Safety, pharmacokinetics, and pharmacodynamics of anti-IL-4Rα antibody SHR-1819 in healthy subjects: A randomized, controlled phase I study.

SHR-1819 is a novel anti-IL-4Rα monoclonal antibody currently under clinical development for use in patients with type 2 inflammatory diseases. In this randomized, double-blind, placebo-controlled, single-dose escalation phase I trial, we evaluated the safety, tolerability, pharmacokinetics, and pharmacodynamics of SHR-1819 in healthy subjects. Subjects received a single subcutaneous injection of SHR-1819 or placebo, with dose escalation starting at 60 mg and subsequently increasing to 120, 240, 360, and 720 mg. A total of 42 eligible subjects were randomized, and 33 received SHR-1819 (1 subject in the 60 mg cohort and 8 subjects each in the 120, 240, 360 , and 720 mg cohorts) and 9 received placebo. SHR-1819 was well-tolerated, with the majority of adverse events being mild in severity. The exposure of SHR-1819 increased in a manner greater than proportionally with a dose range of 120 to 720 mg. The median Tmax was within 4-7 days (60-720 mg), and the mean half-life ranged from 2.88 to 5.97 days (120-720 mg). The clearance rate of SHR-1819 exhibited a decrease with increasing dose level. Administration of SHR-1819 resulted in a certain degree of reduction in the percentage change from baseline in concentrations of inflammatory biomarkers TARC/CCL17 and IgE, while the reduction of TARC/CCL17 concentrations showed a dose-dependent trend. More than half of the total subjects treated with SHR-1819 were reported antidrug antibody-negative. The preliminary data from this phase I study support further development of SHR-1819 for the treatment of type 2 inflammatory diseases.

Improving In Vitro-In Vivo Extrapolation of Clearance Using Rat Liver Microsomes for Highly Plasma Protein-Bound Molecules.

It is common practice in drug discovery and development to predict in vivo hepatic clearance from in vitro incubations with liver microsomes or hepatocytes using the well-stirred model (WSM). When applying the WSM to a set of approximately 3000 Novartis research compounds, 73% of neutral and basic compounds (extended clearance classification system [ECCS] class 2) were well-predicted within 3-fold. In contrast, only 44% (ECCS class 1A) or 34% (ECCS class 1B) of acids were predicted within 3-fold. To explore the hypothesis whether the higher degree of plasma protein binding for acids contributes to the in vitro-in vivo correlation (IVIVC) disconnect, 68 proprietary compounds were incubated with rat liver microsomes in the presence and absence of 5% plasma. A minor impact of plasma on clearance IVIVC was found for moderately bound compounds (fraction unbound in plasma [fup] ≥1%). However, addition of plasma significantly improved the IVIVC for highly bound compounds (fup <1%) as indicated by an increase of the average fold error from 0.10 to 0.36. Correlating fup with the scaled unbound intrinsic clearance ratio in the presence or absence of plasma allowed the establishment of an empirical, nonlinear correction equation that depends on fup Taken together, estimation of the metabolic clearance of highly bound compounds was enhanced by the addition of plasma to microsomal incubations. For standard incubations in buffer only, application of an empirical correction provided improved clearance predictions. SIGNIFICANCE STATEMENT: Application of the well-stirred liver model for clearance in vitro-in vivo extrapolation (IVIVE) in rat generally underpredicts the clearance of acids and the strong protein binding of acids is suspected to be one responsible factor. Unbound intrinsic in vitro clearance (CLint,u) determinations using rat liver microsomes supplemented with 5% plasma resulted in an improved IVIVE. An empirical equation was derived that can be applied to correct CLint,u-values in dependance of fraction unbound in plasma (fup) and measured CLint in buffer.

Introducing the Dynamic Well-Stirred Model for Predicting Hepatic Clearance and Extraction Ratio.

