A Triterpenoid Lupeol as an Antioxidant and Anti-Neuroinflammatory Agent: Impacts on Oxidative Stress in Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disease illustrated by neuronal dysfunctions, leading to memory weaknesses and personality changes mostly in the aged population worldwide. The exact cause of AD is unclear, but numerous studies have addressed the involvement of oxidative stress (OS), induced by reactive oxygen species (ROS), to be one of the leading causes in developing AD. OS dysregulates the cellular homeostasis, causing abnormal protein and lipid metabolism. Nutrition plays a pivotal role in modulating the antioxidant system and decreases the neuronal ROS level, thus playing an important therapeutic role in neurodegenerative diseases, especially in AD. Hence, medicinal herbs and their extracts have received global attention as a commercial source of antioxidants Lupeol. Lupeol is a pentacyclic triterpenoid and has many biological functions. It is available in fruits, vegetables, and medicinal plants. It has shown effective antioxidant and anti-inflammatory properties, and higher blood-brain barrier permeability. Also, the binding and inhibitory potentials of Lupeol have been investigated and proved to be effective against certain receptor proteins and enzymes in AD studies by computational molecular docking approaches. Therefore, AD-related research has gained interest in investigating the therapeutic effects of Lupeol. However, despite its beneficial effects in AD, there is still a lack of research in Lupeol. Hence, we compiled in this analysis all preclinical research that looked at Lupeol as an antioxidant and anti-inflammatory agent for AD.

Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data

Improved pharmacokinetics/pharmacodynamics (PK/PD) prediction in the early stages of drug development is essential to inform lead optimization strategies and reduce attrition rates. Recently, there have been significant advancements in the development of new in vitro and in vivo strategies to better characterize pharmacokinetic properties and efficacy of drug leads. Herein, we review advances in experimental and mathematical models for clearance predictions, advancements in developing novel tools to capture slowly metabolized drugs, in vivo model developments to capture human etiology for supporting drug development, limitations and gaps in these efforts, and a perspective on the future in the field.

Natural barrigenol-like triterpenoids: A comprehensive review of their contributions to medicinal chemistry

Barrigenol-like triterpenoids (BATs), which contain an unusual oleanane substituted by many hydroxyl groups as the skeleton, are subdivided into five subtypes: barrigenol A₁, barrigenol A₂, barrigenol R₁, barringtogenol C, and 16-deoxybarringtogenol C. The variations in acyl derivatives, hydroxyl groups, and carbohydrate chains in their structures have enhanced the diversity of BATs. Moreover, the stable polyhydroxy-replaced pentacyclic skeleton provides an ideal platform for structural modifications. To date, more than 500 BAT derivatives have been isolated from plants. Synchronously, BATs possess anti-tumour, anti-Alzheimer's disease, anti-inflammatory, anti-microbial, anti-obesity and anti-allergic activities by regulating numerous cellular molecules. Some BAT derivatives, such as escin obtained from Aesculus hippocastanum L. and xanthoceraside isolated from Xanthoceras sorbifolia Bunge, have been used to treat encephaloedema or inflammatory diseases. This review aims to provide comprehensive information about the chemistry, sources, bioavailability, and anti-tumour effects of BATs, with a particular emphasis on the molecular mechanisms of action. The pharmacokinetics and clinical progress are also concerned. More than 300 structures identified over past 25 years are summarized here (249 compounds) and in the supplementary information (114 compounds). Accordingly, the pharmaceutical activity of barrigenol triterpenoids suggests that some compounds should be developed as promising anti-tumour or anti- Alzheimer's disease agents in future.

Generating Robust and Informative Nonclinical In Vitro and In Vivo Bacterial Infection Model Efficacy Data To Support Translation to Humans

In June 2017, the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens.” The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry, and government, including the United States Food and Drug Administration.

In June 2017, the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens.” The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry, and government, including the United States Food and Drug Administration. This and the accompanying review on clinical PK/PD summarize the workshop discussions and recommendations. Nonclinical PK/PD models play a critical role in designing human dosage regimens and are essential tools for drug development. These include in vitro and in vivo efficacy models that provide valuable and complementary information for dose selection and translation from the laboratory to human. It is crucial that studies be designed, conducted, and interpreted appropriately. For antibacterial PK/PD, extensive published data and expertise are available. These have been leveraged to develop recommendations, identify common pitfalls, and describe the applications, strengths, and limitations of various nonclinical infection models and translational approaches. Despite these robust tools and published guidance, characterizing nonclinical PK/PD relationships may not be straightforward, especially for a new drug or new class. Antimicrobial PK/PD is an evolving discipline that needs to adapt to future research and development needs. Open communication between academia, pharmaceutical industry, government, and regulatory bodies is essential to share perspectives and collectively solve future challenges.

