Practical anticipation of human efficacious doses and pharmacokinetics using in vitro and preclinical in vivo data

Perfluoropolyether-Based Gut-Liver-on-a-Chip for the Evaluation of First-Pass Metabolism and Oral Bioavailability of Drugs

In the evolving field of drug discovery and development, multiorgans-on-a-chip and microphysiological systems are gaining popularity owing to their ability to emulate in vivo biological environments. Among the various gut-liver-on-a-chip systems for studying oral drug absorption, the chip developed in this study stands out with two distinct features: incorporation of perfluoropolyether (PFPE) to effectively mitigate drug sorption and a unique enterohepatic single-passage system, which simplifies the analysis of first-pass metabolism and oral bioavailability. By introducing a bolus drug injection into the liver compartment, hepatic extraction alone could be evaluated, further enhancing our estimation of intestinal availability. In a study on midazolam (MDZ), PFPE-based chips showed more than 20-times the appearance of intact MDZ in the liver compartment effluent compared to PDMS-based counterparts. Notably, saturation of hepatic metabolism at higher concentrations was confirmed by observations when the dose was reduced from 200 μM to 10 μM. This result was further emphasized when the metabolism was significantly inhibited by the coadministration of ketoconazole. Our chip, which is designed to minimize the dead volume between the gut and liver compartments, is adept at sensitively observing the saturation of metabolism and the effect of inhibitors. Using genome-edited CYP3A4/UGT1A1-expressing Caco-2 cells, the estimates for intestinal and hepatic availabilities were 0.96 and 0.82, respectively; these values are higher than the known human in vivo values. Although the metabolic activity in each compartment can be further improved, this gut-liver-on-a-chip can not only be used to evaluate oral bioavailability but also to carry out individual assessment of both intestinal and hepatic availability.

Perspective on high-throughput bioanalysis to support in vitro assays in early drug discovery

As the desire for a shortened design/make/test/learn cycle increases in early drug discovery, the pressure to rapidly deliver drug metabolism pharmacokinetic data continues to rise. From a bioanalytical standpoint, in vitro assays are challenging because they are amenable to automation and thus capable of generating a high number of samples for analysis. To keep up with analysis demands, automated method development workflows, rapid sample analysis approaches and efficient data analysis software must be utilized. This work provides an outline of how we implemented those three aspects to provide bioanalytical support for in vitro drug metabolism pharmacokinetic assays, which include developing hundreds of mass spectrometry methods and analyzing thousands of samples per week, while delivering a median bioanalytical turnaround time of 1-2 business days.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

Application of an Accessible Interface for Pharmacokinetic Modeling and In Vitro to In Vivo Extrapolation

Regulatory toxicology testing has traditionally relied on in vivo methods to inform decision-making. However, scientific, practical, and ethical considerations have led to an increased interest in the use of in vitro and in silico methods to fill data gaps. While in vitro experiments have the advantage of rapid application across large chemical sets, interpretation of data coming from these non-animal methods can be challenging due to the mechanistic nature of many assays. In vitro to in vivo extrapolation (IVIVE) has emerged as a computational tool to help facilitate this task. Specifically, IVIVE uses physiologically based pharmacokinetic (PBPK) models to estimate tissue-level chemical concentrations based on various dosing parameters. This approach is used to estimate the administered dose needed to achieve in vitro bioactivity concentrations within the body. IVIVE results can be useful to inform on metrics such as margin of exposure or to prioritize potential chemicals of concern, but the PBPK models used in this approach have extensive data requirements. Thus, access to input parameters, as well as the technical requirements of applying and interpreting models, has limited the use of IVIVE as a routine part of in vitro testing. As interest in using non-animal methods for regulatory and research contexts continues to grow, our perspective is that access to computational support tools for PBPK modeling and IVIVE will be essential for facilitating broader application and acceptance of these techniques, as well as for encouraging the most scientifically sound interpretation of in vitro results. We highlight recent developments in two open-access computational support tools for PBPK modeling and IVIVE accessible via the Integrated Chemical Environment (https://ice.ntp.niehs.nih.gov/), demonstrate the types of insights these tools can provide, and discuss how these analyses may inform in vitro-based decision making.

