Survey of pharmaceutical industry's best practices around in vitro transporter assessment and Implications for Drug Development: Considerations from the IQ Transporter Working Group.

The IQ Transporter Working Group had a rare opportunity to analyse a cross-pharma collation of in vitro data and assay methods for the evaluation of drug transporter substrate and inhibitor potential. Experiments were generally performed in accordance with regulatory guidelines. Discrepancies, such as not considering the impact of pre-incubation for inhibition and free or measured in vitro drug concentrations, may be due to the retrospective nature of the dataset and analysis. Lipophilicity was a frequent indicator of cross-transport inhibition (P-gp, BCRP, OATP1B and OCT1) with high molecular weight ({greater than or equal to}500 Da) also common for OATP1B and BCRP inhibitors. A high level of overlap in in vitro inhibition across transporters was identified for BCRP, OATP1B1 and MATE1 suggesting that prediction of DDIs for these transporters will be common. In contrast inhibition of OAT1 did not coincide with inhibition of any other transporter. Neutrals, bases, and compounds with intermediate-high lipophilicity tended to be P-gp and/or BCRP substrates whilst compounds with MW <500 Da tended to be OAT3 substrates. Interestingly the majority of in vitro inhibitors were not reported to be followed up with a clinical study by the submitting company, whilst those compounds identified as substrates generally were. Approaches to metabolite testing were generally found to be similar to parent testing with metabolites generally being equally or less potent than parent compounds. However, examples where metabolites inhibited transporters in vitro were identified supporting the regulatory requirement for in vitro testing of metabolites to enable integrated clinical DDI risk assessment. Significance Statement A diverse dataset showed transporter inhibition often correlated with lipophilicity and molecular weight (>500 Da). Overlapping transporter inhibition was identified, particularly that inhibition of BCRP, OATP1B1 and MATE1 was frequent if the compound inhibited other transporters. In contrast inhibition of OAT1 did not correlate with the other drug transporters tested.

Tissue distribution and retention drives efficacy of rapidly clearing VHL-based PROTACs.

BACKGROUND: Proteolysis-targeting chimeras (PROTACs) are being developed for therapeutic use. However, they have poor pharmacokinetic profiles and their tissue distribution kinetics are not known. METHODS: A typical von Hippel-Lindau tumor suppressor (VHL)-PROTAC 14C-A947 (BRM degrader)-was synthesized and its tissue distribution kinetics was studied by quantitative whole-body autoradiography (QWBA) and tissue excision in rats following IV dosing. Bile duct-cannulated (BDC) rats allowed the elucidation of in vivo clearance pathways. Distribution kinetics was evaluated in the tissues and tumors of mice to support PK-PD correlation. In vitro studies enabled the evaluation of cell uptake mechanisms and cell retention properties. RESULTS: Here, we show that A947 quickly distributes into rat tissues after IV dosing, where it accumulates and is retained in tissues such as the lung and liver although it undergoes fast clearance from circulation. Similar uptake/retention kinetics enable tumor growth inhibition over 2-3 weeks in a lung cancer model. A947 quickly excretes in the bile of rats. Solute carrier (SLC) transporters are involved in hepatocyte uptake of PROTACs. Sustained BRM protein degradation is seen after extensive washout that supports prolonged cell retention of A947 in NCI-H1944 cells. A947 tissue exposure and pharmacodynamics are inversely correlated in tumors. CONCLUSIONS: Plasma sampling for VHL-PROTAC does not represent the tissue concentrations necessary for efficacy. Understanding of tissue uptake and retention could enable less frequent IV administration to be used for therapeutic dosing.

Proteolysis-targeting chimeras (PROTACs) are a type of potential cancer medicine designed to target proteins primarily present in tumours. There is limited data on how it is absorbed, distributed, metabolised and excreted from tissues. Here, we studied the tissue distribution of synthetic PROTAC molecules labelled with radioactivity following intravenous injection in rodent models. We find that PROTAC can rapidly distribute to target tumour tissues and its prolonged retention within the tumour cells can contribute to prevention of further tumour growth, as demonstrated in the lung cancer model. These findings suggest the evaluation of PROTAC therapeutic effectiveness directly from tumour tissues provides more relevant assessment than sampling from blood circulation, which may have implications for a reduction in intravenous dosing.

