Introduction to in vitro estimation of metabolic stability and drug interactions of new chemical entities in drug discovery and development

Determination of metabolic properties of a new chemical entity (NCE) is one of the most important steps during the drug discovery and development process. Nowadays, in vitro methods are used for early estimation and prediction of in vivo metabolism of NCEs. Using in vitro methods, it is possible to determine the metabolic stability of NCEs as well as the risk for drug-drug interactions (DDIs) related to inhibition and induction of drug metabolic enzymes. Metabolic stability is defined as the susceptibility of a chemical compound to biotransformation, and is expressed as in vitro half-life (t(1/2)) and intrinsic clearance (CL(int)). Based on these values, in vivo pharmacokinetic parameters such as bioavailability and in vivo half-life can be calculated. The drug metabolic enzymes possess broad substrate specificity and can metabolize multiple compounds. Therefore, the risk for metabolism-based DDIs is always a potential problem during the drug development process. For this reason, inhibition and induction in vitro screens are used early, before selection of a candidate drug (CD), to estimate the risk for clinically significant DDIs. At present, most pharmaceutical companies perform in vitro drug metabolism studies together with in silico prediction software and automated high-throughput screens (HTS). Available data suggest that in vitro methods are useful tools for identification and elimination of NCEs with unappreciated metabolic properties. However, the quantitative output of the methods has to be improved. The aim of this review is to highlight the practical and theoretical basis of the in vitro metabolic methods and the recent progress in the development of these assays.     

Introduction to chemical proteomics for drug discovery and development

A fundamental goal of chemical proteomics is to identify target proteins for bioactive small molecules and then apply them to drug discovery and development as valid and drugable targets. Here, we introduce integrated technologies for the rapid identification of target proteins, methodologies for validating them as drugable targets, and applications of chemical proteomics in drug discovery and development.     

新化学实体的发现和早期评价(英文)

尽管用于药物开发的经费和时间逐年攀升,但近些年来被批准上市的新化学实体类药物却很少。随着计算化学学科的进展,辅助以X-射线晶体学和核磁共振技术,越来越多有前景的疾病治疗候选药物被发现。多种药物化学策略被发展用于药物早期评价研究。尽管如此,在药物开发的早期阶段,如何有效提高候选药物开发的成功率依然存在一些问题待解决。本文主要综述了药物开发早期阶段新化学实体发现和评价的代表性案例。     

Role of pharmacologically active metabolites in drug discovery and development

Pharmacologically active metabolites can contribute significantly to the overall therapeutic and adverse effects of drugs. Therefore, to fully understand the mechanism of action of drugs, it is important to recognize the role of active metabolites. Active metabolites can also be developed as drugs in their own right. Using illustrative examples, this paper discusses a variety of biotransformation reactions that produce active metabolites and their structure-activity relationships. The paper also describes the role and significance of active metabolites in drug discovery and development, various experimental observations that can be used as indicators of their presence, and methods that can be used to assess their biological activities and contribution to the overall therapeutic and adverse effects of drugs.     

An efficient approach for the rapid assessment of oral rat exposures for new chemical entities in drug discovery

Present study aims to improve efficiency and capacity of in vivo rat pharmacokinetic studies for rapid assessment of systemic exposure (AUC and C(max)) of new chemical entities. Plasma concentration-time profiles in rats from structurally diverse compounds were extracted from the Pfizer database. AUC(0-8) was calculated with 7 data points or a reduced subset of 3 data points. AUC values determined with 7 data points were compared to subset AUC values. A < or = 30% difference in values for 90% of cases was acceptance criteria. In parallel, samples were analyzed individually and pooled at each time point across compounds. For 96% of cases, AUC values estimated using 1, 4, and 8 h were comparable to AUC values obtained from 7 data points suggesting 1, 4, and 8 h sampling should be sufficient to estimate AUC. For C(max), the difference between 1, 4, and 8 h data-point analysis versus 7 data-point analysis is less than 30% for 72% of cases. Concentrations from individual versus pooled sample analysis were found to be equivalent. A rapid rat PK screening paradigm was created by the combination of 1, 4, and 8 h sampling and pooled sample analysis, which improves throughput and cycle time of in vivo PK studies.     

