Circulation through the liver in light of drug metabolism

Circulation through the liver in light of drug metabolism

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I have a lingering question which stems from an answer that I gave to What hydrolyses aspirin within the digestive tract and blood stream?

When a drug or any other substance is absorbed into the bloodstream in the stomach or small intestine, it ultimately passes through the hepatic portal vein and into the liver sinusoids, where it is processed by hepatocytes and introduced into the general circulation via the vena cava. In terms of metabolism, this is what causes a "first-pass" effect for drugs that are ingested.

For drugs that are delivered either by intravenous, intramuscular, or sub-lingually (as in the other Biology.SE question), this first-pass effect is avoided, and the drug is introduced into the general circulation without being metabolized by the liver first.

Even though the first pass is avoided, the blood in the body still makes its way back through the liver eventually via the hepatic artery, which is a branch off of the celiac artery.

The issue I still have is, does the incoming blood from the hepatic artery merge with the blood from the hepatic portal vein? If not, does the blood from the hepatic artery still interact with the hepatocytes in some way? (it makes sense that it does, and I have also read that one of the main functions of the hepatic artery was to deliver blood supply for the liver's metabolic needs) If this is not the case, where in the body would these drugs that were introduced via IV, etc., be metabolized?

Yes, the blood from the hepatic artery (proper) and the portal vein mix in the sinusoids of the liver. The hepatic vein supplies about 75% of the blood to the liver, and the hepatic artery the remaining 25%. Because the portal vein provides such a large part of the blood supply to the liver, then any disease that causes the blood to build up can cause portal hypertension.

The hepatic artery carries oxygen-rich blood from the heart. The portal vein is part of the portal system and connects the capillary beds of the gastrointestinal tract to those of the liver. Because of the larger volume through the portal vein, I think that each vessel carries about half the oxygen supply to the liver.

For drugs introduced through an injection, for example, metabolism occurs throughout the circulatory system and in the liver. Remember that it's all the same blood supply, but the first-pass effect just refers to the blood that goes to the liver before entering the systemic circulation (by which it can travel to its target).

Drug Metabolism

Kenneth Bachmann , in Pharmacology , 2009

8.1.1 Overview and History

The study of drug metabolism or biotransformation is vitally important to our understanding of the time course of drugs in the body, the structuring of dosage regimens, the pharmacology and toxicology of drug metabolites, and the interactions of multivalent drug combinations. Hydrophobicity is an important chemical characteristic of most drug molecules, because the probabilities of both good oral absorption and interactions with molecular targets tend to increase as hydrophobicity increases. Unfortunately, the probability of efficient renal or biliary excretion of drugs from the body diminishes as hydrophobicity increases. Thus, the metabolism or biotransformation of hydrophobic drug molecules to more hydrophilic molecules is a very important factor in the elimination of drugs from the body. Although the enzymes that mediate drug metabolism are found in many tissues, it is within the liver and the epithelial cells of the upper portion of the intestines where most drug metabolism occurs. For a drug that is subject to biotransformation, if it is administered by intravenous infusion, then the liver is likely to be the major site for biotransformation. On the other hand, it is possible that the same drug administered orally will be subject to biotransformation both in the intestine during absorption and in the liver as well. An overview of the relationship between intestinal and hepatic metabolism is shown in Figure 8.1 .

Figure 8.1 . A drug taken orally first encounters the contents of the stomach (1). Dissolved drug will be principally absorbed from the small intestine (2). This process often exposes drug molecules to drug metabolizing enzymes within enterocytes (see #2 in the inset to the right). Drug molecules that traverse enterocytes intact will next be transported via the blood into the hepatic portal vein, and thus enter the sinusoids of the liver (3). The inset to the right shows the movement of drug molecules across the liver sinusoids from the hepatic portal vein (left) toward the central vein of the liver (right). As drug molecules move across the sinusoids they may be diffuse into or be transported into the hepatocytes where they can be biotransformed, transported into the bile cannaliculi, or transported back into the sinusoids. Once drug molecules and their metabolites enter the central vein (right side of inset), they gain access to the general circulation.

The role of biotransformation on drug action was recognized as early as the mid-nineteenth century, however the scientific interest in drug metabolism grew exponentially after the discovery by Axelrod and Estabrook and coworkers that the liver red pigment described by Garfinkel and Klingenberg performed the function of hepatic drug-metabolizing oxido-reductases. The pigment was characterized as a cytochrome by Omura and Sato in the 1960s. The first human study of drug metabolism occurred in 1841 when Ure noted that hippuric acid could be isolated from the urine after the ingestion of benzoic acid, and the first metabolic interaction between drugs was reported by Hoffmann in 1877 who found that quinine could decrease the formation of hippuric acid from benzoic acid.

The preceding reaction is an example of a conjugation or synthetic reaction. Synthetic reactions constitute one of the two broad types of metabolic reactions that were initially classified by R. T. Williams in the middle of the twentieth century. Williams has been referred to as the founder of the field of drug metabolism. Some other mid-twentieth century scientists who are generally recognized as having advanced the field of drug metabolism in significant ways include Bernard B. Brodie, Sidney Udenfriend, James Gillette, Bert LaDu, and Julius Axelrod. Many of those who made major contributions to the field during the last half of the twentieth century took their training with Dr. Brodie at the National Institutes of Health.

Williams proposed the dichotomous scheme of drug metabolism consisting of an initial phase (Phase I) that might possibly be followed by a second (Phase II). In Phase I a drug is either activated or inactivated by one of three types of irreversible chemical modifications or biotransformations, namely oxidation, reduction, or hydrolysis. Phase II was the synthetic phase, which Williams characterized as an additional inactivation step, though it is now understood that Phase II reactions can occur absent Phase I reactions, and that both Phase I and Phase II reactions can activate as well as inactivate drugs. Williams' dichotomy of metabolic reactions is still widely used today.

