Quantitative prediction of CYP3A induction-mediated drug-drug interactions in clinical practice

There have been no reports on the quantitative prediction of CYP3A induction-mediated decreases in AUC and Cmax for drug candidates identified as a "victims" of CYP3A induction. Our previous study separately evaluated the fold-induction of hepatic and intestinal CYP3A by known inducers using clinical induction data and revealed that we were able to quantitatively predict the AUC ratio (AUCR) of a few CYP3A substrates in the presence and absence of CYP3A inducers. In the present study, we investigate the predictability of AUCR and also Cmax ratio (CmaxR) in additional 54 clinical studies. The fraction metabolized by CYP3A (fm), the intestinal bioavailability (Fg), and the hepatic intrinsic clearance (CLint) of substrates were determined by the in vitro experiments as well as clinical data used for calculating AUCR and CmaxR. The result showed that 65-69% and 65-67% of predictions were within 2-fold of observed AUCR and CmaxR, respectively. A simulation using multiple parameter combinations suggested that the variability of fm and Fg within a certain range might have a minimal impact on the calculation output. These findings suggest that clinical AUCR and CmaxR of CYP3A substrates can be quantitatively predicted from the preclinical stage.

Enzyme-mediated drug-drug interactions: a review of in vivo and in vitro methodologies, regulatory guidance, and translation to the clinic

Enzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts.

HLM chip - A microfluidic approach to study the mechanistic basis of cytochrome P450 inhibition using immobilized human liver microsomes

Cytochrome P450 (CYP) system is a critical elimination route to most pharmaceuticals in human, but also prone to drug-drug interactions arising from the fact that concomitantly administered pharmaceuticals inhibit one another's CYP metabolism. The most severe form of CYP interactions is irreversible inhibition, which results in permanent inactivation of the critical CYP pathway and is only restored by de novo synthesis of new functional enzymes. In this study, we conceptualize a microfluidic approach to mechanistic CYP inhibition studies using human liver microsomes (HLMs) immobilized onto the walls of a polymer micropillar array. We evaluated the feasibility of these HLM chips for CYP inhibition studies by establishing the stability and the enzyme kinetics for a CYP2C9 model reaction under microfluidic flow and determining the half-maximal inhibitory concentrations (IC50) of three human CYP2C9 inhibitors (sulfaphenazole, tienilic acid, miconazole), including evaluation of their inhibition mechanisms and nonspecific microsomal binding on chip. Overall, the enzyme kinetics of CYP2C9 metabolism on the HLM chip (KM = 127 ± 55 µM) was shown to be similar to that of static HLM incubations (KM = 114 ± 14 µM) and the IC50 values toward CYP2C9 derived from the microfluidic assays (sulfaphenazole 0.38 ± 0.09 µM, tienilic acid 3.4 ± 0.6 µM, miconazole 0.54 ± 0.09 µM) correlated well with those determined using current standard IC50 shift assays. Most importantly, the HLM chip could distinguish between reversible (sulfaphenazole) and irreversible (tienilic acid) enzyme inhibitors in a single, automated experiment, indicating the great potential of the HLM chip to simplify current workflows used in mechanistic CYP inhibition studies. Furthermore, the results suggest that the HLM chip can also identify irreversible enzyme inhibitors, which are not necessarily resulting in a time-dependent inhibition (like suicide inhibitors), but whose inhibition mechanism is based on other kind of covalent or irreversible interaction with the CYP system. With our HLM chip approach, we could identify miconazole as such a compound that nonselectively inhibits the human CYP system with a prolonged, possibly irreversible impact in vitro, even if it is not a time-dependent inhibitor according to the IC50 shift assay.

Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent Inhibition

Most drugs are mainly metabolized by cytochrome P450 (CYP450), which can lead to drug-drug interactions (DDI). Specifically, time-dependent inhibition (TDI) of CYP3A4 isoenzyme has been associated with clinically relevant DDI. To overcome potential DDI issues, high-throughput in vitro assays were established to assess the TDI of CYP3A4 during the discovery and lead optimization phases. However, in silico machine learning models would enable an earlier and larger-scale assessment of TDI potential liabilities. For CYP inhibition, most modeling efforts have focused on highly imbalanced and small data sets. Moreover, assay variability is rarely considered, which is key to understand the model's quality and suitability for decision-making. In this work, machine learning models were built for the prediction of TDI of CYP3A4, evaluated prospectively, and compared to the variability of the experimental assay. Different modeling strategies were investigated to assess their influence on the model's performance. Through multitask learning, additional data sets were leveraged for model building, coming from public databases, in-house CYP-related assays, or other pharmaceutical companies (federated learning). Apart from the numerical prediction of inactivation rates of CYP3A4 TDI, three-class predictions were carried out, giving a negative (inactivation rate kobs < 0.01 min-1), weak positive (0.01 ≤ kobs ≤ 0.025 min-1), or positive (kobs > 0.025 min-1) output. The final multitask graph neural network model achieved misclassification rates of 8 and 7% for positive and negative TDI, respectively. Importantly, the presented deep learning-based predictions had a similar precision to the reproducibility of in vitro experiments and thus offered great opportunities for drug design, early derisk of DDI potential, and selection of experiments. To facilitate CYP inhibition modeling efforts in the public domain, the developed model was used to annotate ∼16 000 publicly available structures, and a surrogate data set is shared as Supporting Information.

Discovery of Clinical Candidate GLPG3970: A Potent and Selective Dual SIK2/SIK3 Inhibitor for the Treatment of Autoimmune and Inflammatory Diseases

The salt-inducible kinases (SIKs) SIK1, SIK2, and SIK3 belong to the adenosine monophosphate-activated protein kinase (AMPK) family of serine/threonine kinases. SIK inhibition represents a new therapeutic approach modulating pro-inflammatory and immunoregulatory pathways that holds potential for the treatment of inflammatory diseases. Here, we describe the identification of GLPG3970 (32), a first-in-class dual SIK2/SIK3 inhibitor with selectivity against SIK1 (IC50 of 282.8 nM on SIK1, 7.8 nM on SIK2 and 3.8 nM on SIK3). We outline efforts made to increase selectivity against SIK1 and improve CYP time-dependent inhibition properties through the structure-activity relationship. The dual activity of 32 in modulating the pro-inflammatory cytokine TNFα and the immunoregulatory cytokine IL-10 is demonstrated in vitro in human primary myeloid cells and human whole blood, and in vivo in mice stimulated with lipopolysaccharide. Compound 32 shows dose-dependent activity in disease-relevant mouse pharmacological models.