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.

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.

Artificial Intelligence for Quantitative Modeling in Drug Discovery and Development: An Innovation and Quality Consortium Perspective on Use Cases and Best Practices.

Recent breakthroughs in artificial intelligence (AI) and machine learning (ML) have ushered in a new era of possibilities across various scientific domains. One area where these advancements hold significant promise is model-informed drug discovery and development (MID3). To foster a wider adoption and acceptance of these advanced algorithms, the Innovation and Quality (IQ) Consortium initiated the AI/ML working group in 2021 with the aim of promoting their acceptance among the broader scientific community as well as by regulatory agencies. By drawing insights from workshops organized by the working group and attended by key stakeholders across the biopharma industry, academia, and regulatory agencies, this white paper provides a perspective from the IQ Consortium. The range of applications covered in this white paper encompass the following thematic topics: (i) AI/ML-enabled Analytics for Pharmacometrics and Quantitative Systems Pharmacology (QSP) Workflows; (ii) Explainable Artificial Intelligence and its Applications in Disease Progression Modeling; (iii) Natural Language Processing (NLP) in Quantitative Pharmacology Modeling; and (iv) AI/ML Utilization in Drug Discovery. Additionally, the paper offers a set of best practices to ensure an effective and responsible use of AI, including considering the context of use, explainability and generalizability of models, and having human-in-the-loop. We believe that embracing the transformative power of AI in quantitative modeling while adopting a set of good practices can unlock new opportunities for innovation, increase efficiency, and ultimately bring benefits to patients.

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.

Physiologically Based Pharmacokinetic Models Can Be Used to Predict the Unique Nonlinear Absorption Profiles of Vismodegib.

Predicting human pharmacokinetics (PK) during the drug discovery phase is valuable to assess doses required to reach therapeutic exposures. For orally administered compounds, however, this can be especially difficult, since the absorption process is complex. Vismodegib is a compound with unique nonlinear oral PK characteristics in humans. Oral physiologically based pharmacokinetic (PBPK) models were built using preclinical in vitro and in vivo data and successfully predicted the oral PK profiles in rats, dogs, and monkeys. Simulated drug exposures (area under the concentration-time curve from time 0 to infinity and Cmax) following oral administration were within twofold of observed values for dogs and monkeys, and close to twofold for rats, providing validation to the model structure. Adaptation of this oral PBPK model to humans, using human physiologic parameters coupled with predicted human PK, resulted in underpredictions of vismodegib exposure following both single and multiple doses. When observed human PK was used to drive the oral PBPK model, oral PK profiles in humans were well predicted, with fold errors in predicted versus observed drug exposures being close to 1. Importantly, the oral PBPK model captured the unique nonlinear, nondose-dependent PK of vismodegib at a steady state. The mechanism responsible for nonlinearity was consistent with oral absorption being influenced by nonsink permeation conditions. We introduce a new parameter, the permeation gradient factor, to characterize the effect of nonsink conditions on permeation. Using vismodegib as an example, we demonstrate the value of using oral PBPK models in drug discovery to predict the oral PK of compounds with nonlinear absorption characteristics in human. SIGNIFICANCE STATEMENT: A physiologically based pharmacokinetic (PBPK) model was built to demonstrate the value of these models early in the drug discovery stage for the prediction of human pharmacokinetics for compounds with unusual oral pharmacokinetics. In this study, our PBPK model could successfully capture the unique steady-state oral pharmacokinetics of our model compound, vismodegib. The mechanism for nonlinearity can be attributed to nonsink permeation conditions in vivo. We introduce the permeation gradient factor as a parameter to assess this effect.

Development of Robust Quantitative Structure-Activity Relationship Models for CYP2C9, CYP2D6, and CYP3A4 Catalysis and Inhibition.