Large veins that are considered part of the portal venous system are the:

The superior mesenteric vein and the splenic vein come together to form the actual hepatic portal vein. The inferior mesenteric vein connects in the majority of people on the splenic vein, but in some people, it is known to connect on the portal vein or the superior mesenteric vein.

Roughly, the portal venous system corresponds to areas supplied by the celiac trunk, the superior mesenteric artery, and the inferior mesenteric artery.

The portal venous system is responsible for directing blood from parts of the gastrointestinal tract to the liver. Substances absorbed in the small intestine travel first to the liver for processing before continuing to the heart. Not all of the gastrointestinal tract is part of this system. The system extends from about the lower portion of the esophagus to the upper part of the anal canal. It also includes venous drainage from the spleen, pancreas and visceral fat . [2] [3]

The evolutionary purpose of first-pass metabolism, whereby substances absorbed from food in the gut pass through the liver before entering the systemic circulation, is to use the liver as a shield (a first line of defense) between (a) the food, its toxins (whatever they may be), and its metabolic intermediates/metabolites (such as ammonia) and (b) the rest of the body's tissues, including the brain. The necessity of such a system is demonstrated by what happens when the system breaks down, as seen when advanced hepatic fibrosis in cirrhosis leads to hepatic encephalopathy in the brain owing to the blood being loaded with ammonia and other substances not conducive to brain function.

Blood flow to the liver is unique in that it receives both oxygenated and (partially) deoxygenated blood. As a result, the partial gas pressure of oxygen (pO2) and perfusion pressure of portal blood are lower than in other organs of the body. Blood passes from branches of the portal vein through cavities between "plates" of hepatocytes called sinusoids. Blood also flows from branches of the hepatic artery and mixes in the sinusoids to supply the hepatocytes with oxygen. This mixture percolates through the sinusoids and collects in a central vein which drains into the hepatic vein. The hepatic vein subsequently drains into the inferior vena cava.

The hepatic artery provides 30 to 40% of the oxygen to the liver, while only accounting for 25% of the total liver blood flow. The rest comes from the partially deoxygenated blood from the portal vein. The liver consumes about 20% of the total body oxygen when at rest. That is why the total liver blood flow is quite high, at about 1 litre a minute and up to two litres a minute. That is on average one fourth of the average cardiac output at rest.

Portal hypertension is a condition in which the blood pressure of the portal venous system is too high. It is often the result of cirrhosis of the liver.

Drug metabolism Edit

Many drugs that are absorbed through the GI tract are substantially metabolized by the liver before reaching general circulation. This is known as the first pass effect. As a consequence, certain drugs can only be taken via certain routes. For example, nitroglycerin cannot be swallowed because the liver would deactivate the medication, but it can be taken under the tongue or transdermally (through the skin) and thus is absorbed in a way that bypasses the portal venous system. Inversely, dextromethorphan, a cough suppressor, is best taken orally because it needs to be metabolised by the liver into dextrorphan in order to be effective. This latter principle is that of most prodrugs.

The use of suppositories is a way to partially bypass the portal vein: the upper 1/3 of the rectum is drained into the portal vein while the lower 2/3 are drained into the internal iliac vein that goes directly in the inferior vena cava (thus bypassing the liver).

ADME-Tox Approaches Metabolism

Drug metabolism is the phase of biochemical transformation of the drug. It is highly variable among drugs and depends on biological conditions. The metabolism phase is absent for the few drugs that are not transformed. As explained in great detail in other chapters ( see 5.05 Principles of Drug Metabolism 1: Redox Reactions 5.06 Principles of Drug Metabolism 2: Hydrolysis and Conjugation Reactions 5.07 Principles of Drug Metabolism 3: Enzymes and Tissues 5.08 Mechanisms of Toxification and Detoxification which Challenge Drug Candidates and Drugs 5.09 Immunotoxicology 5.10 In Vitro Studies of Drug Metabolism 5.33 Comprehensive Expert Systems to Predict Drug Metabolism 5.43 Metabonomics ), biotransformations may involve one or more successive reactions:

Phase 1 transformations (reactions of functionalization) involve the creation of a functional group or the modification of an existing one by oxidation, reduction, or hydrolysis.

Phase 2 transformations (reactions of conjugation) couple a drug or a metabolite to an endogenous conjugating molecule such as glucuronic acid, sulfuric acid, acetic acid, glutathione, etc.

From a physicochemical point of view, drug metabolism is expected to yield metabolites of lower lipophilicity relative to the parent drug, e.g., by adding an ionizable group. As a result, metabolites are often excreted faster than the parent drug, but there are exceptions. From a pharmacological point of view, it is essential to check the pharmacodynamic consequences of these metabolic reactions. Often but far from always, biotransformation involves inactivation or detoxification. Activation concerns prodrugs, but also active compounds (drugs) giving rise to active metabolites. The latter may exhibit a PK profile different from that of the parent drug, and/or a qualitatively different activity. Prodrugs receive specific treatment in Chapters 5.44 and 5.45

Some enzymes involved in metabolism present a genetic polymorphism, which separates populations of patients according to their phenotypes (i.e., very fast, ‘normal,’ and poor metabolizers). This is the field of pharmacogenetics. Independently of any pathological state, individuals who are very fast or poor metabolizers need to be identified and have their dosages adjusted. 10 Specific monitoring must also be applied for drugs with a low therapeutic index resulting in a low safety margin due to relatively vicinal effective and toxic doses.