High-throughput cytochrome P450 loss and metabolic intermediate complex assays to aid in designing out of CYP3A inactivation

Time-dependent inactivation (TDI) of cytochrome P450 (CYP) enzymes may result in clinical drug-drug interactions (DDIs). Therefore, designing out of CYP TDI prior to advancing a compound to clinical development is highly desirable. As TDI of CYP3A is a common occurrence in small molecule drug discovery, high-throughput methods are sought to help identify the mechanism of inactivation and enable design strategies to mitigate CYP3A TDI. CYP inactivation via modification or destruction of the prosthetic heme group results in loss of the ability of the enzyme to bind carbon monoxide. Additionally, formation of a tight binding complex with the heme iron, referred to as a metabolic intermediate (MI) complex, also results in enzyme inactivation. The methods described herein provide a high-throughput means of identifying and comparing compounds for their ability to inactivate via destruction/modification of the heme via loss of the ability to bind carbon monooxide, as well as via formation of an MI complex.

An Insight into the Metabolism of 2,5-Disubstituted Monotetrazole Bearing Bisphenol Structures: Emerging Bisphenol A Structural Congeners

The non-estrogenic 2,5-disubstituted tetrazole core-bearing bisphenol structures (TbB) are being researched as emerging structural congeners of Bisphenol A, an established industrial endocrine disruptor. However, there is no understanding of TbB's adverse effects elicited via metabolic activation. Therefore, the current study aimed to investigate the metabolism of TbB ligands, with in silico results serving as a guide for in vitro studies. The Cytochrome P450 enzymes (CYP) inhibitory assay of TbB ligands on the seven human liver CYP isoforms (i.e., 1A2, 2A6, 2D6, 2C9, 2C8, 2C19, and 3A4) using human liver microsomes (HLM) revealed TbB ligand 223-3 to have a 50% inhibitory effect on all the CYP isoforms at a 10 μM concentration, except 1A2. The TbB ligand 223-10 inhibited 2B6 and 2C8, whereas the TbB ligand 223-2 inhibited only 2C9. The first-order inactivity rate constant (Kobs) studies indicated TbB ligands 223-3, 223-10 to be time-dependent (TD) inhibitors, whereas the TbB 223-2 ligand did not show such a significant effect. The 223-3 exhibited a TD inhibition for 2C9, 2C19, and 1A2 with Kobs values of 0.0748, 0.0306, and 0.0333 min-1, respectively. On the other hand, the TbB ligand 223-10 inhibited 2C9 in a TD inhibition manner with Kobs value 0.0748 min-1. However, the TbB ligand 223-2 showed no significant TD inhibition effect on the CYPs. The 223-2 ligand biotransformation pathway by in vitro studies in cryopreserved human hepatocytes suggested the clearance via glucuronidation with the predominant detection of only 223-2 derived mono glucuronide as a potential inactive metabolite. The present study demonstrated that the 223-2 ligand did not elicit any significant adverse effect via metabolic activation, thus paving the way for its in vivo drug-drug interactions (DDI) studies.

Development of In Silico Models for Predicting Potential Time-Dependent Inhibitors of Cytochrome P450 3A4

Cytochrome P450 3A4 (CYP3A4) is one of the major drug metabolizing enzymes in the human body and metabolizes ∼30-50% of clinically used drugs. Inhibition of CYP3A4 must always be considered in the development of new drugs. Time-dependent inhibition (TDI) is an important P450 inhibition type that could cause undesired drug-drug interactions. Therefore, identification of CYP3A4 TDI by a rapid convenient way is of great importance to any new drug discovery effort. Here, we report the development of in silico classification models for prediction of potential CYP3A4 time-dependent inhibitors. On the basis of the CYP3A4 TDI data set that we manually collected from literature and databases, both conventional machine learning and deep learning models were constructed. The comparisons of different sampling strategies, molecular representations, and machine-learning algorithms showed the benefits of a balanced data set and the deep-learning model featured by GraphConv. The generalization ability of the best model was tested by screening an external data set, and the prediction results were validated by biological experiments. In addition, several structural alerts that are relevant to CYP3A4 time-dependent inhibitors were identified via information gain and frequency analysis. We anticipate that our effort would be useful for identification of potential CYP3A4 time-dependent inhibitors in drug discovery and design.

Metabolic Activation of the Acrylamide Michael Acceptor Warhead in Futibatinib to an Epoxide Intermediate Engenders Covalent Inactivation of Cytochrome P450 3A

Futibatinib (FUT) is a potent inhibitor of fibroblast growth factor receptor (FGFR) 1-4 that is currently under clinical investigation for intrahepatic cholangiocarcinoma. Unlike its predecessors, FUT possesses an acrylamide warhead which enables it to bind covalently to a free cysteine residue in the FGFR kinase domain. However, it remains uninterrogated if this electrophilic α,β-unsaturated carbonyl scaffold could also directly or indirectly engender off-target covalent binding to nucleophilic centres on other cellular proteins. Here, we discovered that FUT inactivated both cytochrome P450 3A (CYP3A) isoforms with K _I, k _inact, and partition ratio of 12.5 and 51.4 µM, 0.25 and 0.06 min^-1 and ~52 and ~58 for CYP3A4 and CYP3A5, respectively. Along with its time-, concentration- and cofactor-dependent inhibitory profile, FUT also exhibited several cardinal features that were consistent with mechanism-based inactivation. Moreover, the nature of inactivation was unlikely to be pseudo-irreversible and instead arose from the covalent modification of the P450 apoprotein and/or its heme moiety due to the lack of substantial enzyme activity recovery following dialysis and chemical oxidation as well as the absence of the diagnostic Soret peak in spectral analyses. Finally, utilizing GSH trapping and high-resolution mass spectrometry, we illuminated that while the acrylamide moiety in FUT could nonenzymatically conjugate to GSH via Michael addition, it was not implicated in the covalent inactivation of CYP3A. Rather, we surmised that it likely stemmed from the metabolic activation of its acrylamide covalent warhead to a highly electrophilic epoxide intermediate that could covalently modify CYP3A and culminate in its catalytic inactivation. Significance Statement In this study, we reported for the first time the inactivation of CYP3A by FUT. Furthermore, using FUT as an exemplary targeted covalent inhibitor, our study revealed the propensity for its acrylamide Michael acceptor moiety to be metabolically activated to a highly electrophilic epoxide. Due to the growing resurgence of covalent inhibitors and the well-established toxicological ramifications associated with epoxides, we advocate that closer scrutiny be adopted when profiling the reactive metabolites of compounds possessing an α,β-unsaturated carbonyl scaffold.