Cytochrome P450 enzymes are responsible for the metabolism of >75% of marketed drugs, making it essential to identify the contributions of individual cytochromes P450 to the total clearance of a new candidate drug. Overreliance on one cytochrome P450 for clearance levies a high risk of drug-drug interactions; and considering that several human cytochrome P450 enzymes are polymorphic, it can also lead to highly variable pharmacokinetics in the clinic. Thus, it would be advantageous to understand the likelihood of new chemical entities to interact with the major cytochrome P450 enzymes at an early stage in the drug discovery process. Typical screening assays using human liver microsomes do not provide sufficient information to distinguish the specific cytochromes P450 responsible for clearance. In this regard, we experimentally assessed the metabolic stability of ∼5000 compounds for the three most prominent xenobiotic metabolizing human cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4, and used the data sets to develop quantitative structure-activity relationship models for the prediction of high-clearance substrates for these enzymes. Screening library included the NCATS Pharmaceutical Collection, comprising clinically approved low-molecular-weight compounds, and an annotated library consisting of drug-like compounds. To identify inhibitors, the library was screened against a luminescence-based cytochrome P450 inhibition assay; and through crossreferencing hits from the two assays, we were able to distinguish substrates and inhibitors of these enzymes. The best substrate and inhibitor models (balanced accuracies ∼0.7), as well as the data used to develop these models, have been made publicly available (https://opendata.ncats.nih.gov/adme) to advance drug discovery across all research groups. SIGNIFICANCE STATEMENT: In drug discovery and development, drug candidates with indiscriminate cytochrome P450 metabolic profiles are considered advantageous, since they provide less risk of potential issues with cytochrome P450 polymorphisms and drug-drug interactions. This study developed robust substrate and inhibitor quantitative structure-activity relationship models for the three major xenobiotic metabolizing cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4. The use of these models early in drug discovery will enable project teams to strategize or pivot when necessary, thereby accelerating drug discovery research.

Intestinal Excretion, Intestinal Recirculation, and Renal Tubule Reabsorption Are Underappreciated Mechanisms That Drive the Distribution and Pharmacokinetic Behavior of Small Molecule Drugs.

Drug reabsorption following biliary excretion is well-known as enterohepatic recirculation (EHR). Renal tubular reabsorption (RTR) following renal excretion is also common but not easily assessed. Intestinal excretion (IE) and enteroenteric recirculation (EER) have not been recognized as common disposition mechanisms for metabolically stable and permeable drugs. IE and intestinal reabsorption (IR:EHR/EER), as well as RTR, are governed by dug concentration gradients, passive diffusion, active transport, and metabolism, and together they markedly impact disposition and pharmacokinetics (PK) of small molecule drugs. Disruption of IE, IR, or RTR through applications of active charcoal (AC), transporter knockout (KO), and transporter inhibitors can lead to changes in PK parameters. The impacts of intestinal and renal reabsorption on PK are under-appreciated. Although IE and EER/RTR can be an intrinsic drug property, there is no apparent strategy to optimize compounds based on this property. This review seeks to improve understanding and applications of IE, IR, and RTR mechanisms.

Prediction of Transporter-Mediated Rosuvastatin Hepatic Uptake Clearance and Drug Interaction in Humans Using Proteomics-Informed REF Approach.

