Optimizing preclinical study design in oncology research

The current drug development pathway in oncology research has led to a large attrition rate for new drugs, in part due to a general lack of appropriate preclinical studies that are capable of accurately predicting efficacy and/or toxicity in the target population. Because of an obvious need for novel therapeutics in many types of cancer, new compounds are being investigated in human Phase I and Phase II clinical trials before a complete understanding of their toxicity and efficacy profiles is obtained. In fact, for newer targeted molecular agents that are often cytostatic in nature, the conventional preclinical evaluation used for traditional cytotoxic chemotherapies utilizing primary tumor shrinkage as an endpoint may not be appropriate. By utilizing an integrated pharmacokinetic/pharmacodynamic approach, along with proper selection of a model system, the drug development process in oncology research may be improved leading to a better understanding of the determinants of efficacy and toxicity, and ultimately fewer drugs that fail once they reach human clinical trials.     

Modeling opportunities in comparative oncology for drug development

Successful development of novel cancer drugs depends on well-reasoned scientific drug discovery, rigorous preclinical development, and carefully conceived clinical trials. Failure in any of these steps contributes to poor rates of approval for new drugs to treat cancer. As technological and scientific advances have opened the door to a variety of novel approaches to cancer drug discovery and development, preclinical models that can answer questions about the activity and safety of novel therapies are increasingly necessary. The advance of a drug to clinical trials based on information from preclinical models presupposes that the models convey informative data for future use in human patients with cancer. The study of novel cancer drugs using in vitro models is highly controllable, reproducible, relatively inexpensive, and linked to high throughput. However, these models fail to reproduce many of the complex features of human cancer. Mouse models address some of these limitations but have important biological differences from human cancer. The integration of studies using pet dogs with spontaneously occurring tumors as models in the development path can answer questions not adequately addressed in conventional models and is therefore gaining attention and interest in drug development communities. The study of novel cancer drugs in dogs with naturally occurring tumors allows drug assessment in a cancer that shares many fundamental features with the human cancer condition, and thus provides an opportunity to answer questions that inform the cancer drug development path in ways not possible in more conventional models.     

Harnessing genetically engineered mouse models for preclinical testing

Recent studies cast doubt on the value of traditionally used models as tools for testing therapies for human cancer. Although the standard practice of xenografting tumors into immunocompromised mice generates reproducible tumors, drug testing in these models has low predictive power when compared to the clinical responses in Phase II trials. The use of tumor-bearing genetically engineered mouse models holds promise for improving preclinical testing. These models recapitulate specific molecular pathways in tumor initiation or progression and provide a biological system in which to study the disease process for assessing efficacy of new therapies and proof-of-principle for testing molecularly targeted drugs. In this review, we discuss the advantages and limitations of genetically engineered mice and plausible solutions for adapting these valuable tumors for wider use in preclinical testing by transplantation into na?ve recipients. We also provide examples of comparative molecular analysis of mammary tumors from MMTV-Polyoma Middle-T antigen and MMTV-wnt1 models as tools for finding clinical correlates, validating existing models and guiding the development of new genetically engineered mouse models for cancer.     

Drug discovery in academia

Drug discovery and development is generally done in the commercial rather than the academic realm. Drug discovery involves target discovery and validation, lead identification by high-throughput screening, and lead optimization by medicinal chemistry. Follow-up preclinical evaluation includes analysis in animal models of compound efficacy and pharmacology (ADME: administration, distribution, metabolism, elimination) and studies of toxicology, specificity, and drug interactions. Notwithstanding the high-cost, labor-intensive, and non-hypothesis-driven aspects of drug discovery, the academic setting has a unique and expanding niche in this important area of investigation. For example, academic drug discovery can focus on targets of limited commercial value, such as third-world and rare diseases, and on the development of research reagents such as high-affinity inhibitors for pharmacological "gene knockout" in animal models ("chemical genetics"). This review describes the practical aspects of the preclinical drug discovery process for academic investigators. The discovery of small molecule inhibitors and activators of the cystic fibrosis transmembrane conductance regulator is presented as an example of an academic drug discovery program that has yielded new compounds for physiology research and clinical development. high-throughput screening; drug development; pharmacology; fluorescence; cystic fibrosis transmembrane conductance regulator     

Artificial intelligence in drug design

Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology, the computer-aided drug design techniques have been successfully applied in almost every stage of the drug discovery and development pipeline to speed up the process of research and reduce the cost and risk related to preclinical and clinical trials. Owing to the development of machine learning theory and the accumulation of pharmacological data, the artificial intelligence (AI) technology, as a powerful data mining tool, has cut a figure in various fields of the drug design, such as virtual screening, activity scoring, quantitative structure-activity relationship (QSAR) analysis, de novo drug design, and in silico evaluation of absorption, distribution, metabolism, excretion and toxicity (ADME/T) properties. Although it is still challenging to provide a physical explanation of the AI-based models, it indeed has been acting as a great power to help manipulating the drug discovery through the versatile frameworks. Recently, due to the strong generalization ability and powerful feature extraction capability, deep learning methods have been employed in predicting the molecular properties as well as generating the desired molecules, which will further promote the application of AI technologies in the field of drug design.     