The well-stirred model (WSM) incorporating the fraction of unbound drug (fu) to account for the effect of plasma binding on intrinsic clearance has been widely used for predicting hepatic clearance under the assumption that drug protein binding reaches equilibrium instantaneously. Our theoretical analysis reveals that the effect of protein binding on intrinsic clearance is better accounted for with the dynamic free fraction (fD), a measure of drug protein binding affinity, which leads to a putative dynamic well-stirred model (dWSM) without the instantaneous equilibrium assumption. Using recombinant CYP3A4 as the in vitro clearance system, we demonstrate that the binding effect of albumin on the intrinsic clearance of both highly bound midazolam and highly free verapamil is fully corrected by their corresponding fD values, respectively. On the other hand, fu only corrects the binding effect of albumin on the intrinsic clearance of verapamil, and yields severe over-correction of the intrinsic clearance of midazolam. The results suggest that the traditional WSM is suitable for highly free drugs like verapamil but not necessarily for highly bound drugs such as midazolam due to the violation of the instantaneous equilibrium assumption or under-estimating the true free drug concentration. In comparison, the dWSM incorporating fD holds true as long as drug elimination follows steady-state kinetics, and hence, it is more broadly applicable to drugs with different protein binding characteristics. Here we demonstrate with 36 diverse drugs, that the dWSM significantly improves the accuracy of predicting human hepatic clearance and liver extraction ratio from in vitro microsomal clearance data, highlighting the importance of drug plasma protein binding kinetics in addressing the under-prediction of hepatic clearance by the WSM.

Multicenter Population Pharmacokinetics of Fentanyl in Neonatal Surgical Patients Using Dried Blood Spot Specimen Collection Demonstrates Maturation of Elimination Clearance.

BACKGROUND: Fentanyl is widely used for analgesia and sedation in neonates, but pharmacokinetic (PK) analysis in this population has been limited by the relatively large sample volumes required for plasma-based assays. METHODS: In this multicenter observational study of fentanyl kinetics in neonates up to 42 weeks of postmenstrual age (PMA) who received fentanyl boluses and continuous infusions, dried blood spots were used for small-volume sampling. A population PK analysis was used to describe fentanyl disposition in term and preterm neonates. Covariates for the model parameters, including body weight, PMA, birth status (preterm or term), and presence of congenital cardiac disease, were assessed in a stepwise manner. RESULTS: Clearance was estimated to be greater than adult clearance of fentanyl and varied with weight. Covariate selection did not yield a significant relationship for age as a continuous or dichotomous variable (term or preterm, the latter defined as birth with PMA of <37 weeks) and clearance. CONCLUSIONS: A supra-allometric effect on clearance was determined during covariate analyses (exponential scaling factor for body weight >0.75), as has been described in population PK models that account for maturation of intrinsic clearance (here, predominantly hepatic microsomal activity) in addition to scaling for weight, both of which impact clearance in this age group.

Prediction of Human Clearance Using In Silico Models with Reduced Bias.

Predicting human clearance with high accuracy from in silico-derived parameters alone is highly desirable, as it is fast, saves in vitro resources, and is animal-sparing. We derived random forest (RF) models from 1340 compounds with human intravenous pharmacokinetic (PK) data, the largest data set publicly available today. To assess the general applicability of the RF models, we systematically removed structural-therapeutic class analogues and other compounds with structural similarity from the training sets. For a quasi-prospective test set of 343 compounds, we show that RF models devoid of structurally similar compounds in the training set predict human clearance with a geometric mean fold error (GMFE) of 3.3. While the observed GMFE illustrates how difficult it is to generate a useful model that is broadly applicable, we posit that our RF models yield a more realistic assessment of how well human clearance can be predicted prospectively. We deployed the conformal prediction formalism to assess the model applicability and to determine the prediction confidence intervals for each prediction. We observed that clearance can be predicted better for renally cleared compounds than for other clearance mechanisms. We show that applying a classification model for predicting renal clearance identifies a subset of compounds for which clearance can be predicted with higher accuracy, yielding a GMFE of 2.3. In addition, our in silico RF human clearance models compared well to models derived from scaling human hepatocytes or preclinical in vivo data.

Antibacterial micro/nanomotors: current research progress, challenges, and opportunities.