Cytochrome P450 Inhibition by Antimicrobials and Their Mixtures in Rainbow Trout Liver Microsomes In Vitro

Antimicrobials are ubiquitous in the environment and can bioaccumulate in fish. In the present study, we determined the half-maximal inhibitory concentrations (IC50) of 7 environmentally abundant antimicrobials (ciprofloxacin, clarithromycin, clotrimazole, erythromycin, ketoconazole, miconazole, and sulfamethoxazole) on the cytochrome P450 (CYP) system in rainbow trout (Oncorhynchus mykiss) liver microsomes, using 7-ethoxyresorufin O-deethylation (EROD, CYP1A) and 7-benzyloxy-4-trifluoromethylcoumarin O-debenzylation (BFCOD, CYP3A) as model reactions. Apart from ciprofloxacin and sulfamethoxazole, all antimicrobials inhibited either EROD or BFCOD activities or both at concentrations <500 µM. Erythromycin was the only selective and time-dependent inhibitor of BFCOD. Compared with environmental concentrations, the IC50s of individual compounds were generally high (greater than milligrams per liter); but as mixtures, the antimicrobials resulted in strong, indicatively synergistic inhibitions of both EROD and BFCOD at submicromolar (~micrograms per liter) mixture concentrations. The cumulative inhibition of the BFCOD activity was detectable even at picomolar (~nanograms per liter) mixture concentrations and potentiated over time, likely because of the strong inhibition of CYP3A by ketoconazole (IC50 = 1.7 ± 0.3 µM) and clotrimazole (IC50 = 1.2 ± 0.2 µM). The results suggest that if taken up by fish, the mixtures of these antimicrobials may result in broad CYP inactivation and increase the bioaccumulation risk of any other xenobiotic normally cleared by the hepatic CYPs even at biologically relevant concentrations. Environ Toxicol Chem 2022;41:663-676. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Rational Design of a Two-Photon Fluorescent Probe for Human Cytochrome P450 3A and the Visualization of Mechanism-Based Inactivation

Mechanism-based inactivation (MBI) can mediate adverse reactions and hepatotoxicity from drugs, which is a result of their conversion into highly reactive metabolites catalyzed by enzymes such as cytochrome P450 3A (CYP3A). In the present research, we optimized the key interaction domain of the fluorophore with the target protein to develop a two-photon fluorescent probe for CYP3A that is involved in the metabolism of more than half of all clinical drugs. The developed BN-1 probe exhibited appropriate selectivity and sensitivity for the semi-quantitative detection and imaging of endogenous CYP3A activity in various living systems, thereby providing a high-throughput screening system enabling evaluation of MBI-associated hepatotoxicity by CYP3A. Using BN-1 as a fluorescent molecular tool facilitates the efficient discovery and characterization of CYP3A-induced MBI in natural systems.

Roles of cytochrome P450 enzymes in pharmacology and toxicology: Past, present, and future

The development of the cytochrome P450 (P450) field has been remarkable in the areas of pharmacology and toxicology, particularly in drug development. Today it is possible to use the knowledge base and relatively straightforward assays to make intelligent predictions about drug disposition prior to human dosing. Much is known about the structures, regulation, chemistry of catalysis, and the substrate and inhibitor specificity of human P450s. Many aspects of drug-drug interactions and side effects can be understood in terms of P450s. This knowledge has also been useful in pharmacy practice, as well as in the pharmaceutical industry and medical practice. However, there are still basic and practical questions to address regarding P450s and their roles in pharmacology and toxicology. Another aspect is the discovery of drugs that inhibit P450 to treat diseases.

Inhibition of Cytochrome P450 Enzymes by Drugs-Molecular Basis and Practical Applications

Drug-drug interactions are a major cause of hospitalization and deaths related to drug use. A large fraction of these is due to inhibition of enzymes involved in drug metabolism and transport, particularly cytochrome P450 (P450) enzymes. Understanding basic mechanisms of enzyme inhibition is important, particularly in terms of reversibility and the use of the appropriate parameters. In addition to drug-drug interactions, issues have involved interactions of drugs with foods and natural products related to P450 enzymes. Predicting drug-drug interactions is a major effort in drug development in the pharmaceutical industry and regulatory agencies. With appropriate in vitro experiments, it is possible to stratify clinical drug-drug interaction studies. A better understanding of drug interactions and training of physicians and pharmacists has developed. Finally, some P450s have been the targets of drugs in some cancers and other disease states.

Stepwise binding of inhibitors to human cytochrome P450 17A1 and rapid kinetics of inhibition of androgen biosynthesis

Cytochrome P450 (P450) 17A1 catalyzes the 17α-hydroxylation of progesterone and pregnenolone as well as the subsequent lyase cleavage of both products to generate androgens. However, the selective inhibition of the lyase reactions, particularly with 17α-hydroxy pregnenolone, remains a challenge for the treatment of prostate cancer. Here, we considered the mechanisms of inhibition of drugs that have been developed to inhibit P450 17A1, including ketoconazole, seviteronel, orteronel, and abiraterone, the only approved inhibitor used for prostate cancer therapy, as well as clotrimazole, known to inhibit P450 17A1. All five compounds bound to P450 17A1 in a multistep process, as observed spectrally, over a period of 10 to 30 s. However, no lags were observed for the onset of inhibition in rapid-quench experiments with any of these five compounds. Furthermore, the addition of substrate to inhibitor–P450 17A1 complexes led to an immediate formation of product, without a lag that could be attributed to conformational changes. Although abiraterone has been previously described as showing slow-onset inhibition (t_1/2 = 30 min), we observed rapid and strong inhibition. These results are in contrast to inhibitors of P450 3A4, an enzyme with a larger active site in which complete inhibition is not observed with ketoconazole and clotrimazole until the changes are completed. Overall, our results indicate that both P450 17A1 reactions—17α-hydroxylation and lyase activity—are inhibited by the initial binding of any of these inhibitors, even though subsequent conformational changes occur.