Intravenous administration of poorly soluble new drug entities in early drug discovery: the potential impact of formulation on pharmacokinetic parameters

Currently, in early drug discovery, compounds that are formulated for first-animal experiments are increasingly characterized as being lipophilic and poorly water-soluble. Typical examples of intravenous formulations for these compounds include aqueous solutions at non-physiologically high or low pH, co-solvent solutions, solutions in cyclodextrins (CDs), surfactant-based solutions, mixed micellar solutions, parenteral fat emulsions or nano- and microsuspensions. Experiments designed to determine the intrinsic pharmacokinetic behavior of a new drug entity (NDE) are complicated as, depending upon the formulation, disposition in the organism can be affected. This may be due to slow or incomplete dissolution of injected particles, precipitation in the bloodstream, delayed release from the dosing vehicle, competition between compound and formulation ingredients for transport and metabolism mechanisms, or altered binding to blood components. The most important determinant for the successful development of a 'non-interfering' dosing vehicle is the required dose. Provided the analytical technique used to determine drug concentration in the body is sensitive enough to allow compound administration at low doses, screening formulations at comparatively low concentrations may be feasible. In this way, formulation approaches that may potentially impact the pharmacokinetic behavior of the compound of interest can be avoided.     

Pharmacologically active metabolites of currently marketed drugs: potential resources for new drug discovery and development

Biotransformation is the major clearance mechanism of therapeutic agents from the body. Biotransformation is known not only to facilitate the elimination of drugs by changing the molecular structure to more hydrophilic, but also lead to pharmacological inactivation of therapeutic compounds. However, in some cases, the biotransformation of drugs can lead to the generation of pharmacologically active metabolites, responsible for the pharmacological actions. This review provides an update of the kinds of pharmacologically active metabolites and some of their individual pharmacological and pharmacokinetic aspects, and describes their importance as resources for drug discovery and development.     

Biomarkers in drug discovery and development: from target identification through drug marketing

Biomarkers of disease play an important role in medicine and have begun to assume a greater role in drug discovery and development. The challenge for biomarkers is to allow earlier, more robust drug safety and efficacy measurements. Their role in drug development will continue to grow for the foreseeable future. For biomarkers to assume their rightful role, greater understanding of the mechanism of disease progression and therapeutic intervention is needed. In addition, greater understanding of the requirements for biomarker selection and validation, biomarker assay method validation and application, and clinical endpoint validation and application is needed. Biomarkers need to be taken into account while the therapeutic target is still being identified and the concept is being formulated. Biomarkers need to be incorporated into a continuous cycle that takes what is learned from the discovery and development of one series of biomarkers and translates it into the next series of biomarkers. Optimum biomarker development and application will require a team approach because of the multifaceted nature of biomarker selection, validation, and application, using such techniques as pharmacoepidemiology, pharmacogenetics, pharmacogenomics, and functional proteomics; bioanalytical method development and validation; disease process and therapeutic intervention assessments; and pharmacokinetic/pharmacodynamic modeling and simulation to improve and refine drug development. The potential for biomarkers in medicine and drug development will be limited by the least effective component of the processes. The team approach will minimize the potential for the least effective component to be fatal to the rest of the process. As scientific/regulatory foundations for biomarkers in medicine and drug development begin to be established, successes and applications will need to be effectively communicated with all of the stakeholders, including not only internal and external drug developers and regulators but also the medical community, to ensure that biomarkers are totally integrated into drug discovery and development as well as the practice of medicine.     

Using bioinformatics techniques for gene identification in drug discovery and development

As more and more evidence has become available, the link between gene and emergent disease has been made including cancer, heart disease and parkinsonism. Analyzing the diseases and designing drugs with respect to the gene and protein level obviously help to find the underlying causes of the diseases, and to improve their rate of cure. The development of modern molecular biology, biochemistry, data collection and analysis techniques provides the scientists with a large amount of gene data. To draw a link between genes and their relation to disease outcomes and drug discovery is a big challenge: how to analyze large datasets and extract useful knowledge? Combining bioinformatics with drug discovery is a promising method to tackle this issue. Most techniques of bioinformatics are used in the first two phases of drug discovery to extract interesting information and find important genes and/or proteins for speeding the process of drug discovery, enhancing the accuracy of analysis and reducing the cost. Gene identification is a very fundamental and important technique among them. In this paper, we have reviewed gene identification algorithms and discussed their usage, relationships and challenges in drug discovery and development.     