Bacterial infections remain a formidable threat to human health, a situation exacerbated by the escalating problem of antibiotic resistance. While alternative antibacterial strategies such as oxidants, heat treatments, and metal nanoparticles (NPs) have shown potential, they come with significant drawbacks, ranging from non-specificity to potential environmental concerns. In the face of these challenges, the rapid evolution of micro/nanomotors (MNMs) stands out as a revolutionary development in the antimicrobial arena. MNMs harness various forms of energy and convert it into a substantial driving force, offering bright prospects for combating microbial threats. MNMs' mobility allows for swift and targeted interaction with bacteria, which not only improves the carrying potential of therapeutic agents but also narrows the required activation range for non-drug antimicrobial interventions like photothermal and photodynamic therapies, substantially improving their bacterial clearance rates. In this review, we summarized the diverse propulsion mechanisms of MNMs employed in antimicrobial applications and articulated their multiple functions, which include direct bactericidal action, capture and removal of microorganisms, detoxification processes, and the innovative detection of bacteria and associated toxins. Despite MNMs' potential to revolutionize antibacterial research, the translation from laboratory to clinical use remains challenging. Based on the current research status, we summarized the potential challenges and possible solutions and also prospected several key directions for future studies of MNMs for antimicrobial purposes. Collectively, by highlighting the important knowns and unknowns of antimicrobial MNMs, our present review would help to light the way forward for the field of antimicrobial MNMs and prevent unnecessary blindness and detours.

Recommendations on the Use of Multiple Labels in Human Mass Balance Studies.

The administration of radiolabeled drug candidates is considered the gold standard in absorption, distribution, metabolism, and excretion studies for small-molecule drugs since it allows facile and accurate quantification of parent drug, metabolites, and total drug-related material independent of the compound structure. The choice of the position of the radiolabel, typically 14C or 3H, is critical to obtain relevant information. Sometimes, a biotransformation reaction may lead to cleavage of a part of the molecule. As a result, only the radiolabeled portion can be followed, and information on the fate of the nonlabeled metabolite may be lost. Synthesis and administration of two or more radiolabeled versions of the parent drug as a mixture or in separate studies may resolve this issue but comes with additional challenges. In this paper, we address the questions that may be considered to help make the right choice whether to use a single or multiple radiolabel approach and discuss the pros and cons of different multiple-labeling strategies that can be taken as well as alternative methods that allow the nonlabeled part of the molecule to be followed. SIGNIFICANCE STATEMENT: Radiolabeled studies are the gold standard in drug metabolism research, but molecules can undergo cleavage with loss of the label. This often results in discussions around potential use of multiple labels, which seem to be occurring with increased frequency since an increasing proportion of the small-molecule drugs are tending towards larger molecular weights. This review provides insight and decision criteria in considering a multiple-label approach as well as pros and cons of different strategies that can be followed.

Cross-species drug metabolism and impact of metabolic stability testing under anaerobic condition on predicting pharmacokinetics of keto-enol containing compound in humans.

After oral administration of [14C]-S-1360 in rats and dogs, [14C]-S-1360 was absorbed rapidly and the bioavailability was 93.7% in rats and 75.1% in dogs. Based on the results in animals, good systemic exposure would be expected in humans. In contrast to the expectation, the exposure was low in healthy volunteers compared to the exposure expected. In addition, human mass balance study using [14C]-S1360 revealed that a large amount of metabolites existed in human plasma. The major metabolites in human plasma were reduced metabolite (HP1) and S-1360 N-glucuronide, and they respectively accounted for approximately 30% of total AUC. Unchanged S-1360 accounted for only 14% of total AUC. The results showed that a significant difference between humans and animals were observed in metabolism of S-1360. Although S-1360 was stable in human hepatocytes under aerobic condition (approximately 84% remaining at 1 h), S-1360 was labile under anaerobic condition (approximately 55% remaining at 1 h). The present study revealed that the reductive metabolism pathways are the key metabolic pathway of S-1360, especially the metabolic stability test under anaerobic condition is important to predict pharmacokinetics of keto-enol containing compound, such as S-1360.

A Complete Extension of Classical Hepatic Clearance Models Using Fractional Distribution Parameter fd in Physiologically Based Pharmacokinetics.