Pharmacological vs. classical approaches in the design of first in man clinical drug trials

AIMS

The aims of the present study were to investigate the role of pharmacology in the design of first-in-man (FIM) trials in the Netherlands, and to evaluate the change in design approaches between 2007 and 2015.

METHODS

All FIM drug trials approved by all Dutch Institutional Review Boards (IRBs) in 2007 and in 2015 were selected. The original trial protocols, investigator's brochures and investigational medicinal product dossiers were the data sources. The following four design elements were assessed on the justification of the chosen approaches: preclinical information, dose calculation, endpoints, and dose escalation.

RESULTS

In 2007, the Dutch IRBs approved 21 FIM trials, and in 2015 they approved 34 FIM trials (55 in total). Seven out of 21 (33%) of the FIM trials from 2007, and 14 out of the 34 (41%) FIM trials from 2015 discussed only the no-observed-adverse-effect level or no-observed-effect level as preclinical information. Furthermore, five of the 21 (24%) 2007 FIM trials and 12 of the 34 (35%) 2015 FIM trials used unexplained allometric scaling. Pharmacodynamic (PD) parameters were measured in 15 of the 21 (71%) 2007 FIM trials and in 31 of the 34 (91%) of the 2015 FIM trials, and allometric scaling was only guided by safety/tolerability in 11 of the 20 (55%) dose escalation trials in 2007 and in nine of the 33 (27%) dose escalation trials in 2015.

CONCLUSIONS

Trial protocols and investigator's brochures commonly lack pharmacokinetic/PD approaches. Investigators, sponsors and IRBs should require an upfront consideration of pharmacology in these aspects for all FIM trials.

Translational modeling and simulation approaches for molecularly targeted small molecule anticancer agents from bench to bedside

INTRODUCTION

Recent advances in molecular biology have enabled personalized cancer therapies with molecularly targeted agents (MTAs), which offer a promising future for cancer therapy. Dynamic modeling and simulation (M&S) is a powerful mathematical approach linking drug exposures to pharmacological responses, providing a quantitative assessment of in vivo drug potency. Accordingly, a growing emphasis is being placed upon M&S to quantitatively understand therapeutic exposure-response relationships of MTAs in nonclinical models.

AREAS COVERED

An overview of M&S approaches for MTAs in nonclinical models is presented with discussion about mechanistic extrapolation of antitumor efficacy from bench to bedside. Emphasis is placed upon recent advances in M&S approaches linking drug exposures, biomarker responses (e.g. target modulation) and pharmacological outcomes (e.g. antitumor efficacy).

EXPERT OPINION

For successful personalized cancer therapies with MTAs, it is critical to mechanistically and quantitatively understand their exposure-response relationships in nonclinical models, and to logically and properly apply such knowledge to the clinic. Particularly, M&S approaches to predict pharmacologically active concentrations of MTAs in patients based upon nonclinical data would be highly valuable in guiding the design and execution of clinical trials. Proactive approaches to understand their exposure-response relationships could substantially increase probability of achieving a positive proof-of-concept in the clinic.

Modeling and Simulation of In Vivo Drug Effects

The concept of a pharmacokinetics-pharmacodynamics (PK/PD) assessment of drug development candidates is well established in pharmaceutical research and development, and PK/PD modeling is common practice in all pharmaceutical companies. A recent analysis (Morgan et al., Drug Discov Today 17(9-10):419-424, 2012) revealed however that insufficient certainty in the integrity of the causal chain of fundamental pharmacological steps from drug dosing through systemic exposure, target tissue exposure, and engagement of molecular target to pharmacological response is still the major driver of failure in phase II of clinical drug development. Despite the rise of molecular biomarkers, ethical, scientific, and practical constraints very often still prevent a direct assessment of each necessary step ultimately leading to an intended drug effect or an unintended adverse reaction. Yet, incomplete investigation of the causality of drug responses is a major risk for translational assessments and the prediction of drug responses in different species or other populations. Mechanism-based modeling and simulation (M&S) offers a means to investigate complex physiological and pharmacological processes and to complement experimental data for non-accessible steps in the pharmacological causal chain. With the help of two examples, it is illustrated, what level of physiological detail, state-of-the-art models can represent, how predictive these models are and how mechanism-based approaches can be combined with empirical correlation-based concepts.