Metabolite identification in drug discovery

Recent developments in the technologies and approaches to identify metabolites in a drug discovery environment are reviewed. Samples may be generated using either in vitro systems--typically, but not exclusively, liver subcellular fractions, such as microsomes, or whole cells, such as hepatocytes. Alternatively, metabolites are generated in vivo using excreta obtained following dosing in preclinical species. Recombinant drug metabolizing enzymes or microorganisms may offer alternate vectors. New techniques, such as the use of solid-phase microextraction, have found application in the isolation of metabolites from biological matrices. However, this is still dominated by the use of preparative chromatography, which has advanced through the use of mass-directed detection. Detection and structural elucidation by mass spectrometry have improved markedly with increases in sensitivity, allowing lower abundance metabolites to be detected, and increases in selectivity, with the use of high-resolution time-of-flight and quadrupole-time-of-flight instruments. Finally, higher field strength magnets coupled with novel probe designs and increased use of liquid chromatographic hyphenation techniques continue to drive the capabilities of nuclear magnetic resonance spectroscopy as the definitive structural elucidation tool.     

Accelerating the discovery of new drug targets with chemical proteomics

The application of chemical proteomics to new target discovery can lead to a rapid understanding of disease mechanism and new therapeutic methods. Successful application includes a thorough understanding of SAR and the validation of target relevance using multiple genetic and biochemical methods. This feature review highlights several successful applications of chemical proteomics and outlines the strategy and approaches that lead to the discovery of novel therapeutic targets.     

Translation of new technologies: from basic research to drug discovery and development

Despite increasing investment in drug discovery and development, only around one in every ten new medicinal products that progresses to clinical testing ever reach from the registration stage. Approximately half of all drug failures are attributed to problems with efficacy and toxicity not anticipated from preclinical studies. As a consequence, the pharmaceutical industry is adopting a much more flexible and multi-disciplinary approach to drug discovery and development. Indeed, the line between basic and applied science is constantly being eroded, not least because of the increasing sophistication of therapeutic procedures and the complexity of the diseases that they aim to treat. Here, we look at the new technologies that are being explored as a way of reducing drug attrition rates and the development of chemical drugs and biotherapeutics. Specifically, we will consider the ways in which genomics and related disciplines, engineered cell-based and microfluidics systems, and nanotechnologies are being developed and used alongside in silico platforms during early drug pharmacokinetics and toxicity studies. The way in which information from such systems biology-oriented approaches can be integrated with information from animal based preclinical safety, toxicological and pharmacological studies on investigative medicinal products is considered, in view of its current and possible impact on clinical trial design.     

Approaches for the rapid identification of drug metabolites in early clinical studies

Understanding the metabolism of a novel drug candidate in drug discovery and drug development is as important today as it was 30 years ago. What has changed in this period is the technology available for proficient metabolite characterization from complex biological sources. High-efficiency chromatography, sensitive MS and information-rich NMR spectroscopy are approaches that are now commonplace in the modern laboratory. These advancements in analytical technology have led to unequivocal metabolite identification often being performed at the earliest opportunity, following the first dose to man. For this reason an alternative approach is to shift from predicting and extrapolating possible human metabolism from in silico and nonclinical sources, to actual characterization at steady state within early clinical trials. This review provides an overview of modern approaches for characterizing drug metabolites in these early clinical studies. Since much of this progress has come from technology development over the years, the review is concluded with a forward-looking perspective on how this progression may continue into the next decade.     