Detoxification pathways in the liver

The liver plays an important rôle in protecting the organism from potentially toxic chemical insults through its capacity to convert lipophiles into more water-soluble metabolites which can be efficiently eliminated from the body via the urine. This protective ability of the liver stems from the expression of a wide variety of xenobiotic biotransforming enzymes whose common underlying feature is their ability to catalyse the oxidation, reduction and hydrolysis (Phase I) and/or conjugation (Phase II) of functional groups on drug and chemical molecules. The broad substrate specificity, isoenzyme multiplicity and inducibility of many of these enzyme systems make them particularly well adapted to handling the vast array of different chemical structures in the environment to which we are exposed daily. However, some chemicals may also be converted to more toxic metabolites by certain of these enzymes, implying that variations in the latter may be important predisposing factors for toxicity. Pharmacogenetic defects of xenobiotic biotransformation enzymes, a subclass of inborn errors of metabolism which are manifested only upon drug challenge, introduce marked variation into human populations for the pharmacokinetics and pharmacodynamics of therapeutic and toxic agents, and thus may have important clinical consequences for drug efficacy and toxicity.


The results of this study carry two major implications. First, TrxR1 was shown to be a determinant of the global metabolic state of the liver. Genetic deletion of Txnrd1 triggered a metabolic switch that favored glycogen- over lipid-accumulation and high expression of drug-metabolism enzymes. Second, TrxR1 was identified as a high-affinity target for direct inactivation by NAPQI, which might contribute to APAP-induced hepatotoxicity. Interestingly, even though APAP treatment was shown to inhibit hepatic TrxR activity in vivo, mice in which hepatocytes were genetically TrxR1-deficient were refractory to APAP-induced hepatotoxicity. Our results indicate that a chronic shift in hepatocyte metabolic processes resulting from genetic disruption of Txnrd1 preconditions an APAP-resistant state in the liver, whereas the acute loss of TrxR1 activity caused by APAP challenge, itself, is insufficient to induce resistance.

TrxR1 regulates the metabolic state of liver

To our knowledge, this is the first study to show a direct link between Txnrd1 status and a metabolic switch between a glycogen-storage versus a lipid-storage phenotype. Disruption of TrxR1 switched liver bioenergetics toward glycogenesis, indicating that TrxR1 activity biases the liver toward lipogenesis. As possible mechanisms for this switch, a potential role of Txnip should be considered (see Introduction). Txnip has been shown to participate in determining the metabolic state of several cell types and systems [7�], and has been correlated with metabolic switches in others [11, 12]. It is thus possible that the metabolic switch caused by hepatocytic Txnrd1 deletion is a secondary effect related to TrxR1’s influence, via reduction of Trx1, on Txnip. Alternatively, it is possible that TrxR1 and Txnip each independently mediate metabolism through Trx1. Resolving these mechanisms is outside the scope of the present study but clearly warrants future investigation. Here, we can conclude that genetic modulation of the Txnrd1 status in mouse liver has similarly pronounced effects on the metabolic state as have been identified in mouse models with Txnip deletion.

APAP inhibits both the GSH- and the Trx-systems in normal liver

High dose APAP exposure rapidly depletes liver GSH reserves, which will disrupt all hepatic GSH-dependent redox reactions. However, the redox functions of the GSH system are highly overlapping with those of the Trx system, and, indeed, unchallenged hepatocytes in vivo remain overtly normal in the absence of either GSH, Gsr, or TrxR1 [3, 30, 31, 45, 46]. By contrast, short-term depletion of hepatic GSH with buthionine sulfoximine in mice genetically lacking hepatocytic TrxR1 inhibits hepatocyte DNA replication [30], indicating that at least some essential redox reactions require either the GSH- or the Trx-system for activity. In this study, we show that high dose APAP challenge inhibits hepatic TrxR and Trx activities in wild-type livers. This indicates that, under these conditions, both the GSH- and the Trx-system are inhibited and, as a corollary, that all redox reactions requiring either one of these systems will be disrupted. Potential impacts of this on hepatotoxicity are discussed below.

Interplay between the metabolic state of TrxR1-deficient liver and susceptibility to APAP toxicity

Fasting exacerbates APAP hepatotoxicity, and this has been correlated to depleted glycogen stores [39]. However, to our knowledge, it has not been previously shown that glycogen engorgement correlates with APAP resistance. Indeed, the capacity of the UGT pathway is normally insufficient to provide substantial protection against even low-dose APAP challenge [22]. Importantly, the substrate for UGT is APAP, which is not cytotoxic, so the UGT pathway preempts formation of NAPQI, the cytotoxic metabolite. TrxR1-deficient livers contained glycogen levels of

40 µg/mg tissue ( Figures 1B , S2C). This correlates to

0.33 mole-equivalents of glucose or glucuronate, in a 1.5 g liver, and this was consumed very rapidly upon challenge with 1000 mg/kg APAP ( Figure 3B , S2C). This APAP dose is equivalent to 30 mg, or 0.2 moles, in a 30 g mouse. Although we do not know how much glycogen is going toward energetic demands versus conjugation, the molar-ratio of consumed glycogen to administered APAP in these animals was high enough that glucuronidation could have contributed substantially to detoxification, thereby effectively curtailing cellular formation of NAPQI.