An update on the search for a Plasmodium vivax vaccine

Although Plasmodium falciparum is the leading cause of morbidity and mortality due to malaria worldwide, nearly 2.5 billion people, mostly outside Africa, are also at risk from malaria caused by Plasmodium vivax infection. Currently, almost all efforts to develop a malaria vaccine have focused on P. falciparum. For example, there are 23 P. falciparum vaccine candidates undergoing advanced clinical studies and only two P. vivax vaccine candidates being tested in preliminary (Phase I) clinical trials, with few others being assessed in preclinical studies. More investment and a greater effort toward the development of P. vivax vaccine components for a multi-species vaccine are required. This is mainly because of the wide geographical coexistence of both parasite species but also because of increasing drug resistance, recent observations of severe and lethal P. vivax cases and relapsing parasite behaviour. Availability of the P. vivax genome has contributed to antigen discovery but new means to test vaccines in future trials remain to be designed.     

TGN1412: time to change the paradigm for the testing of new pharmaceuticals

Clinical studies in human volunteers are an essential part of drug development. These studies are designed to account for possible differences between the effects of pharmaceutical products in preclinical studies and in humans. However, the tragic outcome of the recent Phase 1 clinical trial on TGN1412 casts considerable doubt over the relevance of this traditional drug development paradigm to the testing of therapeutic agents for human use. The role of alternatives to animal testing is considered, and a series of recommendations are made, which could ensure that clinical trials are well informed and based on the most relevant scientific information.     

Animal models in the pharmacokinetic/pharmacodynamic evaluation of antimicrobial agents

Animal infection models in the pharmacokinetic/pharmacodynamic (PK/PD) evaluation of antimicrobial therapy serve an important role in preclinical assessments of new antibiotics, dosing optimization for those that are clinically approved, and setting or confirming susceptibility breakpoints. The goal of animal model studies is to mimic the infectious diseases seen in humans to allow for robust PK/PD studies to find the optimal drug exposures that lead to therapeutic success. The PK/PD index and target drug exposures obtained in validated animal infection models are critical components in optimizing dosing regimen design in order to maximize efficacy while minimize the cost and duration of clinical trials. This review outlines the key components in animal infection models which have been used extensively in antibiotic discovery and development including PK/PD analyses.     

The basics of preclinical drug development for neurodegenerative disease indications

Preclinical development encompasses the activities that link drug discovery in the laboratory to initiation of human clinical trials. Preclinical studies can be designed to identify a lead candidate from several hits; develop the best procedure for new drug scale-up; select the best formulation; determine the route, frequency, and duration of exposure; and ultimately support the intended clinical trial design. The details of each preclinical development package can vary, but all have some common features. Rodent and nonrodent mammalian models are used to delineate the pharmacokinetic profile and general safety, as well as to identify toxicity patterns. One or more species may be used to determine the drug's mean residence time in the body, which depends on inherent absorption, distribution, metabolism, and excretion properties. For drugs intended to treat Alzheimer's disease or other brain-targeted diseases, the ability of a drug to cross the blood brain barrier may be a key issue. Toxicology and safety studies identify potential target organs for adverse effects and define the Therapeutic Index to set the initial starting doses in clinical trials. Pivotal preclinical safety studies generally require regulatory oversight as defined by US Food and Drug Administration (FDA) Good Laboratory Practices and international guidelines, including the International Conference on Harmonisation. Concurrent preclinical development activities include developing the Clinical Plan and preparing the new drug product, including the associated documentation to meet stringent FDA Good Manufacturing Practices regulatory guidelines. A wide range of commercial and government contract options are available for investigators seeking to advance their candidate(s). Government programs such as the Small Business Innovative Research and Small Business Technology Transfer grants and the National Institutes of Health Rapid Access to Interventional Development Pilot Program provide funding and services to assist applicants in preparing the preclinical programs and documentation for their drugs. Increasingly, private foundations are also funding preclinical work. Close interaction with the FDA, including a meeting to prepare for submission of an Investigational New Drug application, is critical to ensure that the preclinical development package properly supports the planned phase I clinical trial.     

