Handbook of experimental pharmacology最新文献

Natural products have been the most important source for drug development throughout the human history. Over time, the formulation of drugs has evolved from crude drugs to refined chemicals. In modern drug discovery, conventional natural products lead-finding usually uses a top-down approach, namely bio-guided fractionation. In this approach, the crude extracts are separated by chromatography and resulting fractions are tested for activity. Subsequently, active fractions are further refined until a single active compound is obtained. However, this is a painstakingly slow and expensive process. Among the alternatives that have been developed to improve this situation, metabolomics has proved to yield interesting results having been applied successfully to drug discovery in the last two decades. The metabolomics-based approach in lead-finding comprises two steps: (1) in-depth chemical profiling of target samples, e.g. plant extracts, and bioactivity assessment, (2) correlation of the chemical and biological data by chemometrics. In the first step of this approach, the target samples are chemically profiled in an untargeted manner to detect as many compounds as possible. So far, NMR spectroscopy, LC-MS, GC-MS, and MS/MS spectrometry are the most common profiling tools. The profile data are correlated with the biological activity with the help of various chemometric methods such as multivariate data analysis. This in-silico analysis has a high potential to replace or complement conventional on-silica bioassay-guided fractionation as it will greatly reduce the number of bioassays, and thus time and costs. Moreover, it may reveal synergistic mechanisms, when present, something for which the classical top-down approach is clearly not suited. This chapter aims to give an overview of successful approaches based on the application of chemical profiling with chemometrics in natural products drug discovery.

The long-standing goals in diabetes research are to improve β-cell survival, functionality and increase β-cell mass. Current strategies to manage diabetes progression are still not ideal for sustained maintenance of normoglycemia, thereby increasing demand for the development of novel drugs. Available pancreatic cell lines, cadaveric islets, and their culture methods and formats, either 2D or 3D, allow for multiple avenues of experimental design to address diverse aims in the research setting. More specifically, these pancreatic cells have been employed in toxicity testing, diabetes drug screens, and with careful curation, can be optimized for use in efficient high-throughput screenings (HTS). This has since spearheaded the understanding of disease progression and related mechanisms, as well as the discovery of potential drug candidates which could be the cornerstone for diabetes treatment. This book chapter will touch on the pros and cons of the most widely used pancreatic cells, including the more recent human pluripotent stem cell-derived pancreatic cells, and HTS strategies (cell models, design, readouts) that can be used for the purpose of toxicity testing and diabetes drug discovery.

Mounting evidence indicates that the female sex is a risk factor for Alzheimer's disease (AD), the most common cause of dementia worldwide. Decades of research suggest that sex-specific differences in genetics, environmental factors, hormones, comorbidities, and brain structure and function may contribute to AD development. However, although significant progress has been made in uncovering specific genetic factors and biological pathways, the precise mechanisms underlying sex-biased differences are not fully characterized. Here, we review several lines of evidence, including epidemiological, clinical, and molecular studies addressing sex differences in AD. In addition, we discuss the challenges and future directions in advancing personalized treatments for AD.

Sexual dimorphism creates different biological and cellular activities and selective regulation mechanisms in males and females, thus generating differential responses in health and disease. In this scenario, the sex itself is a source of physiologic metabolic disparities that depend on constitutive genetic and epigenetic features that characterize in a specific manner one sex or the other. This has as a direct consequence a huge impact on the metabolic routes that drive the phenotype of an individual. The impact of sex is being clearly recognized also in disease, whereas male and females are more prone to the development of some disorders, or have selective responses to drugs and therapeutic treatments. Actually, very less is known regarding the probable differences guided by sex in the context of inherited metabolic disorders, owing to the scarce consideration of sex in such restricted field, accompanied by an intrinsic bias connected with the rarity of such diseases. Metabolomics technologies have been ultimately developed and adopted for being excellent tools for the investigation of metabolic mechanisms, for marker discovery or monitoring, and for supporting diagnostic procedures of metabolic disorders. Hence, metabolomic approaches can excellently embrace the discovery of sex differences, especially when associated to the outcome or the management of certain inborn errors of the metabolism.

Because women have been excluded from most clinical trials, assessment of sex differences in pharmacokinetics is available for a minority of currently prescribed drugs. In a 2020 analysis, substantial pharmacokinetic (PK) sex differences were established for 86 drugs: women given the same drug dose as men routinely generated higher blood concentrations and longer drug elimination times than men. 96% of drugs with higher PK values in women were associated with a higher incidence of adverse drug reactions (ADRs) in women than men; in the small number of instances when PKs of men exceeded those of women, this sex difference positively predicted male-biased ADRs in only 29% of cases. The absence of sex-stratified PK information for many medications raises the concern that sex differences in pharmacokinetics may be widespread and of clinical significance, contributing to sex-specific patterns of ADRs. Administering equal drug doses to women and men neglects sex differences in pharmacokinetics and body weight, risks overmedication of women, and contributes to female-biased ADRs. Evidence-based dosing adjustments are recommended to counteract this sex bias.

