Cynomolgus monkeys are widely utilized for understanding and predicting human pharmacokinetics (PK) of OATP1B substrates due to their close evolutionary relationship with humans and the high degree of transporter protein homology similarities. We note that some OATP1B tool substrates (e.g., cerivastatin and repaglinide) have steady state volume of distribution (VSS) values in monkeys that are larger than corresponding VSS values reported for humans. To understand VSS and tissue biodistribution of substrate drugs in monkeys, we have performed a series of monkey PK and tissue distribution studies, as well as data analysis with physiologically based pharmacokinetic (PBPK) modeling for several OATP1B substrates (i.e., cerivastatin, repaglinide, glyburide, rosuvastatin, and valsartan). We find that there are unexpectedly high accumulations of these compounds in monkey intestines potentially involving transporter mediated active uptake, which contributed to the higher-than-expected VSS values.

Cisplatin is a cornerstone chemotherapeutic agent frequently associated with dose-limiting ototoxicity. Increasing evidence suggests that immune-mediated mechanisms may influence interindividual susceptibility to this adverse effect; however, the role of inherited immune traits remains poorly understood. This study aimed to evaluate the causal relationship between 33 inherited immune traits and cisplatin-induced ototoxicity using Mendelian randomization (MR), and to identify age-stratified susceptibility markers in pediatric and adult cancer survivors. MR was used to assess the causal effects of genetically predicted immune traits on cisplatin-induced ototoxicity. Single-nucleotide polymorphisms associated with immune traits were selected from large-scale genome-wide association study datasets. The primary analysis used the inverse variance weighted method with MR-Egger, weighted median, weighted mode, and MR-PRESSO as the sensitivity approaches. Bidirectional MR and sensitivity analyses were conducted to assess robustness and rule out reverse causation. Bonferroni correction was employed to minimize potential false-positive findings (P < 0.05/165 ≈ 0.0003). Transforming Growth Factor-beta principal component analysis (TGF-β PCA) showed an age-stratified effect: it was associated with increased risk of hearing loss in pediatric patients (OR (95

In early 2020, severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) infections leading to COVID-19 disease reached a global level leading to the World Health Organization (WHO) declaration of a pandemic. Scientists around the globe rapidly responded to try and discover novel therapeutics and repurpose extant drugs to treat the disease. This work describes the preclinical discovery efforts that led to the invention of PF-07321332 (nirmatrelvir, 14), a potent and orally active inhibitor of the SARS CoV-2 main protease (Mpro) enzyme. At the outset we focused on modifying PF-00835231 (1) discovered in 2004 as a potent inhibitor of the SARS CoV-1 Mpro with poor systemic exposure. Our effort was focused on modifying 1 with the goal of engineering in oral bioavailability by design, while maintaining cellular potency and low metabolic clearance. Modifications of 1 ultimately led to the invention of nirmatrelvir 14, the Mpro inhibitor component in PAXLOVID.

It remains unclear whether phthalates are associated with gallstones and whether the associations of phthalate alternatives with gallstones are different from traditional phthalates. In this study, 1735 participants from the NHANES 2017–2018 were included and their urine was used to detect phthalate metabolites. We used logistic and restricted cubic spline regressions to assess individual associations and dose–response relationships between phthalate metabolites and gallstones, quantile g-computation and Bayesian kernel machine regression to assess mixed associations of phthalate metabolites with gallstones, and subgroup analyses to explore potential effect modifiers. We observed that individual associations of cyclohexane-1,2-dicarboxylic acid-mono(carboxyoctyl) ester phthalate (MCOCHP) (OR: 1.423, 95

