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Computer-Aided Biopharmaceutical Characterization: Gastrointestinal Absorption Simulation and In Silico Computational Modeling

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Computer Aided Pharmaceutics and Drug Delivery

Abstract

Biopharmaceutical characterization of drugs is the most important fundamental part of their development and discovery process. This plays a pivotal role in formulating an efficient dosage form with appropriate bioavailability. Absorption of drugs is a multifaceted process affected by several factors including the physicochemical properties of the drug and the pharmaco-technical parameters of the formulation. Several drugs during their development stages fail due to poor biopharmaceutical properties. Thus to decrease the cost and time involved in the drug discovery process and to develop more effective dosage regimens, computer-aided in silico absorption models are required for better characterization of biopharmaceutical properties. One of the major objectives of in silico absorption models is to envisage the drug’s physicochemical properties virtually. Computer simulations can be applied to predict the oral absorption of virtual compounds and thus offer the potential to screen the molecules under development that is having a prerequisite absorption profile. The present chapter deals with basics and recent advances along with applications and limitations of commonly used in silico and computational models for biopharmaceutical characterization particularly the ACAT model-based GastroPlus™ software package.

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References

  1. Dokoumetzidis A, Kalantzi L, Fotaki N (2007) Predictive models for oral drug absorption: from in silico methods to integrated dynamical models. Expert Opin Drug Metab Toxicol 3:491–505. https://doi.org/10.1517/17425225.3.4.491

    Article  CAS  PubMed  Google Scholar 

  2. Thomas S (2010) Physiologically-based pharmacokinetic modelling for the reduction of animal use in the discovery of novel pharmaceuticals. Altern Lab Anim 38:81–85. https://doi.org/10.1177/026119291003801S16

    Article  CAS  PubMed  Google Scholar 

  3. Agoram B, Woltosz WS, Bolger MB (2001) Predicting the impact of physiological and biochemical processes on oral drug bioavailability. Adv Drug Deliv Rev 50:S41–S67. https://doi.org/10.1016/S0169-409X(01)00179-X

    Article  CAS  PubMed  Google Scholar 

  4. Ayad MH (2015) Rational formulation strategy from drug discovery profiling to human proof of concept. Drug Deliv 22:877–884. https://doi.org/10.3109/10717544.2014.898714

    Article  CAS  PubMed  Google Scholar 

  5. Kuentz M, Nick S, Parrott N, Röthlisberger D (2006) A strategy for preclinical formulation development using GastroPlus™ as pharmacokinetic simulation tool and a statistical screening design applied to a dog study. Eur J Pharm Sci 27:91–99. https://doi.org/10.1016/j.ejps.2005.08.011

    Article  CAS  PubMed  Google Scholar 

  6. Lin L, Wong H (2017) Predicting oral drug absorption: mini review on physiologically-based pharmacokinetic models. Pharmaceutics 9:41. https://doi.org/10.3390/pharmaceutics9040041

    Article  CAS  PubMed Central  Google Scholar 

  7. Daga PR, Bolger MB, Haworth IS, Clark RD, Martin EJ (2018) Physiologically based pharmacokinetic modeling in lead optimization. 1. Evaluation and adaptation of GastroPlus to predict bioavailability of Medchem series. Mol Pharm 15:821–830. https://doi.org/10.1021/acs.molpharmaceut.7b00972

    Article  CAS  PubMed  Google Scholar 

  8. Grbic S, Parojcic J, Djuric Z (2013) Computer-aided biopharmaceutical characterization: gastrointestinal absorption simulation. In: Computer-aided applications in pharmaceutical technology. Woodhead Publishing Limited. https://doi.org/10.1533/9781908818324.177

  9. Huang W, Lee SL, Yu LX (2009) Mechanistic approaches to predicting oral drug absorption. AAPS J 11:217–224. https://doi.org/10.1208/s12248-009-9098-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Waring MJ, Arrowsmith J, Leach AR, Leeson PD, Mandrell S, Owen RM et al (2015) An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat Rev Drug Discov 14:475–486. https://doi.org/10.1038/nrd4609

    Article  CAS  PubMed  Google Scholar 

  11. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 23:3–25. https://doi.org/10.1016/S0169-409X(96)00423-1

    Article  CAS  Google Scholar 

  12. Amidon GL, Lennernäs H, Shah VP, Crison JR (1995) A theoretical basis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution and in vivo bioavailability. Pharm Res 12:413–420. https://doi.org/10.1023/A:1016212804288

