Using the Dynamic Well-Stirred Model to Extrapolate Hepatic Clearance of Organic Anion-Transporting Polypeptide Transporter Substrates without Assuming Albumin-Mediated Hepatic Drug Uptake.

Extrapolating in vivo hepatic clearance from in vitro uptake data is a known challenge, especially for organic anion-transporting polypeptide transporter (OATP) substrates, and the well-stirred model (WSM) commonly yields systematic underpredictions for those anionic drugs, hypothetically due to "albumin-mediated hepatic drug uptake". In the present study, we demonstrate that the WSM incorporating the dynamic free fraction (f D), a measure of drug protein binding affinity, performs reasonably well in predicting hepatic clearance of OATP substrates. For a selection of anionic drugs, including atorvastatin, fluvastatin, pravastatin, rosuvastatin, pitavastatin, cerivastatin, and repaglinide, this dynamic well-stirred model (dWSM) correctly predicts hepatic plasma clearance within 2-fold error for six out of seven OATP substrates examined. The geometric mean of clearance ratios between the predicted and the observed values falls in the range of 1.21-1.38. As expected, the WSM with unbound fraction (f u) systematically underpredicts hepatic clearance with greater than 2-fold error for five out of seven drugs, and the geometric mean of clearance ratios between the predicted and the observed values is in the range of 0.20-0.29. The results suggest that, despite its simplicity, the dWSM operates well for transporter-mediated uptake clearance, and that clearance under-prediction of OATP substrates may not necessarily be associated with the chemical class of the anionic drugs, nor is it a result of albumin-mediated hepatic drug uptake as currently hypothesized. Instead, the superior prediction power of the dWSM confirms the utility of the dynamic free fraction in clearance prediction and the importance of drug plasma binding kinetics in hepatic uptake clearance. SIGNIFICANCE STATEMENT: The traditional well-stirred model (WSM) consistently underpredicts organin anion-transporting polypeptide transporter (OATP)-mediated hepatic uptake clearance, hypothetically due to the albumin-mediated hepatic drug uptake. In this manuscript, we apply the dynamic WSM to extrapolate hepatic clearance of the OATP substrates, and our results show significant improvements in clearance prediction without assuming albumin-mediated hepatic drug uptake.

New Methodology for Determining Plasma Protein Binding Kinetics Using an Enzyme Reporter Assay Coupling with High-Resolution Mass Spectrometry.

Determination of drug binding kinetics in plasma is important yet extremely challenging. Accordingly, we introduce "dynamic free fraction" as a new binding parameter describing drug-protein binding kinetics. We demonstrate theoretically and experimentally that the dynamic free fraction can be determined by coupling the drug binding assay with a reporter enzyme in combination with high-resolution mass spectrometry measuring the relative initial steady-state rates of enzymatic reactions in the absence and presence of matrix proteins. This novel and simple methodology circumvents a long-standing challenge inherent in existing methods for determining binding kinetics constants, such as kon and koff, and enables assessment of the impact of protein binding kinetics on pharmaceutical properties of drugs. As demonstrated with nine model drugs, the predicted liver extraction ratio, a measure of efficiency of drug removal by the liver, correlates significantly better to the observed extraction ratio when using the dynamic free fraction (fD) in place of the unbound fraction (fu) of the drug in plasma. Similarly, the in vivo hepatic clearance of these drugs, a measure of liver drug elimination, is highly comparable to the clearance values calculated with the dynamic free fraction (fD), which is markedly better than those calculated with the unbound fraction (fu). In contrast to the prevailing view, these results indicate that protein binding kinetics is an important pharmacokinetic property of a drug. As plasma protein binding is one of the most important drug properties, this new methodology may represent a breakthrough and could have a real impact on the field.

Identification of a Discrete Diglucuronide of GDC-0810 in Human Plasma after Oral Administration.