The severe acute respiratory syndrome coronavirus-2 main protease inhibitor PF-07321332 (nirmatrelvir), in combination with ritonavir (Paxlovid), has been approved by the US Food and Drug Administration as an oral treatment option for coronavirus disease 2019 patients. In this perspective, we share the expediated absorption, distribution, metabolism, and excretion strategies, which were incorporated as part of discovery efforts, to design orally active severe acute respiratory syndrome coronavirus-2 main protease inhibitors. PF-07321332 (nirmatrelvir) emerged as a potential oral clinical candidate within ∼ 6 months from the time discovery efforts were first initiated. The review also delves into a discussion around the successful use of quantitative fluorine-19 nuclear magnetic resonance spectroscopy in the characterization of the human mass balance and excretion pathways of nirmatrelvir. Human absorption, distribution, metabolism, and excretion data that emerged from the fluorine-19 nuclear magnetic resonance study were used to support the Emergency Use Authorization and new drug application filing, which was accepted by regulatory agencies worldwide. Efficient operational and technical strategies, incorporating the elements of speed without sacrificing data quality, which were crucial to the success of the program, are highlighted. SIGNIFICANCE STATEMENT: This perspective discusses the expedited absorption, distribution, metabolism, and excretion efforts utilized in the discovery and development of the orally active severe acute respiratory syndrome coronavirus-2 main protease inhibitor nirmatrelvir, which in combination with the cytochrome P450 3A inhibitor ritonavir (Paxlovid), is used in the oral treatment of COVID-19. Paxlovid was granted an Emergency Use Authorization by global regulatory agencies in less than 2 years from the initiation of the discovery program and has since been fully approved by the US Food and Drug Administration.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) main protease (Mpro) inhibitor PF-07321332 (nirmatrelvir), in combination with ritonavir (PaxlovidTM), has been approved by the United States Food and Drug Administration (FDA) as an oral treatment option for coronavirus disease 2019 (COVID-19) patients. In this perspective, we share the expediated absorption, distribution, metabolism, and excretion (ADME) strategies, which were incorporated as part of discovery efforts, to design orally active SARS-CoV-2 Mpro inhibitors. PF-07321332 (nirmatrelvir) emerged as a potential oral clinical candidate within ∼ six months from the time, discovery efforts were first initiated. The review also delves into a discussion around the successful use of quantitative fluorine-19 nuclear magnetic resonance (19F-NMR) spectroscopy in the characterization of the human mass balance and excretion pathways of nirmatrelvir. Human ADME data that emerged from the 19F-NMR study was utilized to support the Emergency Use Authorization (EUA) and new drug application filing, which was accepted by regulatory agencies worldwide. Efficient operational and technical strategies, incorporating the elements of speed without sacrificing data quality, which were crucial to the success of the program, are highlighted.

Acidic drugs generally have small steady-state volumes of distribution (Vss) around 0.1-0.25 L/kg, due to high binding to serum albumin and low binding to phospholipids in tissues. Acids can reach pharmacological targets in tissues despite small Vss. Enterohepatic recirculation (EHR) of parent drug or reversible acyl glucuronide can increase the Vss of acids. However, rational design to incorporate EHR as a mechanism to increase Vss remains challenging because of the complexity of EHR and lack of reliable predictive tools. Uptake transporters can increase the Vss of acidic drugs by increasing the liver drug concentration and can facilitate EHR through enhancing biliary elimination and glucuronide formation. Half-life extension of acids mainly relies on reducing clearance or using modified release formulations rather than modulating Vss.

The worldwide outbreak of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic. Alongside vaccines, antiviral therapeutics are an important part of the healthcare response to countering the ongoing threat presented by COVID-19. Here, we report the discovery and characterization of PF-07321332, an orally bioavailable SARS-CoV-2 main protease inhibitor with in vitro pan-human coronavirus antiviral activity and excellent off-target selectivity and in vivo safety profiles. PF-07321332 has demonstrated oral activity in a mouse-adapted SARS-CoV-2 model and has achieved oral plasma concentrations exceeding the in vitro antiviral cell potency in a phase 1 clinical trial in healthy human participants.