    Article  CAS  PubMed  Google Scholar 

  13. Oh DM, Curl RL, Amidon GL (1993) Estimating the fraction dose absorbed from suspensions of poorly soluble compounds in humans: a mathematical model. Pharm Res 10:264–270. https://doi.org/10.1023/A:1018947113238

    Article  CAS  PubMed  Google Scholar 

  14. Wu C-Y, Benet LZ (2005) Predicting drug disposition via application of BCS: transport/absorption/elimination interplay and development of a biopharmaceutics drug disposition classification system. Pharm Res 22:11–23. https://doi.org/10.1007/s11095-004-9004-4

    Article  CAS  PubMed  Google Scholar 

  15. Chu X, Bleasby K, Evers R (2013) Species differences in drug transporters and implications for translating preclinical findings to humans. Expert Opin Drug Metab Toxicol 9:237–252. https://doi.org/10.1517/17425255.2013.741589

    Article  CAS  PubMed  Google Scholar 

  16. Dressman JB, Amidon GL, Fleisher D (1985) Absorption potential: estimating the fraction absorbed for orally administered compounds. J Pharm Sci 74:588–589. https://doi.org/10.1002/jps.2600740523

    Article  CAS  PubMed  Google Scholar 

  17. Johnson KC, Swindell AC (1996) Guidance in the setting of drug particle size specifications to minimize variability in absorption. Pharm Res 13:1795–1798. https://doi.org/10.1023/A:1016068705255

    Article  CAS  PubMed  Google Scholar 

  18. Ding X, Rose JP, Van Gelder J (2012) Developability assessment of clinical drug products with maximum absorbable doses. Int J Pharm 427:260–269. https://doi.org/10.1016/j.ijpharm.2012.02.003

    Article  CAS  PubMed  Google Scholar 

  19. Sun D, Yu LX, Hussain MA, Wall DA, Smith RL, Amidon GL (2004) In vitro testing of drug absorption for drug “developability” assessment: forming an interface between in vitro preclinical data and clinical outcome. Curr Opin Drug Discov Devel 7:75–85

    CAS  PubMed  Google Scholar 

  20. Kostewicz ES, Aarons L, Bergstrand M, Bolger MB, Galetin A, Hatley O et al (2014) PBPK models for the prediction of in vivo performance of oral dosage forms. Eur J Pharm Sci 57:300–321. https://doi.org/10.1016/j.ejps.2013.09.008. Elsevier B.V.

    Article  CAS  PubMed  Google Scholar 

  21. Sugano K (2009) Introduction to computational oral absorption simulation. Expert Opin Drug Metab Toxicol 5:259–293. https://doi.org/10.1517/17425250902835506

    Article  CAS  PubMed  Google Scholar 

  22. Sjögren E, Thörn H, Tannergren C (2016) In silico modeling of gastrointestinal drug absorption: predictive performance of three physiologically based absorption models. Mol Pharm 13:1763–1778. https://doi.org/10.1021/acs.molpharmaceut.5b00861

    Article  CAS  PubMed  Google Scholar 

  23. Yu LX, Lipka E, Crison JR, Amidon GL (1996) Transport approaches to the biopharmaceutical design of oral drug delivery systems: prediction of intestinal absorption. Adv Drug Deliv Rev 19:359–376. https://doi.org/10.1016/0169-409X(96)00009-9

    Article  CAS  PubMed  Google Scholar 

  24. Yu LX, Crison JR, Amidon GL (1996) Compartmental transit and dispersion model analysis of small intestinal transit flow in humans. Int J Pharm 140:111–118. https://doi.org/10.1016/0378-5173(96)04592-9

    Article  CAS  Google Scholar 

  25. Oberle RL, Amidon GL (1987) The influence of variable gastric emptying and intestinal transit rates on the plasma level curve of cimetidine; an explanation for the double peak phenomenon. J Pharmacokinet Biopharm 15:529–544. https://doi.org/10.1007/BF01061761

    Article  CAS  PubMed  Google Scholar 

  26. Dressman JB, Fleisher D (1986) Mixing-tank model for predicting dissolution rate control of oral absorption. J Pharm Sci 75:109–116. https://doi.org/10.1002/jps.2600750202

    Article  CAS  PubMed  Google Scholar 

  27. Yu LX, Amidon GL (1998) Saturable small intestinal drug absorption in humans: modeling and interpretation of cefatrizine data. Eur J Pharm Biopharm 45:199–203. https://doi.org/10.1016/S0939-6411(97)00088-X

    Article  CAS  PubMed  Google Scholar 

  28. Grass GM (1997) Simulation models to predict oral drug absorption from in vitro data. Adv Drug Deliv Rev 23:199–219. https://doi.org/10.1016/S0169-409X(96)00436-X

    Article  CAS  Google Scholar 

  29. Abuhelwa AY, Williams DB, Upton RN, Foster DJR (2017) Food, gastrointestinal pH, and models of oral drug absorption. Eur J Pharm Biopharm 112:234–248. https://doi.org/10.1016/j.ejpb.2016.11.034. Elsevier B.V.