Pharmacokinetic-pharmacodynamic modelling of the anti-FcRn monoclonal antibody rozanolixizumab: Translation from preclinical stages to the clinic

Rozanolixizumab is a fully humanized high‐affinity anti‐human neonatal Fc receptor (FcRn) monoclonal antibody (mAb) that accelerates the removal of circulating immunoglobulin G (IgG), including pathogenic IgG autoantibodies, via the natural lysosomal degradation pathway. The aim of this study was to develop a pharmacokinetic/pharmacodynamic (PK/PD) model characterizing the effect of rozanolixizumab on IgG levels in cynomolgus monkeys, translate it into humans to support the first‐in‐human (FIH) rozanolixizumab clinical trial study design, and, ultimately, develop a PK/PD model in humans. Simulations from the preclinical model were performed to predict IgG responses in humans and select clinically relevant doses in the FIH study. Good alignment was observed between predicted and observed reductions in IgG, which increased with increasing dose in the FIH study. The model successfully described the PK of the 4 and 7 mg/kg intravenous (i.v.) dose groups, although the PKs were underpredicted for the 1 mg/kg i.v. dose group. Updating the model with subsequent human data identified parameters that deviated from preclinical assumptions. The updated PK/PD model was able to effectively characterize the PK FcRn‐IgG nonlinear system in response to rozanolixizumab in the FIH data.

Pharmacodynamics-based approach for efficacious human dose projection of BMS-986260, a small molecule transforming growth factor beta receptor 1 inhibitor

Transforming growth factor beta (TGF-β) is a pleiotropic cytokine that has a wide array of biological effects. For decades, tumor biology implicated TGF-β as an attractive therapeutic target due to its immunosuppressive effects. Toward this end, multiple pharmaceutical companies developed a number of drug modalities that specifically target the TGF-β pathway. BMS-986260 is a small molecule, selective TGF-βR1 kinase inhibitor that was under preclinical development for oncology. In vivo studies across mouse, rat, dog, and monkey and cryopreserved hepatocytes predicted human pharmacokinetics (PK) and distribution of BMS-986260. Efficacy studies of BMS-986260 were undertaken in the MC38 murine colon cancer model, and target engagement, as measured by phosphorylation of SMAD2/3, was assessed in whole blood to predict the clinical efficacious dose. The human clearance is predicted to be low, 4.25 ml/min/kg. BMS-986260 provided a durable and robust antitumor response at 3.75 mg/kg daily and 1.88 mg/kg twice-daily dosing regimens. Phosphorylation of SMAD2/3 was 3.5-fold less potent in human monocytes than other preclinical species. Taken together, the projected clinical efficacious dose was 600 mg QD or 210 mg BID for 3 days followed by a 4-day drug holiday. Mechanism-based cardiovascular findings in the rat ultimately led to the termination of BMS-986260. This study describes the preclinical PK characterization and pharmacodynamics-based efficacious dose projection of a novel small molecule TGF-βR1 inhibitor.

Application and Impact of Human Dose Projection from Discovery to Early Drug Development

The application and impact of human dose projection (HDP) has been well recognized in the late drug development phase, with increasing appreciation earlier during discovery and early development. This commentary describes the perspective of pharmaceutical scientists on the evolving application and impact of HDP at various phases from discovery to early development, including lead generation, lead optimization, lead up to candidate nomination, and early drug development. The underlying fundamental concepts and key input parameters for HDP are briefly discussed. A broad overview of phase-specific tools and approaches commonly utilized for human dose projection in the pharmaceutical industry is provided. A discussion of phase-appropriate implementation strategies, associated limitations/assumptions and continuous refinement for HDP from discovery to early development is presented. The authors describe the phase-specific applications of human dose projection to facilitate key assessments and relative impact on decision points.