Hepatocytes are one of the most physiologically relevant in vitro liver systems for human translation of clearance and drug-drug interactions (DDI). However, the cell membranes of hepatocytes can limit the entry of certain compounds into the cells for metabolism and DDI. Passive permeability through hepatocytes can be different in vitro and in vivo, which complicates the human translation. Permeabilized hepatocytes offer a useful tool to probe mechanistic understanding of permeability-limited metabolism and DDI. Incubation with saponin of 0.01

PAXLOVIDTM is a combination medicine of nirmatrelvir tablets co-packaged with ritonavir tablets. Nirmatrelvir is a peptidomimetic inhibitor of SARS-CoV2 main protease (Mpro), developed for the treatment of COVID19. Ritonavir is co-administered as a pharmacokinetics (PK) enhancer to inhibit CYP3A mediated metabolism increasing exposures of nirmatrelvir. In the solid form, nirmatrelvir exists in a stable single conformational state (ANTI form). However, nirmatrelvir exhibits atropisomerism in solution whereby upon dissolution the ANTI rotational isomer reversibly converts to another conformation state (SYN form). Nirmatrelvir rotamer conversion follows pseudo first order kinetics with a conversion half-life of approximately 15 min in aqueous solutions, which is on a similar time scale of diffusion mediated dissolution from the solid form. In vitro dissolution studies further indicated that rotamer conversion is one of the processes controlling nirmatrelvir dissolution. It was hypothesized that rotamer conversion kinetics would affect oral absorption of nirmatrelvir in vivo. Consequently, a physiologically based pharmacokinetic (PBPK) model for Paxlovid was developed in SimcypTM using the advanced dissolution, absorption, and metabolism model (ADAM) by incorporating rotamer conversion kinetics to achieve a more mechanistic description of nirmatrelvir oral absorption. The results demonstrate that the established absorption model with rotamer kinetics adequately described observed clinical data from various nirmatrelvir doses, dosage forms, and dosing regimens. The predicted vs. observed AUCinf and Cmax ratios were within 2-fold. The model has been internally used to inform clinical studies and dose recommendations for pediatrics.(c) 2023 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.

CYP3A is one of the most important classes of enzymes and is involved in the metabolism of over 70

Selective chemical inhibitors are critical for reaction phenotyping to identify drug-metabolizing enzymes that are involved in the elimination of drug candidates. Although relatively selective inhibitors are available for the major cytochrome P450 enzymes (CYP), they are quite limited for the less common CYPs and non-CYPs. To address this gap, we developed a multiplexed high throughput screening (HTS) assay using 20 substrate reactions of multiple enzymes to simultaneously monitor the inhibition of enzymes in a 384-well format. Four 384-well assay plates can be run at the same time to maximize throughput. This is the first multiplexed HTS assay for drug-metabolizing enzymes reported. The HTS assay is technologically enabled with state-of-the-art robotic systems and highly sensitive modern LC-MS/MS instrumentation. Virtual screening is utilized to identify inhibitors for HTS based on known inhibitors and enzyme structures. Screening of 4600 compounds generated many hits for many drug-metabolizing enzymes including the two time-dependent and selective aldehyde oxidase inhibitors, erlotinib and dibenzothiophene. The hit rate is much higher than that for the traditional HTS for biological targets due to the promiscuous nature of the drug-metabolizing enzymes and the biased compound selection process. Future efforts will focus on using this method to identify selective inhibitors for enzymes that do not currently have quality hits and thoroughly characterizing the newly identified selective inhibitors from our screen. We encourage colleagues from other organizations to explore their proprietary libraries using a similar approach to identify better inhibitors that can be used across the industry.

