Skip to main content
SpringerLink
Log in

Pharmacokinetics in Drug Discovery: An Exposure-Centred Approach to Optimising and Predicting Drug Efficacy and Safety

  • Chapter
New Approaches to Drug Discovery

Part of the book series: Handbook of Experimental Pharmacology ((HEP,volume 232))

Abstract

The role of pharmacokinetics (PK) in drug discovery is to support the optimisation of the absorption, distribution, metabolism and excretion (ADME) properties of lead compounds with the ultimate goal to attain a clinical candidate which achieves a concentration–time profile in the body that is adequate for the desired efficacy and safety profile. A thorough characterisation of the lead compounds aiming at the identification of the inherent PK liabilities also includes an early generation of PK/PD relationships linking in vitro potency and target exposure/engagement with expression of pharmacological activity (mode-of-action) and efficacy in animal studies. The chapter describes an exposure-centred approach to lead generation, lead optimisation and candidate selection and profiling that focuses on a stepwise generation of an understanding between PK/exposure and PD/efficacy relationships by capturing target exposure or surrogates thereof and cellular mode-of-action readouts in vivo. Once robust PK/PD relationship in animal PD models has been constructed, it is translated to anticipate the pharmacologically active plasma concentrations in patients and the human therapeutic dose and dosing schedule which is also based on the prediction of the PK behaviour in human as described herein. The chapter outlines how the level of confidence in the predictions increases with the level of understanding of both the PK and the PK/PD of the new chemical entities (NCE) in relation to the disease hypothesis and the ability to propose safe and efficacious doses and dosing schedules in responsive patient populations. A sound identification of potential drug metabolism and pharmacokinetics (DMPK)-related development risks allows proposing of an effective de-risking strategy for the progression of the project that is able to reduce uncertainties and to increase the probability of success during preclinical and clinical development.

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

Access this chapter

Log in via an institution
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

  • Ballard P, Brassil P, Bui KH, Dolgos H, Petersson C, Tunek A, Webborn PJ (2012) The right compound in the right assay at the right time: an integrated discovery DMPK strategy. Drug Metab Rev 44(3):224–252

    Article  CAS  PubMed  Google Scholar 

  • Beaumont K, Smith DA (2009) Does human pharmacokinetic prediction add significant value to compound selection in drug discovery research? Curr Opin Drug Discov Dev 12(1):61–71

    CAS  Google Scholar 

  • Bueters T, Ploeger BA, Visser SA (2013) The virtue of translational PKPD modeling in drug discovery: selecting the right clinical candidate while sparing animal lives. Drug Discov Today 18(17–18):853–862

    Article  PubMed  Google Scholar 

  • Chen Y, Jin JY, Mukadam S, Malhi V, Kenny JR (2012) Application of IVIVE and PBPK modeling in prospective prediction of clinical pharmacokinetics: strategy and approach during the drug discovery phase with four case studies. Biopharm Drug Dispos 33(2):85–98

    Article  PubMed  Google Scholar 

  • Cook D, Brown D, Alexander R, March R, Morgan P, Satterthwaite G, Pangalos MN (2014) Lessons learned from the fate of AstraZeneca’s drug pipeline: a five-dimensional framework. Nat Rev Drug Discov 13(6):419–431

    Article  CAS  PubMed  Google Scholar 

  • Danhof M, de Jongh J, De Lange EC, Della Pasqua O, Ploeger BA, Voskuyl RA (2007) Mechanism-based pharmacokinetic-pharmacodynamic modeling: biophase distribution, receptor theory, and dynamical systems analysis. Annu Rev Pharmacol Toxicol 47:357–400

    Article  CAS  PubMed  Google Scholar 

  • Danhof M, de Lange EC, Della Pasqua OE, Ploeger BA, Voskuyl RA (2008) Mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling in translational drug research. Trends Pharmacol Sci 29(4):186–191

    Article  CAS  PubMed  Google Scholar 

  • DiMasi JA, Feldman L, Seckler A, Wilson A (2010) Trends in risks associated with new drug development: success rates for investigational drugs. Clin Pharmacol Ther 87(3):272–277