A generally applicable, high-throughput screening-compatible assay to identify, evaluate, and optimize antimicrobial agents for drug therapy

Efficacy and tolerability are the key criteria for a successful medication in the clinic. Therefore, a new test method to obtain selective and active lead molecules has been developed. Recently, this novel screening strategy enabled a breakthrough in drug discovery in the field of herpes viruses. Here the authors report that this assay is a generally applicable screening test, which allows not only for identifying tolerable and potent antimicrobial agents in compound libraries, but also covers all potential in vitro targets of both the pathogen and the host simultaneously. The test system mimics the smallest unit of a natural infection. Host cells are incubated in the presence of the test sample and are infected with microbes, such as viruses, bacteria, or fungi. Analogous to (lethal challenge) animal models, cell survival is determined. This assay maximizes the chances of success of anti-infective drug discovery, is sensitive, robust, time- and cost-efficient, and especially effective in optimizing screening hits to lead structures and development candidates. In addition to the minimal inhibitory concentration or dose, this test system simultaneously provides the selectivity index, a measure of tolerability in vitro. The authors propose the activity selectivity assay format as a new standard in anti-infective drug discovery and clinical development.     

Patient-derived model systems and the development of next-generation anticancer therapeutics

Anticancer drug discovery and development using conventional cell line and animal models has traditionally had a low overall success rate. Despite yielding game-changing new therapeutics, 10–20 new molecules have to be brought to the clinic to obtain one new approval, making this approach costly and inefficient. The use of in vitro experimental models based on primary human tumour tissues has the potential to provide a representation of human cancer biology that is closer to an actual patient and to ‘bridge the translational gap’ between preclinical and clinical research. Here, we review recent advances in the use of human tumour samples for preclinical research through organoid development or as primary patient materials. While challenges still remain regarding analysis, validation and scalability, evidence is mounting for the applicability of both models as preclinical research tools.     

Phase 0 clinical trials in cancer drug development: from FDA guidance to clinical practice

The Food and Drug Administration (FDA) recently introduced the Exploratory Investigational New Drug Guidance to expedite the clinical evaluation of new therapeutic and imaging agents. Early clinical studies performed under the auspices of this guidance, so-called "Phase 0" trials, have been initiated at the National Cancer Institute to integrate qualified pharmacodynamic biomarker assays into first-in-human cancer clinical trials of molecularly targeted agents. The goal of this integration is to perform molecular proof-of-concept investigations at the earliest stage of cancer drug development. Phase 0 trials do not offer any possibility of patient benefit; instead, intensive, real-time pharmacodynamic and pharmacokinetic analyses of patient tumor samples and/or surrogate tissues are performed to inform subsequent trials. Phase 0 studies do not replace formal Phase I drug safety testing and require a substantial investment of resources in assay development early on; however, they offer the promise of more rational selection of agents for further, large-scale development as well as the molecular identification of potential therapeutic failures early in the development process.     

Systems biology in drug discovery

The hope of the rapid translation of 'genes to drugs' has foundered on the reality that disease biology is complex, and that drug development must be driven by insights into biological responses. Systems biology aims to describe and to understand the operation of complex biological systems and ultimately to develop predictive models of human disease. Although meaningful molecular level models of human cell and tissue function are a distant goal, systems biology efforts are already influencing drug discovery. Large-scale gene, protein and metabolite measurements ('omics') dramatically accelerate hypothesis generation and testing in disease models. Computer simulations integrating knowledge of organ and system-level responses help prioritize targets and design clinical trials. Automation of complex primary human cell-based assay systems designed to capture emergent properties can now integrate a broad range of disease-relevant human biology into the drug discovery process, informing target and compound validation, lead optimization, and clinical indication selection. These systems biology approaches promise to improve decision making in pharmaceutical development.     

Biomarker technology roundup: from discovery to clinical applications, a broad set of tools is required to translate from the lab to the clinic

Biomarkers are being utilized throughout the drug discovery and development process to understand fundamental biological processes and relationships. Specific biomarkers for disease states, prognosis, and response to therapy have been applied to screening tissues and serum, and serve as new tools in the development of therapeutics, to segment the population for specific treatments. The use of specific biomarkers to screen subjects to determine clinical trial eligibility, and for early toxicology studies, holds the potential to decrease drug failure rates in the later phases of the clinical trial process. Traditional research tools have been employed to study the genes, proteins, and metabolites of interest. In addition, new technologies and permutations of existing technologies have been developed particularly for investigation in the preclinical and clinical phases of drug development. More importantly, the transition of a compound from preclinical to clinical is aided by technologies that span both process segments. Identification of biomarkers that can be studied throughout the development process requires technologies that are both feasible and cost-effective for large patient populations.     