Cytochrome P450 Enzyme Inhibition and Herb-Drug Interaction Potential of Medicinal Plant Extracts Used for Management of Diabetes in Nigeria

BACKGROUND AND OBJECTIVE

The use of herbal medicines is common in Africa, and patients often use a combination of herbs and drugs. Concurrent herbal and pharmaceuticals treatments can cause adverse effects through herb-drug interactions (HDI). This study evaluated the potential risk of HDI for five medicinal plants, Vernonia amygdalina, Ocimum gratissimum, Moringa oleifera, Azadirachta indica, and Picralima nitida, using in vitro assays. Patients with diabetes and some other disease conditions commonly use these medicinal plants in Nigeria, and little is known regarding their potential for drug interaction, despite their enormous use.

METHODS

Crude extracts of the medicinal plants were evaluated for reversible and time-dependent inhibition (TDI) activity of six cytochrome P450 (CYP) enzymes using pooled human liver microsomes and cocktail probe-based assays. Enzyme activity was determined by quantifying marker metabolites' formation using liquid chromatography-mass spectrometry/mass spectrometry. The drug interaction potential was predicted for each herbal extract using the in vitro half-maximal inhibitory concentration (IC₅₀) values and the percentage yield.

RESULTS

O. gratissimum methanol extracts reversibly inhibited CYP 1A2, 2C8, 2C9 and 2C19 enzymes (IC₅₀: 6.21 µg/ml, 2.96 µg/ml, 3.33 µg/ml and 1.37 µg/ml, respectively). Additionally, V. amygdalina methanol extract inhibited CYP2C8 activity (IC₅₀: 5.71 µg/ml); P. nitida methanol and aqueous extracts inhibited CYP2D6 activity (IC₅₀: 1.99 µg/ml and 2.36 µg/ml, respectively) while A. indica methanol extract inhibited CYP 3A4/5, 2C8 and 2C9 activity (IC₅₀: 7.31 µg/ml, 9.97 µg/ml and 9.20 µg/ml, respectively). The extracts showed a potential for TDI of the enzymes when incubated at 200 µg/ml; V. amygdalina and A. indica methanol extracts exhibited TDI potential for all the major CYPs.

CONCLUSIONS

The medicinal plants inhibited CYP activity in vitro, with the potential to cause in vivo HDI. Clinical risk assessment and proactive monitoring are recommended for patients who use these medicinal plants concurrently with drugs that are cleared through CYP metabolism.

Cytochrome P450 3A Time-Dependent Inhibition Assays Are Too Sensitive for Identification of Drugs Causing Clinically Significant Drug-Drug Interactions: A Comparison of Human Liver Microsomes and Hepatocytes and Definition of Boundaries for Inactivation Rate Constants

Time-dependent inhibition (TDI) of CYP3A is an important mechanism underlying numerous drug-drug interactions (DDIs), and assays to measure this are done to support early drug research efforts. However, measuring TDI of CYP3A in human liver microsomes (HLMs) frequently yields overestimations of clinical DDIs and thus can lead to the erroneous elimination of many viable drug candidates from further development. In this investigation, 50 drugs were evaluated for TDI in HLMs and suspended human hepatocytes (HHEPs) to define appropriate boundary lines for the TDI parameter rate constant for inhibition (k_obs) at a concentration of 30 µM. In HLMs, a k_obs value of 0.002 minute^-1 was statistically distinguishable from control; however, many drugs show k_obs greater than this but do not cause DDI. A boundary line defined by the drug with the lowest k_obs that causes a DDI (diltiazem) was established at 0.01 minute^-1 Even with this boundary, of the 33 drugs above this value, only 61% cause a DDI (true positive rate). A corresponding analysis was done using HHEPs; k_obs of 0.0015 minute^-1 was statistically distinguishable from control, and the boundary was established at 0.006 minute^-1 Values of k_obs in HHEPs were almost always lower than those in HLMs. These findings offer a practical guide to the use of TDI data for CYP3A in early drug-discovery research. SIGNIFICANCE STATEMENT: Time-dependent inhibition of CYP3A is responsible for many drug interactions. In vitro assays are employed in early drug research to identify and remove CYP3A time-dependent inhibitors from further consideration. This analysis demonstrates suitable boundaries for inactivation rates to better delineate drug candidates for their potential to cause clinically significant drug interactions.

Discovery of LYS006, a Potent and Highly Selective Inhibitor of Leukotriene A4 Hydrolase

The cytosolic metalloenzyme leukotriene A4 hydrolase (LTA4H) is the final and rate-limiting enzyme in the biosynthesis of pro-inflammatory leukotriene B4 (LTB4). Preclinical studies have validated this enzyme as an attractive drug target in chronic inflammatory diseases. Despite several attempts, no LTA4H inhibitor has reached the market, yet. Herein, we disclose the discovery and preclinical profile of LYS006, a highly potent and selective LTA4H inhibitor. A focused fragment screen identified hits that could be cocrystallized with LTA4H and inspired a fragment merging. Further optimization led to chiral amino acids and ultimately to LYS006, a picomolar LTA4H inhibitor with exquisite whole blood potency and long-lasting pharmacodynamic effects. Due to its high selectivity and its ability to fully suppress LTB4 generation at low exposures in vivo, LYS006 has the potential for a best-in-class LTA4H inhibitor and is currently investigated in phase II clinical trials in inflammatory acne, hidradenitis suppurativa, ulcerative colitis, and NASH.