Interactions of APAP with drug metabolism enzymes in null/null or null/+ livers

Although null/null and null/+ livers accumulated similar levels of glycogen, the null/+ livers exhibited greater pathology following APAP challenge. This can be explained by the different degrees to which drug metabolism pathways were activated in each genotype. For example, null/null hepatocytes but not null/+ hepatocytes overexpress the mRNA for Nqo1 ( Figure 5D ), an enzyme that catalyzes the conversion of NAPQI into APAP [47]. APAP and NAPQI are in equilibrium in APAP-challenged hepatocytes, with Cyps catalyzing the formation of APAP into NAPQI and Nqo1 playing a protective role by reversing this reaction. Increasing Nqo1 activity will shift this equilibrium toward APAP, thereby lowering cytoplasmic NAPQI concentrations [22, 47]. Although mRNAs encoding several Cyps were up-regulated in null/+ and null/null livers ( Figure 5 , Table S1), these did not include Cyp family members that convert APAP into NAPQI [48�]. Compared to +/+ livers, both null/null and null/+ livers overexpress Abcc3, yet only null/null livers also overexpress Abcc4 ( Figure 5D ). As a result, livers of both genotypes likely exhibit augmented elimination of APAP metabolites, with null/null livers being more effective at this than null/+ livers. In addition, we found that the null/null livers have an augmented GSH biosynthetic pathway, increased steady-state GSH levels, and they exhibit very high accumulation A- and M-class GST mRNAs and proteins, all of which should bolster glutathionylation-mediated export of NAPQI. In summary, the constitutive drug metabolism profile of the TrxR1-deficient livers, as compared to wild-type livers, will be particularly proficient at preventing cytosolic accumulation of NAPQI by (1) more effectively eliminating APAP before it becomes NAPQI and (2) shunting any NAPQI that does form either back into APAP and out of the cell by glucuronidation-medated export, or directly out of the cell via glutathionylation-mediated export. Although it is outside the scope of the current study to distinguish the relative contributions of each pathway to APAP detoxification in these mice, the observation that GSH levels rebound to resting or higher levels within 4 h of high-dose APAP challenge in both null/null and null/+ livers attests to the efficacy with which the overall metabolic shift in TrxR1-deficient livers allows them to resist APAP-induced GSH depletion and hepatotoxicity.

Factors contributing to NAPQI-induced cytotoxicity

The mechanisms of NAPQI toxicity remain incompletely understood. Because other means of GSH depletion are not cytotoxic [45], GSH depletion, alone, cannot account for toxicity. Since NAPQI is highly electrophilic, cysteine residues will react with it at rates that will depend on the accessibility and relative reactivity of individual residues. As such, active site cysteines on molecules like GSH or Trx will be preferred targets. The even more reactive Sec residue on TrxR1 [6] should be particularly susceptible to NAPQI. Here we show that NAPQI is indeed highly effective at inhibiting TrxR1 through its Sec residue, and that APAP-treated wild-type mice undergo marked losses of Trx and TrxR activities. Recent studies have shown that NAPQI also inhibits the mitochondrial superoxide dismutase (MnSOD), presaging mitochondrial oxidative damage [51]. MnSOD inhibition likely also results from the high reactivity of the enzyme’s active site, which is expected to make it a favorable NAPQI target. Thus, NAPQI disrupts both the GSH- and the Trx-systems, which are the cell’s two major NADPH-driven antioxidant systems, and it impedes mitochondrial detoxification of reactive oxygen species (ROS), all of which likely contribute to hepatotoxicity.

Recent biochemical studies have shown that, upon reacting with certain electrophilic drugs, TrxR1 can adopt novel activities. For example, like we here show for NAPQI, cisplatin reacts with the TrxR1 Sec residue it inhibits its Trx-reductase activity but not its juglone-reductase activity and it induces irreversible binding of TrxR1 to Trx1 [52]. Some other electrophilic compounds that react with the TrxR1 Sec residue can, in the presence of certain small molecule substrates, induce the enzyme to become a cytotoxic NADPH-oxidase, entitled a “SecTRAP” ( Sec -compromised t hioredoxin r eductase-derived pro- a poptotic p rotein) that can generate large amounts of ROS [40]. Whereas it is unknown whether NAPQI-bound TrxR1 in hepatocytes might similarly generate ROS, it is intriguing to consider that TrxR1-deficient hepatocytes might be refractory to APAP not only as a consequence of their glycogen stores and augmented drug-metabolism capacity, but also as a consequence of not having TrxR1 converted into a SecTRAP. Further studies will be required to test this possibility.

Finally, our study reveals a surprisingly integrated network of metabolic systems in hepatocytes, with TrxR1 playing a key role in feed-forward cross-talk between systems. The importance of this is emphasized by the synergistic roles that various metabolic pathways play in protecting hepatocytes during APAP exposure. Clinical APAP remediation currently focuses on augmenting GSH production [53]. However it is known that nutritional deficiency is a compromising factor in APAP sensitivity [39], and the increase in APAP-induced glycogen consumption that we see in TrxR1-deficient livers suggests that bioenergetic modulation might provide an additional means to abrogate the hepatotoxic effects of APAP. In the future, combinatorial therapies that sustain GSH production, augment glucuronidation-based detoxification, and possibly prevent SecTRAP formation might lead to improved survival upon APAP overdose.

Neuroendocrine responses

Ageing is accompanied by changes in neuroendocrine responses to psychosocial or physical stress. In particular, an altered function of the hypothalamic-pituitary-adrenal (HPA) axis has been observed. Excessive HPA activation and hypersecretion of glucocorticoids can lead to dendritic atrophy in neurones in the hippocampus, resulting in learning and memory impairment. Damage or loss of hippocampal neurones results in impaired feedback inhibition of the HPA axis and glucocorticoid secretion, leading to further damage caused by elevated glucocorticoid concentrations. This positive feedback effect on hippocampal neuronal loss is known as the glucocorticoid cascade hypothesis [34]. Thus, glucocorticoids may sensitize hippocampal neurones to cell death and/or functional impairment, indirect effects that are likely to be age-dependent.

Under conditions of chronic stress, there would be insufficient adjustments in HPA axis activity in response to the challenge of sustained glucocorticoid levels. This might be caused by impaired feedback regulation of the HPA axis activity [35].