Allometric Scaling Approaches for Predicting Human Pharmacokinetic of a Locked Nucleic Acid Oligonucleotide Targeting Cancer-Associated miR-221

: LNA-i-miR-221 is a novel phosphorothioate backbone 13-mer locked nucleic acid oligonucleotide-targeting microRNA-221 designed for the treatment of human malignancies. To understand the pharmacokinetic properties of this new agent, including unbound/total clearance, we investigated the LNA-i-miR-221 protein binding in three different species, including rat (Sprague-Dawley), monkey (Cynomolgus), and human. To this end, we generated a suitable ultrafiltration method to study the binding of LNA-i-miR-221 to plasma proteins. We identified that the fraction of LNA-i-miR-221 (at concentration of 1 and 10 µM) bound to rat, monkey, and human plasma proteins was high and ranged from 98.2 to 99.05%. This high protein binding of LNA-i-miR-221 to plasma proteins in all the species tested translates into a pharmacokinetic advantage by preventing rapid renal clearance. The integration of these results into multiple allometric interspecies scaling methods was then used to draw inferences about LNA-i-miR-221 pharmacokinetics in humans, thereby providing a framework for definition of safe starting and escalation doses and moving towards a first human clinical trial of LNA-i-miR-221.

Strategic Priorities for Research on Antibiotic Alternatives in Animal Agriculture-Results From an Expert Workshop

The emergence, spread, and expansion of antibiotic resistance and increasing restrictions on the use of antibiotics in animal agriculture have created a need for efficacious alternatives that remains unmet. Prioritizing research needs in the development of alternatives is key to ensuring that scarce research resources are dedicated to the most promising approaches. However, frameworks to enable a consistent, systematic, and transparent evaluation of antibiotic alternative candidates are lacking. Here, we present such an evaluation framework.

Circadian clock-controlled drug metabolism and transport

Metabolism and transport of many drugs oscillate with times of the day (solar time), resulting in circadian time-dependent drug exposure and pharmacokinetics.Time-dependent pharmacokinetics (also known as chronopharmacokinetics) is associated with time-varying drug effects and toxicity.This review summarizes drug-metabolizing enzymes and transporters with rhythmic expressions in the liver, intestine and/or kidney. Correlations of these diurnal proteins with circadian variations in drug exposure and effects/toxicity are covered. We also discuss the molecular mechanisms for circadian control of enzymes and transporters.Mechanism-based chronopharmacokinetics would facilitate a better understanding of chronopharmacology and the design of time-specific drug delivery systems, ultimately leading to improved drug efficacy and minimized toxicity.

Involvement of UDP-glucuronosyltransferases in higenamine glucuronidation and the gender and species differences in liver

OBJECTIVES

Higenamine (HG), an active ingredient of Aconite root in Chinese herbal medicine, is mainly metabolized by UDP-glucuronosyltransferases (UGT). However, the systematic glucuronidation of HG in humans remains unclear. The purpose of this study was to investigate the glucuronidation of HG.

METHODS

12 recombinant human UGT (rUGT) isozymes were used to characterize the HG glucuronidation. Liver microsomes from male and female mice, rats, guinea pigs, dogs, and humans were used to determine the species and gender differences using liquid chromatography-mass spectrometry.

KEY FINDINGS

One monoglucuronide was detected in reactions catalyzed by rUGT1A6, rUGT1A8, rUGT1A9, also human and dog liver microsomes. UGT1A9 is the most important glucuronosyltransferase that metabolizes HG. Because carvacrol, a specific inhibitor of UGT1A9, can significantly decrease the glucuronidation of HG in Human liver microsomes and UGT1A9. HG metabolism by UGT1A9 described in Michaelis-Menten kinetics (K_m=15.4 mM,V_max=2.2 nmol/mg/min) and glucuronidation in liver microsomes were species dependent. Gender did not affect the kinetic parameters among species except in rats.