The classical organ clearance models have been proposed to relate the plasma clearance CLp to probable mechanism(s) of hepatic clearance. However, the classical models assume the intrinsic capability of drug elimination (CLu,int) that is physically segregated from the vascular blood but directly acts upon the unbound drug concentration in the blood (fubCavg), and do not handle the transit-time delay between the inlet/outlet concentrations in their closed-form clearance equations. Therefore, we propose unified model structures that can address the internal blood concentration patterns of clearance organs in a more mechanistic/physiological manner, based on the fractional distribution parameter fd operative in PBPK. The basic partial/ordinary differential equations for four classical models are revisited/modified to yield a more complete set of extended clearance models, i.e., the Rattle, Sieve, Tube, and Jar models, which are the counterparts of the dispersion, series-compartment, parallel-tube, and well-stirred models. We demonstrate the feasibility of applying the resulting extended models to isolated perfused rat liver data for 11 compounds and an example dataset for in vitro-in vivo extrapolation of the intrinsic to the systemic clearances. Based on their feasibilities to handle such real data, these models may serve as an improved basis for applying clearance models in the future.

Modelling changes in the pharmacokinetics of tacrolimus during pregnancy after kidney transplantation: A retrospective cohort study.

AIMS: Pregnancy after kidney transplantation is realistic but immunosuppressants should be continued to prevent rejection. Tacrolimus is safe during pregnancy and is routinely dosed based on whole-blood predose concentrations. However, maintaining these concentrations is complicated as physiological changes during pregnancy affect tacrolimus pharmacokinetics. The aim of this study was to describe tacrolimus pharmacokinetics throughout pregnancy and explain the changes by investigating covariates in a population pharmacokinetic model. METHODS: Data of pregnant women using a twice-daily tacrolimus formulation following kidney transplantation were retrospectively collected from 6 months before conception, throughout gestation and up to 6 months postpartum. Pharmacokinetic analysis was performed using nonlinear mixed effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. The final model was evaluated using goodness-of-fit plots, visual predictive checks and a bootstrap analysis. RESULTS: A total of 260 whole-blood tacrolimus predose concentrations from 14 pregnant kidney transplant recipients were included. Clearance increased during pregnancy from 34.5 to 41.7 L/h, by 15, 19 and 21% in the first, second and third trimester, respectively, compared to prior to pregnancy. This indicates a required increase in the tacrolimus dose by the same percentage to maintain the prepregnancy concentration. Haematocrit and gestational age were negatively correlated with tacrolimus clearance (P ≤ 0.01), explaining 18% of interindividual and 85% of interoccasion variability in oral clearance. CONCLUSIONS: Tacrolimus clearance increases during pregnancy, resulting in decreased exposure to tacrolimus, which is explained by gestational age and haematocrit. To maintain prepregnancy target whole-blood tacrolimus predose concentrations during pregnancy, increasing the dose is required.

Construction of a fused grid-based CYP2C18-Template system and its application to drug metabolism.

Detailed estimation of cytochrome P450 (CYP)-mediated metabolisms of medicine and other chemicals is necessary for the efficacy and safety assessments. Data on the metabolisms mediated by minor CYP enzymes like CYP2C18 are often not available in metabolisms and safety assessments of chemicals except for medical drugs developed recently. A ligand-accessible space in the active site of human CYP2C18 was thus reconstituted as a fused grid-based Template with the use of structural data of its ligands. An evaluation system of CYP2C18-mediated metabolism was then developed on Template with the introduction of the idea of movement and fastening of ligands after Trigger-residue contact. Reciprocal comparison of the data of simulations on Template with experimental results suggested a unified way of the interaction of CYP2C18, in similar to the CYP2C8 interaction (Drug Metab Pharmacokinet 2023, in press). These experiments also displayed the roles of initial Trigger-residue-localizations on their distinct catalyses among human CYP2C enzymes. Simulation experiments for over 130 reactions of CYP2C18 ligands supported the system established.

A Comprehensive Mixed-Method Approach to Characterize the Source of Diurnal Tacrolimus Exposure Variability in Children: Systematic Review, Meta-analysis, and Application to an Existing Data Set.