The liver plays a central role in metabolism. Although many studies have described in vitro liver models for drug discovery, to date, no model has been described that can stably maintain liver function. Here, we used a unique, scaffold-free 3D bio-printing technology to construct a small portion of liver tissue that could stably maintain drug, glucose, and lipid metabolism, in addition to bile acid secretion. This bio-printed normal human liver tissue maintained expression of several kinds of hepatic drug transporters and metabolic enzymes that functioned for several weeks. The bio-printed liver tissue displayed glucose production via cAMP/protein kinase A signaling, which could be suppressed with insulin. Bile acid secretion was also observed from the printed liver tissue, and it accumulated in the culture medium over time. We observed both bile duct and sinusoid-like structures in the bio-printed liver tissue, which suggested that bile acid secretion occurred via a sinusoid-hepatocyte-bile duct route. These results demonstrated that our bio-printed liver tissue was unique, because it exerted diverse liver metabolic functions for several weeks. In future, we expect our bio-printed liver tissue to be applied to developing new models that can be used to improve preclinical predictions of long-term toxicity in humans, generate novel targets for metabolic liver disease, and evaluate biliary excretion in drug development.


Distribution describes the reversible transfer of a drug from one location in the body to another. Drug developers can get a big-picture view of drug concentration in various tissues and organs over time from radiolabeled in vivo ADME studies, including quantitative whole body autoradiography (QWBA), microautoradiography (mARG), and tissue dissection.

Other in vitro studies can help piece together the more minute details of a compound&rsquos distribution. For example, permeability assays can characterize the potential of a compound to enter cells, drug transporter studies help to identify proteins responsible for moving a drug into (uptake) and out of (efflux) cells, and plasma protein binding (PPB) studies quantify the extent of binding to plasma proteins, which could limit the amount of free drug available for therapeutic action or interaction with transporters or enzymes.

5.1 Overview of Pharmacology

As mentioned in the introduction, this chapter is the start of our exploration of pharmacology, which is the study of the actions and effects of drugs. You can easily see how such a field is relevant to a class with the words “effects of alcohol and other drugs” in its name. Pharmacology is the foundation of many health sciences and is critical to developing therapeutic drugs and drug treatments.

By the end of this section, you should be able to:

  • Differentiate between pharmaceutics, pharmacokinetics, and pharmacodynamics.
  • Define the four different components of pharmacokinetics.

5.1.1 The Pharmaceutical Sciences

Pharmacology can be broken down into two different branches: pharmacokinetics, which is the study of how the drug moves around the body, and pharmacodynamics, which is the study of how the drug changes the body. You can use these meanings to tell the two terms apart the suffixes ‑kinetics [movement] and ‑dynamics [change] refer to how the drug moves and what the drug changes.

Pharmacology is only one of many different areas of study related to drugs. Another example is medicinal chemistry, which is the synthesis of new drug compounds. We briefly touched on it during the discussion of the New Drug Approval process in the first chapter, although not by name. There are other fields as well, each with many different subspecialties.

One area worth mentioning is pharmaceutics, or the study of how a drug is formulated and dispensed. In the past, pharmacists often dispensed drugs directly as a powder containing just the active ingredients. Nowadays, drugs are usually designed with a dosage form in mind, which is a mix of active and inactive ingredients prepared in a particular form, such as a capsule or tablet. Dosage forms allow for greater control over the dose of the drug and how it is taken.

Although we will not cover pharmaceutics in detail in this course, it is worth knowing because of the relationship between pharmaceutics and pharmacokinetics. As you can see in the diagram below, the dosage form determines how the drug is made available to the body. This influences the pharmacokinetics of the drug, which in turn influences the pharmacodynamics of the drug.

The focus of this chapter is pharmacokinetics, which as we just mentioned is concerned with how the drug moves throughout the body. In reality, the drug isn’t moving on its own—it’s actually being moved around by the natural systems in our body. Because of this, we can also say that pharmacokinetics is what the body does to the drug. (Next chapter we will look at pharmacodynamics, which is the opposite—what the drug does to the body.)

There are four main things that the body does to the drug: it absorbs it into the bloodstream, distributes it to various areas of the body, metabolizes it into different compounds, and excretes it from the system. A useful mnemonic that can help you remember this process is ADMEAbsorption, Distribution, Metabolism, and Excretion. We will spend the rest of this chapter examining each of these in detail.

Liver in vitro Models for Toxicological Studies

Both liver metabolism and the mechanisms of initial liver injury are important to comprehend the potential toxicity of a drug. Therefore, the development of efficient and fit-for-purpose in vitro models should mimic the complexity of the in vivo hepatic milieu. As such, when building a relevant liver in vitro model, the hepatic cell sources and tissue architecture, flow dynamics and the formation of molecular gradients need to be carefully considered.

No universally accepted hepatocyte source that provides robust, predictive and significant toxicological and pharmacological results is currently available. Cell source selection depends on cell availability and study requirements while understanding the limitations associated to each cell origin, namely metabolic competence, stability, and population representativeness (Soldatow et al., 2013). Regarding culture architecture, efforts have been focused in better mimic the in vivo microenvironment, giving special attention to culture three-dimensionality either by taking advantage of cell self-assembling capacity or by using natural polymers. More complex systems, such as bioreactors, micropatterning techniques, or microfluidic devices can also be employed (Miranda et al., 2010 Bell et al., 2016 Knospel et al., 2016 Adiels et al., 2017). Those platforms should also allow acute toxicity studies and long-term assessment so that the exposure to a xenobiotic generates relevant responses (Jiang et al., 2019). Overall, the value of an in vitro model depends on how well it reproduces the key physiological characteristics of an in vivo system. However, the criteria for defining liver function maintenance in vitro are not consensual, ranging from focusing on the preservation of hepatocyte phase I and II enzyme functions to the inclusion of a broader spectrum of tissue characteristics involved in human liver toxicity, such as the incorporation of NPCs for mimicking cells’ crosstalk (Bale et al., 2014 Zeilinger et al., 2016 Langhans, 2018 Bell et al., 2020).