GDC-0810 is a small molecule therapeutic agent having potential to treat breast cancer. In plasma of the first-in-human study, metabolite M2, accounting for 20.7% of total drug-related materials, was identified as a discrete diglucuronide that was absent in rats. Acyl glucuronide M6 and N-glucuronide M4 were also identified as prominent metabolites in human plasma. Several in vitro studies were conducted in incubations of [14C]GDC-0810, synthetic M6 and M4 with liver microsomes, intestinal microsomes, and hepatocytes of different species as well as recombinant UDP-glucuronosyltransferase (UGT) enzymes to further understand the formation of M2. The results suggested that 1) M2 was more efficiently formed from M6 than from M4, and 2) acyl glucuronidation was mainly catalyzed by UGT1A8/7/1 that is highly expressed in the intestines whereas N-glucuronidation was mainly catalyzed by UGT1A4 that is expressed in the human liver. This complicated mechanism presented challenges in predicting M2 formation using human in vitro systems. The absence of M2 and M4 in rats can be explained by low to no expression of UGT1A4 in rodents. M2 could be the first discrete diglucuronide that was formed from both acyl- and N-glucuronidation on a molecule identified in human plasma. SIGNIFICANCE STATEMENT: A discrete diglucuronidation metabolite of GDC-0810, a breast cancer drug candidate, was characterized as a unique circulating metabolite in humans that was not observed in rats or little formed in human in vitro system.

Isotretinoin and its Metabolites Alter mRNA of Multiple Enzyme and Transporter Genes In Vitro, but Downregulation of Organic Anion Transporting Polypeptide Does Not Translate to the Clinic.

Isotretinoin [13-cis-retinoic acid (13cisRA)] is widely used for the treatment of neuroblastoma and acne. It acts via regulating gene transcription through binding to retinoic acid receptors. Yet, the potential for isotretinoin to cause transcriptionally mediated drug-drug interactions (DDIs) has not been fully explored. We hypothesized that isotretinoin and its active metabolites all-trans-retinoic acid (atRA) and 4-oxo-13cisRA would alter the transcription of enzymes and transporters in the human liver via binding to nuclear receptors. The goal of this study was to define the DDI potential of isotretinoin and its metabolites resulting from transcriptional regulation of cytochrome P450 and transporter mRNAs. In human hepatocytes (n = 3), 13cisRA, atRA, and 4-oxo-13cisRA decreased OATP1B1, CYP1A2, CYP2C9, and CYP2D6 mRNA and increased CYP2B6 and CYP3A4 mRNA in a concentration-dependent manner. The EC50 values for OATP1B1 mRNA downregulation ranged from 2 to 110 nM, with maximum effect (Emax ) ranging from 0.17- to 0.54-fold. Based on the EC50 and Emax values and the known circulating concentrations of 13cisRA and its metabolites after isotretinoin dosing, a 55% decrease in OATP1B1 activity was predicted in vivo. In vivo DDI potential was evaluated clinically in participants dosed with isotretinoin for up to 32 weeks using coproporphyrin-I (CP-I) as an OATP1B1 biomarker. CP-I steady-state serum concentrations were unaltered following 2, 8, or 16 weeks of isotretinoin treatment. These data show that isotretinoin and its metabolites alter transcription of multiple enzymes and transporters in vitro, but translation of these changes to in vivo drug-drug interactions requires clinical evaluation for each enzyme. SIGNIFICANCE STATEMENT: Isotretinoin and its metabolites alter the mRNA expression of multiple cytochrome P450s (CYPs) and transporters in human hepatocytes, suggesting that isotretinoin may cause clinically significant drug-drug interactions (DDIs). Despite the observed changes in organic anion transporting polypeptide 1B1 (OATP1B1) mRNA in human hepatocytes, no clinical DDI was observed when measuring a biomarker, coproporphyrin-I. Further work is needed to determine whether these findings can be extrapolated to a lack of a DDI with CYP1A2, CYP2B6, and CYP2C9 substrates.

Application of empirical scalars to enable early prediction of human hepatic clearance using IVIVE in drug discovery: an evaluation of 173 drugs.

The utilization of in vitro data to predict drug pharmacokinetics (PK) in vivo has been a consistent practice in early drug discovery for decades. However, its success is hampered by mispredictions attributed to uncharacterized biological phenomena/experimental artifacts. Predicted drug clearance (CL) from experimental data (i.e. hepatocyte intrinsic clearance: CLint, fraction unbound in plasma: fu,p) is often systematically underpredicted using the well-stirred model (WSM). The objective of this study was to evaluate using empirical scalars in the WSM to correct for CL mispredictions. Drugs (N=28) were used to generate numerical scalars on CLint (α), and fu,p (ß) to minimize the error (AAFE) for CL predictions. These scalars were validated using an additional dataset (N=28 drugs) and applied to a non-redundant AstraZeneca (AZ) dataset available in the literature (N=117 drugs) for a total of 173 compounds. CL predictions using the WSM were improved for most compounds using an α value of 3.66 (~64%<2-fold) compared to no scaling (~46%<2-fold). Similarly, using a ß value of 0.55 or combination of α and ß scalars (values of 1.74 and 0.66, respectively) resulted in a similar improvement in predictions (~64%<2-fold and ~65%<2-fold, respectively). For highly bound compounds (fu,p{less than or equal to}0.01), AAFE was substantially reduced across all scaling methods. Using the ß scalar alone or a combination of α and ß appeared optimal; and produce larger magnitude corrections for highly-bound compounds. Some drugs are still disproportionally mispredicted, however the improvements in prediction error and simplicity of applying these scalars suggests its utility for early-stage CL predictions. Significance Statement In early drug discovery, prediction of human clearance using in vitro experimental data plays an essential role in triaging compounds prior to in vivo studies. These predictions have been systematically underestimated. Here we introduce empirical scalars calibrated on the extent of plasma protein binding that appear to improve clearance prediction across multiple datasets. This approach can be used in early phases of drug discovery prior to the availability of pre-clinical data for early quantitative predictions of human clearance.