Tacrolimus is widely reported to display diurnal variation in pharmacokinetic parameters with twice-daily dosing. However, the contribution of chronopharmacokinetics versus food intake is unclear, with even less evidence in the pediatric population. The objectives of this study were to summarize the existing literature by meta-analysis and evaluate the impact of food composition on 24-hour pharmacokinetics in pediatric kidney transplant recipients. For the meta-analysis, 10 studies involving 253 individuals were included. The pooled effect sizes demonstrated significant differences in area under the concentration-time curve from time 0 to 12 hours (standardized mean difference [SMD], 0.27; 95% confidence interval [CI], 0.03-0.52) and maximum concentration (SMD, 0.75; 95% CI, 0.35-1.15) between morning and evening dose administration. However, there was significant between-study heterogeneity that was explained by food exposure. The effect size for minimum concentration was not significantly different overall (SMD, -0.09; 95% CI, -0.27 to 0.09) or across the food exposure subgroups. A 2-compartment model with a lag time, linear clearance, and first-order absorption best characterized the tacrolimus pharmacokinetics in pediatric participants. As expected, adding the time of administration and food composition covariates reduced the unexplained within-subject variability for the first-order absorption rate constant, but only caloric composition significantly reduced variability for lag time. The available data suggest food intake is the major driver of diurnal variation in tacrolimus exposure, but the associated changes are not reflected by trough concentrations alone.

Effect of changes in metabolic enzymes and transporters on drug metabolism in the context of liver disease: Impact on pharmacokinetics and drug-drug interactions.

Changes in the pharmacokinetic and resulting pharmacodynamic properties of drugs are common in many chronic liver diseases, leading to adverse effects, drug interactions and increased risk of over- or underdosing of medications. Structural and functional hepatic impairment can have major effects on drug metabolism and transport. This review summarizes research on the functional changes in phase I and II metabolic enzymes and in transport proteins in patients with metabolic diseases such as type 2 diabetes, metabolic dysfunction-associated steatotic liver disease, metabolic dysfunction-associated steatohepatitis and cirrhosis, providing a clinical perspective on how these changes affect drug uptake and metabolism. Generally, a decrease in expression and/or activity of many enzymes of the cytochrome P450 family (e.g. CYP2E1 and CYP3A4), and of influx and efflux transporters (e.g. organic anion-transporting polypeptide [OATP]1B1, OATP2B1, OAT2 and bile salt export pump), has been recently documented in patients with liver disease. Decreased enzyme levels often correlate with increased severity of chronic liver disease. In subjects with hepatic impairment, there is potential for strong alterations of drug pharmacokinetics due to reduced absorption, increased volume of distribution, metabolism and extraction. Due to the altered pharmacokinetics, specific drug-drug interactions are also a potential issue to consider in patients with liver disease. Given the huge burden of liver disease in western societies, there is a need to improve awareness among all healthcare professionals and patients with liver disease to ensure appropriate drug prescriptions.

Pharmacokinetics, Mass Balance, Tissue Distribution and Metabolism of [14C]101BHG-D01, a Novel Muscarinic Receptor Antagonist, in Rats.

BACKGROUND: 101BHG-D01, a novel long-acting and selective muscarinic receptor antagonist for the treatment of chronic obstructive pulmonary disease (COPD), is undergoing Phase Ib clinical trial in patients and has shown its potential efficacy. Its preparation method and medical use thereof have been patented in the United States (Patent No.US9751875B2). OBJECTIVE: In this study, the pharmacokinetics, mass balance, tissue distribution and metabolism of radioactive 101BHG-D01 were investigated in rats after an intravenous dose of 1 mg/kg [14C]101BHG-D01 (100 µCi/kg). METHODS: Radioactivity in rat plasma, urine, feces, and tissues was measured by liquid scintillation counting (LSC), and metabolite profiling and identification were conducted by UHPLC-ß-RAM and UHPLC-Q-Exactive Plus MS. RESULTS: The total radioactivity of the study drug in rat plasma rapidly declined with an average terminal elimination half-life of 0.35 h. The radioactivity in most tissues reached the maximum concentration at 0.25 h post-- dosing. The radioactivity mainly concentrated in the kidney and pancreas. The drug-related substances tended to be distributed into the blood cells in the circulation. At 168 h post dosing, the mean recovery of the total radioactivity in urine and feces was 78.82%. Fecal excretion was the major excretion route, accounting for approximately 61% of the radioactive dose. The study drug was metabolized extensively, and a total of 17 metabolites were identified in rat plasma, urine, and feces. The major metabolic pathways involved oxidation, oxidation and dehydrogenation, and O-dephenylation. CONCLUSION: In conclusion, the study results are useful for better understanding the pharmacokinetic profiles of 101BHG-D01 and provide a robust foundation for subsequent clinical studies.