Some common evaluated features to compare hepatic cell-based in vitro culture systems’ value for toxicological applications include cell morphology, viability, and functional stability metabolic capacity preservation of hepatic-specific gene expression under long-term cultures and response to a panel of well-accepted reference drugs (e.g., paracetamol and valproic acid) capable of replicating human in vivo intrinsic DILI (Miranda et al., 2009, 2010 Leite et al., 2011 Mueller et al., 2011 Tostoes et al., 2011 Cipriano et al., 2017b Pinheiro et al., 2017 Vinken and Hengstler, 2018 Bell et al., 2020). Moreover, the generated data should be able to be correlated to clinical observations, reproducible, comparable among laboratories, and analyzed properly to support decision-making with a clear definition of the models’ applicability and limitations (Dash et al., 2009 Vinken and Hengstler, 2018 Albrecht et al., 2019).

Liver Cell-Based Versus Stem Cell-Based Models

Over the past decades, large efforts have been made to establish predictive in vitro liver test models. However, despite the number of reports available, a comprehensive and systematic comparison between cell culture systems adequate to objectively rank or select them for pharmacological and toxicological applications is still scarce.

Several in vitro human-based models for the prediction of hepatotoxicity have been developed using a range of cell sources and endpoints. These include the use of liver slices, genetically engineered cells, human hepatoma cell lines (e.g., HepG2, THLE, and HepaRG cells), primary hepatocytes or stem cell (SC)-derived models (Gomez-Lechon et al., 2008 Asha and Vidyavathi, 2010 Sirenko et al., 2016 Gao and Liu, 2017 Pinheiro et al., 2017 Nudischer et al., 2020). Figure 2 summarizes the advantages and limitations of each cell source for in vitro testing, as well as their in vivo physiological relevance.

Figure 2. Summary of the advantages and limitations of commonly used cell sources for in vitro liver models. HLCs, hepatocyte-like cells hpHep, human primary hepatocytes NPCs, non-parenchymal cells.

Liver slices and isolated perfused livers, containing both parenchymal and NPCs, retain liver’s structure and thus maintain zone-specific enzymatic activity. However, within hours, the cell functionality decreases and necrosis takes place (Lerche-Langrand and Toutain, 2000 Boess et al., 2003 Haschek et al., 2009). It is associated with limited throughput and requires continuous animal experimentation and personnel expertise (Vernetti et al., 2017).

Alternatively, cell-based models are less complex and associated to higher throughput screening for the identification of hepatotoxic compounds. Primary hepatocytes, either obtained from human liver autopsies or biopsies or from animal livers, have been used for cytotoxicity, biotransformation, and PK studies (Vernetti et al., 2017). Human primary hepatocytes (hpHep), in particular, are considered the gold standard in human-relevant liver in vitro models for cytotoxicity and drug metabolism testing, retaining most of the native tissue’s functionality, namely phase I and phase II enzymes (Godoy et al., 2013 Zeilinger et al., 2016). However, both the limited availability of primary human cells and its suitability only for short-term studies under monolayer cultures are major disadvantages. Indeed, in 2D conditions, it is observed a progressive loss of the hepatic phenotype in a process called de-differentiation, which is a consequence of the disruption of cell�ll and cell-matrix connections (Zeilinger et al., 2016). Additionally, hpHep display inter-donor variability and thus the use of different cell batches to validate results is advised, covering several metabolic genetic polymorphism and phenotypes (Godoy et al., 2013 Zeilinger et al., 2016). On the other hand, rat primary hepatocytes (rpHep), despite being more easily available, present relevant interspecies differences (Sandker et al., 1994 Li et al., 2008 Ménochet et al., 2012 Shen et al., 2012).

Human hepatoma cell lines, such as HepG2 and HepaRG, have no limitations in terms of cell numbers and are easy to culture, but display poor phenotype and functional match to in vivo hepatocytes (Gerets et al., 2012). The use of these cell lines do not consider populational differences and may reflect characteristics that primary cells do not have, e.g., beingmore sensitive to compounds with anti-proliferative properties (Sirenko et al., 2016). HepG2 present low levels of CYPs and normal levels of phase II enzymes except for UGTs (Westerink and Schoonen, 2007a, b), which make them appropriate for testing the toxicity of the parent compound but less suited for metabolite toxicity testing. Instead, HepaRG cell line composed of a mixture of both hepatocyte-like and biliary-like cells, have been reported to maintain hepatic functions and expression of liver-specific genes comparable to hpHep without the inter-donor variability and functional instability issues (Guillouzo et al., 2007). Nevertheless, it should be noted that a cell characterization study at the mRNA/gene expression and CYP activity levels, by Gerets et al. (2012), revealed that although it is a suitable model for induction studies, these cells were not as indicative as hpHep for the prediction of human hepatotoxic drugs, being comparable to HepG2 cells. On the other hand, L󼮾rstedt et al. (2011) showed that HepaRG presented similar or even higher CYP2C9, CYP2D6, and CYP3A4 enzyme activity than that of hpHep, whereas Aninat et al. (2006) confirmed the presence of relevant UGT1A1 and GST activity levels. Still, high metabolic capacity in cell lines does not necessarily correlate with high sensitivity for the hepatotoxicity detection (Gerets et al., 2012). Thus, unfortunately, even the most promising and differentiated hepatoma cells do not constitute an ideal surrogate system for human hepatocytes for hepatotoxicity studies, as they do not reproduce the drug-metabolizing enzyme pattern of human hepatocytes. An alternative approach to overcome the limitations of hepatic cell lines is to genetically modify cells with vectors encoding for human CYP enzymes and other genes involved in xenobiotic metabolism (Coecke et al., 2001 Kanamori et al., 2003 Gomez-Lechon et al., 2008 Prakash et al., 2008 Godoy et al., 2013). However, the number of enzymes that can be satisfactorily transfected into cells is low and the metabolic profiles differ from those of primary hepatocytes (Frederick et al., 2011 Godoy et al., 2013).