Suspended, plated, or sandwich-cultured human hepatocytes are routinely used for in vitro to in vivo extrapolation (IVIVE) of transporter-mediated hepatic clearance (CL) of drugs. However, these hepatocyte models have been reported to underpredict transporter-mediated in vivo hepatic uptake CL (CL uptake,in vivo ) of some drugs. Therefore, we determined whether transporter-expressing cells (TECs) can accurately predict the CL uptake,in vivo of drugs. To do so, we determined the uptake CL (CL int,uptake,cells ) of rosuvastatin (RSV) by TECs (organic anion transporting polypeptides/Na+-taurocholate cotransporting polypeptide) and then scaled it to that in vivo by relative expression factor (REF) (the ratio of transporter abundance in human livers and TEC) determined by liquid chromatography tandem mass spectrometry-based quantitative proteomics. Both the TEC and hepatocyte models did not meet our predefined success criteria of predicting within 2-fold the RSV CL uptake,in vivo value obtained from our positron emission tomography (PET) imaging. However, the TEC performed better than the hepatocyte models. Interestingly, using REF, TECs successfully predicted RSV CL int,uptake,hep obtained by the hepatocyte models, suggesting that the underprediction of RSV CL uptake,in vivo by TECs and hepatocytes is due to endogenous factor(s) not present in these in vitro models. Therefore, we determined whether inclusion of plasma (or albumin) in TEC uptake studies improved IVIVE of RSV CL uptake,in vivo It did, and our predictions were close to or just fell above our lower 2-fold acceptance boundary. Despite this success, additional studies are needed to improve transporter-mediated IVIVE of hepatic uptake CL of drugs. However, using REF and TEC, we successfully predicted the magnitude of PET-imaged inhibition of RSV CL uptake,in vivo by cyclosporine A. SIGNIFICANCE STATEMENT: We showed that the in vivo transporter-mediated hepatic uptake CL of rosuvastatin, determined by PET imaging, can be predicted (within 2-fold) from in vitro studies in transporter-expressing cells (TECs) (scaled using REF), but only when plasma proteins were included in the in vitro studies. This conclusion did not hold when plasma proteins were absent in the TEC or human hepatocyte studies. Thus, additional studies are needed to improve in vitro to in vivo extrapolation of transporter-mediated drug CL.

Strategy for Determining the Free Fraction of Labile Covalent Modulators in Plasma Using Equilibrium Dialysis.

Determination of free drug fraction (fu) in plasma can be challenging for labile covalent modulators due to the off-target reactivity of chemical warheads to matrix proteins. The resulting poor drug recovery yields low confidence in fu. Two approaches using diluted plasma and low temperature (4 & 20 °C) for equilibrium dialysis (ED) have been investigated using covalent modulators including osimertinib, ibrutinib, rociletinib, afatinib, neratinib and acalabrutinib. Our data indicate that stability of covalent modulators in plasma varies in different species, and drug depletion may lead to overestimation of fu if true equilibrium is not reached. Additionally, although ED at low temperature improves the recovery of covalent modulators, the impact of low temperature may lead to underestimate of fu. Overall, ED using diluted plasma is a preferred method because of its faster equilibrium, improved recovery and free of temperature effect on fu. If low temperature ED must be used for extremely labile compounds, precaution must be taken to ensure no temperature dependence of fu in plasma. Nevertheless, an orthogonal ED approach is recommended for labile covalent modulators to confirm the true equilibrium and impact of temperature on fu. Additionally, this strategy can be used for determining fu of other liable compounds.

Characterization of Antineovascularization Activity and Ocular Pharmacokinetics of Phosphoinositide 3-Kinase/Mammalian Target of Rapamycin Inhibitor GNE-947.

