Pharmacodynamics and pharmacokinetics of drugs in early life stages

July 6, 2022

Physiologically based pharmacokinetic (PBPK) modeling is now used for drug regulatory submissions.  Interest continues to grow for the use of PBPK modeling to help inform drug pharmacokinetics and pharmacodynamics for data-poor reproductive states and life stages such as pregnancy ( mother and fetus), lactation (mother and nursing infant), and the child.  PBPK models for drugs can inform dose-selection when clinical pharmacokinetic data are missing or forecast population level variability in pharmacokinetics. Many of the age-related physiological changes occur in the fetus and maturing neonate are expected to alter the pharmacokinetics of medicines.  Additionally, maternal physiological and biochemical changes that occur during pregnancy and lactation may also alter the pharmacokinetics of medicines. At this juncture, drug dose selection is usually based on adequate pharmacokinetic data in adults.  An adult PBPK model can be modified to forecast the pharmacokinetics of medicines during pregnancy and lactation or in the developing infant and child.  This is accomplished by the inclusion of the physiology of pregnancy, lactation, and childhood growth.   If available, opportunistic drug pharmacokinetic data is used in PBPK models.  With continued support and interest, these specialized PBPK models can help with clinical trial design and perhaps someday, reduce clinical trial requirements.

Most recently Dr. Fisher, a senior research fellow, was a coauthor on a manuscript in which In Vitro to In Vivo Extrapolation (IVIVE) was used to predict human milk to plasma drug ratios at steady state for numerous drugs (Yang et al. 2022).  The ratio of a drug in human breast milk relative to the plasma level of a drug is a key PBPK model parameter for estimating a nursing infant’s intake of a drug. For pediatrics and drugs, Dr. Fisher has assisted in or developed drug PBPK models for premature (Fisher et al. 2019, Troutman et al. 2018, and Yang et al. 2019) and full-term birthed neonates (Duan et al. 2019, 2018, Van den Anker 2020, Zhang et al. 2020).  In the case of preterm births, the neonate drug PBPK models were developed, de novo.

The shift from the use of animals to other alternative testing methods has gained the attention of congress. On June 9th 2022, the US House passed legislation to end FDA animal testing ( Eventually, new alternative methods involving human cells will likely be a central feature for the evaluation of drug safety.  These cell-based methods require companion in silico techniques (e.g., PBPK modeling) to extrapolate from cell exposures for drugs to predict human whole-body in vivo tissue and organ exposures, including pregnancy and lactation. ScitoVation is positioned to help the drug industry in this regard.  The in-silico extrapolation from cells to whole body is called In Vitro to In Vivo Extrapolation (IVIVE). ScitoVation has a strong track record for involvement in NAMs, New Approach Methodologies, and in silico IVIVE.

If you have any questions in translating data from in vitro exposures (or animal studies) to humans, please send an email to our customer service center []. We have helped clients tackled complex questions related to



  1. Duan P, Wu F, Moore JN, Fisher J, Crentsil V, Gonzalez D, Zhang L, Burckart GJ, and Wang J. 2019. Assessing CYPC19 ontogeny in neonates and infants using physiologically based pharmacokinetic models: Impact of enzyme inhibition maturation versus inhibition. CTP Pharmacometrics Syst Pharmacol 3, 158-166.
  2. Duan P, Fang W, Moore JN, Fisher J, Crentsil V, Gonzalez D, Zhang L, Burckart GJ, and Wang J. 2018. Assessing CYP2C19 Ontogeny in Neonates and Infants Using Physiologically-Based Pharmacokinetic Models: Impact of Enzyme Maturation versus Inhibition. CTP Pharmacometrics Syst. Pharmacol., 1-9, doi:10.1002/pso4.12350. 
  3. Fisher JW, Wu H, Cohen-Wolkowiez M, Watt K, Wang J, Burckart GJ, Troutman JA, and Yang X. 2019. Predicting the pharmacokinetics of piperacillin and tazobactam in preterm and term neonates using physiologically based pharmacokinetic modeling. Comp Toxicol 12, 1-12.
  4. Troutman, JA, Sullivan MC, Carr GJ, and Fisher J. 2018. Development of growth equations from longitudinal studies of body weight and height in the full term and preterm neonate: From birth to four years postnatal age. Birth Defects Res. 110(11), 916-932.
  5. Van den Anker JN, McCune S, Annaert P, Baer GR, Mulugeta Y, Abdelrahman R, Wu K, Krudys KM, Fisher J, Slikker W, Chen C, Burckart GJ, and Allegaert K.  Approaches to Dose Finding in Neonates, Illustrating the Variability between Neonatal Drug Development Programs. Pharmaceutics. 2020;12(7):E685. Published 2020 Jul 20. doi:10.3390/pharmaceutics12070685.
  6. Yang H, Xue I, Gu G., Zou P., Zhang, T, Lu Y, Fisher J, and Tran D. 2022. Developing an In Vitro to In Vivo Extrapolation (IVIVE) Model to Predict Human Milk-to-Plasma Drug Concentration Ratios Molecular Pharmaceutics DOI: 10.1021/acs.molpharmaceut.2c00193.
  7. Yang X,  Wu H, Mehta D, Sullivan MC, Wang J, Burckart GJ, Troutman, JA and Fisher JW. 2019. Ontogeny equations with probability distributions for anthropomorphic measurements in preterm and term neonates and infants for use in a PBPK model. Comp Toxicol 11, 101-119
  8. Zhang Y, Sherwin CM, Gonzalez D, Gonzalez D, Zhang Q, Khurara M, Fisher J, Burckart GJ, Wang Y, Yao L, Ganley CJ, and Wang J.  Creatinine-Based Renal Function Assessment in Pediatric Drug Development: An Analysis Using Clinical Data for Renally Eliminated Drugs [published online ahead of print, 2020 Jul 22]. Clin Pharmacol Ther. 2020;10.1002/cpt.1991. doi:10.1002/cpt.1991