To overcome the limitations of the above mentioned cell sources, SC-derived human hepatocyte-like cells (HLCs) have been suggested as a reliable alternative (Szkolnicka et al., 2014 Takayama et al., 2014 Freyer et al., 2016 Cipriano et al., 2017a, b, 2020 Figure 2). SCs represent normal primary cells with a mostly stable genotype than hepatoma cell lines. Moreover, compared to hpHep, present unlimited supply, can be maintained for long-term and may also represent a broad patient population (Godoy et al., 2013 Horvath et al., 2016). As such, stem or progenitor cells are an exciting prospect for drug metabolism studies and cell transplantation, providing that high levels of hepatocyte-like functions can be induced and tumorigenicity concerns are overcome. Many protocols have been developed for differentiating SCs into HLCs with different approaches, such as mimicking liver development through the sequential addition of growth factors and cytokines (Cai et al., 2007 Hay et al., 2008b Brolén et al., 2010), modulation of signaling pathways (Hay et al., 2008a) or by using epigenetic modifiers (Sharma et al., 2006 Dong et al., 2009 Norrman et al., 2013). Currently, most work has been developed using induced pluripotent SCs (iPSCs) isolated from adult tissues in an non-invasive way, with promising outcomes (Sauer et al., 2014 Sirenko et al., 2016 Yamashita et al., 2018 Pareja et al., 2020). An example is the work from Gao and Liu (2017), that revealed that iPSC-derived HLCs resembled hpHep more closely than most hepatoma cell lines in global gene expression profiles, specifically in the expression of genes involved in hepatotoxicity, drug-metabolizing enzymes, transporters, and nuclear receptors. Interestingly, Freyer et al. (2016) detected CYP1A2, CYP2B6, and CYP3A4 activities in iPSC-derived HLCs, but also at a lower level than in hpHep. Likewise, Takayama et al. (2014) showed that iPSC-derived HLCs retained donor-specific drug metabolism capacity and drug responsiveness, reflecting interindividual differences, but lower CYP1A2, CYP2C9, CYP2D6, and CYP3A4 activities when compared to the correspondent hpHep donors. Besides hepatocytes, efforts have also been made to generate NPCs from iPSCs, including cholangiocytes (Ogawa et al., 2015 Sampaziotis et al., 2015), Kupffer cells (Tasnim et al., 2019), LSECs (Koui et al., 2017), and hepatic stellate cells (Koui et al., 2017 Coll et al., 2018). Nevertheless, iPSC technology has some limitations related to the genomic instability and to residual iPSC-specific methylation patterns that links these cells to their tissue of origin, which ultimately may affect their final differentiation (Robinton and Daley, 2012). Still, iPSC-derived HLCs show powerful value not only for toxicology applications but also for disease modeling and personalized drug therapy.

Alternatively, adult liver SCs (LSCs) are a particularly interesting SC source. LSCs can be obtained from liver biopsies, propagated in vitro and differentiated into mature hepatocytes (Huch et al., 2015 Wang et al., 2015 Luo et al., 2018). LSCs are located in the epithelium of the canals of Hering and contribute to liver regeneration in response to an injury (Overi et al., 2018). LSCs are bipotent, being able to differentiate into hepatocytes or cholangiocytes. As such, these cells express SC (e.g., SRY-box transcription factor 9, Sox9), cholangiocyte (CK-19), and hepatocyte (CK-18) markers (Overi et al., 2018). The identification of populations of proliferating and self-renewing cells that can replace injured hepatocytes can be performed with lineage tracing approaches using Wnt-responsive genes such as Axin2 or Lgr5 (Huch et al., 2013 Wang et al., 2015).

Mesenchymal SCs (MSCs) including liver, bone-marrow, adipose, or umbilical cord tissue-derived MSCs have also been used for deriving human HLCs (Snykers et al., 2006, 2007 Banas et al., 2007 Kazemnejad et al., 2008 Okura et al., 2010 Yin et al., 2015 Fu et al., 2016 Yang et al., 2020). From those, human neonatal MSCs stand as a promising choice due to the non-invasive access and to its more primitive origin (Hass et al., 2011 Lee et al., 2012 Cipriano et al., 2017a Yu Y. B. et al., 2018. The first report using human neonatal umbilical cord tissue-derived MSCs (hnMSCs) was from Campard et al. (2008). Therein, hnMSCs were differentiated into HLCs with impressive results, i.e., presenting hepatic-specific markers, urea production, glycogen accumulation, and CYP3A4 activity. Afterward, other researchers also differentiated hnMSCs into HLCs exhibiting hepatic markers, urea and albumin (ALB) production. However, their biotransformation activity was not assessed (Zhang et al., 2009 Zhao et al., 2009 Zhou et al., 2014). More recently, Cipriano et al. (2017a) generated hnMSC-derived HLCs with more partial hepatic phenotype, sharing expression of gene groups with hpHep that was not observed between HepG2 and hnMSCs, as shown by genome-wide analysis (Cipriano et al., 2017a). Importantly, when resorting to the 3D culture technology, MSC-derived HLCs demonstrate an improvement in phase I biotransformation activity, urea and ALB production, as well as relevant diclofenac and nevirapine biotransformation capacity, which supports its potential usefulness for toxicological studies (Cipriano et al., 2017b, 2020). Nevertheless, despite the growing efforts made in this research field a complete mature hepatocyte phenotype of HLCs derived from MSCs has not yet been achieved. Perhaps liver MSCs may be the best choice, because they are originally committed to hepatic lineage, but an accurate comparison of hepatocytes derived from human liver MSCs and other sources must still be done (Kholodenko et al., 2019 Shi et al., 2020).