Accurate prediction of drug-drug interactions (DDI) from invitro data is important, as it provides insights on clinical DDI risk and study design. Historically, the lower limit of plasma fraction unbound (f(u,p)) is set at 1% for DDI prediction of highly bound compounds by the regulatory agencies due to the uncertainty of the f(u,p) measurements. This leads to high false positive DDI predictions for highly bound compounds. The recently published ICH M12 DDI guideline allows the use of experimental f(u,p) for DDI prediction of highly bound compounds. To further build confidence in DDI prediction of highly bound compounds using experimental f(u,p) values, we evaluated a set of drugs with f(u,p) < 1% and clinical DDI > 20% using both basic and mechanistic static models. All the compounds evaluated were flagged for DDI risk with the mechanistic model using experimental f(u,p) values. There was no false negative DDI prediction. Similarly, using the basic model, the DDI risk of all the compounds was identified except for CYP2D6 inhibition of almorexant. The totality of the data demonstrates that the DDI potential of highly bound compounds can be predicted accurately when actual protein binding numbers are measured.

Accurate measurement of plasma protein binding (PPB) is of critical importance in drug discovery. Methodologies for PPB measurement continue to evolve to address the challenges of highly bound compounds. In order to generate high quality PPB data, it is crucial to not only apply state-of-the-art methods and highly sensitive and selective detectors, but also use high-quality plasma. In this study, we found that plasticizers, leaching from polyvinyl chloride (PVC) plasma storage bags, interfered with drug binding to both human α1-acid glycoprotein (AAG) and human serum albumin (HSA). Several AAG and HSA binding drugs were used to probe the differences in PPB using blood/plasma collected and stored in PVC bags or glass tubes through vacutainers. The results showed that plasma collected using vacutainers into the glass tubes has lower plasma fraction unbound (fu,p) values than those from the PVC bags. The fu,p differences can be as high as 32-fold. Hence, it is recommended to use vacutainers and glass tubes rather than PVC bags, for blood collection and plasma storage. Plasma from animal species collected using polypropylene syringes into polyethylene tubes showed no differences in fu,p from plasma collected using vacutainers into glass tubes. Not all compounds are sensitive to plasticizer interference for PPB. It is therefore important to select appropriate positive controls for fu,p measurement, such as warfarin for HSA and imatinib for AAG, to monitor the quality of plasma and minimize the interference from plasticizers.

Tumor binding is an important parameter to derive unbound tumor concentration to explore pharmacokinetics (PK) and pharmacodynamics (PD) relationships for oncology disease targets. Tumor binding was evaluated using eleven matrices, including various commonly used ex vivo human and mouse xenograft and syngeneic tumors, tumor cell lines and liver as a surrogate tissue. The results showed that tumor binding is highly correlated among the different tumors and tumor cell lines except for the mouse melanoma (B16F10) tumor type. Liver fraction unbound (fu) has a good correlation with B16F10 tumor binding. Liver also demonstrates a two-fold equivalency, on average, with binding of other tumor types when a scaling factor is applied. Predictive models were developed for tumor binding, with correlations established with LogD (acids), predicted muscle fu (neutrals) and measured plasma protein binding (bases) to estimate tumor fu when experimental data are not available. Many approaches can be applied to obtain and estimate tumor binding values. One strategy proposed is to use a surrogate tumor tissue, such as mouse xenograft ovarian cancer (OVCAR3) tumor, as a surrogate for tumor binding (except for B16F10) to provide an early assessment of unbound tumor concentrations for development of PK/PD relationships.

