ESTONIAN ACADEMY
PUBLISHERS
eesti teaduste
akadeemia kirjastus
PUBLISHED
SINCE 1952
 
Proceeding cover
proceedings
of the estonian academy of sciences
ISSN 1736-7530 (Electronic)
ISSN 1736-6046 (Print)
Impact Factor (2022): 0.9
Predictive modelling and simulation for taming the chance and luck in biologics drug discovery; pp. 371–381
PDF | https://doi.org/10.3176/proc.2023.4.02

Author
Armin Sepp
Abstract

Three Pillars of Survival paradigm in the pharmaceutical drug discovery stipulates that a drug candidate is more likely to reach Phase III if it meets the following criteria: 1) it reaches the required tissue compartment, 2) engages the desired target, 3) triggers the desired downstream pharmacological effect. This paper describes the progress made along this track for biologics, in the first instance for monoclonal antibodies, their fragments and therapeutic proteins in general. Cross­species/cross­modality physiologically­based pharmacokinetics (PBPK) framework aims to provide the first principle quantitative predictions for the first two of the declared Pillars. The approach is based on two­pore hypothesis of extravasation, further developed with PBPK in mind and parameterized for fractional tissue lymph flow rates using rodent data. The biologics PBPK framework is validated by accurately predicting the tissue distribution and elimination properties of normal and modified antibodies and their fragments in primate and human studies.

References

Aweda, T. A., Cheng, S.-H., Lenhard, S. C., Sepp, A., Skedzielewski, T., Hsu, C.-Y. et al. 2023. In vivo biodistribution and pharmacokinetics of sotrovimab, a SARS-CoV-2 monoclonal antibody, in healthy cynomolgus monkeys. Eur. J. Nucl. Med. Mol. Imaging50, 667–678.
https://doi.org/10.1007/s00259-022-06012-3

Baxter, L. T., Zhu, H., Mackensen, D. G. and Jain, R. K. 1994. Physiologically based pharmacokinetic model for specific and nonspecific monoclonal antibodies and fragments in normal tissues and human tumor xenografts in nude mice. Cancer Res.54(6), 1517–1528.

Betts, A., Keunecke, A., van Steeg, T. J., van der Graaf, P. H., Avery, L. B., Jones, H. et al. 2018. Linear pharmacokinetic parameters for monoclonal antibodies are similar within a species and across different pharmacological targets: a comparison between human, cynomolgus monkey and hFcRn Tg32 transgenic mouse using a population-modeling approach. mAbs.10(5), 751–764. 
https://doi.org/10.1080/19420862.2018.1462429

Chang, H.-P., Li, Z. and Shah, D. K. 2022. Development of a physiologically-based pharmacokinetic model for whole-body disposition of MMAE containing antibody-drug conjugate in mice. Pharm. Res.39(1), 1–24. 
https://doi.org/10.1007/s11095-021-03162-1

Chang, H.-Y., Wu, S., Meno-Tetang, G. and Shah, D. K. 2019. A translational platform PBPK model for antibody disposition in the brain. J. Pharmacokinet. Pharmacodyn.46(4), 319–338. 
https://doi.org/10.1007/s10928-019-09641-8

Chang, H.-Y., Wu, S., Li, Y., Guo, L., Li, Y. and Shah, D. K. 2022. Effect of the size of protein therapeutics on brain pharmacokinetics following systematic administration. AAPS J.24(3), 62. 
https://doi.org/10.1208/s12248-022-00701-5

Feher, J. 2012. Regulation of arterial pressure. In  Quantitative Human Physiology. Boston, Academic Press,  538–548.
https://doi.org/10.1016/B978-0-12-382163-8.00058-X

Ferl, G. Z., Wu, A. M. and DiStefano, J. J. III. 2005. A predictive model of therapeutic monoclonal antibody dynamics and regulation by the neonatal Fc receptor (FcRn). Ann. Biomed. Eng.33(11), 1640–1652. 
https://doi.org/10.1007/s10439-005-7410-3