Application of predictive biosimulation within pharmaceutical clinical development: examples of significance for translational medicine and clinical trial design

The challenge of accurately predicting human clinical outcome based on preclinical data has led to a high failure rate of compounds in human clinical trials. A series of methods are described by which biosimulation can address these challenges and guide the design and evaluation of experimental and clinical protocols. Early compound development often proceeds on the basis of preclinical data from animal models. The systematic evaluation possible in a simulation can assist in the critical step of translating the preclinical outcomes to human physiology. Later in the process, clinical trials definitively establish a therapy's beneficial effects, as well as any adverse side effects. Biosimulation allows for the optimal design of clinical trials to ensure that key issues are addressed effectively and efficiently, and in doing so, improves the success rate of the trials.     

Do stroke models model stroke?

Stroke is one of the leading causes of death worldwide and the biggest reason for long-term disability. Basic research has formed the modern understanding of stroke pathophysiology, and has revealed important molecular, cellular and systemic mechanisms. However, despite decades of research, most translational stroke trials that aim to introduce basic research findings into clinical treatment strategies – most notably in the field of neuroprotection – have failed. Among other obstacles, poor methodological and statistical standards, negative publication bias, and incomplete preclinical testing have been proposed as ‘translational roadblocks’. In this article, we introduce the models commonly used in preclinical stroke research, discuss some of the causes of failed translational success and review potential remedies. We further introduce the concept of modeling ‘care’ of stroke patients, because current preclinical research models the disorder but does not model care or state-of-the-art clinical testing. Stringent statistical methods and controlled preclinical trials have been suggested to counteract weaknesses in preclinical research. We conclude that preclinical stroke research requires (1) appropriate modeling of the disorder, (2) appropriate modeling of the care of stroke patients and (3) an approach to preclinical testing that is similar to clinical testing, including Phase 3 randomized controlled preclinical trials as necessary additional steps before new therapies enter clinical testing.     

Development of new RNAi therapeutics

RNAi-mediated gene inactivation has become a cornerstone of the present day gene function studies that are the foundation of mechanism and target based drug discovery and development, which could potentially shorten the otherwise long process of drug development. In particular, the coming of age of "RNAi drug" could provide new promising therapeutics bypassing traditional approaches. However, there are technological hurdles need to overcome and the biological limitations need to consider for achieving effective therapeutics. Major hurdles include the intrinsic poor pharmacokinetic property of siRNA and major biological restrictions include off-target effects, interferon response and the interference with endogenous miRNA. Recent innovations in nucleic acid chemistry, formulations and delivery methods have gradually rendered it possible to develop effective RNAi-based therapeutics. Careful design based on the newest RNAi/miRNA biology can also help to minimize the potential tissue toxicity. If successful with systemic application, RNAi drug will no doubt revolutionize the whole drug development process. This review attempts to describe the progress in this area, including applications in preclinical models and recent favorable experience in a number of human trials of local diseases, along with the discussion on the potential limitations of RNAi therapeutics.     

Platform for Plasmodium vivax vaccine discovery and development

Plasmodium vivax is the most prevalent malaria parasite on the American continent. It generates a global burden of 80-100 million cases annually and represents a tremendous public health problem, particularly in the American and Asian continents. A malaria vaccine would be considered the most cost-effective measure against this vector-borne disease and it would contribute to a reduction in malaria cases and to eventual eradication. Although significant progress has been achieved in the search for Plasmodium falciparum antigens that could be used in a vaccine, limited progress has been made in the search for P. vivax components that might be eligible for vaccine development. This is primarily due to the lack of in vitro cultures to serve as an antigen source and to inadequate funding. While the most advanced P. falciparum vaccine candidate is currently being tested in Phase III trials in Africa, the most advanced P. vivax candidates have only advanced to Phase I trials. Herein, we describe the overall strategy and progress in P. vivax vaccine research, from antigen discovery to preclinical and clinical development and we discuss the regional potential of Latin America to develop a comprehensive platform for vaccine development.     

Who will develop new antibacterial agents?

The golden age of antimicrobial drug development is a distant memory, and the likelihood of there being another seems slim. In part, this is because the pharmaceutical industry, which has now adopted an unsustainable business model, abandoned the anti-infective sector, and the pipeline is almost empty. The contribution to this crisis of national governments, health agencies and funders also merits discussion. Much of the basis for drug discovery is funded by the public sector, thereby generating intellectual property and leads for drug development that are often not pursued owing to funding gaps. In particular, the cost of testing drug efficacy in clinical trials is beyond the means of most companies and organizations. Lack of a concerted international effort to develop new antimicrobials is particularly alarming at a time when multidrug-resistant bacteria threaten all areas of human medicine globally. Here, the steps that led to this situation are retraced, and some possible solutions to the dilemma are proposed.