Pharmaceutical Technology REGULATORY SOURCEBOOK MARCH 2021 27
that when the effect of food administration involves changes
in gastrointestinal physiology such as fluid volume, motility,
pH, and bile salts, the food effects were generally predictable. A
decision tree was formulated based upon the analysis to guide
the categorization of application of PBPK models of food ef-
fects into those of high, medium, and low confidence (7).
Such categorization will be helpful in the interpretation of
PBPK food effect models as well as in identifying areas where
additional research is needed (i.e., those models considered
moderate and low confidence).
Conclusion
PBPK modeling has been established as an important predictive
science in pharmaceutical drug development over the past two
decades; the aforementioned case studies from the IQ Consor-
tium demonstrate the significant progress that the industry
is making toward enabling 'virtual' human experiments and
streamlining drug development.
References
1. C. Perry, et al., Curr Pharmacol Rep 6 71–84 (2020).
2. M. Jamei, G. L. Dickinson, A. Rostami-Hodjegan, Drug Metab
Pharmacokinet 24 (1) 53–75 (2009).
3. L. Kuepfer L, et al., CPT Pharmacometrics Syst Pharmacol 5 (10)
516–531 (2016).
4. M. Shebley, et al., Clin Pharmacol Ther 104 (1) 88-110 (2018).
5. M. Jamei, et al., Expert Opinion on Drug Metabolism & Toxicology 5
(2) 211–223 (2009).
6. N. Miller, et al., Clinical Pharmacokinetics 58 (6) 727–746 (June
2019).
7. A.E. Riedmaier, et al., AAPS J 22(6) 123 (2020).
8. H.M. Jones, et al., Clin Pharmacol Ther 97 (3) 247–262 (2015).
9. H.J. Einolf, et al., Clin Pharmacol. Ther.95 (2) 179–188 (2014).
10. M.L. Vieira, et al., Clin Pharmacol Ther 95 (2) 189–198 (2014).
11. FDA, In Vitro Drug Interaction Studies — Cytochrome P450 En-
zyme- and Transporter-Mediated Drug Interactions Guidance for In-
dustry (CDER, January 2020).
12. I.E. Templeton, et al., CPT Pharmacometrics Syst. Pharmacol 5 (10)
505–515 (2016).
13. Y. Chen, et al., CPT Pharmacometrics Syst. Pharmacol 8 (9) 685–695
(2019).
14. O.A. Fahmi, et al., Drug Metab Dispos 44 (10) 1720–1730 (2016).
15. T. Heimbach, et al., Clin Pharmacol Ther in press.
PT
About the authors
Heidi J. Einolf is director, modeling and simulation, pharma-
cokinetic sciences, Novartis; Stephen D. Hall is senior research
fellow, drug disposition, and Tracy Williams is senior director
ADME/Toxicology/PKPD, both with Eli Lilly and Co; Aarti
Patel is director, DMPK modeling, GlaxoSmithKline; Christo-
pher Gibson is distinguished scientist and Nancy G.B. Agrawal
is vice-president, pharmacokinetics, pharmacodynamics, and
drug metabolism, both with Merck; and Jens Sydor,* jens.x.sy-
dor@gsk.com, is vice-president, DMPK, GlaxoSmithKline; all
authors are members of the IQ Consortium.
*To whom all correspondence should be addressed.
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