    Article  CAS  PubMed  Google Scholar 

  30. Sawamoto T, Haruta S, Kurosaki Y, Higaki K, Kimura T (1997) Prediction of the plasma concentration profiles of orally administered drugs in rats on the basis of gastrointestinal transit kinetics and absorbability. J Pharm Pharmacol 49:450–457. https://doi.org/10.1111/j.2042-7158.1997.tb06823.x

    Article  CAS  PubMed  Google Scholar 

  31. Kimura T, Higaki K (2002) Gastrointestinal transit and drug absorption. Biol Pharm Bull 25:149–164. https://doi.org/10.1248/bpb.25.149

    Article  CAS  PubMed  Google Scholar 

  32. Yokoe J, Iwasaki N, Haruta S, Kadono K, Ogawara K, Higaki K et al (2003) Analysis and prediction of absorption behavior of colon-targeted prodrug in rats by GI-transit-absorption model. J Control Release 86:305–313. https://doi.org/10.1016/S0168-3659(02)00424-8

    Article  CAS  PubMed  Google Scholar 

  33. Jamei M, Turner D, Yang J, Neuhoff S, Polak S, Rostami-Hodjegan A et al (2009) Population-based mechanistic prediction of oral drug absorption. AAPS J 11:225–237. https://doi.org/10.1208/s12248-009-9099-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Cheng L, Wong H (2020) Food effects on oral drug absorption: application of physiologically-based pharmacokinetic modeling as a predictive tool. Pharmaceutics 12:672. https://doi.org/10.3390/pharmaceutics12070672

    Article  CAS  PubMed Central  Google Scholar 

  35. Jamei M, Marciniak S, Feng K, Barnett A, Tucker G, Rostami-Hodjegan A (2009) The Simcyp ® population-based ADME simulator. Expert Opin Drug Metab Toxicol 5:211–223. https://doi.org/10.1517/17425250802691074

    Article  CAS  PubMed  Google Scholar 

  36. Zhang T, Wells E (2020) A review of current methods for food effect prediction during drug development. Curr Pharmacol Rep 6:267–279. https://doi.org/10.1007/s40495-020-00230-9

    Article  Google Scholar 

  37. Yu LX, Amidon GL (1999) A compartmental absorption and transit model for estimating oral drug absorption. Int J Pharm 186:119–125. https://doi.org/10.1016/S0378-5173(99)00147-7

    Article  CAS  PubMed  Google Scholar 

  38. Xia B, Yang Z, Zhou H, Lukacova V, Zhu W, Milewski M et al (2015) Development of a novel oral cavity compartmental absorption and transit model for sublingual administration: illustration with zolpidem. AAPS J 17:631–642. https://doi.org/10.1208/s12248-015-9727-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Le Merdy M, Spires J, Lukacova V, Tan M-L, Babiskin A, Xu X et al (2020) Ocular physiologically based pharmacokinetic modeling for ointment formulations. Pharm Res 37:245. https://doi.org/10.1007/s11095-020-02965-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Miller NA, Reddy MB, Heikkinen AT, Lukacova V, Parrott N (2019) Physiologically based pharmacokinetic modelling for first-in-human predictions: an updated model building strategy illustrated with challenging industry case studies. Clin Pharmacokinet 58:727–746. https://doi.org/10.1007/s40262-019-00741-9

    Article  CAS  PubMed  Google Scholar 

  41. Ahmad A, Pepin X, Aarons L, Wang Y, Darwich AS, Wood JM et al (2020) IMI—oral biopharmaceutics tools project—evaluation of bottom-up PBPK prediction success part 4: prediction accuracy and software comparisons with improved data and modelling strategies. Eur J Pharm Biopharm 156:50–63. https://doi.org/10.1016/j.ejpb.2020.08.006