Safety and pharmacokinetics of SPR206 in subjects with varying degrees of renal impairment.

SPR206 is a novel polymyxin derivative with potent in vitro activity against susceptible and multidrug-resistant strains of Acinetobacter baumannii, Pseudomonas aeruginosa, Klebsiella pneumoniae, Escherichia coli, and Enterobacter species. SPR206 is eliminated renally. The safety, tolerability, and pharmacokinetics (PK) of SPR206 were evaluated in healthy subjects with normal renal function (Cohort 1) and subjects with varying degrees of renal impairment (RI) (Cohorts 2-4) or end-stage renal disease (ESRD) on hemodialysis (HD) (Cohort 5). Subjects in Cohorts 1-4 received a 100-mg intravenous (IV) dose of SPR206. Subjects in Cohort 5 received a 100-mg IV dose within 2 h after HD on day 1 and 1 h before HD on day 5. Safety and PK analyses included 37 subjects. Mostly mild but no serious treatment-related adverse events were reported. Systemic exposure to SPR206 increased as renal function decreased, with mean area under the concentration-time curve from time 0 to the last quantifiable concentration (AUC0-last) values 39% to 239% greater in subjects with RI vs healthy subjects. Mean plasma clearance (CL) of SPR206 decreased with decreasing renal function (29% to 76% lower vs healthy subjects). In subjects with ESRD, AUC0-last decreased by 51%, and CL increased by 92% for dialyzed vs nondialyzed conditions. SPR206 was excreted in urine within 12 h in healthy subjects and subjects with mild RI (Cohort 2) but was prolonged in those with moderate and severe RI (Cohorts 3 and 4, respectively). In summary, SPR206 was generally safe and well tolerated, and the PK of SPR206 was well characterized in subjects with RI.

A Novel Milli-fluidic Liver Tissue Chip with Continuous Recirculation for Predictive Pharmacokinetics Applications.

A crucial step in lead selection during drug development is accurate estimation and optimization of hepatic clearance using in vitro methods. However, current methods are limited by factors such as lack of physiological relevance, short culture/incubation times that are not consistent with drug exposure patterns in patients, use of drug absorbing materials, and evaporation during long-term incubation. To address these technological needs, we developed a novel milli-fluidic human liver tissue chip (LTC) that was designed with continuous media recirculation and optimized for hepatic cultures using human primary hepatocytes. Here, we characterized the LTC using a series of physiologically relevant metrics and test compounds to demonstrate that we could accurately predict the PK of both low- and high-clearance compounds. The non-biological characterization indicated that the cyclic olefin copolymer (COC)-based LTC exhibited negligible evaporation and minimal non-specific binding of drugs of varying ionic states and lipophilicity. Biologically, the LTC exhibited functional and polarized hepatic culture with sustained metabolic CYP activity for at least 15 days. This long-term culture was then used for drug clearance studies for low- and high-clearance compounds for at least 12 days, and clearance was estimated for a range of compounds with high in vitro-in vivo correlation (IVIVC). We also demonstrated that LTC can be induced by rifampicin, and the culture age had insignificant effect on depletion kinetic and predicted clearance value. Thus, we used advances in bioengineering to develop a novel purpose-built platform with high reproducibility and minimal variability to address unmet needs for PK applications.

Metabolic profiling to evaluate the impact of amantadine and rimantadine on the secondary metabolism of a model organism.

Metabolic profiling offers huge potential to highlight markers and mechanisms in support of toxicology and pathology investigations during drug development. The main objective was to modify therapy with adamantane derivatives: amantadine and rimantadine, to increase their bioavailability and evaluate the influence of such therapy on drug metabolism using Saccharomyces cerevisiae as the model organism. In this study, the profile of endogenous metabolites of a model organism was measured and interpreted to provide an opportunity to investigate changes induced by treatment with amantadine and rimantadine. It was found that resveratrol supplementation synergistically enhanced the effects of amantadine treatment and increased rimantadine metabolism, potentially reducing side effects. The fingerprinting strategy was used as an efficient technique for qualitatively evaluating and monitoring changes in the profiles of endogenous components and their contents in a model organism. Chemometric tools were employed to find marker compounds that can be defined as characteristic indicators of a pharmacological response to a therapeutic intervention. An improved understanding of the mechanisms involved in drug effect and an increased ability to predict individual variations in the drug response of organisms will improve the treatment process and the development of new therapies.