CONCLUSIONS

UGT1A9 is a major isoenzyme responsible for the glucuronidation of HG in Human liver microsomes (HLMs). Dog may be an appropriate animal model to evaluate HG metabolism.

Pharmacokinetic/Pharmacodynamic Modeling of the PDE4 Inhibitor TAK-648 in Type 2 Diabetes: Early Translational Approaches for Human Dose Prediction

TAK‐648 is a PDE4 inhibitor with demonstrated preclinical antidiabetic properties. Our objective was to develop a translational pharmacokinetic/pharmacodynamic (PK/PD) model for human type 2 diabetes (T2D) dose prediction using HbA_1c results from a db/db mouse study. Estimated parameters in combination with tPDE4i values calculated for the clinical roflumilast dose of 500 μg were used to translate preclinical effects of TAK‐648 to required exposure in humans. A first‐in‐human study with single TAK‐648 doses of 0.05–0.85 mg in healthy volunteers yielded mean maximum TAK‐648 concentrations (Cmax) and area under the curve (AUC) values from 0.62–11.9 μg/L and 4.58–93.8 μg*h/L, respectively. Based on the performed pharmacokinetic/pharmacodynamic analysis and clinical PK results, clinical efficacy would be expected at a daily dose of 0.1 mg, which is well within the investigated clinical dose range. This result significantly enhanced the confidence in TAK‐648 for type 2 diabetes treatment and underlines the necessity of translational approaches in early preclinical phases.

Clinical Exposure Boost Predictions by Integrating Cytochrome P450 3A4-Humanized Mouse Studies With PBPK Modeling

NVS123 is a poorly water-soluble protease 56 inhibitor in clinical development. Data from in vitro hepatocyte studies suggested that NVS123 is mainly metabolized by CYP3A4. As a consequence of limited solubility, NVS123 therapeutic plasma exposures could not be achieved even with high doses and optimized formulations. One approach to overcome NVS123 developability issues was to increase plasma exposure by coadministrating it with an inhibitor of CYP3A4 such as ritonavir. A clinical boost effect was predicted by using physiologically based pharmacokinetic (PBPK) modeling. However, initial boost predictions lacked sufficient confidence because a key parameter, fraction of drug metabolized by CYP3A4 (fmCYP3A4), could not be estimated with accuracy on account of disconnects between in vitro and in vivo preclinical data. To accurately estimate fmCYP3A4 in human, an in vivo boost effect study was conducted using CYP3A4-humanized mouse model which showed a 33- to 56-fold exposure boost effect. Using a top-down approach, human fmCYP3A4 for NVS123 was estimated to be very high and included in the human PBPK modeling to support subsequent clinical study design. The combined use of the in vivo boost study in CYP3A4-humanized mouse model mice along with PBPK modeling accurately predicted the clinical outcome and identified a significant NVS123 exposure boost (∼42-fold increase) with ritonavir.

Pharmacokinetics in Drug Discovery: An Exposure-Centred Approach to Optimising and Predicting Drug Efficacy and Safety

The role of pharmacokinetics (PK) in drug discovery is to support the optimisation of the absorption, distribution, metabolism and excretion (ADME) properties of lead compounds with the ultimate goal to attain a clinical candidate which achieves a concentration-time profile in the body that is adequate for the desired efficacy and safety profile. A thorough characterisation of the lead compounds aiming at the identification of the inherent PK liabilities also includes an early generation of PK/PD relationships linking in vitro potency and target exposure/engagement with expression of pharmacological activity (mode-of-action) and efficacy in animal studies. The chapter describes an exposure-centred approach to lead generation, lead optimisation and candidate selection and profiling that focuses on a stepwise generation of an understanding between PK/exposure and PD/efficacy relationships by capturing target exposure or surrogates thereof and cellular mode-of-action readouts in vivo. Once robust PK/PD relationship in animal PD models has been constructed, it is translated to anticipate the pharmacologically active plasma concentrations in patients and the human therapeutic dose and dosing schedule which is also based on the prediction of the PK behaviour in human as described herein. The chapter outlines how the level of confidence in the predictions increases with the level of understanding of both the PK and the PK/PD of the new chemical entities (NCE) in relation to the disease hypothesis and the ability to propose safe and efficacious doses and dosing schedules in responsive patient populations. A sound identification of potential drug metabolism and pharmacokinetics (DMPK)-related development risks allows proposing of an effective de-risking strategy for the progression of the project that is able to reduce uncertainties and to increase the probability of success during preclinical and clinical development.