Inhaled JAK inhibitor GDC-0214 reduces exhaled nitric oxide in patients with mild asthma: A randomized, controlled, proof-of-activity trial.

BACKGROUND: The Janus kinase (JAK) pathway mediates the activity of many asthma-relevant cytokines, including IL-4 and IL-13. GDC-0214 is a potent, inhaled, small-molecule JAK inhibitor being developed for the treatment of asthma. OBJECTIVE: We sought to determine whether GDC-0214 reduces fractional exhaled nitric oxide (Feno), a JAK1-dependent biomarker of airway inflammation, in patients with mild asthma. METHODS: We conducted a double-blind, randomized, placebo-controlled, phase 1 proof-of-activity study in adults with mild asthma and Feno higher than 40 parts per billion (ppb). Subjects were randomized 2:1 (GDC-0214:placebo) into 4 sequential ascending-dose cohorts (1 mg once daily [QD], 4 mg QD, 15 mg QD, or 15 mg twice daily). All subjects received 4 days of blinded placebo, then 10 days of either active drug or placebo. The primary outcome was placebo-corrected percent reduction in Feno from baseline to day 14. Baseline was defined as the average Feno during the blinded placebo period. Pharmacokinetics, safety, and tolerability were also assessed. RESULTS: Thirty-six subjects (mean age, 28 years; 54% females) were enrolled. Mean Feno at baseline across all subjects was 93 ± 43 ppb. At day 14, placebo-corrected difference in Feno was -23% (95% CI, -37.3 to -9) for 15 mg QD and -42% (95% CI, -57 to -27.4) for 15 mg twice daily. Higher plasma exposure was associated with greater Feno reduction. No dose-limiting adverse events, serious adverse events, or treatment discontinuations occurred. There were no major imbalances in adverse events or laboratory findings, or evidence of systemic JAK inhibition. CONCLUSIONS: GDC-0214, an inhaled JAK inhibitor, caused dose-dependent reductions in Feno in mild asthma and was well tolerated without evidence of systemic toxicity.

Strategies to Mitigate the Bioactivation of Aryl Amines.

The bioactivation of xenobiotics to yield reactive metabolites can lead to tolerability and toxicity concerns within a drug discovery program. Development of strategies for mitigating the metabolic liability of commonly encountered toxicophores, such as anilines, relies on an understanding of the relative tendency of these functionalities to undergo bioactivation. In this report, we present the first systematic study of the structure-activity relationships of the bioactivation of aryl amine fragments (molecular weight < 250 Da) using a glutathione (GSH) trapping assay in the presence of human liver microsomes and the reduced form of nicotinamide adenine dinucleotide phosphate. This study demonstrates that conversion of anilines to nitrogen-containing heteroarylamines results in a lower abundance of GSH conjugates in the order phenyl > pyrimidine ≈ pyridine > pyridazine. Introduction of electron-withdrawing functionality on the aromatic ring had a less pronounced effect on the extent of GSH conjugation. Examination of more drug-like compounds sourced from in-house drug discovery programs revealed similar trends in bioactivation between matched pairs containing (hetero)aryl amines. This study provides medicinal chemists with insights and qualitative guidance for the minimization of risks related to aryl amine metabolism.

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.

Drug Concentration Asymmetry in Tissues and Plasma for Small Molecule-Related Therapeutic Modalities.