Quantitative Translation of Substrate Intrinsic Clearance from Recombinant CYP1A1 to Humans.

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.

The Comparison of Machine Learning and Mechanistic In Vitro-In Vivo Extrapolation Models for the Prediction of Human Intrinsic Clearance.

Accurate prediction of human pharmacokinetics (PK) remains one of the key objectives of drug metabolism and PK (DMPK) scientists in drug discovery projects. This is typically performed by using in vitro-in vivo extrapolation (IVIVE) based on mechanistic PK models. In recent years, machine learning (ML), with its ability to harness patterns from previous outcomes to predict future events, has gained increased popularity in application to absorption, distribution, metabolism, and excretion (ADME) sciences. This study compares the performance of various ML and mechanistic models for the prediction of human IV clearance for a large (645) set of diverse compounds with literature human IV PK data, as well as measured relevant in vitro end points. ML models were built using multiple approaches for the descriptors: (1) calculated physical properties and structural descriptors based on chemical structure alone (classical QSAR/QSPR); (2) in vitro measured inputs only with no structure-based descriptors (ML IVIVE); and (3) in silico ML IVIVE using in silico model predictions for the in vitro inputs. For the mechanistic models, well-stirred and parallel-tube liver models were considered with and without the use of empirical scaling factors and with and without renal clearance. The best ML model for the prediction of in vivo human intrinsic clearance (CLint) was an in vitro ML IVIVE model using only six in vitro inputs with an average absolute fold error (AAFE) of 2.5. The best mechanistic model used the parallel-tube liver model, with empirical scaling factors resulting in an AAFE of 2.8. The corresponding mechanistic model with full in silico inputs achieved an AAFE of 3.3. These relative performances of the models were confirmed with the prediction of 16 Pfizer drug candidates that were not part of the original data set. Results show that ML IVIVE models are comparable to or superior to their best mechanistic counterparts. We also show that ML IVIVE models can be used to derive insights into factors for the improvement of mechanistic PK prediction.

The African Liver Tissue Biorepository Consortium: Capacitating Population-Appropriate Drug Metabolism, Pharmacokinetics, and Pharmacogenetics Research in Drug Discovery and Development.

Pharmaceutical companies subject all new molecular entities to a series of in vitro metabolic characterizations that guide the selection and/or design of compounds predicted to have favorable pharmacokinetic properties in humans. Current drug metabolism research is based on liver tissue predominantly obtained from people of European origin, with limited access to tissue from people of African origin. Given the interindividual and interpopulation genomic variability in genes encoding drug-metabolizing enzymes, efficacy and safety of some drugs are poorly predicted for African populations. To address this gap, we have established the first comprehensive liver tissue biorepository inclusive of people of African origin. The African Liver Tissue Biorepository Consortium currently includes three institutions in South Africa and one in Zimbabwe, with plans to expand to other African countries. The program has collected 67 liver samples as of July 2023. DNA from the donors was genotyped for 120 variants in 46 pharmacogenes and revealed variants that are uniquely found in African populations, including the low-activity, African-specific CYP2C9*5 and *8 variants relevant to the metabolism of diclofenac. Larger liver tissue samples were used to isolate primary human hepatocytes. Viability of the hepatocytes and microsomal fractions was demonstrated by the activity of selected cytochrome P450s. This resource will be used to ensure the safety and efficacy of existing and new drugs in African populations. This will be done by characterizing compounds for properties such as drug clearance, metabolite and enzyme identification, and drug-drug and drug-gene interactions. SIGNIFICANCE STATEMENT: Standard optimization of the drug metabolism of new molecular entities in the pharmaceutical industry uses subcellular fractions such as microsomes and isolated primary hepatocytes, being done mainly with tissue from donors of European origin. Pharmacogenetics research has shown that variants in genes coding for drug-metabolizing enzymes have interindividual and interpopulation differences. We established an African liver tissue biorepository that will be useful in ensuring drug discovery and development research takes into account drug responses in people of African origin.