Application of Absorption Modeling in Rational Design of Drug Product Under Quality-by-Design Paradigm

Physiologically based absorption models can be an important tool in understanding product performance and hence implementation of Quality by Design (QbD) in drug product development. In this report, we show several case studies to demonstrate the potential application of absorption modeling in rational design of drug product under the QbD paradigm. The examples include application of absorption modeling—(1) prior to first-in-human studies to guide development of a formulation with minimal sensitivity to higher gastric pH and hence reduced interaction when co-administered with PPIs and/or H2RAs, (2) design of a controlled release formulation with optimal release rate to meet trough plasma concentrations and enable QD dosing, (3) understanding the impact of API particle size distribution on tablet bioavailability and guide formulation design in late-stage development, (4) assess impact of API phase change on product performance to guide specification setting, and (5) investigate the effect of dissolution rate changes on formulation bioperformance and enable appropriate specification setting. These case studies are meant to highlight the utility of physiologically based absorption modeling in gaining a thorough understanding of the product performance and the critical factors impacting performance to drive design of a robust drug product that would deliver the optimal benefit to the patients.

Implementation of pharmacokinetic and pharmacodynamic strategies in early research phases of drug discovery and development at Novartis Institute of Biomedical Research

Characterizing the relationship between the pharmacokinetics (PK, concentration vs. time) and pharmacodynamics (PD, effect vs. time) is an important tool in the discovery and development of new drugs in the pharmaceutical industry. The purpose of this publication is to serve as a guide for drug discovery scientists toward optimal design and conduct of PK/PD studies in the research phase. This review is a result of the collaborative efforts of DMPK scientists from various Metabolism and Pharmacokinetic (MAP) departments of the global organization Novartis Institute of Biomedical Research (NIBR). We recommend that PK/PD strategies be implemented in early research phases of drug discovery projects to enable successful transition to drug development. Effective PK/PD study design, analysis, and interpretation can help scientists elucidate the relationship between PK and PD, understand the mechanism of drug action, and identify PK properties for further improvement and optimal compound design. Additionally, PK/PD modeling can help increase the translation of in vitro compound potency to the in vivo setting, reduce the number of in vivo animal studies, and improve translation of findings from preclinical species into the clinical setting. This review focuses on three important elements of successful PK/PD studies, namely partnership among key scientists involved in the study execution; parameters that influence study designs; and data analysis and interpretation. Specific examples and case studies are highlighted to help demonstrate key points for consideration. The intent is to provide a broad PK/PD foundation for colleagues in the pharmaceutical industry and serve as a tool to promote appropriate discussions on early research project teams with key scientists involved in PK/PD studies.

Case studies for practical food effect assessments across BCS/BDDCS class compounds using in silico, in vitro, and preclinical in vivo data