    Article  CAS  PubMed  Google Scholar 

  • DiMasi JA, Reichert JM, Feldman L, Malins A (2013) Clinical approval success rates for investigational cancer drugs. Clin Pharmacol Ther 94(3):329–335

    Article  CAS  PubMed  Google Scholar 

  • Empfield JR, Leeson PD (2010) Lessons learned from candidate drug attrition. IDrugs 13(12):869–873

    PubMed  Google Scholar 

  • Frank R, Hargreaves R (2003) Clinical biomarkers in drug discovery and development. Nat Rev Drug Discov 2(7):566–580

    Article  CAS  PubMed  Google Scholar 

  • Gabrielsson J, Hjorth S (2012) Quantitative pharmacology: an introduction to integrative pharmacokinetic-pharmacodynamic analysis. Apotekarsocieteten, Stockholm, p 262

    Google Scholar 

  • Gabrielsson J, Dolgos H, Gillberg PG, Bredberg U, Benthem B, Duker G (2009) Early integration of pharmacokinetic and dynamic reasoning is essential for optimal development of lead compounds: strategic considerations. Drug Discov Today 14:358–372

    Article  CAS  PubMed  Google Scholar 

  • Gabrielsson J, Green AR, Van der Graaf PH (2010) Optimising in vivo pharmacology studies–practical PKPD considerations. J Pharmacol Toxicol Methods 61(2):146–156

    Article  CAS  PubMed  Google Scholar 

  • Gabrielsson J, Fjellström O, Ulander J, Rowley M, Van Der Graaf PH (2011) Pharmacodynamic-pharmacokinetic integration as a guide to medicinal chemistry. Curr Top Med Chem 11(4):404–418

    Article  CAS  PubMed  Google Scholar 

  • Giacomini KM, Huang SM, Tweedie DJ, Benet LZ, Brouwer KL, Chu X, Dahlin A, Evers R, Fischer V, Hillgren KM, Hoffmaster KA, Ishikawa T, Keppler D, Kim RB, Lee CA, Niemi M, Polli JW, Sugiyama Y, Swaan PW, Ware JA, Wright SH, Yee SW, Zamek-Gliszczynski MJ, Zhang L (2010) Membrane transporters in drug development. Nat Rev Drug Discov 9(3):215–236

    Article  CAS  PubMed  Google Scholar 

  • Grime KH, Barton P, McGinnity DF (2013) Application of in silico, in vitro and preclinical pharmacokinetic data for the effective and efficient prediction of human pharmacokinetics. Mol Pharm 10(4):1191–1206

    Article  CAS  PubMed  Google Scholar 

  • Hartung IV, Hitchcock M, PĂĽhler F, Neuhaus R, Scholz A, Hammer S, Petersen K, Siemeister G, Brittain D, Hillig RC (2013) Optimization of allosteric MEK inhibitors. Part 1: venturing into underexplored SAR territories. Bioorg Med Chem Lett 23(8):2384–2390

    Article  CAS  PubMed  Google Scholar 

  • Heimbach T, Lakshminarayana SB, Hu W, He H (2009) Practical anticipation of human efficacious doses and pharmacokinetics using in vitro and preclinical in vivo data. AAPS J 11(3):602–614

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hopkins AL, KeserĂĽ GM, Leeson PD, Rees DC, Reynolds CH (2014) The role of ligand efficiency metrics in drug discovery. Nat Rev Drug Discov 13(2):105–121

    Article  CAS  PubMed  Google Scholar 

  • Jones HM, Chen Y, Gibson C, Heimbach T, Parrott N, Peters SA, Snoeys J, Upreti VV, Zheng M, Hall SD (2015) Physiologically based pharmacokinetic modeling in drug discovery and development: a pharmaceutical industry perspective. Clin Pharmacol Ther 97(3):247–262

    Article  CAS  PubMed  Google Scholar 

  • Kennedy T (1997) Managing the drug discovery/development interface. Drug Discov Today 2(10):436–444

