Biotransformation novel advances – 2021 year in review

Figures & data

Table 1. Articles covered in this review.

	Title	First author	Source
1	Future of biotransformation science in the pharmaceutical industry	VM Kramlinger	Drug Metab Dispos. 50:258–267, 2022
New modalities biotransformation
2	Nonclinical pharmacokinetics and absorption, distribution, metabolism, and excretion of givosiran, the first approved N-acetylgalactosamine–conjugated RNA interference therapeutic	J Li	Drug Metab Dispos. 49:572–580, 2021
3	Emerging siRNA design principles and consequences for biotransformation and disposition in drug development	SC Humphreys	J Med Chem. 63:6407–6422, 2020
Drug discovery biotransformation
4	Contribution of extrahepatic aldehyde oxidase activity to human clearance	KD Kozminski	Drug Metab Dispos 2021
5	Investigation of Janus kinase (JAK) Inhibitors for lung delivery and the importance of aldehyde oxidase metabolism	CR Wellaway	J Med Chem 65:633–664, 2022
6	Static and dynamic projections of drug-drug interactions caused by cytochrome P450 3 A time-dependent inhibitors measured in human liver microsomes and hepatocytes	E Tseng	Drug Metab Dispos. 49:947–960, 2021
7	Progesterone receptor membrane component 1 (PGRMC1) binds and stabilizes cytochromes P450 through a heme-independent mechanism	MR McGuire	J Biol Chem 297:101316
Drug development biotransformation
8	Addressing today’s ADME challenges in the translation of in vitro absorption, distribution, metabolism and excretion characteristics to human: A case study of the SMN2 mRNA splicing modifier risdiplam	S Fowler	Drug Metab Dispos. 2021
9	Role of human flavin-containing monooxygenase (FMO) 5 in the metabolism of nabumetone: Baeyer-Villiger oxidation in the activation of the intermediate metabolite, 3-hydroxynabumetone, to the active metabolite, 6-methoxy-2-naphthylacetic acid in vitro	K Matsumoto	Xenobiotica. 51:155–166, 2021
10	CYP2C8-mediated formation of a human disproportionate metabolite of the selective NaV 1.7 inhibitor DS-1971a, a mixed cytochrome P450 and aldehyde oxidase substrate	D Asano	Drug Metab Dispos. 50:235–242, 2022
11	Metabolism and mass balance of the novel nonsteroidal androgen receptor inhibitor darolutamide in humans	P Taavitsainen	Drug Metab Dispos 49:420–433, 2021
12	Evaluation of the absorption, metabolism, and excretion of a single oral 1-mg dose of tropifexor in healthy male subjects and the concentration dependence of tropifexor metabolism	L Wang-Lakshman	Drug Metab Dispos. 49:548–562, 2021
13	Extrahepatic metabolism of ibrutinib	JJM Rood	Invest New Drugs. 39:1–14, 2021
14	Investigation into MAO B–mediated formation of CC112273, a major circulating metabolite of ozanimod, in humans and preclinical species: stereospecific oxidative deamination of (S)-enantiomer of indaneamine (RP101075) by MAO B	A Bai	Drug Metab Dispos. 49:601–609, 2021
15	Absorption, metabolism, and excretion, in vitro pharmacology, and clinical pharmacokinetics of ozanimod, a novel sphingosine 1-phosphate receptor modulator	S Surapaneni	Drug Metab Dispos. 49:405–419, 2021
16	Pharmacokinetics, metabolism, and excretion of licogliflozin, a dual inhibitor of SGLT1/2, in rats, dogs, and humans	L Wang-Lakshman	Xenobiotica. 51:413–426, 2021

Figure 1. Bioactivation pathway of empagliflozin to 4-OH-CTA. Adapted from Taub et al. (2015).

Figure 2. (A) Structure of givosiran and its metabolites. (B) Structures of (A) unmodified, 2′-O-methyl (2′-OMe), 2′-deoxy-2′-fluoro (2′-F), and phosphorothioate (PS) modified nucleotides; (C) triantennary GalNAc linker from givosiran.

Figure 3. Known biotransformation products of ligand-conjugated siRNA and proposed biotransformation mechanisms: B, RNA base adenine, guanine, cytosine, or uracil; R, 2′-ribose modification, i.e. 2’-F or 2’-OMe. SS is sense strand and AS is antisense strand. Figure from Humphreys et al. (2020) (Copyright 2020, American Chemical Society).

Figure 4. Carbazeran enzymatic conversation to 4-oxo-carbazeran aldehyde oxidase (AO) was chosen as a selective probe substrate for the contribution of various tissue in its metabolism.

Figure 5. JAK inhibitor that displays poor lung exposure due to AO metabolism (left) and a JAK inhibitor lacking AO susceptibility that displays high lung exposure (right). Arrow indicates site of AO oxidation.