Rethinking risk assessment for emerging technology first-in-human trials

Recent progress in synthetic biology (SynBio) has enabled the development of novel therapeutic opportunities for the treatment of human disease. In the near future, first-in-human trials (FIH) will be indicated. FIH trials mark a key milestone in the translation of medical SynBio applications into clinical practice. Fostered by uncertainty of possible adverse events for trial participants, a variety of ethical concerns emerge with regards to SynBio FIH trials, including 'risk' minimization. These concerns are associated with any FIH trial, however, due to the novelty of the approach, they become more pronounced for medical applications of emerging technologies (emTech) like SynBio. To minimize potential harm for trial participants, scholars, guidelines, regulations and policy makers alike suggest using 'risk assessment' as evaluation tool for such trials. Conversely, in the context of emTech FIH trials, we believe it to be at least questionable to contextualize uncertainty of potential adverse events as 'risk' and apply traditional risk assessment methods. Hence, this issue needs to be discussed to enable alterations of the evaluation process before the translational phase of SynBio applications begins. In this paper, we will take the opportunity to start the debate and highlight how a misunderstanding of the concept of risk, and the possibilities and limitations of risk assessment, respectively, might impair decision-making by the relevant regulatory authorities and research ethics committees, and discuss possible solutions to tackle the issue.

Mechanistic understanding of translational pharmacokinetic-pharmacodynamic relationships in nonclinical tumor models: a case study of orally available novel inhibitors of anaplastic lymphoma kinase

The orally available novel small molecules PF06463922 [(10R)-7-amino-12-fluoro-2,10,16-trimethyl-15-oxo-10,15,16,17-tetrahydro-2H-8,4-(metheno)pyrazolo[4,3-h][2,5,11]benzoxadiazacyclotetradecine-3-carbonitrile] and PF06471402 [(10R)-7-amino-12-fluoro-2,10,16-trimethyl-15-oxo-10,15,16,17-tetrahydro-2H-8,4-(azeno)pyrazolo[4,3-h][2,5,11]benzoxadiazacyclo-tetradecine-3-carbonitrile] are second-generation anaplastic lymphoma kinase (ALK) inhibitors targeted to both naïve and resistant patients with non-small cell lung cancer (NSCLC) to the first-generation ALK inhibitor crizotinib. The objectives of the present study were to characterize and compare the pharmacokinetic-pharmacodynamic (PKPD) relationships of PF06463922 and PF06471402 for target modulation in tumor and antitumor efficacy in athymic mice implanted with H3122 NSCLC cells expressing a crizotinib-resistant echinoderm microtubule-associated protein-like 4 (EML4)-ALK mutation, EML4-ALK(L1196M). Furthermore, the PKPD relationships for these ALK inhibitors were evaluated and compared between oral administration and subcutaneous constant infusion (i.e., between different pharmacokinetic [PK] profiles). Oral and subcutaneous PK profiles of these ALK inhibitors were adequately described by a one-compartment PK model. An indirect response model extended with a modulator fit the time courses of PF06463922- and PF06471402-mediated target modulation (i.e., ALK phosphorylation) with an estimated unbound EC50,in vivo of 36 and 20 nM, respectively, for oral administration, and 100 and 69 nM, respectively, for subcutaneous infusion. A drug-disease model based on the turnover concept fit tumor growth curves inhibited by PF06463922 and PF06471402 with estimated unbound tumor stasis concentrations of 51 and 27 nM, respectively, for oral administration, and 116 and 70 nM, respectively, for subcutaneous infusion. Thus, the EC50,in vivo to EC60,in vivo estimates for ALK inhibition corresponded to the concentrations required tumor stasis in all cases, suggesting that the pharmacodynamic relationships of target modulation to antitumor efficacy were consistent among the ALK inhibitors, even when the PK profiles with different administration routes were considerably different.