Galluzzi, L., Humeau, J., Buqué, A., Zitvogel, L. and Kroemer, G. 2020. Immunostimulation with chemotherapy in the era of immune checkpoint inhibitors. Nat. Rev. Clin. Oncol.17(12), 725–741. 
https://doi.org/10.1038/s41571-020-0413-z

Gill, K. L., Gardner, I., Li, L. and Jamei, M. 2016. A bottom-up whole-body physiologically based pharmacokinetic model to mechanistically predict tissue distribution and the rate of subcutaneous absorption of therapeutic proteins. AAPS J.18(1), 156–170.
https://doi.org/10.1208/s12248-015-9819-4

Jagdale, P., Sepp, A. and Shah, D. K. 2022. Physiologically-based pharmacokinetic model for pulmonary disposition of protein therapeutics in humans. J. Pharmacokinet. Pharmacodyn.49(6), 607–624. 
https://doi.org/10.1007/s10928-022-09824-w

Kagan, L. and Mager, D. E. 2013. Mechanisms of subcutaneous absorption of rituximab in rats. Drug Metab. Dispos.41(1), 248–255. 
https://doi.org/10.1124/dmd.112.048496

Kagan, L., Turner, M. R., Balu-Iyer, S. V. and Mager, D. E. 2012. Subcutaneous absorption of monoclonal antibodies: role of dose, site of injection, and injection volume on rituximab pharmacokinetics in rats. Pharm. Res.29(2), 490–499. 
https://doi.org/10.1007/s11095-011-0578-3

Li, Z., Li, Y., Chang, H. P., Yu, X. and Shah, D. K. 2021. Two-pore physiologically based pharmacokinetic model validation using whole-body biodistribution of trastuzumab and different-size fragments in mice. J. Pharmacokinet. Pharmacodyn.48(6), 743–762. 
https://doi.org/10.1007/s10928-021-09772-x

Lipinski, C. A., Lombardo, F., Dominy, B. W. and Feeney, P. J. 2001. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev.46(1–3), 3–26. 
https://doi.org/10.1016/s0169-409x(00)00129-0

Mikkilineni, L. and Kochenderfer, J. N. 2021. CAR T cell therapies for patients with multiple myeloma. Nat. Rev. Clin. Oncol.18(2), 71–84. 
https://doi.org/10.1038/s41571-020-0427-6

Moore, J. E., Jr. and Bertram, C. D. 2018. Lymphatic system flows. Annu. Rev. Fluid Mech.50, 459–482. 
https://doi.org/10.1146/annurev-fluid-122316-045259

Morgan, P., Van Der Graaf, P. H., Arrowsmith, J., Feltner, D. E., Drummond, K. S., Wegner, C. D. et al. 2012. Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival. Drug Discov. Today17(9–10), 419–424. 
https://doi.org/10.1016/j.drudis.2011.12.020

Patlak, C. S., Goldstein, D. A. and Hoffman, J. F. 1963. The flow of solute and solvent across a two-membrane system. J. Theor. Biol.5(3), 426–442. 
https://doi.org/10.1016/0022-5193(63)90088-2

Pavelka, M. and Roth, J. 2010. Fluid-phase endocytosis and phagocytosis. In  Functional Ultrastructure: Atlas of Tissue Biology and Pathology. Springer, Vienna,  104–105.
https://doi.org/10.1007/978-3-211-99390-3_54

Porter, C. J. and Charman, S. A. 2000. Lymphatic transport of proteins after subcutaneous administration. J. Pharm. Sci.89(3), 297–310. 
https://doi.org/10.1002/(sici)1520-6017(200003)89:3%3C297::aid-jps2%3E3.0.co;2-p

Richter, W. F. and Jacobsen, B. 2014. Subcutaneous absorption of biotherapeutics: knowns and unknowns. Drug Metab. Dispos.42(11), 1881–1889. 
https://doi.org/10.1124/dmd.114.059238