Bioterrorism: a new frontier for drug discovery and development

Only a few years ago bioterrorism was considered a remote concern but today it has reached the forefront of the public imagination following recent terrorist attacks around the world. The disaster of September 11 2001, followed by anthrax letters sent via the US postal system, and now the renewed tension in the Middle East, have all brought the possibility of bioterrorism a little closer to reality. A number of biological agents could be used in a terrorist attack, including anthrax, botulinum, plague, smallpox, staphylococcal and streptococcal toxins, and the list of emerging pathogens is evolving rapidly. The serious diseases that these agents produce could cause considerable morbidity and mortality if used in a terrorist attack. This evolving threat presents the medical, public health and scientific communities with pressing challenges. The present research efforts in academia are primarily focused on the basic research on the pathogens that are considered to be bioweapons for terrorist attack. Thus, collaborative efforts between academic institutes, pharmaceutical industries and governmental agencies are warranted to translate basic research into drugs, vaccines and diagnostic tests. This review provides a brief overview of the threat from biological weapons and the current biodefense strategy to prevent and control outbreaks of diseases caused by intentional release of these bioweapons of mass destruction.     

Active drug metabolites in drug development

Active drug metabolites discovered during the course of drug development constitute a subset of the larger issue of metabolic drug interactions, but still demand unique consideration from both an efficacy and a safety point of view. Improved technology has allowed better identification and quantification of metabolites, raising new issues to be addressed during the course of drug development. Several new molecular identities recently entering the marketplace have active metabolites, and many more are (or have been) in development. The MIST (Metabolites in Safety Testing) committee of PhRMA (Pharmaceutical Research and Manufacturers of America) has prepared a position paper (in press) on the subject, which has been widely discussed (with and by regulatory authorities) over the past three years.     

In vitro screening techniques for reactive metabolites for minimizing bioactivation potential in drug discovery

Drug induced toxicity remains one of the major reasons for failures of new pharmaceuticals, and for the withdrawal of approved drugs from the market. Efforts are being made to reduce attrition of drug candidates, and to minimize their bioactivation potential in the early stages of drug discovery in order to bring safer compounds to the market. Therefore, in addition to potency and selectivity; drug candidates are now selected on the basis of acceptable metabolism/toxicology profiles in preclinical species. To support this, new approaches have been developed, which include extensive in vitro methods using human and animal hepatic cellular and subcellular systems, recombinant human drug metabolizing enzymes, increased automation for higher-throughput screens, sensitive analytical technologies and in silico computational models to assess the metabolism aspects of the new chemical entities. By using these approaches many compounds that might have serious adverse reactions associated with them are effectively eliminated before reaching clinical trials, however some toxicities such as those caused by idiosyncratic responses, are not detected until a drug is in late stages of clinical trials or has become available to the market. One of the proposed mechanisms for the development of idiosyncratic drug toxicity is the bioactivation of drugs to form reactive metabolites by drug metabolizing enzymes. This review discusses the different approaches to, and benefits of using existing in vitro techniques, for the detection of reactive intermediates in order to minimize bioactivation potential in drug discovery.     

Principles of early drug discovery

Developing a new drug from original idea to the launch of a finished product is a complex process which can take 12-15 years and cost in excess of $1 billion. The idea for a target can come from a variety of sources including academic and clinical research and from the commercial sector. It may take many years to build up a body of supporting evidence before selecting a target for a costly drug discovery programme. Once a target has been chosen, the pharmaceutical industry and more recently some academic centres have streamlined a number of early processes to identify molecules which possess suitable characteristics to make acceptable drugs. This review will look at key preclinical stages of the drug discovery process, from initial target identification and validation, through assay development, high throughput screening, hit identification, lead optimization and finally the selection of a candidate molecule for clinical development.     

Opportunities to minimise risk in drug discovery and development

ABSTRACT

Introduction: Artificial neural networks (ANNs) are highly adaptive nonlinear optimization algorithms that have been applied in many diverse scientific endeavors, ranging from economics, engineering, physics, and chemistry to medical science. Notably, in the past two decades, ANNs have been used widely in the process of drug discovery.

Areas covered: In this review, the authors discuss advantages and disadvantages of ANNs in drug discovery as incorporated into the quantitative structure-activity relationships (QSAR) framework. Furthermore, the authors examine the recent studies, which span over a broad area with various diseases in drug discovery. In addition, the authors attempt to answer the question about the expectations of the ANNs in drug discovery and discuss the trends in this field.

Expert opinion: The old pitfalls of overtraining and interpretability are still present with ANNs. However, despite these pitfalls, the authors believe that ANNs have likely met many of the expectations of researchers and are still considered as excellent tools for nonlinear data modeling in QSAR. It is likely that ANNs will continue to be used in drug development in the future.