In vitro-in vivo extrapolation ((IVIVE) and empirical scaling factors (SF) of human intrinsic clearance (CLint) were developed using one of the largest dataset of 455 compounds with data from human liver microsomes (HLM) and human hepatocytes (HHEP). For extended clearance classification system (ECCS) class 2/4 compounds, linear SFs (SFlin) are approximately 1, suggesting enzyme activities in HLM and HHEP are similar to those in vivo under physiological conditions. For ECCS class 1A/1B compounds, a unified set of SFs was developed for CLint. These SFs contain both SFlin and an exponential SF (SFβ) of fraction unbound in plasma (fu,p). The unified SFs for class 1A/1B eliminate the need to identify the transporters involved prior to clearance prediction. The underlying mechanisms of these SFs are not entirely clear at this point, but they serve practical purposes to reduce biases and increase prediction accuracy. Similar SFs have also been developed for preclinical species. For HLM-HHEP disconnect (HLM > HHEP) ECCS class 2/4 compounds that are mainly metabolized by cytochrome P450s/FMO, HLM significantly overpredicted in vivo CLint, while HHEP slightly underpredicted and geometric mean of HLM and HHEP slightly overpredicted in vivo CLint. This observation is different than in rats, where rat liver microsomal CLint correlates well with in vivo CLint for compounds demonstrating permeability-limited metabolism. The good CLint IVIVE developed using HLM and HHEP helps build confidence for prospective predictions of human clearance and supports the continued utilization of these assays to guide structure–activity relationships to improve metabolic stability.

Abstract Plasma protein binding (PPB) studies on the SARS-CoV-2 main protease inhibitor nirmatrelvir revealed considerable species differences primarily in dog and rabbit, which prompted further investigations into the biochemical basis for these differences. The unbound fraction (fu) of nirmatrelvir in dog and rabbit plasma was concentration (2–200 µM)-dependent (dog fu,p 0.024–0.69, rabbit fu,p 0.010–0.82). Concentration (0.1–100 µM)-dependent binding in serum albumin (SA) (fu,SA 0.040–0.82) and alpha-1-acid glycoprotein (AAG) (fu,AAG 0.050–0.64) was observed in dogs. Nirmatrelvir showed minimal binding to rabbit SA (1–100 µM: fu,SA 0.70–0.79), while binding to rabbit AAG was concentration-dependent (0.1–100 µM: fu,AAG 0.024–0.66). In contrast, nirmatrelvir (2 µM) revealed minimal binding (fu,AAG 0.79–0.88) to AAG from rat and monkeys. Nirmatrelvir showed minimal-to-moderate binding to SA (1–100 µM; fu,SA 0.70–1.0) and AAG (0.1–100 µM; fu,AAG 0.48–0.58) from humans across tested concentrations. Nirmatrelvir molecular docking studies using published crystal structures and homology models of human and preclinical species SA and AAG were used to rationalise the species differences to plasma proteins. This suggested that species differences in PPB are primarily driven by molecular differences in albumin and AAG resulting in differences in binding affinity.

CYP1A1 is a cytochrome P450 family 1 enzyme that is mostly expressed in the extrahepatic tissues. To understand the CYP1A1 contribution to drug clearance in humans, we examined the in vitro-in vivo extrapolation (IVIVE) of intrinsic clearance (CLint) for a set of drugs that are in vitro CYP1A1 substrates. Despite being strong in vitro CYP1A1 substrates, 82% of drugs gave good IVIVE with predicted CLint within 2-3-fold of the observed values using human liver microsomes and hepatocytes, suggesting they were not in vivo CYP1A1 substrates due to the lack of extrahepatic contribution to CLint. Only three drugs (riluzole, melatonin and ramelteon) that are CYP1A2 substrates yielded significant underprediction of in vivo CLint up to 11-fold. The fold of CLint underprediction was linearly proportional to human recombinant CYP1A1 (rCYP1A1) CLint, indicating they were likely to be in vivo CYP1A1 substrates. Using these three substrates, a calibration curve can be developed to enable direct translation from in vitro rCYP1A1 CLint to in vivo extrahepatic contributions in humans. In vivo CYP1A1 substrates are planar and small, which is consistent with the structure of the active site. This is in contrast to the in vitro substrates, which include large and nonplanar molecules, suggesting rCYP1A1 is more accessible than what is in vivo. The impact of CYP1A1 on first-pass intestinal metabolism was also evaluated and shown to be minimal. This is the first study providing new insights on in vivo translation of CYP1A1 contributions to human clearance using in vitro rCYP1A1 data.