Practical food effect predictions and assessments were described using in silico, in vitro, and/or in vivo preclinical data to anticipate food effects and Biopharmaceutics Classification System (BCS)/Biopharmaceutics Drug Disposition Classification System (BDDCS) class across drug development stages depending on available data: (1) limited in silico and in vitro data in early discovery; (2) preclinical in vivo pharmacokinetic, absorption, and metabolism data at candidate selection; and (3) physiologically based absorption modeling using biorelevant solubility and precipitation data to quantitatively predict human food effects, oral absorption, and pharmacokinetic profiles for early clinical studies. Early food effect predictions used calculated or measured physicochemical properties to establish a preliminary BCS/BDDCS class. A rat-based preclinical BCS/BDDCS classification used rat in vivo fraction absorbed and metabolism data. Biorelevant solubility and precipitation kinetic data were generated via animal pharmacokinetic studies using advanced compartmental absorption and transit (ACAT) models or in vitro methods. Predicted human plasma concentration-time profiles and the magnitude of the food effects were compared with observed clinical data for assessment of simulation accuracy. Simulations and analyses successfully identified potential food effects across BCS/BDDCS classes 1-4 compounds with an average fold error less than 1.6 in most cases. ACAT physiological absorption models accurately predicted positive food effects in human for poorly soluble bases after oral dosage forms. Integration of solubility, precipitation time, and metabolism data allowed confident identification of a compound's BCS/BDDCS class, its likely food effects, along with prediction of human exposure profiles under fast and fed conditions.

Applications of human pharmacokinetic prediction in first-in-human dose estimation

Quantitative estimations of first-in-human (FIH) doses are critical for phase I clinical trials in drug development. Human pharmacokinetic (PK) prediction methods have been developed to project the human clearance (CL) and bioavailability with reasonable accuracy, which facilitates estimation of a safe yet efficacious FIH dose. However, the FIH dose estimation is still very challenging and complex. The aim of this article is to review the common approaches for FIH dose estimation with an emphasis on PK-guided estimation. We discuss 5 methods for FIH dose estimation, 17 approaches for the prediction of human CL, 6 methods for the prediction of bioavailability, and 3 tools for the prediction of PK profiles. This review may serve as a practical protocol for PK- or pharmacokinetic/pharmacodynamic-guided estimation of the FIH dose.

Multiscale mathematical modeling to support drug development

It is widely recognized that major improvements are required in the methods currently being used to develop new therapeutic drugs. The time from initial target identification to commercialization can be 10-14 years and incur a cost in the hundreds of millions of dollars. Even after substantial investment, only 30-40% of the candidate compounds entering clinical trials are successful. We propose that multiscale mathematical pathway modeling can be used to decrease time required to bring candidate drugs to clinical trial and increase the probability that they will be successful in humans. The requirements for multiple time scales and spatial scales are discussed, and new computational paradigms are identified to address the increased complexity of modeling.

A pH-dilution method for estimation of biorelevant drug solubility along the gastrointestinal tract: application to physiologically based pharmacokinetic modeling

Physiologically based pharmacokinetic (PBPK) modeling tools have become an integral part of the modern drug discovery-development process. However, accurate PK prediction of enabling formulations of poorly soluble compounds by applying PBPK modeling has been very limited. This is because current PBPK models rely only on thermodynamic drug solubility inputs (e.g., pH-solubility profile) and give little consideration to the dynamic changes in apparent drug solubility (e.g., supersaturation) that occur during gastrointestinal (GI) transit of an enabling formulation of a water insoluble drug. Moreover, biorepresentative and predictive in vitro tools to measure formulation dependent solubility changes during GI transit remain underdeveloped. In this work, we have developed an in vitro dual pH-dilution method based on rat physiology to estimate the apparent drug concentration in solution along the GI tract during release from solubility enabling formulations. This simple dual pH-dilution method was evaluated using various solubility enabling formulations (i.e., cosolvent solution, amorphous solid dispersions) made using a model early development drug candidate with poor aqueous solubility. The in vitro drug concentration-time profiles from the enabling formulations were used as solubility inputs for PBPK modeling using GastroPlus software. This resulted in excellent predictions of the in vivo oral plasma concentration-time profiles, as compared to using the traditional inputs of thermodynamic pH-solubility profiles. In summary, this work describes a novel in vitro method for facile estimation of formulation dependent GI drug concentration-time profiles and demonstrates the utility of PBPK modeling for oral PK prediction of enabling formulations of poorly soluble drugs.