Figure 6. Evaluating the ability of in vitro CYP3A time-dependent inhibition (TDI) data to predict clinically significant drug-drug interactions (DDI). AUC: Area under the plasma concentration-time curve; k_inact: maximal inactivation rate; K_I: time-dependent inhibition constant; K_i: reversible inhibition constant.

Table 2. Relevant equations used by Tseng et al. (2021) for DDI predictions in static Model 4.

Parameter	Input value (Model 4)	Equation
[I]g: inhibitor concentration exiting the gut	Cavg,portal,u: unbound average portal vein concentration	$$C_{avg,portal,u}= f_{u,p}\times \left(C_{avg}+\frac{F_a\times F_g\times Dose}{\tau \times BPR\times Q_{pv}}\right)$$Definitions: fu,p = free fraction of test drug in plasma Cavg = average concentration Fa = fraction of test drug absorbed after oral administration Fg = fraction of test drug escaping intestinal metabolism BPR = blood-to-plasma ratio Qpv = portal vein blood flow t = dosing interval for inhibitor
[I]h: inhibitor concentration exiting the liver	Cavg,systemic,u: unbound steady state average systemic concentration	$$C_{avg, systemic,u}$$
AUCR:AUC ratio	Model to determine the extent of DDI with competitive inhibition and time-dependent inactivation of CYP3A in liver and gut	$$AUCR = \frac{AUCi}{AUC} =$$$$\frac{1}{\left(\left(\frac{1}{1+ \frac{{\left[I\right]}_h}{K_i}} \times \frac{1}{1+\left(\frac{k_{inact}\times {\left[I\right]}_h}{\left(K_I+{\left[I\right]}_h\right)\times k_{deg,\hspace{0.17em}CYP3A,h}}\right)}\right)\times f_{m\left(CYP3A\right)}\right) +\left(1 -f_{m\left(CYP3A\right)}\right)}$$$$\times \frac{1}{\left(\left(\frac{1}{1+ \frac{{\left[I\right]}_g}{K_i}} \times \frac{1}{1+\left(\frac{k_{inact} \times {\left[I\right]}_g}{\left(K_I+{\left[I\right]}_g\right)\times k_{deg,\hspace{0.17em}CYP3A,g}}\right)}\right)\times {(1 -F}_g)\right) +F_g}$$$$$$Definitions: AUC = area under the concentration versus time curve without inhibitor AUCi = area under the concentration versus time curve with inhibitor [I]g = inhibitor concentration in intestine [I]h = inhibitor concentration in liver Ki = reversible inhibition constant KI = time-dependent inhibition constant kinact = kinetic constant for the maximum rate of enzyme inactivation kdeg,CYP3A,g = degradation rate of CYP3A enzyme in intestine kdeg,CYP3A,h = degradation rate of CYP3A enzyme in liver Fg = fraction of test drug escaping intestinal metabolism fm(CYP3A) = fraction of victim drug metabolized by CYP3A enzyme

Figure 7. The role of PGRMC1 in CYP2E1 stability as well as acetaminophen metabolism and toxicity.

Figure 8. Major metabolic structures of risdiplam.

Figure 9. Known metabolic pathways for the oxidative cleavage of nonsteroidal anti-inflammatory prodrug nabumetone to its biologically active metabolite 6-MNA. ALDH: Aldehyde dehydrogenase.

Figure 10. (A) Identification of the potent and selective Na_V1.7 inhibitor DS-1971a via optimization of the previously disclosed benzenesulfonamide chemotypes from 1 and PF-05089771. (B) Major metabolites of DS-1971a in animals and human.

Figure 11. Interconversion of the two diastereomers of darolutamide via keto-darolutamide.

Figure 12. Proposed sites of oxidations of tropifexor.

Figure 13. Biotransformation pathways of ibrutinib.

Figure 14. Proposed mechanism of oxidation of RP101075 by MAO-B.

Figure 15. Metabolism of ozanimod by gut microbiota.

Figure 16. Direct glucuronidation of licogliflozin to M17, M23, and M27.

Taub ME, Ludwig-Schwellinger E, Ishiguro N, Kishimoto W, Yu H, Wagner K, Tweedie D. 2015. Sex-, species-, and tissue-specific metabolism of empagliflozin in male mouse kidney forms an unstable hemiacetal metabolite (M466/2) that degrades to 4-hydroxycrotonaldehyde, a reactive and cytotoxic species. Chem Res Toxicol. 28(1):103–115.

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Humphreys SC, Thayer MB, Campbell J, Chen WLK, Adams D, Lade JM, Rock BM. 2020. Emerging siRNA design principles and consequences for biotransformation and disposition in drug development. J Med Chem. 63(12):6407–6422.

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Tseng E, Eng H, Lin J, Cerny MA, Tess DA, Goosen TC, Obach RS. 2021. Static and dynamic projections of drug-drug interactions caused by cytochrome P450 3A time-dependent inhibitors measured in human liver microsomes and hepatocytes. Drug Metab Dispos. 49(10):947–960.

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