Modernizing Clinical Trial Eligibility Criteria: Recommendations of the ASCO-Friends of Cancer Research Washout Period and Concomitant Medication Work Group

PURPOSE

Washout periods and concomitant medication exclusions are common in cancer clinical trial protocols. These exclusion criteria are often applied inconsistently and without evidence to justify their use. The authors sought to determine how washout period and concomitant medication allowances can be broadened to speed trial enrollment and improve the generalizability of trial data to a larger oncology practice population without compromising the safety of trial participants.

EXPERIMENTAL DESIGN

A multistakeholder working group was convened to define problems associated with excessively long washout periods and exclusion of patients due to concomitant medications. The group performed a literature search and evaluated study data from the Pancreatic Cancer Action Network (PanCAN), Emory University School of Medicine (Atlanta, GA), and the FDA to understand recent approaches to these eligibility criteria. The group convened to develop consensus recommendations for broadened eligibility criteria.

RESULTS

The data analysis found that exclusion criteria based on washout periods and concomitant medications are frequently inconsistent and lack scientific rationale. Scientific rationale for appropriate eligibility criteria are presented in the article; for washout periods, rationale is presented by treatment type.

CONCLUSIONS

Arbitrary or blanket washout and concomitant medication exclusions should be eliminated. Where there is evidence to support them, clinically relevant washout periods and concomitant medication-related eligibility criteria may be included.See related commentary by Giantonio, p. 2369.

Kinetics of cytochrome P450 3A4 inhibition by heterocyclic drugs defines a general sequential multistep binding process

Cytochrome P450 (P450) 3A4 is the enzyme most involved in the metabolism of drugs and can also oxidize numerous steroids. This enzyme is also involved in one-half of pharmacokinetic drug-drug interactions, but details of the exact mechanisms of P450 3A4 inhibition are still unclear in many cases. Ketoconazole, clotrimazole, ritonavir, indinavir, and itraconazole are strong inhibitors; analysis of the kinetics of reversal of inhibition with the model substrate 7-benzoyl quinoline showed lag phases in several cases, consistent with multiple structures of P450 3A4 inhibitor complexes. Lags in the onset of inhibition were observed when inhibitors were added to P450 3A4 in 7-benzoyl quinoline O-debenzylation reactions, and similar patterns were observed for inhibition of testosterone 6β-hydroxylation by ritonavir and indinavir. Upon mixing with inhibitors, P450 3A4 showed rapid binding as judged by a spectral shift with at least partial high-spin iron character, followed by a slower conversion to a low-spin iron-nitrogen complex. The changes were best described by two intermediate complexes, one being a partial high-spin form and the second another intermediate, with half-lives of seconds. The kinetics could be modeled in a system involving initial loose binding of inhibitor, followed by a slow step leading to a tighter complex on a multisecond time scale. Although some more complex possibilities cannot be dismissed, these results describe a system in which conformationally distinct forms of P450 3A4 bind inhibitors rapidly and two distinct P450-inhibitor complexes exist en route to the final enzyme-inhibitor complex with full inhibitory activity.

Reversible Mechanisms of Enzyme Inhibition and Resulting Clinical Significance

Inhibition of a drug-metabolizing enzyme by the reversible interaction of a drug with the enzyme, thus decreasing the metabolism of another drug, is a major cause of clinically significant drug-drug interactions. This chapter defines the four reversible mechanisms of inhibition exhibited by drugs: competitive, noncompetitive, uncompetitive, and mixed competitive/noncompetitive. An in vitro procedure to determine the potential of a drug to be a reversible inhibitor is also provided. Finally, a number of examples of clinically significant drug-drug interactions resulting from reversible inhibition are described.

A history of the roles of cytochrome P450 enzymes in the toxicity of drugs

The history of drug metabolism began in the 19th Century and developed slowly. In the mid-20th Century the relationship between drug metabolism and toxicity became appreciated, and the roles of cytochrome P450 (P450) enzymes began to be defined in the 1960s. Today we understand much about the metabolism of drugs and many aspects of safety assessment in the context of a relatively small number of human P450s. P450s affect drug toxicity mainly by either reducing exposure to the parent molecule or, in some cases, by converting the drug into a toxic entity. Some of the factors involved are enzyme induction, enzyme inhibition (both reversible and irreversible), and pharmacogenetics. Issues related to drug toxicity include drug-drug interactions, drug-food interactions, and the roles of chemical moieties of drug candidates in drug discovery and development. The maturation of the field of P450 and drug toxicity has been facilitated by advances in analytical chemistry, computational capability, biochemistry and enzymology, and molecular and cell biology. Problems still arise with P450s and drug toxicity in drug discovery and development, and in the pharmaceutical industry the interaction of scientists in medicinal chemistry, drug metabolism, and safety assessment is critical for success.

Enzyme Kinetics, Pharmacokinetics, and Inhibition of Aldehyde Oxidase

Aldehyde oxidase (AO) has emerged as an important drug metabolizing enzyme over the last decade. Several compounds have failed in the clinic because the clearance or toxicity was underestimated by preclinical species. Human AO is much more active than rodent AO, and dogs do not have functional AO. Metabolic products from AO-catalyzed oxidation are generally nonreactive and often they have much lower solubility. AO metabolism is not limited to oxidation as AO can also catalyze reduction of oxygen and nitrite. Reduction of oxygen leads to the reactive oxygen species (ROS) superoxide radical anion and hydrogen peroxide. Reduction of nitrite leads to the formation of nitric oxide with potential pharmacological implications. AO is also reported to catalyze the reductive metabolism of nitro-compounds, N-oxides, sulfoxides, isoxazoles, isothiazoles, nitrite, and hydroxamic acids. These reductive transformations may cause toxicity due to the formation of reactive metabolites. Moreover, the inhibition kinetics are complex, and multiple probe substrates should be used when assessing the potential for DDIs. Finally, AO appears to be amenable to computational predictions of both regioselectivity and rates of reaction, which holds promise for virtual screening.