All these strategies are not deprived of challenges as they require specialized personnel and expensive culture medium supplementation, whereas a complete mature phenotype has not yet been achieved. The fetal HLC phenotype is still a challenge, revealing the need to further understand hepatic differentiation mechanisms and optimizing differentiation strategies (Raju et al., 2018 Raasch et al., 2019). Moreover, the use of diverse differentiation protocols across different laboratories hinders the robustness assessment of the use of HLCs for toxicology applications. To address this issue, some authors proposed a set of cellular markers and functional assays to control the quality of iPSC-derived cells, since these are the most common type of SCs used in vitro (Daston et al., 2015 Beken et al., 2016). Although the specific metrics to monitor cell characteristics may vary according to the differentiation protocol and cell line used, this guide provides an important reference for quality control of other types of SC-based models. For HLCs, the most important markers to be analyzed are CYP3A4, CYP2B6, CYP1A1/2, CYP2C9, CYP2C19, CYP2D6, alpha-fetoprotein (AFP), ALB, Sox17, C-X-C motif chemokine receptor 4 (CXCR4), hepatocyte growth factor (HGF), hepatocyte nuclear factor 4 alpha (HNF-4α), tyrosine aminotransferase (TAT), transthyretin (TTR) while functional assays include urea and ALB synthesis, glycogen uptake, fibrinogen secretion, ATP, and GSH levels, CYP3A activity in particular, phase II activities and drug transporter capacity (Beken et al., 2016). Nonetheless, due to overall unsatisfactory phenotype of the currently available cell sources, at least for some hepatic features, the improvement of the cell culture system has been explored as will be further described in the following sections.

Three-Dimensional Liver Systems

The major shortcoming of the currently available in vitro liver preparations lays on insufficient hepatocyte-like functions and metabolic competence. In fact, none of the hpHep-, HepG2-, or HepaRG-based 2D models are suitable to indicate the risk of hepatotoxicity for novel chemical entities unless PK data are incorporated in the study, supporting the need to employ more sophisticated technologies to increase prediction sensitivity (Sison-Young et al., 2017). Accordingly, recent reports emphasize a shift, by the industry, from 2D in vitro approaches to more complex 3D assays where multicellular microphysiological devices are being evaluated within a vision to replicate the characteristics and response of human tissues in vivo (Vivares et al., 2015).

Traditionally, 2D cultures are employed as in vitro models due to their ease of use to quickly screen large numbers of compounds. However, this culture approach negatively impacts cell expression profiles (Engler et al., 2006) and causes primary hepatocytes to rapidly lose their differentiation markers (Treyer and Müsch, 2013), compromising long-term and repeated dose studies. On the other hand, 3D cell culture systems have been shown to improve the biotransformation capacities in primary hepatocytes (Tibbitt and Anseth, 2009 Miranda et al., 2010 Mandenius et al., 2011 Mueller et al., 2011 Zeilinger et al., 2011 Schyschka et al., 2013), hepatoma cell lines (Fey and Wrzesinski, 2012 Molina-Jimenez et al., 2012 Wrzesinski et al., 2014) and SC-derived HLCs (Gieseck et al., 2014 Freyer et al., 2016 Cipriano et al., 2017b, 2020) over time in culture.

In general, as summarized in Figure 3 and Table 1, 3D cell culture systems are prone to high-throughput adaptation and scale up but vary in complexity and on remote monitoring of cell culture parameters. Three-dimensional systems can comprise extracellular matrix (ECM) sandwich cultures (Chatterjee et al., 2014 Deharde et al., 2016), spheroid and organoid cultures (Miranda et al., 2009 Leite et al., 2011, 2012 Tostoes et al., 2011 Wrzesinski et al., 2014 Huch et al., 2015 Bell et al., 2016 Peng et al., 2018 Ramli et al., 2020), cells adherent to a scaffold (Kazemnejad et al., 2008 Lin and Chang, 2008 Haycock, 2011), or more complex cellular systems such as hollow-fiber bioreactors (Darnell et al., 2011, 2012 L󼮾rstedt et al., 2011 Mueller et al., 2011 Zeilinger et al., 2011 Hoffmann et al., 2012 Cipriano et al., 2017b), bioartificial livers (Chan et al., 2004), multi-well perfused bioreactors (Domansky et al., 2010 Vivares et al., 2015 Aeby et al., 2018 Mannaerts et al., 2020), and more recently bioprinted systems (Lauschke et al., 2016 Goulart et al., 2019) and microfluidic platforms (MP) (Rennert et al., 2015 Ma C. et al., 2016 Bauer et al., 2017 Danoy et al., 2019).

Figure 3. Summary of the characteristics of complex 3D in vitro cell culture systems for hepatotoxicity studies. (A) Sandwich cultures (B) static spheroid cultures (C) dynamic spheroid cultures (D) bioreactors (E) bioprinting (F) microfluidic platforms. PBPK, physiologically based pharmacokinetic modeling TD, toxicodynamics TK, toxicokinetics.


  1. Faine

    Thank you :) Cool topic, write more often - you are doing great :)

  2. Abdul-Wahid

    Nifiga surprises myself

  3. Dolkis

    It seems to read carefully but I don't understand

  4. Cocytus

    Words are bigger!

  5. Tavin

    Unambiguously, the excellent answer

  6. Gabirel

    Endless discussion :)

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