Aldosterone is a steroid hormone produced in the zona glomerulosa (ZG) of the adrenal cortex. The most prominent function of aldosterone is the control of electrolyte homeostasis and blood pressure via the kidneys. The primary factors regulating aldosterone synthesis are the serum concentrations of angiotensin II and potassium. The T-type voltage-gated calcium channel Ca_V3.2 (encoded by CACNA1H) is an important component of electrical as well as intracellular calcium oscillations, which govern aldosterone production in the ZG. Excessive aldosterone production that is (partially) uncoupled from physiological stimuli leads to primary aldosteronism, the most common cause of secondary hypertension. Germline gain-of-function mutations in CACNA1H were identified in familial hyperaldosteronism, whereas somatic mutations are a rare cause of aldosterone-producing adenomas. In this review, we summarize these findings, put them in perspective, and highlight missing knowledge.

The rhythmically beating heart is the foundation of life-sustaining blood flow. There are four chambers and many different types of cell in the heart, but the twisted myofibrillar structures formed by cardiomyocytes are particularly important for cardiac contraction and electrical impulse transmission properties. The ability to generate cardiomyocytes using human-induced pluripotent stem cells has essentially solved the cell supply shortage for in vitro simulation of cardiac tissue function; however, modeling heart at the tissue level needs mature myocardial structure, electrophysiology, and contractile characteristics. Here, the current research on human functionalized cardiac microtissue in modeling cardiac diseases is reviewed and the design criteria and practical applications of different human engineered heart tissues, including cardiac organoids, cardiac thin films, and cardiac microbundles are analyzed. Table summarizing the ability of several in vitro myocardial models to assess heart structure and function for cardiac disease modeling.

The development and approval of the tyrosine kinase inhibitor imatinib in 2001 has heralded the advance of directed therapy options. Today, an armamentarium of targeted therapeutics is available and enables the use of precision medicine in non-solid cancer. Precision medicine is guided by the detection of tumor-specific and targetable characteristics. These include pathogenic fusions and/or mutations, dependency on specific signaling pathways, and the expression of certain cell surface markers. Within the first part, we review approved targeted therapies for the compound classes of small molecule inhibitors, antibody-based therapies and cellular therapies. Particular consideration is given to the underlying pathobiology and the respective mechanism of action. The second part emphasizes on how biomarkers, whether they are of diagnostic, prognostic, or predictive relevance, are indispensable tools to guide therapy choice and management in precision medicine. Finally, the examples of acute myeloid leukemia, chronic lymphocytic leukemia, and chronic myeloid leukemia illustrate how integration of these biomarkers helps to tailor therapy.

In the last decade, alcohol consumption in the US has risen by 84% in women compared with 35% in men. Furthermore, research has shown that sex- and gender-related differences may disadvantage women in terms of developing a range of psychological, cognitive, and medical problems considerably earlier in their drinking history than men, and despite consuming a similar quantity of substances. While this "telescoping" process has been acknowledged in the literature, a concomitant understanding of the underlying biobehavioral mechanisms, and an increase in the development of specific treatments tailored to women, has not occurred. In the current chapter we focus on understanding why the need for personalized, sex-specific medications is imperative, and highlight some of the potential sex-specific gonadal and stress-related adaptations underpinning the accelerated progress from controlled to compulsive drug and alcohol seeking in women. We additionally discuss the efficacy of these mechanisms as novel targets for medications development, using exogenous progesterone and guanfacine as examples. Finally, we assess some of the challenges faced and progress made in terms of developing innovative medications in women. We suggest that agents such as exogenous progesterone and adrenergic medications, such as guanfacine, may provide some efficacy in terms of attenuating stress-induced craving for several substances, as well as improving the ability to emotionally regulate in the face of stress, preferentially in women. However, to fully leverage the potential of these therapeutics in substance-using women, greater focus needs to the placed on reducing barriers to treatment and research by encouraging women into clinical trials.

The metabolome is composed of a vast array of molecules, including endogenous metabolites and lipids, diet- and microbiome-derived substances, pharmaceuticals and supplements, and exposome chemicals. Correct identification of compounds from this diversity of classes is essential to derive biologically relevant insights from metabolomics data. In this chapter, we aim to provide a practical overview of compound identification strategies for mass spectrometry-based metabolomics, with a particular eye toward pharmacologically-relevant studies. First, we describe routine compound identification strategies applicable to targeted metabolomics. Next, we discuss both experimental (data acquisition-focused) and computational (software-focused) strategies used to identify unknown compounds in untargeted metabolomics data. We then discuss the importance of, and methods for, assessing and reporting the level of confidence of compound identifications. Throughout the chapter, we discuss how these steps can be implemented using today's technology, but also highlight research underway to further improve accuracy and certainty of compound identification. For readers interested in interpreting metabolomics data already collected, this chapter will supply important context regarding the origin of the metabolite names assigned to features in the data and help them assess the certainty of the identifications. For those planning new data acquisition, the chapter supplies guidance for designing experiments and selecting analysis methods to enable accurate compound identification, and it will point the reader toward best-practice data analysis and reporting strategies to allow sound biological and pharmacological interpretation.