Mechanism-based inactivation of cytochrome P450 2D6 by Notopterol

Notopterol (NOT) is a major bioactive ingredient extracted from the rhizomes of either Notopterygium incisum Ting ex H. T. Chang or N. forbesii Boiss (Qianghuo in Chinese), a botanical drug that was adopted as a traditional Chinese medicine. NOT is suggested to show analgesic and anti-inflammatory effects in clinical practice. The inhibitory effects of NOT on human cytochrome P450 enzymes were investigated in the present study. Our results indicate that NOT inhibited the activity of CYP2D6 in a time-, concentration- and NADPH-dependent manner. The values of K_I and k_inact were 10.8 μM and 0.62 min^-1, respectively. The calculated k_obs at 10 μM was 0.29 min^-1, above the 0.02 min^-1 risk level. After incubation with NOT at 10 μM for 9 min, approximately 92% of CYP2D6 activity was inhibited. Such loss of enzyme activity was not restored through dialysis, which indicates that the observed enzyme inhibition was irreversible. Partition ratio of the inactivation was approximately 29. Quinidine, a competitive CYP2D6 inhibitor, demonstrated protection on enzymes against the NOT-induced inactivation, but such protection was not found in incubation systems fortified with glutathione or catalase/superoxide dismutase. Additionally, CYP3A4 was observed to function as an enzyme mainly involved in the biotransformation of NOT. Taken together, these findings indicate that NOT served as a mechanism-based inactivator of CYP2D6, meanwhile, those observed effects may induce the latent drug-drug interactions. The metabolic activation of NOT may be the key to trigger the inactivation of the enzyme.

Time-dependent enzyme inactivation: Numerical analyses of in vitro data and prediction of drug-drug interactions

Cytochrome P450 (CYP) enzyme kinetics often do not conform to Michaelis-Menten assumptions, and time-dependent inactivation (TDI) of CYPs displays complexities such as multiple substrate binding, partial inactivation, quasi-irreversible inactivation, and sequential metabolism. Additionally, in vitro experimental issues such as lipid partitioning, enzyme concentrations, and inactivator depletion can further complicate the parameterization of in vitro TDI. The traditional replot method used to analyze in vitro TDI datasets is unable to handle complexities in CYP kinetics, and numerical approaches using ordinary differential equations of the kinetic schemes offer several advantages. Improvement in the parameterization of CYP in vitro kinetics has the potential to improve prediction of clinical drug-drug interactions (DDIs). This manuscript discusses various complexities in TDI kinetics of CYPs, and numerical approaches to model these complexities. The extrapolation of CYP in vitro TDI parameters to predict in vivo DDIs with static and dynamic modeling is discussed, along with a discussion on current gaps in knowledge and future directions to improve the prediction of DDI with in vitro data for CYP catalyzed drug metabolism.

Critical Impact of Drug-Drug Interactions via Intestinal CYP3A in the Risk Assessment of Weak Perpetrators Using Physiologically Based Pharmacokinetic Models

A great deal of effort has been being made to improve the accuracy of the prediction of drug-drug interactions (DDIs). In this study, we addressed CYP3A-mediated weak DDIs, in which a relatively high false prediction rate was pointed out. We selected 17 orally administered drugs that have been reported to alter area under the curve (AUC) of midazolam, a typical CYP3A substrate, 0.84-1.47 times. For weak CYP3A perpetrators, the predicted AUC ratio mainly depends on intestinal DDIs rather than hepatic DDIs because the drug concentration in the enterocytes is higher. Thus, DDI prediction using simulated concentration-time profiles in each segment of the digestive tract was made by physiologically based pharmacokinetic (PBPK) modeling software GastroPlus. Although mechanistic static models tend to overestimate the risk to ensure the safety of patients, some underestimation is reported about PBPK modeling. Our in vitro studies revealed that 16 out of 17 tested drugs exhibited time-dependent inhibition (TDI) of CYP3A, and the subsequent DDI simulation that ignored these TDIs provided false-negative results. This is considered to be the cause of past underestimation. Inclusion of the DDI parameters of all the known DDI mechanisms, reversible inhibition, TDI, and induction, which have opposite effects on midazolam AUC, to PBPK model was successful in improving predictability of the DDI without increasing false-negative prediction as trade-off. This comprehensive model-based analysis suggests the importance of the intestine in assessing weak DDIs via CYP3A and the usefulness of PBPK in predicting intestinal DDIs. SIGNIFICANCE STATEMENT: Although drug-drug interaction (DDI) prediction has been extensively performed previously, the accuracy of prediction for weak interactions via CYP3A has not been thoroughly investigated. In this study, we simulate DDIs considering drug concentration-time profile in the enterocytes and discuss the importance and the predictability of intestinal DDIs about weak CYP3A perpetrators.

Advances in covalent kinase inhibitors

This comprehensive review details recent advances, challenges and innovations in covalent kinase inhibition within a 10 year period (2007–2018).

Quantitative evaluation of hepatic and intestinal induction of CYP3A in clinical practice

This is the first report quantitatively evaluating the clinical induction of CYP3A in the liver and the intestine.To evaluate hepatic induction, we collected literature data on endogenous biomarkers of hepatic CYP3A induction which we then used to calculate the fold-induction (inducer-mediated change in biomarker level). Literature data on decreases in the area under the curve (AUC) of alfentanil, a CYP3A substrate, caused by CYP3A inducers were also collected. We used the hepatic intrinsic clearance of alfentanil to calculate the hepatic induction ratio (inducer-mediated change in intrinsic clearance). For intestinal induction, the intestinal bioavailability (F_g) of alfentanil was used to calculate the intestinal induction ratio. We determined in vivo maximum induction (E_max) and the average unbound plasma concentration (C_av,u) required for half the maximum induction (EC₅₀) for inducers using an E_max model analysis.In our results, fold-induction was comparable to the induction ratio at several inducer concentrations, and almost the maximum induction was achieved by a therapeutic dose. Induction ratios in the intestine were similar to the liver.Our findings suggest that, by knowing only hepatic induction ratios for common inducers, we can quantitatively predict the decreases in the AUC of substrates by CYP3A induction.

Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates

A recent publication from the Innovation and Quality Consortium Induction Working Group collated a large clinical data set with the goal of evaluating the accuracy of drug-drug interaction (DDI) prediction from in vitro data. Somewhat surprisingly, comparison across studies of the mean- or median-reported area under the curve ratio showed appreciable variability in the magnitude of outcome. This commentary explores the possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression, and the number of subjects contribute. Since variability in perpetrator pharmacokinetics (PK) could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5-7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors and/or inactivators based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in area under the curve over time is warranted. With selective CYP3A substrates, the net effect was often inhibition, whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives, which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction, such as applying biomarkers and physiologically based pharmacokinetic modeling (PBPK), are also considered. SIGNIFICANCE STATEMENT: The goal of this commentary is to stimulate discussion on whether there are opportunities to optimize clinical drug-drug interaction study design. The overall aim is to reduce, understand and contextualize the variability observed in the magnitude of induction across reported clinical studies. A large clinical CYP3A induction dataset was collected and further analyzed to identify trends and gaps. Reporting individual victim PK data, characterizing perpetrator PK and including additional PK assessments for mixed-mechanism perpetrators may provide insights into how these factors impact differences observed in clinical outcomes. The potential utility of biomarkers and PBPK modeling are discussed in considering future directions.

Design, Synthesis, and Preclinical Efficacy of Novel Nonretinoid Antagonists of Retinol-Binding Protein 4 in the Mouse Model of Hepatic Steatosis

Retinol-binding protein 4 (RBP4) serves as a transporter for all- trans-retinol (1) in the blood, and it has been proposed to act as an adipokine. Elevated plasma levels of the protein have been linked to diabetes, obesity, cardiovascular diseases, and nonalcoholic fatty liver disease (NAFLD). Recently, adipocyte-specific overexpression of RBP4 was reported to cause hepatic steatosis in mice. We previously identified an orally bioavailable RBP4 antagonist that significantly lowered RBP4 serum levels in Abca4^-/- knockout mice with concomitant normalization of complement system protein expression and reduction of bisretinoid formation within the retinal pigment epithelium. We describe herein the discovery of novel RBP4 antagonists 48 and 59, which reduce serum RBP4 levels by >80% in mice upon acute oral dosing. Furthermore, 59 demonstrated efficacy in the transgenic adi-hRBP4 murine model of hepatic steatosis, suggesting that RBP4 antagonists may also have therapeutic utility for the treatment of NAFLD.

Design and Discovery of N-(3-(2-(2-Hydroxyethoxy)-6-morpholinopyridin-4-yl)-4-methylphenyl)-2-(trifluoromethyl)isonicotinamide, a Selective, Efficacious, and Well-Tolerated RAF Inhibitor Targeting RAS Mutant Cancers: The Path to the Clinic

Direct pharmacological inhibition of RAS has remained elusive, and efforts to target CRAF have been challenging due to the complex nature of RAF signaling, downstream of activated RAS, and the poor overall kinase selectivity of putative RAF inhibitors. Herein, we describe 15 (LXH254, Aversa, R.; et al. Int. Patent WO2014151616A1, 2014), a selective B/C RAF inhibitor, which was developed by focusing on drug-like properties and selectivity. Our previous tool compound, 3 (RAF709; Nishiguchi, G. A.; et al. J. Med. Chem. 2017, 60, 4969), was potent, selective, efficacious, and well tolerated in preclinical models, but the high human intrinsic clearance precluded further development and prompted further investigation of close analogues. A structure-based approach led to a pyridine series with an alcohol side chain that could interact with the DFG loop and significantly improved cell potency. Further mitigation of human intrinsic clearance and time-dependent inhibition led to the discovery of 15. Due to its excellent properties, it was progressed through toxicology studies and is being tested in phase 1 clinical trials.

High throughput screening of complex biological samples with mass spectrometry – from bulk measurements to single cell analysis

We review the state of the art in HTS using mass spectrometry with minimal sample preparation from complex biological matrices. We focus on industrial and biotechnological applications.

Physiologically Based Pharmacokinetic Modeling of Fimasartan, Amlodipine, and Hydrochlorothiazide for the Investigation of Drug-Drug Interaction Potentials

PURPOSE

To build a physiologically based pharmacokinetic (PBPK) model for fimasartan, amlodipine, and hydrochlorothiazide, and to investigate the drug-drug interaction (DDI) potentials.

METHODS

The PBPK model of each drug was developed using Simcyp software (Version 15.0), based on the information obtained from literature sources and in vitro studies. The predictive performance of the model was assessed by comparing the predicted PK profiles and parameters with the observed data collected from healthy subjects after multiple oral doses of fimasartan, amlodipine, and hydrochlorothiazide. The DDI potentials after co-administration of three drugs were simulated using the final model.

RESULTS

The predicted-to-observed ratios of all the pharmacokinetic parameters met the acceptance criterion. The PBPK model predicted no significant DDI when fimasartan was co-administered with amlodipine or hydrochlorothiazide, which is consistent with the observed clinical data. In the simulation of DDI at steady-state after co-administration of three drugs, the model predicted that fimasartan exposure would be increased by ~24.5%, while no changes were expected for the exposures of amlodipine and hydrochlorothiazide.

CONCLUSIONS

The developed PBPK model adequately predicted the pharmacokinetics of fimasartan, amlodipine, and hydrochlorothiazide, suggesting that the model can be used to further investigate the DDI potential of each drug.

Kinetic mechanism of time-dependent inhibition of CYP2D6 by 3,4-methylenedioxymethamphetamine (MDMA): Functional heterogeneity of the enzyme and the reversibility of its inactivation

We investigate the mechanism of time-dependent inhibition (TDI) of human cytochrome P450 2D6 (CYP2D6) by 3,4-methylenedioxymethamphetamine (MDMA, ecstasy), one of the most widespread recreational drugs of abuse. In an effort to unravel the kinetic mechanism of the formation of metabolic inhibitory complex (MIC) of CYP2D6 with MDMA-derived carbene we carried out a series of spectrophotometric studies paralleled with registration of the kinetics of time-dependent inhibition (TDI) in CYP2D6-incorporated proteoliposomes. The high amplitude of spectral signal in this system allowed us to characterize the spectral properties of the formed MIC in details and obtain an accurate spectral signature of MIC formation. This information was then used in the studies with CYP2D6-containing microsomes of insect cells (CYP2D6 Supersomes™). Our results demonstrate that in both systems the formation of the ferrous carbene-derived MIC is relatively slow, reversible and is not associated with the accumulation of the ferric carbene intermediate, as takes place in the case of CYP3A4 and podophylotoxin. Furthermore, the limited amplitude of MIC formation suggests that only a fraction (∼50%) of spectrally detectable CYP2D6 in both proteoliposomes and Supersomes participates in the formation of MIC and is therefore involved in the MDMA metabolism. This observation reveals yet another example of a cytochrome P450 that exhibits persistent functional heterogeneity of its population in microsomal membranes. Our study provides a solid methodological background for further mechanistic studies of MIC formation in human liver microsomes and demonstrates that the potency and physiological relevance of MDMA-dependent TDI of CYP2D6 may be overestimated.