The well accepted "free drug hypothesis" for small-molecule drugs assumes that only the free (unbound) drug concentration at the therapeutic target can elicit a pharmacologic effect. Unbound (free) drug concentrations in plasma are readily measurable and are often used as surrogates for the drug concentrations at the site of pharmacologic action in pharmacokinetic-pharmacodynamic analysis and clinical dose projection in drug discovery. Furthermore, for permeable compounds at pharmacokinetic steady state, the free drug concentration in tissue is likely a close approximation of that in plasma; however, several factors can create and maintain disequilibrium between the free drug concentration in plasma and tissue, leading to free drug concentration asymmetry. These factors include drug uptake and extrusion mechanisms involving the uptake and efflux drug transporters, intracellular biotransformation of prodrugs, membrane receptor-mediated uptake of antibody-drug conjugates, pH gradients, unique distribution properties (covalent binders, nanoparticles), and local drug delivery (e.g., inhalation). The impact of these factors on the free drug concentrations in tissues can be represented by K p,uu, the ratio of free drug concentration between tissue and plasma at steady state. This review focuses on situations in which free drug concentrations in tissues may differ from those in plasma (e.g., K p,uu > or <1) and discusses the limitations of the surrogate approach of using plasma-free drug concentration to predict free drug concentrations in tissue. This is an important consideration for novel therapeutic modalities since systemic exposure as a driver of pharmacologic effects may provide limited value in guiding compound optimization, selection, and advancement. Ultimately, a deeper understanding of the relationship between free drug concentrations in plasma and tissues is needed.

Discovery of a class of highly potent Janus Kinase 1/2 (JAK1/2) inhibitors demonstrating effective cell-based blockade of IL-13 signaling.

Disruption of interleukin-13 (IL-13) signaling with large molecule antibody therapies has shown promise in diseases of allergic inflammation. Given that IL-13 recruits several members of the Janus Kinase family (JAK1, JAK2, and TYK2) to its receptor complex, JAK inhibition may offer an alternate small molecule approach to disrupting IL-13 signaling. Herein we demonstrate that JAK1 is likely the isoform most important to IL-13 signaling. Structure-based design was then used to improve the JAK1 potency of a series of previously reported JAK2 inhibitors. The ability to impede IL-13 signaling was thereby significantly improved, with the best compounds exhibiting single digit nM IC50's in cell-based assays dependent upon IL-13 signaling. Appropriate substitution was further found to influence inhibition of a key off-target, LRRK2. Finally, the most potent compounds were found to be metabolically labile, which makes them ideal scaffolds for further development as topical agents for IL-13 mediated diseases of the lungs and skin (for example asthma and atopic dermatitis, respectively).

Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidances from Regulatory Agencies: Focus on CYP3A4 mRNA In Vitro Response Thresholds, Variability, and Clinical Relevance.

The Innovation and Quality Induction Working Group presents an assessment of best practice for data interpretation of in vitro induction, specifically, response thresholds, variability, application of controls, and translation to clinical risk assessment with focus on CYP3A4 mRNA. Single concentration control data and Emax/EC50 data for prototypical CYP3A4 inducers were compiled from many human hepatocyte donors in different laboratories. Clinical CYP3A induction and in vitro data were gathered for 51 compounds, 16 of which were proprietary. A large degree of variability was observed in both the clinical and in vitro induction responses; however, analysis confirmed in vitro data are able to predict clinical induction risk. Following extensive examination of this large data set, the following recommendations are proposed. a) Cytochrome P450 induction should continue to be evaluated in three separate human donors in vitro. b) In light of empirically divergent responses in rifampicin control and most test inducers, normalization of data to percent positive control appears to be of limited benefit. c) With concentration dependence, 2-fold induction is an acceptable threshold for positive identification of in vitro CYP3A4 mRNA induction. d) To reduce the risk of false positives, in the absence of a concentration-dependent response, induction ≥ 2-fold should be observed in more than one donor to classify a compound as an in vitro inducer. e) If qualifying a compound as negative for CYP3A4 mRNA induction, the magnitude of maximal rifampicin response in that donor should be ≥ 10-fold. f) Inclusion of a negative control adds no value beyond that of the vehicle control.

Development of a mass spectrometry-based tryptophan 2, 3-dioxygenase assay using liver cytosol from multiple species.