Richter, W. F., Christianson, G. J., Frances, N., Grimm, H. P., Proetzel, G. and Roopenian, D. C. 2018. Hematopoietic cells as site of first-pass catabolism after subcutaneous dosing and contributors to systemic clearance of a monoclonal antibody in mice. mAbs.10(5), 803–813. 
https://doi.org/10.1080/19420862.2018.1458808

Rippe, B. and Haraldsson, B. 1994. Transport of macromolecules across microvascular walls: the two-pore theory. Physiol. Rev.74(1), 163–219. 
https://doi.org/10.1152/physrev.1994.74.1.163

Rossing, N. 1978. Intra- and extravascular distribution of albumin and immunoglobulin in man. Lymphology11(4), 138–142.

Rudnick, S. I. and Adams, G. P. 2009. Affinity and avidity in antibody-based tumor targeting. Cancer Biother. Radiopharm.24(2), 155–161. 
https://doi.org/10.1089/cbr.2009.0627

Sarin, H. 2010. Physiologic upper limits of pore size of different blood capillary types and another perspective on the dual pore theory of microvascular permeability. J. Angiogenes. Res.2(1), 14. 
https://doi.org/10.1186/2040-2384-2-14

Sarin, H., Kanevsky, A. S., Wu, H., Sousa, A. A., Wilson, C. M., Aronova, M. A. et al. 2009. Physiologic upper limit of pore size in the blood-tumor barrier of malignant solid tumors. J. Transl. Med.7, 51. 
https://doi.org/10.1186/1479-5876-7-51

Schlander, M., Hernandez-Villafuerte, K., Cheng, C.-Y., Mestre-Ferrandiz, J. and Baumann, M. 2021. How much does it cost to research and develop a new drug? A systematic review and assessment. PharmacoEconomics39(11), 1243–1269. 
https://doi.org/10.1007/s40273-021-01065-y

Sepp, A., Berges, A., Sanderson, A. and Meno-Tetang, G. 2015. Development of a physiologically based pharmacokinetic model for a domain antibody in mice using the two-pore theory. J. Pharmacokinet. Pharmacodyn.42(2), 97–109. 
https://doi.org/10.1007/s10928-014-9402-0

Sepp, A., Meno-Tetang, G., Weber, A., Sanderson, A., Schon, O. and Berges, A. 2019. Computer-assembled cross-species/cross-modalities two-pore physiologically based pharmacokinetic model for biologics in mice and rats. J. Pharmacokinet. Pharmacodyn.46(4), 339–359. 
https://doi.org/10.1007/s10928-019-09640-9

Sepp, A., Bergström, M. and Davies, M. 2020. Cross-species/cross-modality physiologically based pharmacokinetics for biologics: 89Zr-labelled albumin-binding domain antibody GSK3128349 in humans. mAbs.12(1), 1832861. 
https://doi.org/10.1080/19420862.2020.1832861

Shah, D. K. and Betts, A. M. 2012. Towards a platform PBPK model to characterize the plasma and tissue disposition of monoclonal antibodies in preclinical species and human. J. Pharmacokinet. Pharmacodyn.39(1), 67–86. 
https://doi.org/10.1007/s10928-011-9232-2

Shah, D. K. and Betts, A. M. 2013. Antibody biodistribution coefficients: inferring tissue concentrations of monoclonal antibodies based on the plasma concentrations in several preclinical species and human. mAbs.5(2), 297–305. 
https://doi.org/10.4161/mabs.23684

Slastnikova, T. A., Ulasov, A. V., Rosenkranz, A. A. and Sobolev, A. S. 2018. Targeted intracellular delivery of antibodies: the state of the art. Front. Pharmacol.,9
https://doi.org/10.3389/fphar.2018.01208

Suhorutsenko, J., Oskolkov, N., Arukuusk, P., Kurrikoff, K., Eriste, E., Copolovici, D. M. et al. 2011. Cell-penetrating peptides, PepFects, show no evidence of toxicity and immunogenicity in vitro and in vivo. Bioconjug. Chem.22(11), 2255–2262. 
https://doi.org/10.1021/bc200293d