    Article  Google Scholar 

  • Kerns E, Di L (2008) Drug-like properties: concepts, structure design and methods: from ADME to toxicity optimization. Academic, Amsterdam, p 552

    Google Scholar 

  • Kola I, Landis J (2004) Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 3(8):711–715

    Article  CAS  PubMed  Google Scholar 

  • Li C, Liu B, Chang J, Groessl T, Zimmerman M, He YQ, Isbell J, Tuntland T (2013) A modern in vivo pharmacokinetic paradigm: combining snapshot, rapid and full PK approaches to optimize and expedite early drug discovery. Drug Discov Today 18(1–2):71–78

    Article  CAS  PubMed  Google Scholar 

  • Lowe PJ, Hijazi Y, Luttringer O, Yin H, Sarangapani R, Howard D (2007) On the anticipation of the human dose in first-in-man trials from preclinical and prior clinical information in early drug development. Xenobiotica 37:1331–1354

    Article  CAS  PubMed  Google Scholar 

  • LĂĽcking U, Jautelat R, KrĂĽger M, Brumby T, Lienau P, Schäfer M, Briem H, Schulze J, Hillisch A, Reichel A, Wengner AM, Siemeister G (2013) The lab oddity prevails: discovery of pan-CDK inhibitor (R)-S-cyclopropyl-S-(4-{[4-{[(1R,2R)-2-hydroxy-1-methylpropyl]oxy}-5-(trifluoromethyl) pyrimidin-2-yl]amino}phenyl)sulfoximide (BAY 1000394) for the treatment of cancer. ChemMedChem 8(7):1067–1085

    Article  PubMed  Google Scholar 

  • LĂĽpfert C, Reichel A (2005) Development and application of physiologically based pharmacokinetic-modeling tools to support drug discovery. Chem Biodivers 2(11):1462–1486

    Article  PubMed  Google Scholar 

  • Mahmood I (2005) Interspecies pharmacokinetic scaling: principles and application of allometric scaling. Pine House Publishers, Rockville, p 393

    Google Scholar 

  • Meanwell NA (2011) Improving drug candidates by design: a focus on physicochemical properties as a means of improving compound disposition and safety. Chem Res Toxicol 24(9):1420–1456

    Article  CAS  PubMed  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 

  • Muenster U, Pelzetter C, Backensfeld T, Ohm A, Kuhlmann T, Mueller H, Lustig K, Keldenich J, Greschat S, Göller AH, Gnoth MJ (2011) Volume to dissolve applied dose (VDAD) and apparent dissolution rate (ADR): tools to predict in vivo bioavailability from orally applied drug suspensions. Eur J Pharm Biopharm 78(3):522–530

    Article  CAS  PubMed  Google Scholar 

  • Muller PY, Milton MN (2012) The determination and interpretation of the therapeutic index in drug development. Nat Rev Drug Discov 11(10):751–761

    Article  CAS  PubMed  Google Scholar 

  • Parkinson J, Visser SA, Jarvis P, Pollard C, Valentin JP, Yates JW, Ewart L (2013) Translational pharmacokinetic-pharmacodynamic modeling of QTc effects in dog and human. J Pharmacol Toxicol Methods 68(3):357–366

    Article  CAS  PubMed  Google Scholar 

  • Parrott N, Paquereau N, Coassolo P, LavĂ© T (2005) An evaluation of the utility of physiologically based models of pharmacokinetics in early drug discovery. J Pharm Sci 94(10):2327–2343

    Article  CAS  PubMed  Google Scholar 

  • Pelkonen O, Baumann A, Reichel A (2002) Pharmacokinetic challenges in drug discovery. Ernst Schering research foundation workshop, vol 37. Springer, Heidelberg, p 306

    Google Scholar 

  • Peters SA, Ungell AL, Dolgos H (2009) Physiologically based pharmacokinetic (PBPK) modeling and simulation: applications in lead optimization. Curr Opin Drug Discov Dev 12(4):509–518

