Skip to main content

Modeling and Simulation of In Vivo Drug Effects

  • Chapter
New Approaches to Drug Discovery

Abstract

The concept of a pharmacokinetics–pharmacodynamics (PK/PD) assessment of drug development candidates is well established in pharmaceutical research and development, and PK/PD modeling is common practice in all pharmaceutical companies. A recent analysis (Morgan et al., Drug Discov Today 17(9–10):419–424, 2012) revealed however that insufficient certainty in the integrity of the causal chain of fundamental pharmacological steps from drug dosing through systemic exposure, target tissue exposure, and engagement of molecular target to pharmacological response is still the major driver of failure in phase II of clinical drug development. Despite the rise of molecular biomarkers, ethical, scientific, and practical constraints very often still prevent a direct assessment of each necessary step ultimately leading to an intended drug effect or an unintended adverse reaction. Yet, incomplete investigation of the causality of drug responses is a major risk for translational assessments and the prediction of drug responses in different species or other populations. Mechanism-based modeling and simulation (M&S) offers a means to investigate complex physiological and pharmacological processes and to complement experimental data for non-accessible steps in the pharmacological causal chain. With the help of two examples, it is illustrated, what level of physiological detail, state-of-the-art models can represent, how predictive these models are and how mechanism-based approaches can be combined with empirical correlation-based concepts.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Cartwright ME et al (2010) Proof of concept: a PhRMA position paper with recommendations for best practice. Clin Pharmacol Ther 87:278–285

    Article  CAS  PubMed  Google Scholar 

  • Cohen A (2008) Pharmacokinetic and pharmacodynamic data to be derived from early-phase drug development-designing informative human pharmacological studies. Clin Pharmacokinet 47:373–381

    Article  CAS  PubMed  Google Scholar 

  • US Food and Drug Administration (1999) Guidance for industry: population pharmacokinetics, U.S. Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER), Center for Biologics Evaluation and Research (CBER), February 1999

    Google Scholar 

  • Edginton AN, Schmitt W, Willmann S (2006) Development and evaluation of a generic physiologically based pharmacokinetic model for children. Clin Pharmacokinet 45(10):1013–1034

    Article  CAS  PubMed  Google Scholar 

  • Eissing T, Kuepfer L, Becker C, Block M, Coboeken K, Gaub T, Goerlitz L, Jaeger J, Loosen R, Ludewig B, Meyer M, Niederalt C, Sevestre M, Siegmund HU, Solodenko J, Thelen K, Telle U, Weiss W, Wendl T, Willmann S, Lippert J (2011) A computational systems biology software platform for multiscale modeling and simulation: integrating whole-body physiology, disease biology, and molecular reaction networks. Front Physiol 2:4

    Article  PubMed  PubMed Central  Google Scholar 

  • El-Khatib FH, Russell SJ, Nathan DM, Sutherlin RG, Damiano ER (2010) A bihormonal closed-loop artificial pancreas for type 1 diabetes. Sci Transl Med 2:27ra27

    PubMed  PubMed Central  Google Scholar 

  • Empfield JR, Leeson PD (2010) Lessons learned from candidate drug attrition. IDrugs 13:869–887

    PubMed  Google Scholar 

  • Ette EI, Williams PJ (2004) Population pharmacokinetics I: background, concepts, and models. Ann Pharmacother 38(10):1702–1706

    Article  PubMed  Google Scholar 

  • European Medicines Agency (2007) Guideline on reporting the results of population pharmacokinetic analyses. European Medicines Agency, June 2007

    Google Scholar 

  • Gabrielsson J et al (2011) Pharmacodynamic–pharmacokinetic integration as a guide to medicinal chemistry. Curr Top Med Chem 11:404–418

    Article  CAS  PubMed  Google Scholar 

  • Geanacopoulos M, Barratt R (2015) How the critical path initiative addresses CDER’s regulatory science needs some illustrative examples. Ther Innov Regul Sci, January 29, 2015

    Google Scholar 

  • Hodgkin AL, Huxley AF (1952) Propagation of electrical signals along giant nerve fibres. Proc R Soc Lond B Biol Sci 140(899):177–183

    Article  CAS  PubMed  Google Scholar 

  • Kobayashi M, Chisaki I, Narumi K, Hidaka K, Kagawa T, Itagaki S, Hirano T, Iseki K (2008) Association between risk of myopathy and cholesterol-lowering effect: a comparison of all statins. Life Sci 82(17):969–975

    Article  CAS  PubMed  Google Scholar 

  • Link E, Parish S, Armitage J, Bowman L, Heath S, Matsuda F, Gut I, Lathrop M, Collins R (2008) SLCO1B1 variants and statin-induced myopathy – a genomewide study. N Engl J Med 359(8):789–799