A novel and rapid method to determine the potency of inhibitors for tryptophan 2, 3-dioxygenase (TDO2) activities in human and preclinical species was successfully developed and validated utilizing LC-MS/MS. Previously reported TDO2 activity assays are resource intensive, requiring cloning and overexpression of TDO2. Here, we demonstrated that liver cytosol contained sufficient active TDO2 for evaluating the potency of TDO2 inhibitors across multiple species. TDO2 expression in human cytosol was estimated by LC-MS/MS to be 41 pmoL/mg cytosolic protein, with similar levels in dogs and monkeys, whereas mice and rats had 9.6 and 5.0-fold greater expression, respectively. Reaction conditions for TDO2-mediated conversion of l-tryptophan to kynurenine were optimized. Marked differences in kinetic parameters and inhibition potency were observed in TDO2 across species, with different Km values in dog (0.055 mM), monkey (0.070 mM), human (0.19 mM), mouse (0.32 mM) and rat (0.36 mM). Subsequently, IC50 values were determined for a series of TDO2 inhibitors in liver cytosol of five species, and good agreement with the literature values was observed for human enzyme. Taken together, these data indicate that TDO2 inhibition can be rapidly determined in readily available hepatic cytosol to assess potential species differences in potency.

Considerations from the IQ Induction Working Group in Response to Drug-Drug Interaction Guidance from Regulatory Agencies: Focus on Downregulation, CYP2C Induction, and CYP2B6 Positive Control.

The European Medicines Agency (EMA), the Pharmaceutical and Medical Devices Agency (PMDA), and the Food and Drug Administration (FDA) have issued guidelines for the conduct of drug-drug interaction studies. To examine the applicability of these regulatory recommendations specifically for induction, a group of scientists, under the auspices of the Drug Metabolism Leadership Group of the Innovation and Quality (IQ) Consortium, formed the Induction Working Group (IWG). A team of 19 scientists, from 16 of the 39 pharmaceutical companies that are members of the IQ Consortium and two Contract Research Organizations reviewed the recommendations, focusing initially on the current EMA guidelines. Questions were collated from IQ member companies as to which aspects of the guidelines require further evaluation. The EMA was then approached to provide insights into their recommendations on the following: 1) evaluation of downregulation, 2) in vitro assessment of CYP2C induction, 3) the use of CITCO as the positive control for CYP2B6 induction by CAR, 4) data interpretation (a 2-fold increase in mRNA as evidence of induction), and 5) the duration of incubation of hepatocytes with test article. The IWG conducted an anonymous survey among IQ member companies to query current practices, focusing specifically on the aforementioned key points. Responses were received from 19 companies. All data and information were blinded before being shared with the IWG. The results of the survey are presented, together with consensus recommendations on downregulation, CYP2C induction, and CYP2B6 positive control. Results and recommendations related to data interpretation and induction time course will be reported in subsequent articles.

Prediction of Drug-Drug Interactions Arising from CYP3A induction Using a Physiologically Based Dynamic Model.

Using physiologically based pharmacokinetic modeling, we predicted the magnitude of drug-drug interactions (DDIs) for studies with rifampicin and seven CYP3A4 probe substrates administered i.v. (10 studies) or orally (19 studies). The results showed a tendency to underpredict the DDI magnitude when the victim drug was administered orally. Possible sources of inaccuracy were investigated systematically to determine the most appropriate model refinement. When the maximal fold induction (Indmax) for rifampicin was increased (from 8 to 16) in both the liver and the gut, or when the Indmax was increased in the gut but not in liver, there was a decrease in bias and increased precision compared with the base model (Indmax = 8) [geometric mean fold error (GMFE) 2.12 vs. 1.48 and 1.77, respectively]. Induction parameters (mRNA and activity), determined for rifampicin, carbamazepine, phenytoin, and phenobarbital in hepatocytes from four donors, were then used to evaluate use of the refined rifampicin model for calibration. Calibration of mRNA and activity data for other inducers using the refined rifampicin model led to more accurate DDI predictions compared with the initial model (activity GMFE 1.49 vs. 1.68; mRNA GMFE 1.35 vs. 1.46), suggesting that robust in vivo reference values can be used to overcome interdonor and laboratory-to-laboratory variability. Use of uncalibrated data also performed well (GMFE 1.39 and 1.44 for activity and mRNA). As a result of experimental variability (i.e., in donors and protocols), it is prudent to fully characterize in vitro induction with prototypical inducers to give an understanding of how that particular system extrapolates to the in vivo situation when using an uncalibrated approach.

Evaluation of Time Dependent Inhibition Assays for Marketed Oncology Drugs: Comparison of Human Hepatocytes and Liver Microsomes in the Presence and Absence of Human Plasma.

