * | |
DNIB0600A | 854 | 630 | 726 | 0.74 | 0.85 |
DMOT4039A | 1400 | 665 | 766 | 0.48 | 0.55 |
DSTP3086S | 574 | 693 | 799 | 1.21 | 1.43 |
TDM1 | 343 | 560 | 645 | 1.63 | 1.94 |
Polatuzumab | 1015 | 356 | 411 | 0.35 | 0.42 |
Pinatuzumab | 966 | 427 | 492 | 0.44 | 0.52 |
ADC1 | 756 | 462 | 532 | 0.61 | 0.72 |
Brentuximab | 742 | 420 | 484 | 0.57 | 0.67 |
Thiomab | 200 | 338 | 390 | 1.69 | 1.99 |
Anti-5T4 | 360 | 1361 | 1618 | 3.78 | 4.49 |
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Mahmood, I. Interspecies Scaling of Antibody–Drug Conjugates (ADC) for the Prediction of Human Clearance. Antibodies 2021, 10, 1. https://doi.org/10.3390/antib10010001
Mahmood I. Interspecies Scaling of Antibody–Drug Conjugates (ADC) for the Prediction of Human Clearance. Antibodies. 2021; 10(1):1. https://doi.org/10.3390/antib10010001
Chicago/Turabian StyleMahmood, Iftekhar. 2021. "Interspecies Scaling of Antibody–Drug Conjugates (ADC) for the Prediction of Human Clearance" Antibodies 10, no. 1: 1. https://doi.org/10.3390/antib10010001
APA StyleMahmood, I. (2021). Interspecies Scaling of Antibody–Drug Conjugates (ADC) for the Prediction of Human Clearance. Antibodies, 10(1), 1. https://doi.org/10.3390/antib10010001