    Article  CAS  PubMed  Google Scholar 

  42. Jones HM, Parrott N, Ohlenbusch G, Lavé T (2006) Predicting pharmacokinetic food effects using biorelevant solubility media and physiologically based modelling. Clin Pharmacokinet 45:1213–1226. https://doi.org/10.2165/00003088-200645120-00006

    Article  CAS  PubMed  Google Scholar 

  43. Grbic S, Lukic V, Kovacevic I, Parojcic J, Djuric Z (2012) An investigation into the possibilities and limitations of in silico absorption modeling: GastroPlus™ simulation of nimesulide oral absorption. In: Proc 2nd Electron Conf Pharm Sci. MDPI, Basel, Switzerland, p 816. https://doi.org/10.3390/ecps2012-00816

  44. Grbic S, Parojcic J, Ibric S, Djuric Z (2011) In vitro–in vivo correlation for gliclazide immediate-release tablets based on mechanistic absorption simulation. AAPS PharmSciTech 12:165–171. https://doi.org/10.1208/s12249-010-9573-y

    Article  CAS  PubMed  Google Scholar 

  45. Parrott N, Stillhart C, Lindenberg M, Wagner B, Kowalski K, Guerini E et al (2020) Physiologically based absorption modelling to explore the impact of food and gastric pH changes on the pharmacokinetics of entrectinib. AAPS J 22:78. https://doi.org/10.1208/s12248-020-00463-y

    Article  CAS  PubMed  Google Scholar 

  46. Zhang X, Lionberger RA, Davit BM, Yu LX (2011) Utility of physiologically based absorption modeling in implementing quality by design in drug development. AAPS J 13:59–71. https://doi.org/10.1208/s12248-010-9250-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Tubic M, Wagner D, Spahn-Langguth H, Bolger MB, Langguth P (2006) In silico modeling of non-linear drug absorption for the P-gp substrate talinolol and of consequences for the resulting pharmacodynamic effect. Pharm Res 23:1712–1720. https://doi.org/10.1007/s11095-006-9020-7

    Article  CAS  PubMed  Google Scholar 

  48. Koziolek M, Alcaro S, Augustijns P, Basit AW, Grimm M, Hens B et al (2019) The mechanisms of pharmacokinetic food-drug interactions—a perspective from the UNGAP group. Eur J Pharm Sci 134:31–59. https://doi.org/10.1016/j.ejps.2019.04.003

    Article  CAS  PubMed  Google Scholar 

  49. Deng J, Zhu X, Chen Z, Fan CH, Kwan HS, Wong CH et al (2017) A review of food–drug interactions on oral drug absorption. Drugs 77:1833–1855. https://doi.org/10.1007/s40265-017-0832-z

    Article  CAS  PubMed  Google Scholar 

  50. Gu C-H, Li H, Levons J, Lentz K, Gandhi RB, Raghavan K et al (2007) Predicting effect of food on extent of drug absorption based on physicochemical properties. Pharm Res 24:1118–1130. https://doi.org/10.1007/s11095-007-9236-1

    Article  CAS  PubMed  Google Scholar 

  51. da Silva Honório T, Pinto EC, Rocha HVA, Esteves VSD, dos Santos TC, Castro HCR et al (2013) In vitro–in vivo correlation of efavirenz tablets using GastroPlus®. AAPS PharmSciTech 14:1244–1254. https://doi.org/10.1208/s12249-013-0016-4

    Article  CAS  Google Scholar 

  52. CDER/FDA (2015) Guidance for Industry, Waiver of in vivo bioavailability and bioequivalence studies for immediate release solid oral dosage forms based on a biopharmaceutics classification system. Cent Drug Eval Res

    Google Scholar 

  53. Okumu A, DiMaso M, Löbenberg R (2009) Computer simulations using GastroPlus™ to justify a biowaiver for etoricoxib solid oral drug products. Eur J Pharm Biopharm 72:91–98. https://doi.org/10.1016/j.ejpb.2008.10.019. Elsevier B.V.

    Article  CAS  PubMed  Google Scholar 

  54. Tubic-Grozdanis M, Bolger MB, Langguth P (2008) Application of gastrointestinal simulation for extensions for biowaivers of highly permeable compounds. AAPS J 10:213–226. https://doi.org/10.1208/s12248-008-9023-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Arora, D., Khurana, B. (2022). Computer-Aided Biopharmaceutical Characterization: Gastrointestinal Absorption Simulation and In Silico Computational Modeling. In: Saharan, V.A. (eds) Computer Aided Pharmaceutics and Drug Delivery. Springer, Singapore. https://doi.org/10.1007/978-981-16-5180-9_7

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