PURPOSE: To evaluate an alternative in vitro system which can provide more quantitatively accurate drug drug interaction (DDI) prediction for 10 protein kinase inhibitors for which DDI risk was over-predicted by inhibition data generated in human liver microsomes (HLM). METHODS: Three cryopreserved human hepatocyte (hHEP) systems: 1) plated hHEPs; 2) hHEPs suspended in Dulbecco's Modified Eagle Medium (DMEM) and 3) hHEPs suspended in human plasma (plasma hHEPs) were developed to detect CYP3A time dependent inhibition, and the static mechanistic model was used to predict clinical outcomes. RESULTS: A general trend was observed in the CYP3A inactivation potency (k inact /K I, app ) as HLM > plated > DMEM ≥ plasma hHEPs. Using the static mechanistic model, DDIs predicted using parameters estimated from plated, DMEM and plasma hHEPs had 84, 74 and 95% accuracy (out of 19 clinical interaction studies) within 2-fold of the reported interaction, respectively. They demonstrated significant improvement compared to the DDIs predicted using parameters estimated from HLMs where 58% accuracy was obtained. CONCLUSIONS: Based on 19 DDIs, plasma hHEPs demonstrate a more reliable clinical DDI prediction for 10 protein kinase inhibitors and prototypical CYP3A time dependent inhibitors.

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.

Critical review of preclinical approaches to investigate cytochrome p450-mediated therapeutic protein drug-drug interactions and recommendations for best practices: a white paper.

Drug-drug interactions (DDIs) between therapeutic proteins (TPs) and small-molecule drugs have recently drawn the attention of regulatory agencies, the pharmaceutical industry, and academia. TP-DDIs are mainly caused by proinflammatory cytokine or cytokine modulator-mediated effects on the expression of cytochrome P450 enzymes. To build consensus among industry and regulatory agencies on expectations and challenges in this area, a working group was initiated to review the preclinical state of the art. This white paper represents the observations and recommendations of the working group on the value of in vitro human hepatocyte studies for the prediction of clinical TP-DDI. The white paper was developed following a "Workshop on Recent Advances in the Investigation of Therapeutic Protein Drug-Drug Interactions: Preclinical and Clinical Approaches" held at the Food and Drug Administration White Oak Conference Center on June 4 and 5, 2012. Results of a workshop poll, cross-laboratory data comparisons, and the overall recommendations of the in vitro working group are presented herein. The working group observed that evaluation of TP-DDI for anticytokine monoclonal antibodies is currently best accomplished with a clinical study in patients with inflammatory disease. Treatment-induced changes in appropriate biomarkers in phase 2 and 3 studies may indicate the potential for a clinically measurable treatment effect on cytochrome P450 enzymes. Cytokine-mediated DDIs observed with anti-inflammatory TPs cannot currently be predicted using in vitro data. Future success in predicting clinical TP-DDIs will require an understanding of disease biology, physiologically relevant in vitro systems, and more examples of well conducted clinical TP-DDI trials.

Design and evaluation of novel 8-oxo-pyridopyrimidine Jak1/2 inhibitors.

A highly ligand efficient, novel 8-oxo-pyridopyrimidine containing inhibitor of Jak1 and Jak2 isoforms with a pyridone moiety as the hinge-binding motif was discovered. Structure-based design strategies were applied to significantly improve enzyme potency and the polarity of the molecule was adjusted to gain cellular activity. The crystal structures of two representative inhibitors bound to Jak1 were obtained to enable SAR exploration.

Novel triazolo-pyrrolopyridines as inhibitors of Janus kinase 1.

The identification of a novel fused triazolo-pyrrolopyridine scaffold, optimized derivatives of which display nanomolar inhibition of Janus kinase 1, is described. Prototypical example 3 demonstrated lower cell potency shift, better permeability in cells and higher oral exposure in rat than the corresponding, previously reported, imidazo-pyrrolopyridine analogue 2. Examples 6, 7 and 18 were subsequently identified from an optimization campaign and demonstrated modest selectivity over JAK2, moderate to good oral bioavailability in rat with overall pharmacokinetic profiles comparable to that reported for an approved pan-JAK inhibitor (tofacitinib).

2-Amino-[1,2,4]triazolo[1,5-a]pyridines as JAK2 inhibitors.

The advancement of a series of ligand efficient 2-amino-[1,2,4]triazolo[1,5-a]pyridines, initially identified from high-throughput screening, to a JAK2 inhibitor with pharmacodynamic activity in a mouse xenograft model is disclosed.