Swanson, J. A. and King, J. S. 2019. The breadth of macropinocytosis research. Philos. Trans. R. Soc. Lond. B. Biol. Sci.374(1765), 20180146. 
https://doi.org/10.1098/rstb.2018.0146

Swartz, M. A. 2001. The physiology of the lymphatic system. Adv. Drug Deliv. Rev.50(1–2), 3–20. 
https://doi.org/10.1016/s0169-409x(01)00150-8

Thorneloe, K. S., Sepp, A., Zhang, S., Galinanes-Garcia, L., Galette, P., Al-Azzam, W. et al. 2019. The biodistribution and clearance of AlbudAb, a novel biopharmaceutical medicine platform, assessed via PET imaging in humans. EJNMMI Res.9(1), 45. 
https://doi.org/10.1186/s13550-019-0514-9

Thurber, G. M. and Wittrup, K. D. 2008. Quantitative spatiotemporal analysis of antibody fragment diffusion and endocytic consumption in tumor spheroids. Cancer Res.68(9), 3334–3341. 
https://doi.org/10.1158/0008-5472.can-07-3018

Thurber, G. M., Schmidt, M. M. and Wittrup, K. D. 2008. Antibody tumor penetration: transport opposed by systemic and antigen-mediated clearance. Adv. Drug Deliv. Rev.60(12), 1421–1434. 
https://doi.org/10.1016/j.addr.2008.04.012

Vaiksaar, R. and Käänik, J. 2022. Millest tulenevad vähiravimite hirmkallid hinnad? (Origin of over-the-top prices of cancer drugs). 
https://www.delfi.ee/artikkel/120118518/selgitav-video-21-000-eurot-41-000-eurot-millest-tulenevad-vahiravimite-hirmkallid-hinnad (accessed 2023-02-10).

Venturoli, D. and Rippe, B. 2005. Ficoll and dextran vs. globular proteins as probes for testing glomerular permselectivity: effects of molecular size, shape, charge, and deformability. Am. J. Physiol. Renal Physiol.288(4), F605–F613. 
https://doi.org/10.1152/ajprenal.00171.2004

Viola, M., Sequeira, J., Seiça, R., Veiga, F., Serra, J., Santos, A. C. et al. 2018. Subcutaneous delivery of monoclonal antibodies: how do we get there? J. Control. Release, 286, 301–314. 
https://doi.org/10.1016/j.jconrel.2018.08.001

Wagner, M. and Wiig, H. 2015. Tumor interstitial fluid formation, characterization, and clinical implications. Front. Oncol., 5, 115. 
https://doi.org/10.3389/fonc.2015.00115

Wells, J. A. and McClendon, C. L. 2007. Reaching for high-hanging fruit in drug discovery at protein–protein interfaces. Nature450, 1001–1009.

Westermann, J. and Pabst, R. 1992. Distribution of lymphocyte subsets and natural killer cells in the human body. Clin. Investig.70(7), 539–544. 
https://doi.org/10.1007/bf00184787

Wiig, H. and Swartz, M. A. 2012. Interstitial fluid and lymph formation and transport: physiological regulation and roles in inflammation and cancer. Physiol. Rev.92(3), 1005–1060. 
https://doi.org/10.1152/physrev.00037.2011

Wittrup, K. D., Thurber, G. M., Schmidt, M. M. and Rhoden, J. J. 2012. Practical theoretic guidance for the design of tumor-targeting agents. Methods Enzymol., 503,  255–268.
https://doi.org/10.1016/b978-0-12-396962-0.00010-0

Wu, S., Le Prieult, F., Phipps, C. J., Mezler, M. and Shah, D. K. 2022. PBPK model for antibody disposition in mouse brain: validation using large-pore microdialysis data. J. Pharmacokinet. Pharmacodyn.49(6), 579–592. 
https://doi.org/10.1007/s10928-022-09823-x

Back to Issue