The objectives of the present study were to characterize GNE-947 for its phosphoinositide 3-kinase (PI3K) and mammalian target of rapamycin (mTOR) inhibitory activities, in vitro anti-cell migration activity in human umbilical vein endothelial cells (HUVECs), in vivo antineovascularization activity in laser-induced rat choroidal neovascular (CNV) eyes, pharmacokinetics in rabbit plasma and eyes, and ocular distribution using matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) and autoradioluminography. Its PI3K and mTOR K i were 0.0005 and 0.045 µM, respectively, and its HUVEC IC50 was 0.093 µM. GNE-947 prevented neovascularization in the rat CNV model at 50 or 100 µg per eye with repeat dosing. After a single intravenous injection at 2.5 and 500 µg/kg in rabbits, its plasma terminal half-lives (t 1/2) were 9.11 and 9.59 hours, respectively. After a single intravitreal injection of a solution at 2.5 µg per eye in rabbits, its apparent t 1/2 values were 14.4, 16.3, and 23.2 hours in the plasma, vitreous humor, and aqueous humor, respectively. After a single intravitreal injection of a suspension at 33.5, 100, 200 µg per eye in rabbits, the t 1/2 were 29, 74, and 219 days in the plasma and 46, 143, and 191 days in the eyes, respectively. MALDI-IMS and autoradioluminography images show that GNE-947 did not homogenously distribute in the vitreous humor and aggregated at the injection sites after injection of the suspension, which was responsible for the long t 1/2 of the suspension because of the slow dissolution process. This hypothesis was supported by pharmacokinetic modeling analyses. In conclusion, the PI3K/mTOR inhibitor GNE-947 prevented neovascularization in a rat CNV model, with t 1/2 up to approximately 6 months after a single intravitreal injection of the suspension in rabbit eyes. SIGNIFICANCE STATEMENT: GNE-947 is a potent phosphoinositide 3-kinase/mammalian target of rapamycin inhibitor and exhibits anti-choroidal neovascular activity in rat eyes. The duration of GNE-947 in the rabbit eyes after intravitreal injection in a solution is short, with a half-life (t 1/2) of less than a day. However, the duration after intravitreal dose of a suspension is long, with t 1/2 up to 6 months due to low solubility and slow dissolution. These results indicate that intravitreal injection of a suspension for low-solubility drugs can be used to achieve long-term drug exposure.

Exposure-Efficacy Analysis of Antibody-Drug Conjugates Delivering an Excessive Level of Payload to Tissues.

Antibody-drug conjugates (ADCs) contain a disease-receptor antibody and a payload drug connected via a linker. The payload delivery depends on both tumor properties and ADC characteristics. In this study, we used different linkers, attachment sites, and doses to modulate payload delivery of several ADCs bearing maytansinoids (e.g., DM1), auristatins (e.g., MMAE), and DNA alkylating agents [e.g., pyrrolo[2,1-c][1,4]benzodiazepine-dimer (PBD)] as payloads in HER2- or CD22-expressing xenograft models. The tumor growth inhibition and ADC stability and exposure data were collected and analyzed from these dosed animals. The trend analysis suggests that intratumoral payload exposures that directly related the combination of conjugate linker and dose correlate with the corresponding efficacies of three payload types in two antigen-expressing xenograft models. These preliminary correlations also suggest that a minimal threshold concentration of intratumoral payload is required to support sustained efficacy. In addition, an ADC can deliver an excessive level of payload to tumors that does not enhance efficacy ("Plateau" effect). In contrast to tumor payload concentrations, the assessments of systemic exposures of total antibody (Tab) as well as the linker, dose, site of attachment, plasma stability, and drug-to-antibody ratio changes of these ADCs did not consistently rationalize the observed ADC efficacies. The requirement of a threshold payload concentration for efficacy is further supported by dose fractionation studies with DM1-, MMAE-, and PBD-containing ADCs, which demonstrated that single-dose regimens showed better efficacies than fractionated dosing. Overall, this study demonstrates that 1) the linker and dose together determine the tissue payload concentration that correlates with the antitumor efficacy of ADCs and 2) an ADC can deliver an unnecessary level of payload to tumors in xenograft models.

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.

Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper.

Quantitative translation of information on drug absorption, disposition, receptor engagement, and drug-drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state-of-the-art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 and 28, 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry, and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this "White Paper" alongside unresolved issues that were outlined for future debates.

Positron Emission Tomography Imaging of [11 C]Rosuvastatin Hepatic Concentrations and Hepatobiliary Transport in Humans in the Absence and Presence of Cyclosporin A.