    Article  CAS  PubMed  Google Scholar 

  • Lippert J, Brosch M, von Kampen O, Meyer M, Siegmund HU, Schafmayer C, Becker T, Laffert B, Görlitz L, Schreiber S, Neuvonen PJ, Niemi M, Hampe J, Kuepfer L (2012) A mechanistic, model‐based approach to safety assessment in clinical development. CPT Pharmacometrics Syst Pharmacol 1(11):1–8

    Article  Google Scholar 

  • Morgan P, Van Der Graaf PH, Arrowsmith J, Feltner DE, Drummond KS, Wegner CD, Street SD (2012) Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival. Drug Discov Today 17(9-10):419–424

    Article  CAS  PubMed  Google Scholar 

  • Niemi M, Pasanen MK, Neuvonen PJ (2011) Organic anion transporting polypeptide 1B1: a genetically polymorphic transporter of major importance for hepatic drug uptake. Pharmacol Rev 63(1):157–181

    Article  CAS  PubMed  Google Scholar 

  • Paul SM et al (2010) How to improve R&D productivity: the pharmaceutical industry’s grand challenge. Nat Rev Drug Discov 9:203–214

    CAS  PubMed  Google Scholar 

  • Romero K, Sinha V, Allerheiligen S, Danhof M, Pinheiro J, Kruhlak N, Wang Y, Wang SJ, Sauer JM, Marier JF, Corrigan B, Rogers J, Lambers Heerspink HJ, Gumbo T, Vis P, Watkins P, Morrison T, Gillespie W, Gordon MF, Stephenson D, Hanna D, Pfister M, Lalonde R, Colatsky T (2013) Modeling and simulation for medical product development and evaluation: highlights from the FDA-C-Path-ISOP 2013 workshop. J Pharmacokinet Pharmacodyn 41(6):545–552

    Article  Google Scholar 

  • Schaller S, Willmann S, Lippert J, Schaupp L, Pieber TR, Schuppert A, Eissing T (2013) A generic integrated physiologically based whole‐body model of the glucose‐insulin‐glucagon regulatory system. CPT Pharmacometrics Syst Pharmacol 2(8):1–10

    Article  Google Scholar 

  • Schuck E, Bohnert T, Chakravarty A, Damian-Iordache V, Gibson C, Hsu CP, Heimbach T, Krishnatry AS, Liederer BM, Lin J, Maurer T, Mettetal JT, Mudra DR, Nijsen MJ, Raybon J, Schroeder P, Schuck V, Suryawanshi S, Su Y, Trapa P, Tsai A, Vakilynejad M, Wang S, Wong H (2015) Preclinical pharmacokinetic/pharmacodynamic modeling and simulation in the pharmaceutical industry: an IQ consortium survey examining the current landscape. AAPS J 17(2):462–473

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sistonen J, Sajantila A, Lao O et al (2007) CYP2D6 worldwide genetic variation shows high frequency of altered activity variants and no continental structure. Pharmacogenet Genomics 17(2):93–101

    CAS  PubMed  Google Scholar 

  • Sorger PK, Allerheiligen SR, Abernethy DR, Altman RB, Brouwer KL, Califano A, D’Argenio DZ, Iyengar R, Jusko WJ, Lalonde R, Lauffenburger DA, Shoichet B, Stevens JL, Subramaniam S, Van der Graaf P, Ward R (2011) Quantitative and systems pharmacology in the post-genomic era: new approaches to discovering drugs and understanding therapeutic mechanisms. In: An NIH white paper by the QSP workshop group. NIH, Bethesda, pp 1–48

    Google Scholar 

  • Wagner C, Pan Y, Hsu V, Grillo JA, Zhang L, Reynolds KS, Sinha V, Zhao P (2015) Predicting the effect of cytochrome P450 inhibitors on substrate drugs: analysis of physiologically based pharmacokinetic modeling submissions to the US food and drug administration. Clin Pharmacokinet 54(1):117–127

    Article  CAS  PubMed  Google Scholar 

  • Willmann S, Lippert J, Schmitt W (2005) From physicochemistry to absorption and distribution: predictive mechanistic modelling and computational tools. Expert Opin Drug Metab Toxicol 1(1):159–168

    Article  CAS  PubMed  Google Scholar 

  • Willmann S, Höhn K, Edginton A, Sevestre M, Solodenko J, Weiss W, Lippert J, Schmitt W (2007) Development of a physiology-based whole-body population model for assessing the influence of individual variability on the pharmacokinetics of drugs. J Pharmacokinet Pharmacodyn 34(3):401–431

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jörg Lippert .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Lippert, J. et al. (2015). Modeling and Simulation of In Vivo Drug Effects. In: Nielsch, U., Fuhrmann, U., Jaroch, S. (eds) New Approaches to Drug Discovery. Handbook of Experimental Pharmacology, vol 232. Springer, Cham. https://doi.org/10.1007/164_2015_21

Download citation

Publish with us

Policies and ethics