Translational pharmacokinetic-pharmacodynamic modeling from nonclinical to clinical development: a case study of anticancer drug, crizotinib

Attrition risk related to efficacy is still a major reason why new chemical entities fail in clinical trials despite recently increased understanding of translational pharmacology. Pharmacokinetic-pharmacodynamic (PKPD) analysis is key to translating in vivo drug potency from nonclinical models to patients by providing a quantitative assessment of in vivo drug potency with mechanistic insight of drug action. The pharmaceutical industry is clearly moving toward more mechanistic and quantitative PKPD modeling to have a deeper understanding of translational pharmacology. This paper summarizes an anticancer drug case study describing the translational PKPD modeling of crizotinib, an orally available, potent small molecule inhibitor of multiple tyrosine kinases including anaplastic lymphoma kinase (ALK) and mesenchymal-epithelial transition factor (MET), from nonclinical to clinical development. Overall, the PKPD relationships among crizotinib systemic exposure, ALK or MET inhibition, and tumor growth inhibition (TGI) in human tumor xenograft models were well characterized in a quantitative manner using mathematical modeling: the results suggest that 50% ALK inhibition is required for >50% TGI whereas >90% MET inhibition is required for >50% TGI. Furthermore, >75% ALK inhibition and >95% MET inhibition in patient tumors were projected by PKPD modeling during the clinically recommended dosing regimen, twice daily doses of crizotinib 250 mg (500 mg/day). These simulation results of crizotinib-mediated ALK and MET inhibition appeared consistent with the currently reported clinical responses. In summary, the present paper presents an anticancer drug example to demonstrate that quantitative PKPD modeling can be used for predictive translational pharmacology from nonclinical to clinical development.

Reducing systems biology to practice in pharmaceutical company research; selected case studies

Reviews of the productivity of the pharmaceutical industry have concluded that the current business model is unsustainable. Various remedies for this have been proposed, however, arguably these do not directly address the fundamental issue; namely, that it is the knowledge required to enable good decisions in the process of delivering a drug that is largely absent; in turn, this leads to a disconnect between our intuition of what the right drug target is and the reality of pharmacological intervention in a system such as a human disease state. As this system is highly complex, modelling will be required to elucidate emergent properties together with the data necessary to construct such models. Currently, however, both the models and data available are limited. The ultimate solution to the problem of pharmaceutical productivity may be the virtual human, however, it is likely to be many years, if at all, before this goal is realised. The current challenge is, therefore, whether systems modelling can contribute to improving productivity in the pharmaceutical industry in the interim and help to guide the optimal route to the virtual human. In this context, this chapter discusses the emergence of systems pharmacology in drug discovery from the interface of pharmacokinetic-pharmacodynamic modelling and systems biology. Examples of applications to the identification of optimal drug targets in given pathways, selecting drug modalities and defining biomarkers are discussed, together with future directions.

Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival

In an effort to uncover systematic learnings that can be applied to improve compound survival, an analysis was performed on data from Phase II decisions for 44 programs at Pfizer. It was found that not only were the majority of failures caused by lack of efficacy but also that, in a large number of cases (43%), it was not possible to conclude whether the mechanism had been tested adequately. A key finding was that an integrated understanding of the fundamental pharmacokinetic/pharmacodynamic principles of exposure at the site of action, target binding and expression of functional pharmacological activity (termed together as the 'three Pillars of survival') all determine the likelihood of candidate survival in Phase II trials and improve the chance of progression to Phase III.

Developing drug prototypes: pharmacology replaces safety and tolerability?

New medicines are designed to bind to receptors or enzymes and are tested in animal cells, tissues and whole organisms in a highly scientific process. Subsequently they are often administered to human subjects with tolerability as the primary objective. The process of development is considered to be linear and consecutive and passes through the famous four phases of development (Phase I-Phase IV). This is efficient for those projects for which the uncertainty about the development is low. There is, however, an increasing number of new prototypical compounds resulting from the increased biological knowledge with a high level of uncertainty. For these prototypical drugs development has to proceed in a much more adaptive manner, using tailor-made objectives, the development of special methodology and a cyclical rather than a linear type of project management.

PK/PD modelling and beyond: impact on drug development

PK/PD modelling will play an increasingly important role in drug development, because it will identify key properties of a drug in vivo, allowing the characterization and prediction of the time course of drug effects under physiological and pathological conditions (intensity and duration). It has developed from a descriptive to a mechanism-based approach, taking the relevant processes on the causal path between drug administration and drug effect into account. Recent developments and insights from systems biology and systems pharmacology will provide new information on the complexities of disease associated with the identification of multiple targets for drug treatment. This will give rise to new opportunities of drug combinations, which can only be developed rationally through the appropriate application of dynamical systems-based PK/PD models.