Using positron emission tomography imaging, we determined the hepatic concentrations and hepatobiliary transport of [11 C]rosuvastatin (RSV; i.v. injection) in the absence (n = 6) and presence (n = 4 of 6) of cyclosporin A (CsA; i.v. infusion) following a therapeutic dose of unlabeled RSV (5 mg, p.o.) in healthy human volunteers. The sinusoidal uptake, sinusoidal efflux, and biliary efflux clearance (CL; mL/minute) of [11 C]RSV, estimated through compartment modeling were 1,205.6 ± 384.8, 16.2 ± 11.2, and 5.1 ± 1.8, respectively (n = 6). CsA (blood concentration: 2.77 ± 0.24 µM), an organic-anion-transporting polypeptide, Na+ -taurocholate cotransporting polypeptide, and breast cancer resistance protein inhibitor increased [11 C]RSV systemic blood exposure (45%; P < 0.05), reduced its biliary efflux CL (52%; P < 0.05) and hepatic uptake (25%; P > 0.05) but did not affect its distribution into the kidneys. CsA increased plasma concentrations of coproporphyrin I and III and total bilirubin by 297 ± 69%, 384 ± 102%, and 81 ± 39%, respectively (P < 0.05). These data can be used in the future to verify predictions of hepatic concentrations and hepatobiliary transport of RSV.

Catalytic Cleavage of Disulfide Bonds in Small Molecules and Linkers of Antibody-Drug Conjugates.

In cells, catalytic disulfide cleavage is an essential mechanism in protein folding and synthesis. However, detailed enzymatic catalytic mechanism relating cleavage of disulfide bonds in xenobiotics is not well understood. This study reports an enzymatic mechanism of cleavage of disulfide bonds in xenobiotic small molecules and antibody conjugate (ADC) linkers. The chemically stable disulfide bonds in substituted disulfide-containing pyrrolobenzodiazepine (PBD, pyrrolo[2,1-c][1,4]benzodiazepine) monomer prodrugs in presence of glutathione or cysteine were found to be unstable in incubations in whole blood of humans and rats. It was shown the enzymes involved were thioredoxin (TRX) and glutaredoxin (GRX). For a diverse set of drug-linker conjugates, we determined that TRX in the presence of TRX-reductase and NADPH generated the cleaved products that are consistent with catalytic disulfide cleavage and linker immolation. GRX was less rigorously studied; in the set of compounds studied, its role in the catalytic cleavage was also confirmed. Collectively, these in vitro experiments demonstrate that TRX as well as GRX can catalyze the cleavage of disulfide bonds in both small molecules and linkers of ADCs.

Exposure-Effect Relationships in Established Rat Adjuvant-Induced and Collagen-Induced Arthritis: A Translational Pharmacokinetic-Pharmacodynamic Analysis.

The ability of rodent immune-mediated arthritis models to quantitatively predict therapeutic activity of antiarthritis agents is poorly understood. Two commonly used preclinical models of arthritis are adjuvant-induced arthritis (AIA) and collagen-induced arthritis (CIA) in rats. The objective of the current study is to investigate the relationship between efficacy in AIA and CIA in rats, and clinical efficacy in rheumatoid arthritis patients using translational pharmacokinetic-pharmacodynamic (PK-PD) analysis. A range of doses of indomethacin (a nonsteroidal anti-inflammatory drug), and three disease-modifying antirheumatic drugs (DMARDs), methotrexate, etanercept, and tofacitinib, were evaluated in AIA and CIA rats. Dexamethasone was included in this study as a positive control. The area under the ankle diameter-time profile (AUCankle) and ankle histopathology summed scores (AHSS) were used as efficacy endpoints for activity against disease symptoms (joint inflammation) and disease progression (joint damage), respectively. Translational PK-PD analysis was performed to rank order preclinical efficacy endpoints at clinically relevant concentrations. For each drug tested, inhibition of AUCankle and AHSS scores was generally comparable in both magnitude and rank order. Overall, based on both AUCankle and the AHSS inhibition, the rank ordering of preclinical activity for the DMARDs evaluated was tofacitinib > etanercept ≥ methotrexate. This ranking of preclinical efficacy was consistent with reported clinical efficacy. Of interest, indomethacin showed equal or often better efficacy than the three DMARDs evaluated on inhibiting AHSS despite having limited ability to prevent joint damage clinically in patients. The translational value of performing PK-PD analysis of arthritis models in rats is discussed.