    CAS  Google Scholar 

  • Plowright AT, Johnstone C, Kihlberg J, Pettersson J, Robb G, Thompson RA (2012) Hypothesis driven drug design: improving quality and effectiveness of the design-make-test-analyse cycle. Drug Discov Today 17(1–2):56–62

    Article  CAS  PubMed  Google Scholar 

  • Poulin P, Jones RD, Jones HM, Gibson CR, Rowland M, Chien JY, Ring BJ, Adkison KK, Ku MS, He H, Vuppugalla R, Marathe P, Fischer V, Dutta S, Sinha VK, Bjornsson T, Lave T, Yates JW (2011) PHRMA CPCDC initiative on predictive models of human pharmacokinetics. Part 5: prediction of plasma concentration-time profiles in human by using the physiologically-based pharmacokinetic modeling approach. J Pharm Sci 100(10):4127–4157

    Article  CAS  PubMed  Google Scholar 

  • Prueksaritanont T, Chu X, Gibson C, Cui D, Yee KL, Ballard J, Cabalu T, Hochman J (2013) Drug-drug interaction studies: regulatory guidance and an industry perspective. AAPS J 15(3):629–645

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Reichel A (2009) Addressing central nervous system (CNS) penetration in drug discovery: basics and implications of the evolving new concept. Chem Biodivers 6(11):2030–2049

    Article  CAS  PubMed  Google Scholar 

  • Reichel A (2014) Integrated approach to optimizing CNS penetration in drug discovery: from the old to the new paradigm and assessment of drug–transporter interactions. In: Hammarlund-Udenaes M, de Lange E (Autor, Herausgeber), Thorne RG (eds) Drug delivery to the brain. AAPS Advances in the pharmaceutical sciences series. Springer, New York, pp 339–374

    Google Scholar 

  • Reichel A (2015) Pharmacokinetics of CNS penetration. In: Di L, Kerns EH (eds) Blood-brain barrier in drug discovery: optimizing brain exposure of CNS drugs and minimizing brain side effects for peripheral drugs. Wiley, New Jersey, pp 7–41

    Google Scholar 

  • Reynolds CH, Tounge BA, Bembenek SD (2008) Ligand binding efficiency: trends, physical basis, and implications. J Med Chem 51(8):2432–2438

    Article  CAS  PubMed  Google Scholar 

  • Roberts SA (2001) High-throughput screening approaches for investigating drug metabolism and pharmacokinetics. Xenobiotica 31(8–9):557–589

    Article  CAS  PubMed  Google Scholar 

  • Roberts SA (2003) Drug metabolism and pharmacokinetics in drug discovery. Curr Opin Drug Discov Dev 6(1):66–80

    CAS  Google Scholar 

  • Rocchetti M, Simeoni M, Pesenti E, De Nicolao G, Poggesi I (2007) Predicting the active doses in humans from animal studies: a novel approach in oncology. Eur J Cancer 43(12):1862–1868

    Article  CAS  PubMed  Google Scholar 

  • Rostami-Hodjegan A (2012) Physiologically based pharmacokinetics joined with in vitro-in vivo extrapolation of ADME: a marriage under the arch of systems pharmacology. Clin Pharmacol Ther 92(1):50–61

    Article  CAS  PubMed  Google Scholar 

  • Schmieder R, Puehler F, Neuhaus R, Kissel M, Adjei AA, Miner JN, Mumberg D, Ziegelbauer K, Scholz A (2013) Allosteric MEK1/2 inhibitor refametinib (BAY 86-9766) in combination with sorafenib exhibits antitumor activity in preclinical murine and rat models of hepatocellular carcinoma. Neoplasia 15(10):1161–1171

    Article  PubMed  PubMed Central  Google Scholar 

  • Simeoni M, De Nicolao G, Magni P, Rocchetti M, Poggesi I (2013) Modeling of human tumor xenografts and dose rationale in oncology. Drug Discov Today Technol 10(3):e365–e372

    Article  PubMed  Google Scholar 

  • Smith DA (2011) Discovery and ADMET: where are we now. Curr Top Med Chem 11(4):467–481