A strategy for early-risk predictions of clinical drug-drug interactions involving the GastroPlusTM DDI module for time-dependent CYP inhibitors

1. A set of reference compounds for time-dependent inhibition (TDI) of cytochrome P450 with available literature data for k_inact and K_I was used to predict clinical implications using the GastroPlus^TM software. Comparisons were made to in vivo literature interaction data. 2. The predicted AUC ratios (AUC_+inhibitor/AUC_control) could be compared with the observed ratios from literature for all compounds with detailed information about in vivo administration, pharmacokinetics and in vivo interactions (N = 21). For this dataset, the difference between predicted and observed AUC ratios for interactions with midazolam was within twofold for all compounds except one (telaprevir, for which non-CYP-mediated metabolism likely plays a role after multiple dosing). 3. The sensitivity, specificity and accuracy of the GastroPlus^TM predictions using a binary classification as no-to-weak interaction versus moderate-to-strong interaction for all compounds with available in vivo interaction data, were 80%, 82% and 81%, respectively (N = 31). 4. As a result of our evaluations of the DDI module in GastroPlus^TM, we have implemented an early TDI risk assessment decision tree for our drug discovery projects involving in vitro screening and early GastroPlus^TM predictions. Shifted IC₅₀ values are determined and k_inact/K_I estimated (by using a regression line established with in house-shifted IC₅₀ values and literature k_inact/K_I ratios), followed by GastroPlus^TM predictions.

Progress in Prediction and Interpretation of Clinically Relevant Metabolic Drug-Drug Interactions: a Minireview Illustrating Recent Developments and Current Opportunities

PURPOSE OF REVIEW

This review gives a perspective on the current "state of the art" in metabolic drug-drug interaction (DDI) prediction. We highlight areas of successful prediction and illustrate progress in areas where limits in scientific knowledge or technologies prevent us from having full confidence.

RECENT FINDINGS

Several examples of success are highlighted. Work done for bitopertin shows how in vitro and clinical data can be integrated to give a model-based understanding of pharmacokinetics and drug interactions. The use of interpolative predictions to derive explicit dosage recommendations for untested DDIs is discussed using the example of ibrutinib, and the use of DDI predictions in lieu of clinical studies in new drug application packages is exemplified with eliglustat and alectinib. Alectinib is also an interesting case where dose adjustment is unnecessary as the activity of a major metabolite compensates sufficiently for changes in parent drug exposure. Examples where "unusual" cytochrome P450 (CYP) and non-CYP enzymes are responsible for metabolic clearance have shown the importance of continuing to develop our repertoire of in vitro regents and techniques. The time-dependent inhibition assay using human hepatocytes suspended in full plasma allowed improved DDI predictions, illustrating the importance of continued in vitro assay development and refinement.

SUMMARY

During the past 10 years, a highly mechanistic understanding has been developed in the area of CYP-mediated metabolic DDIs enabling the prediction of clinical outcome based on preclinical studies. The combination of good quality in vitro data and physiologically based pharmacokinetic modeling may now be used to evaluate DDI risk prospectively and are increasingly accepted in lieu of dedicated clinical studies.

A physiologically based pharmacokinetic modeling approach to predict drug-drug interactions between domperidone and inhibitors of CYP3A4

Domperidone is a dopamine receptor antagonist and a substrate of CYP3A4, hence there is a potential for CYP3A inhibition-based drug-drug interactions (DDI). A physiologically based pharmacokinetic model was developed to describe DDIs between domperidone and three different inhibitors of CYP3A4. Simcyp V13.1 was used to simulate human domperidone pharmacokinetics and DDIs. Inputs included domperidone chemical and physical properties (LogP, pKa, etc.), in vitro human liver microsomal data and pharmacokinetic parameters from single-dose intravenous clinical studies in healthy participants. The simulated mean maximum domperidone plasma concentration and AUC after single- and multiple-oral doses under diverse conditions were within 1.1-1.4 fold of the observed values. The simulated intestinal availability, hepatic availability and the fraction absorbed were 0.45 ± 0.14, 0.31 ± 0.10 and 0.89 ± 0.11, respectively, and comparable to observed in vivo values. The simulated ratios of AUC and C(max) in the presence of ketoconazole, erythromycin or itraconazole to baseline were consistent with the observed ratios. Simulated ketoconazole, erythromycin, itraconazole and C(max,ss) and AUC(ss) were within 1.5-fold of the observed values.

A Perspective on the Kinetics of Covalent and Irreversible Inhibition

The clinical and commercial success of covalent drugs has prompted a renewed and more deliberate pursuit of covalent and irreversible mechanisms within drug discovery. A covalent mechanism can produce potent inhibition in a biochemical, cellular, or in vivo setting. In many cases, teams choose to focus on the consequences of the covalent event, defined by an IC₅₀ value. In a biochemical assay, the IC₅₀ may simply reflect the target protein concentration in the assay. What has received less attention is the importance of the rate of covalent modification, defined by k_inact/K_I. The k_inact/K_I is a rate constant describing the efficiency of covalent bond formation resulting from the potency (K_I) of the first reversible binding event and the maximum potential rate (k_inact) of inactivation. In this perspective, it is proposed that the k_inact/K_I should be employed as a critical parameter to identify covalent inhibitors, interpret structure-activity relationships (SARs), translate activity from biochemical assays to the cell, and more accurately define selectivity. It is also proposed that a physiologically relevant k_inact/K_I and an (unbound) AUC generated from a pharmacokinetic profile reflecting direct exposure of the inhibitor to the target protein are two critical determinants of in vivo covalent occupancy. A simple equation is presented to define this relationship and improve the interpretation of covalent and irreversible kinetics.