    Article  CAS  PubMed  Google Scholar 

  • Smith DA, Di L, Kerns EH (2010) The effect of plasma protein binding on in vivo efficacy: misconceptions in drug discovery. Nat Rev Drug Discov 9(12):929–939

    Article  CAS  PubMed  Google Scholar 

  • Smith DA, Allerton C, Kalgutkar A, van de Waterbeemd H, Walker DK (2012) Pharmacokinetics and metabolism in drug design. Wiley-VCH, Weinheim, p 268

    Book  Google Scholar 

  • Tsaioun K, Kates SA (2011) ADMET for medicinal chemists: a practical guide. Wiley, New Jersey, p 512

    Book  Google Scholar 

  • Tuntland T, Ethell B, Kosaka T, Blasco F, Zang RX, Jain M, Gould T, Hoffmaster K (2014) Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research. Front Pharmacol 5:174

    Article  PubMed  PubMed Central  Google Scholar 

  • van den Bergh A, Sinha V, Gilissen R, Straetemans R, Wuyts K, Morrison D, Bijnens L, Mackie C (2011) Prediction of human oral plasma concentration-time profiles using preclinical data: comparative evaluation of prediction approaches in early pharmaceutical discovery. Clin Pharmacokinet 50(8):505–517

    Article  PubMed  Google Scholar 

  • Venkatakrishnan K, Friberg L, Ouellet D, Mettetal J, Stein A, TrocĂłniz I, Bruno R, Mehrotra N, Gobburu J, Mould D (2015) Optimizing oncology therapeutics through quantitative translational and clinical pharmacology: challenges and opportunities. Clin Pharmacol Ther 97(1):37–54

    Article  CAS  PubMed  Google Scholar 

  • Visser SA, Aurell M, Jones RD, Schuck VJ, Egnell AC, Peters SA, Brynne L, Yates JW, Jansson-Löfmark R, Tan B, Cooke M, Barry ST, Hughes A, Bredberg U (2013) Model-based drug discovery: implementation and impact. Drug Discov Today 18(15–16):764–775

    Article  CAS  PubMed  Google Scholar 

  • Wang J, Urban L (2014) PREDICTIVE ADMET integrative approaches in drug discovery and development. Wiley, New Jersey, p 616

    Book  Google Scholar 

  • Yamazaki S (2013) Translational pharmacokinetic-pharmacodynamic modeling from nonclinical to clinical development: a case study of anticancer drug, crizotinib. AAPS J 15(2):354–366

    Article  PubMed  PubMed Central  Google Scholar 

  • Yamazaki S, Lam JL, Zou HY, Wang H, Smeal T, Vicini P (2015) Mechanistic understanding of translational pharmacokinetic-pharmacodynamic relationships in nonclinical tumor models: a case study of orally available novel inhibitors of anaplastic lymphoma kinase. Drug Metab Dispos 43(1):54–62

    Article  PubMed  Google Scholar 

  • Zhang D, Surapaneni S (2012) ADME-enabling technologies in drug design and development. Wiley, New Jersey, p 622

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Research Pharmacokinetics, Global Drug Discovery, Bayer Pharma, Berlin, Germany

    Andreas Reichel & Philip Lienau

Authors
  1. Andreas Reichel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Philip Lienau
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Andreas Reichel or Philip Lienau .

Editor information

Editors and Affiliations

  1. Drug Discovery-Cross Indication Platform, Bayer Pharma AG, Wuppertal, Germany

    Ulrich Nielsch

  2. Drug Discovery-Cross Indication Platform, Bayer Pharma AG, Berlin, Berlin, Germany

    Ulrike Fuhrmann

  3. Drug Discovery-Global External Innovation & Alliances, Bayer Pharma AG, Berlin, Berlin, Germany

    Stefan Jaroch

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Reichel, A., Lienau, P. (2015). Pharmacokinetics in Drug Discovery: An Exposure-Centred Approach to Optimising and Predicting Drug Efficacy and Safety. 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_26

Download citation

Publish with us

Policies and ethics

Search

Navigation